# document

id: 2fc6468fc398f0ef1ed3ebbd05f85ea9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5661
content:
"The carbon cycle provides for additional feedbacks on climate owing \r\nto the sensitivity of land-atmosphere and ocean-atmosphere carbon \r\nfluxes and storage to changes in climate and in atmospheric CO2\r\n(Figure TS.17c). Because of the time scales associated with land and \r\nocean carbon uptake, these feedbacks are known to be scenario \r\ndependent. Feedback estimates deviate from linearity in scenarios \r\nof stabilizing or reducing concentrations. With high confidence, \r\nincreased atmospheric CO2 will lead to increased land and ocean \r\ncarbon uptake, acting as a negative feedback on climate change. It \r\nis likely that a warmer climate will lead to reduced land and ocean \r\ncarbon uptake, acting as a positive feedback (Box TS.5). {4.3.2, \r\n5.4.1-5}"


id: 267dcb49e02ec7e79476d24027bd0c94
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3936
content:
"The near-linear relationship between cumulative CO2\r\nemissions and maximum global surface temperature increase \r\ncaused by CO2 implies that stabilizing human-induced global \r\ntemperature increase at any level requires net anthropogenic \r\nCO2 emissions to become zero. This near-linear relationship \r\nfurther implies that mitigation requirements for limiting \r\nwarming to specific levels can be quantified in terms of a \r\ncarbon budget (high confidence). Remaining carbon budget \r\nestimates have been updated since AR5 with methodological \r\nimprovements, resulting in larger estimates that are \r\nconsistent with SR1.5. Several factors, including estimates \r\nof historical warming, future emissions from thawing \r\npermafrost, variations in projected non-CO2 warming, and \r\nthe global surface temperature change after cessation of \r\nCO2 emissions, affect the exact value of carbon budgets (high \r\nconfidence). {1.3.5, Box 1.2, 4.7.1, 5.5}"


id: d4b6feb38413891bd26909fb38c589ad
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34743
content:
"but they may vary by an estimated +-220 GtCO2 depending on \r\nhow deeply future non-CO2 emissions are assumed to be reduced \r\n(Table TS.3). {5.5.2, 5.6, Box 5.2, 7.6}"


id: 6f28261d4397f2ee4a0c5b128127d34e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16825
content:
"There is high confidence that several factors, including estimates of \r\nhistorical warming, future emissions from thawing permafrost, and \r\nvariations in projected non-CO2 warming, affect the value of carbon \r\nbudgets but do not change the conclusion that global CO2 emissions \r\nwould need to decline to net zero to halt global warming. Estimates \r\nmay vary by +-220 GtCO2 depending on the level of non-CO2 emissions \r\nat the time global anthropogenic CO2 emissions reach net zero levels. \r\nThis variation is referred to as non-CO2 scenario uncertainty and \r\nwill be further assessed in the AR6 Working Group III Contribution. \r\nGeophysical uncertainties surrounding the climate response to these \r\nnon-CO2 emissions result in an additional uncertainty of at least \r\n+-220  GtCO2, and uncertainties in the level of historical warming \r\nresult in a +-550 GtCO2 uncertainty. {5.4, 5.5.2}"


id: 55e733cbce94be6bbb6f8a67134cc452
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12384
content:
"Table TS.3 | Estimates of remaining carbon budgets and their uncertainties. Assessed estimates are provided for additional human-induced warming, expressed as \r\nglobal surface temperature, since the recent past (2010-2019), likely amounted to 0.8deg to 1.3degC with a best estimate of 1.07degC relative to 1850-1900. Historical CO2 emissions \r\nbetween 1850 and 2014 have been estimated at about 2180 +- 240 GtCO2 (1-sigma range), while since 1 January 2015, an additional 210 GtCO2 has been emitted until the \r\nend of 2019. GtCO2 values to the nearest 50. {Table 3.1, 5.5.1, 5.5.2, Box 5.2, Table 5.1, Table 5.7, Table 5.8}"


id: d94123eccd87acb975c025757fad4dd4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35518
content:
"a\r\n Human-induced global surface temperature increase between 1850-1900 and 2010-2019 is assessed at 0.8-1.3degC (likely range; Cross-Section Box TS.1) with a best estimate \r\nof 1.07degC. Combined with a central estimate of TCRE (1.65degC per 1000 PgC) this uncertainty in isolation results in a potential variation of remaining carbon budgets of +-550 \r\nGtCO2, which, however, is not independent of the assessed uncertainty of TCRE and thus not fully additional."


id: f58269ce71d680916d8129ada0449a3
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40557
content:
"b\r\n TCRE: transient climate response to cumulative emissions of carbon dioxide, assessed to fall likely between 1.0-2.3degC per 1000 PgC with a normal distribution, from which \r\nthe percentiles are taken. Additional Earth system feedbacks are included in the remaining carbon budget estimates as discussed in Section 5.5.2.2.5."


id: 2b73fb14da43383ec3b0a0bd12aef8f2
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4898
content:
"c\r\n Estimates assume that non-CO2 emissions are mitigated consistent with the median reductions found in scenarios in the literature as assessed in SR1.5. Non-CO2 scenario \r\nvariations indicate how much remaining carbon budget estimates vary due to different scenario assumptions related to the future evolution of non-CO2 emissions in mitigation \r\nscenarios from SR1.5 that reach net zero CO2 emissions. This variation is additional to the uncertainty in TCRE. The Working Group III Contribution to AR6 will reassess the \r\npotential for non-CO2 mitigation based on literature since SR1.5."


id: 9765f2838c165bf0c4882b5955efc57
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23846
content:
"d\r\n Geophysical uncertainties reported in these columns and TCRE uncertainty are not statistically independent, as uncertainty in TCRE depends on uncertainty in the assessment \r\nof historical temperature, non-CO2 versus CO2 forcing, and uncertainty in emissions estimates. These estimates cannot be formally combined, and these uncertainty variations \r\nare not directly additional to the spread of remaining carbon budgets due to TCRE uncertainty reported in columns three to seven.\r\ne\r\n Recent emissions uncertainty reflects the +-10% uncertainty in the historical CO2 emissions estimate since 1 January 2015."


id: e6010a6e0e4534c5adcd849e2996269f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37762
content:
"to be removed to compensate for an emission of a given \r\nmagnitude to attain the same change in atmospheric CO2\r\n(medium confidence). CDR methods have wide-ranging side\u0002effects that can either weaken or strengthen the carbon \r\nsequestration and cooling potential of these methods and \r\naffect the achievement of sustainable development goals \r\n(high confidence). {4.6.3, 5.6}"


id: a844cc2cf6d4dd4b17dff36f99ef2e8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26826
content:
"Based on idealized model simulations that explore the climate \r\nresponse once CO2 emissions have been brought to zero, the \r\nmagnitude of the zero CO2 emissions commitment (ZEC, see Glossary) \r\nis assessed to be likely smaller than 0.3degC for time scales of about \r\nhalf a century and cumulative CO2 emissions broadly consistent with \r\nglobal warming of 2degC. However, there is low confidence about its \r\nsign on time scales of about half a century. For lower cumulative CO2\r\nemissions, the range would be smaller yet with equal uncertainty \r\nabout the sign. If the ZEC is positive on decadal time scales, additional \r\nwarming leads to a reduction in the estimates of remaining carbon \r\nbudgets, and vice versa if it is negative. {4.7.1, 5.5.2}"


id: 3bc7fab0ba67768205b2cbe19416e5cc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7701
content:
"Permafrost thaw is included in estimates together with other \r\nfeedbacks that are often not captured by models. Limitations in \r\nmodelling studies combined with weak observational constraints \r\nonly allow low confidence in the magnitude of these estimates \r\n(Section TS.3.2.2). Despite the large uncertainties surrounding the \r\nquantification of the effect of additional Earth system feedback \r\nprocesses, such as emissions from wetlands and permafrost thaw, \r\nthese feedbacks represent identified additional risk factors that \r\nscale with additional warming and mostly increase the challenge of \r\nlimiting warming to specific temperature levels. These uncertainties \r\ndo not change the basic conclusion that global CO2 emissions would \r\nneed to decline to net zero to halt global warming. {5.4.8, 5.5.2, \r\nBox 5.1}"


id: 4f902786ed9351c4cc5cd10e2b9b1e95
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11285
content:
"Due to non-linearities in the climate system, the century-scale \r\nclimate-carbon cycle response to a CO2 removal from the atmosphere \r\nis not always equal and opposite to its response to a simultaneous \r\nCO2 emission (medium confidence). For CO2 emissions of 100 PgC \r\nreleased from a state in equilibrium with pre-industrial atmospheric \r\nCO2 levels, CMIP6 models simulate that 27+- 6% (mean +- 1 standard \r\ndeviation) of emissions remain in the atmosphere 80-100 years \r\nafter the emissions, whereas for removals of 100 PgC only 23 \r\n+- 6% of removals remain out of the atmosphere. This asymmetry \r\nimplies that an extra amount of CDR is required to compensate for \r\na positive emission of a given magnitude to attain the same change \r\nin atmospheric CO2. Due to low agreement between models, there "


id: 41576da4a6edac2b23b7df6e04616489
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8680
content:
"Deliberate carbon dioxide removal (CDR) from the \r\natmosphere has the potential to compensate for residual \r\nCO2 emissions to reach net zero CO2 emissions or to \r\ngenerate net negative CO2 emissions. In the same way \r\nthat part of current anthropogenic net CO2 emissions \r\nare taken up by land and ocean carbon stores, net CO2\r\nremoval will be partially counteracted by CO2 release from \r\nthese stores (very high confidence). Asymmetry in the \r\ncarbon cycle response to simultaneous CO2 emissions and \r\nremovals implies that a larger amount of CO2 would need "


id: 567b8c48bebb72165c150f3368cb114a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12474
content:
"is low confidence in the sign of the asymmetry of the temperature \r\nresponse to CO2 emissions and removals. {4.6.3, 5.6.2.1, Figure 5.35}"


id: 6e3dcd570689d614ed43bc45cfe6a1c1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16663
content:
"When including other GHGs, the choice of emissions metric \r\naffects the quantification of net zero GHG emissions and \r\ntheir resulting temperature outcome (high confidence). \r\nReaching and sustaining net zero GHG emissions typically \r\nleads to a peak and decline in temperatures when \r\nquantified with the global warming potential over a 100-\r\nyear period (GWP-100). Carbon-cycle responses are more \r\nrobustly accounted for in emissions metrics compared to \r\nAR5 (high confidence). New emissions metric approaches \r\ncan be used to generate equivalent cumulative emissions \r\nof CO2 for short-lived greenhouse gases based on their rate \r\nof emissions. {7.6.2}"


id: 12df129df264383bf9041c9db8fe9ac1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 524
content:
"Over 10- to 20-year time scales, the temperature response \r\nto a single year's worth of current emissions of short\u0002lived climate forcers (SLCFs) is at least as large as that of \r\nCO2, but because the effects of SLCFs decay rapidly over \r\nthe first few decades after emission, the net long-term \r\ntemperature response to a single year's worth of emissions \r\nis predominantly determined by cumulative CO2 emissions. "


id: e4729919737fed639bf4bd3a2e996c8e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37483
content:
"As pointed out in AR5, ultimately, it is a matter for policymakers \r\nto decide which emissions metric is most applicable to their needs. \r\nThis Report does not recommend the use of any specific emissions \r\nmetric, as the most appropriate metric depends on the policy goal \r\nand context (see Chapter 7, Section 7.6). A detailed assessment of \r\nGHG metrics to support climate change mitigation and associated \r\npolicy contexts is provided in the WGIII contribution to the AR6."


id: 51ca65f4b0c6a0398bf9b8ae58ae87bf
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11676
content:
"Emissions reductions in 2020 associated with COVID-19 \r\ncontainment led to small and positive global ERF; however, \r\nglobal and regional climate responses to the forcing are \r\nundetectable above internal variability due to the temporary \r\nnature of emissions reductions. {6.6, Cross-Chapter Box 6.1}"


id: 54a15c4da774d4d4224648a1bcb3704d
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12165
content:
"New emissions metric approaches, such as GWP* and Combined\u0002GTP (CGTP), relate changes in the emissions rate of short-lived \r\ngreenhouse gases to equivalent cumulative emissions of CO2\r\n(CO2-e). Global surface temperature response from aggregated \r\nemissions of short-lived greenhouse gases over time is determined \r\nby multiplying these cumulative CO2-e by TCRE (see Section TS.3.2.1). \r\nWhen GHGs are aggregated using standard metrics such as GWP or \r\nGTP, cumulative CO2-e emissions are not necessarily proportional to "


id: b99de6d30b3acba262670330abe35c1c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29865
content:
"COVID-19 restrictions led to detectable reductions in global \r\nanthropogenic emissions of nitrogen oxides (NOx) (about 35% in \r\nApril 2020) and fossil CO2 (7%, with estimates ranging from 5.8% to \r\n13.0%), driven largely by reduced emissions from the transportation "


id: f9e464a5988897a1aad77e53244496c2
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41328
content:
"temporarily adding to the total anthropogenic climate influence, \r\nwith positive forcing (warming influence) from aerosol changes \r\ndominating over negative forcings (cooling influence) from CO2, NOx\r\nand contrail cirrus changes. Consistent with this small net radiative \r\nforcing, and against a large component of internal variability, Earth \r\nsystem models show no detectable effect on global or regional \r\nsurface temperature or precipitation (high confidence). {Cross \r\nChapter Box 6.1}"


id: 186a9756e0c6b45699c12d15bee1029b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1507
content:
"sector (medium confidence). There is high confidence that, with \r\nthe exception of surface ozone, reductions in pollutant precursors \r\ncontributed to temporarily improved air quality in most regions of \r\nthe world. However, these reductions were lower than what would \r\nbe expected from sustained implementation of policies addressing \r\nair quality and climate change (medium confidence). Overall, the net \r\nglobal ERF from COVID-19 containment was likely small and positive \r\nfor 2020 (with a temporary peak value less than 0.2 W m-2), thus "


id: 87073c940a53d1afb8d04c6d3d4ea569
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20916
content:
"Box TS.7 | Climate and Air Quality Responses to Short-lived Climate Forcers in Shared \r\nSocio-economic Pathways"


id: 8ca5a74deab3d072e29b45834da1162a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21930
content:
"Future changes in emissions of short-lived climate forcers (SLCFs) are expected to cause an additional global mean \r\nwarming, with a large diversity in the end-of-century response across the WGI core set of Shared Socio-economic \r\nPathways (SSPs), depending upon the level of climate change and air pollution mitigation (Box TS.7, Figure 1). This \r\nadditional warming is either due to reductions in cooling aerosols for air pollution regulation or due to increases in \r\nmethane (CH4), ozone and hydrofluorocarbons (HFCs). This additional warming is stable after 2040 in SSPs associated \r\nwith lower global air pollution as long as CH4 emissions are also mitigated, but the overall warming induced by SLCF \r\nchanges is higher in scenarios in which air quality continues to deteriorate (induced by growing fossil fuel use and \r\nlimited air pollution control) (high confidence). "


id: d9803508ddbeb7a3f631cdd56a94be7d
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35564
content:
"Sustained CH4 mitigation reduces global surface ozone, contributing to air quality improvements, and also reduces \r\nsurface temperature in the longer term, but only sustained CO2 emissions reductions allow long-term climate \r\nstabilization (high confidence). Future changes in air quality (near-surface ozone and particulate matter, or PM) at \r\nglobal and local scales are predominantly driven by changes in ozone and aerosol precursor emissions rather than \r\nclimate (high confidence). Air quality improvements driven by rapid decarbonization strategies, as in SSP1-1.9 and \r\nSSP1-2.6, are not sufficient in the near term to achieve air quality guidelines set by the World Health Organization in \r\nsome highly polluted regions (high confidence). Additional policies (e.g., access to clean energy, waste management) \r\nenvisaged to attain United Nations Sustainable Development Goals bring complementary SLCF reduction. {4.4.4, 6.6.3, \r\n6.7.3, Box 6.2}"


id: aef0b9347cbe55c93b4930e8443ffc2
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28020
content:
"The net effect of SLCF emissions changes on temperature will depend on how emissions of warming and cooling SLCFs will evolve \r\nin the future. The magnitude of the cooling effect of aerosols remains the largest uncertainty in the effect of SLCFs in future climate \r\nprojections. Since the SLCFs have undergone large changes over the past two decades, the temperature and air pollution responses \r\nare estimated relative to the year 2019 instead of 1995-2014."


id: d028b429d8e8cce441755a0406fd0cda
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33983
content:
"Assuming implementation and efficient enforcement of both the Kigali Amendment to the Montreal Protocol on Substances that \r\nDeplete the Ozone Layer and current national plans result in limiting emissions (as in SSP1-2.6), the effects of HFCs on global \r\nsurface temperature, relative to 2019, would remain below +0. 02degC from 2050 onwards versus about +0.04degC-0.08degC in 2050 and \r\n+0.1degC-0.3degC in 2100 considering only national HFC regulations decided prior to the Kigali Amendment (as in SSP5-8.5) (medium \r\nconfidence). {6.6.3, 6.7.3}"


id: ff03707c4d4009e5ed051ee1249578bc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 42265
content:
"Air pollution projections range from strong reductions in global surface ozone and PM (e.g., SSP1-2.6, with stringent mitigation of both \r\nair pollution and climate change) to no improvement and even degradation (e.g., SSP3-7.0 without climate change mitigation and \r\nwith only weak air pollution control) (high confidence). Under the SSP3-7.0 scenario, PM levels are projected to increase until 2050 \r\nover large parts of Asia, and surface ozone pollution is projected to worsen over all continental areas through 2100 (high confidence). \r\nIn SSP5-8.5, a scenario without climate change mitigation but with stringent air pollution control, PM levels decline through 2100, but \r\nhigh CH4 levels hamper the decline in global surface ozone at least until 2080 (high confidence). {6.7.1}"


id: 9f392e0bc61549c4e50ebb78bd1959ad
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 25236
content:
"Although cirrus cloud thinning aims to cool the planet by increasing longwave emissions to space, it is included in the portfolio of SRM options for consistency with AR5 and SR1.5. {4.6.3.3"


id: a555be8ad9d253220dc7dc1d1d06d44e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26317
content:
"Solar radiation modification (SRM) refers to deliberate, large-scale climate intervention options that are studied as potential \r\nsupplements to deep mitigation, for example, in scenarios that overshoot climate stabilization goals. SRM options aim to offset some \r\nof the warming effects of GHG emissions by modification of Earth's shortwave radiation budget. Following SR1.5, the SRM assessed \r\nin this Report also includes some options, such as cirrus cloud thinning, that alter the longwave radiation budget. "


id: d123e938d37391d5436f5a21888828ab
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34145
content:
"SRM contrasts with climate change mitigation activities, such as emissions reductions and CDR, as it introduces a 'mask' to the \r\nclimate change problem by altering Earth's radiation budget, rather than attempting to address the root cause of the problem, which \r\nis the increase in GHGs in the atmosphere. By masking only the climate effects of GHG emissions, SRM does not address other issues \r\nrelated to atmospheric CO2 increase, such as ocean acidification. This Report assesses physical understanding of the Earth system \r\nresponse to proposed SRM, and the assessment is based primarily on idealized climate model simulations. There are other important \r\nconsiderations, such as risk to human and natural systems, perceptions, ethics, cost, governance, and trans-boundary issues and their \r\nrelationship to the United Nations Sustainable Development Goals - issues that the WGII (Chapter 16) and WGIII (Chapter 14) Reports \r\naddress. {4.6.3}"


id: 35663f7be096725eef01d82690e3599
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6641
content:
"SRM options include those that increase surface albedo, brighten marine clouds by increasing the amount of cloud condensation \r\nnuclei, or reduce the optical depth of cirrus clouds by seeding them with ice nucleating particles. However, the most commonly studied \r\napproaches attempt to mimic the cooling effects of major volcanic eruptions by injecting reflective aerosols (e.g., sulphate aerosols) \r\nor their precursors (e.g., sulphur dioxide) into the stratosphere. {4.6.3, 5.6.3, 6.4.6}"


id: 60d53d296f3476cad29757b4e1d7e017
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14335
content:
"SRM could offset some effects of greenhouse gas-induced warming on global and regional climate, but there would be substantial \r\nresidual and overcompensating climate change at the regional scale and seasonal time scales (high confidence). Since AR5, more \r\nmodelling work has been conducted with more sophisticated treatment of aerosol-based SRM approaches, but the uncertainties in \r\ncloud-aerosol-radiation interactions are still large (high confidence). Modelling studies suggest that it is possible to stabilize multiple \r\nlarge-scale temperature indicators simultaneously by tailoring the deployment strategy of SRM options (medium confidence) but with \r\nlarge residual or overcompensating regional and seasonal climate changes. {4.6.3}"


id: 86c671f735f805eebbe4bfe563d42056
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20878
content:
"SRM approaches targeting shortwave radiation are likely to reduce global mean precipitation, relative to future CO2 emissions \r\nscenarios, if all global mean warming is offset. In contrast, cirrus cloud thinning, targeting longwave radiation, is expected to cause \r\nan increase in global mean precipitation (medium confidence). If shortwave approaches are used to offset global mean warming, \r\nthe magnitude of reduction in regional precipitation minus evapotranspiration (P-E) (Box TS.5), which is more relevant to freshwater \r\navailability, is smaller than precipitation decrease because of simultaneous reductions in both precipitation and evapotranspiration \r\n(medium confidence). {4.6.3, 8.2.1, 8.6.3}."


id: f1a587abd014cff9e3dfb0babb51ed4e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39896
content:
"If SRM is used to cool the planet, it would cause a reduction in plant and soil respiration and slow the reduction of ocean carbon \r\nuptake due to warming (medium confidence). The result would be an enhancement of the global land and ocean CO2 sinks (medium \r\nconfidence) and a slight reduction in atmospheric CO2 concentration relative to unmitigated climate change. However, SRM would \r\nnot stop CO2 from increasing in the atmosphere or affect the resulting ocean acidification under continued anthropogenic emissions \r\n(high confidence). {5.6.3}"


id: e51e2149582e9376674c25b283e559da
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37607
content:
"The effect of stratospheric aerosol injection on global temperature and precipitation is projected by models to be detectable after one \r\nto two decades, which is similar to the time scale for the emergence of the benefits of emissions reductions. A sudden and sustained \r\ntermination of SRM in a high GHG emissions scenario would cause rapid climate change and a reversal of the SRM effects on the \r\ncarbon sinks (high confidence). It is also likely that a termination of strong SRM would drive abrupt changes in the water cycle globally \r\nand regionally, especially in the tropical regions by shifting the Inter-tropical Convergence Zone and Hadley cells. At the regional scale, \r\nnon-linear responses cannot be excluded, due to changes in evapotranspiration. However, a gradual phase-out of SRM combined with \r\nemissions reductions and CDR would avoid larger rates of changes (medium confidence). {4.6.3, 5.6.3, 8.6.3}."


id: 38f1c2b63f0f1dbc7975411c4bec86a1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7225
content:
"The present rates of response of many aspects of the climate system are proportionate to the rate of recent temperature \r\nchange, but some aspects may respond disproportionately. Some climate system components are slow to respond, \r\nsuch as the deep ocean overturning circulation and the ice sheets (Box TS.4). It is virtually certain that irreversible, \r\ncommitted change is already underway for the slow-to-respond processes as they come into adjustment for past and \r\npresent emissions. "


id: aafd10a3ddd21634a4435b009810f370
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27308
content:
"The paleoclimate record indicates that tipping elements exist in the climate system where processes undergo sudden \r\nshifts toward a different sensitivity to forcing, such as during a major deglaciation, where 1degC degree of temperature \r\nchange might correspond to a large or small ice-sheet mass loss during different stages (Box TS.2). For global climate \r\nindicators, evidence for abrupt change is limited, but deep ocean warming, acidification and sea level rise are committed \r\nto ongoing change for millennia after global surface temperatures initially stabilize and are irreversible on human time \r\nscales (very high confidence). At the regional scale, abrupt responses, tipping points and even reversals in the direction of \r\nchange cannot be excluded (high confidence). Some regional abrupt changes and tipping points could have severe local \r\nimpacts, such as unprecedented weather, extreme temperatures and increased frequency of droughts and forest fires. "


id: 2c9996599186963a29948df9cc6b54ad
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5111
content:
"Models that exhibit such tipping points are characterized by abrupt changes once the threshold is crossed, and even \r\na return to pre-threshold surface temperatures or to atmospheric carbon dioxide concentrations does not guarantee \r\nthat the tipping elements return to their pre-threshold state. Monitoring and early warning systems are being put into \r\nplace to observe tipping elements in the climate system. {1.3, 1.4.4, 1.5, 4.3.2, Table 4.10, 5.3.4, 5.4.9, 7.5.3, 9.2.2, \r\n9.2.4, 9.4.1, 9.4.2, 9.6.3, Cross-chapter Box 12.1}"


id: 9740686b33b04bf4d1cdd6450fc5957b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23804
content:
"Understanding of multi-decadal reversibility (i.e., the system returns to the previous climate state within multiple decades after \r\nthe radiative forcing is removed) has improved since AR5 for many atmospheric, land surface and sea ice climate metrics following \r\nsea surface temperature recovery. Some processes suspected of having tipping points, such as the Atlantic Meridional Overturning \r\nCirculation (AMOC), have been found to often undergo recovery after temperature stabilization with a time delay (low confidence). \r\nHowever, substantial irreversibility is further substantiated for some cryosphere changes, ocean warming, sea level rise, and ocean \r\nacidification. {4.7.2, 5.3.3, 5.4.9, 9.2.2, 9.2.4, 9.4.1, 9.4.2, 9.6.3}"


id: 7a611957cdc149c687e56afd2c3e7905
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18725
content:
"The response of biogeochemical cycles to anthropogenic perturbations can be abrupt at regional scales and irreversible on decadal to \r\ncentury time scales (high confidence). The probability of crossing uncertain regional thresholds increases with climate change (high "


id: f844fc88bc9c5e537cb97dd4ce5c0b1e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41054
content:
"requirements, and demand (very high confidence). The \r\ndecision-making context, level of user engagement, \r\nand co-production between scientists, practitioners and \r\nusers are important determinants of the type of climate \r\nservice developed and its utility in supporting adaptation, \r\nmitigation and risk management decisions. {10.3, 10.6, \r\nCross-Chapter Box 10.3, 12.6, Cross-Chapter Box 12.2}"


id: b3a9555f4ef9f719ed4ac7d3424a1798
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28853
content:
"This section focuses on how to generate regional climate change \r\ninformation and its relevance for climate services; the drivers of regional \r\nclimate variability and change and how they are being affected by \r\nanthropogenic factors; and observed, attributed and projected changes \r\nin climate, including extreme events and climatic impact-drivers (CIDs), \r\nacross all regions of the world. There is a small set of CID changes \r\ncommon to all land or ocean regions and a specific set of changes from \r\na broader range of CIDs seen in each region. This regional diversity \r\nresults from regional climate being determined by a complex interplay \r\nbetween the seasonal-to-multi-decadal variation of large-scale modes \r\nof climate variability, external natural and anthropogenic forcings, local \r\nclimate processes and related feedbacks."


id: e5b323f3b783ca3e022ee024254d2eef
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37715
content:
"Climate change information at regional scale is generated \r\nusing a range of data sources and methodologies. Multi\u0002model ensembles and models with a range of resolutions \r\nare important data sources, and discarding models that \r\nfundamentally misrepresent relevant processes improves \r\nthe credibility of ensemble information related to these \r\nprocesses. A key methodology is distillation - combining \r\nlines of evidence and accounting for stakeholder context \r\nand values - which helps ensure the information is relevant, \r\nuseful and trusted for decision-making (see Core Concepts \r\nBox) (high confidence). "


id: 6e7055d565606809e623553f24d69a58
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16691
content:
"Since AR5, physical climate storylines have emerged as \r\na complementary approach to ensemble projections for \r\ngenerating more accessible climate information and \r\npromoting a more comprehensive treatment of risk. They \r\nhave been used as part of the distillation process within \r\nclimate services to generate the required context-relevant, \r\ncredible and trusted climate information. "


id: 4315ea6b78a1f5bfbea0a68b34897a6a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9007
content:
"Depending on the region of interest, representing regionally important \r\nforcings (e.g., aerosols, land-use change and ozone concentrations) \r\nand feedbacks (e.g., between snow and albedo, soil moisture and \r\ntemperature, or soil moisture and precipitation) in climate models is a \r\nprerequisite for them to reproduce past regional trends to underpin the "


id: 5c7f9a2940f6b9b3e40607ec82738daa
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13534
content:
"Methodologies such as statistical downscaling, bias adjustment and \r\nweather generators are beneficial as an interface between climate \r\nmodel projections and impact modelling and for deriving user\u0002relevant indicators (high confidence). However, the performance of \r\nthese techniques depends on that of the driving climate model: in \r\nparticular, bias adjustment cannot overcome all consequences of \r\nunresolved or strongly misrepresented physical processes, such as \r\nlarge-scale circulation biases or local feedbacks (medium confidence). \r\n{10.3.3, Cross-Chapter Box 10.2, 12.2, Atlas.2.2}"


id: 85dcafd367061f1fb4ce8b865333c3b0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20695
content:
"reliability of future projections (medium confidence) (Section TS.1.2.2). \r\nIn some cases, even the sign of a projected change in regional climate \r\ncannot be trusted if relevant regional processes are not represented, for \r\nexample, for variables such as precipitation and wind speed (medium \r\nconfidence). In some regions, either geographical (e.g., Central Africa, \r\nAntarctica) or typological (e.g., mountainous areas, Small Islands and \r\ncities), and for certain phenomena, fewer observational records are \r\navailable or accessible, which limits the assessment of regional climate \r\nchange in these cases. {1.5.1, 1.5.3, 1.5.4, 8.5.1, 10.2, 10.3.3, 10.4.1, \r\n11.1.6, 11.2, 12.4, Atlas.8.3, Atlas.11.1.5, Cross-Chapter Box Atlas.2}"


id: b0ad4fe5a353f6e9614a6f61f4a5ca1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28311
content:
"The attribution of observed changes in extremes to human influence (including greenhouse gas and aerosol emissions \r\nand land-use changes) has substantially advanced since AR5, in particular for extreme precipitation, droughts, \r\ntropical cyclones, and compound extremes (high confidence). There is limited evidence for windstorms and convective \r\nstorms. Some recent hot extreme events would have been extremely unlikely to occur without human influence on the \r\nclimate system. (Section TS.1) {Cross-Working Group Box: Attribution in Chapter 1, 11.2, 11.3, 11.4, 11.6, 11.7, 11.8}"


id: 68f03056d25588766861ba224c1bac89
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15732
content:
"Since AR5, the attribution of extreme weather events has emerged as a growing field of climate research with an increasing body of \r\nliterature. It provides evidence that greenhouse gases and other external forcings have affected individual extreme weather events \r\nby disentangling anthropogenic drivers from natural variability. Event attribution is now an important line of evidence for assessing \r\nchanges in extremes on regional scales. (Section TS.1) {Cross-Working Group Box: Attribution, 11.1.4}"


id: 853e660f516f2e94c4e014fb88d0522a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20581
content:
"It is very likely that human influence is the main contributor to the observed increase in the intensity and frequency of hot extremes and \r\nthe observed decrease in the intensity and frequency of cold extremes on continental scales. Some specific recent hot extreme events \r\nwould have been extremely unlikely to occur without human influence on the climate system. Changes in aerosol concentrations \r\nhave likely slowed the increase in hot extremes in some regions, in particular from 1950-1980. No-till farming, irrigation and crop \r\nexpansion have similarly attenuated increases in summer hot extremes in some regions, such as central North America (medium \r\nconfidence). {11.3.4}"


id: 186ca256e7801ecec85378d4309ed472
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1509
content:
"Human influence has contributed to the intensification of heavy precipitation in three continents where observational data are most \r\nabundant: North America, Europe and Asia (high confidence). On regional scales, evidence of human influence on extreme precipitation \r\nis limited, but new evidence from attributing individual heavy precipitation events found that human influence was a significant driver \r\nof the events. {11.4.4}"


id: 1911288b0189e86c20d751550e04e045
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1626
content:
"There is low confidence that human influence has affected trends in meteorological droughts in most regions, but medium confidence\r\nthat they have contributed to the severity of some specific events. There is medium confidence that human-induced climate change \r\nhas contributed to increasing trends in the probability or intensity of recent agricultural and ecological droughts, leading to an \r\nincrease of the affected land area. {11.6.4}"


id: f5fe67d48506272382b127983a0f15ea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40636
content:
"Event attribution studies of specific strong tropical cyclones provide limited evidence for anthropogenic effects on tropical cyclone \r\nintensifications so far, but high confidence for increases in precipitation. There is high confidence that anthropogenic climate change \r\ncontributed to extreme rainfall amounts during Hurricane Harvey (in 2017) and other intense tropical cyclones. {11.7.3}"


id: 78515b8ff1718b3c93f7c36d3200ab88
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18375
content:
"The number of evident attribution studies on compound events is limited. There is medium confidence that weather conditions that \r\npromote wildfires have become more probable in southern Europe, northern Eurasia, the USA, and Australia over the last century. In \r\nAustralia a number of event attribution studies show that there is medium confidence of increase in fire weather conditions due to \r\nhuman influence. {11.8.3, 12.4.3.2}"


id: 821984308b081b1d67cc1a024d249928
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20010
content:
"changes in a key mode of variability (the Southern Annular Mode) \r\nand drought in Cape Town among different observation periods and \r\nin model simulations. {10.5.3, 10.6, 10.6.2, 10.6.4, Cross-Chapter \r\nBox 10.3, 12.4}"


id: b6d5939f59758ca8623ad60223879af8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29364
content:
"The construction of regional climate information involves people with \r\na variety of backgrounds, from various disciplines, who have different \r\nsets of experiences, capabilities and values. The process of synthesizing \r\nclimate information from different lines of evidence from a number \r\nof sources, taking into account the context of a user vulnerable to \r\nclimate variability and change and the values of all relevant actors, is \r\ncalled distillation. Distillation is conditioned by the sources available, \r\nthe actors involved, and the context, which all depend heavily on the \r\nregions considered, and is framed by the question being addressed. \r\nDistilling regional climate information from multiple lines of evidence \r\nand taking the user context into account increases fitness, usefulness, \r\nrelevance and trust in that information for use in climate services \r\n(Box TS.11) and decision-making (high confidence). {1.2.3, 10.1.4, \r\n10.5, Cross-Chapter Box 10.3, 12.6}"


id: e57444add5adc20a0dbb73de569da882
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37674
content:
"Climate services involve providing climate information to assist decision-making, for example, about how extreme \r\nrainfall will change to inform improvements in urban drainage. Since AR5, there has been a significant increase in the \r\nrange and diversity of climate service activities (very high confidence). The level of user-engagement, co-design and \r\nco-production are factors determining the utility of climate services, while resource limitations for these activities \r\nconstrain their full potential. {12.6, Cross-Chapter Box 12.2}"


id: c4213df35955299a110bb9bc6253af7c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31792
content:
"Climate services include engagement from users and providers and an effective access mechanism; they are responsive to user needs \r\nand based on integrating scientifically credible information and relevant expertise. Climate services are being developed across \r\nregions, sectors, time scales and user-groups and include a range of knowledge brokerage and integration activities. These involve \r\nidentifying knowledge needs; compiling, translating and disseminating knowledge; coordinating networks and building capacity \r\nthrough informed decision-making; analysis, evaluation and development of policy; and personal consultation."


id: 618de4d3e1355f710155b51edd33f252
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14455
content:
"Since AR5, climate change information produced in climate service contexts has increased significantly due to scientific and \r\ntechnological advancements and growing user awareness, requirements and demand (very high confidence). Climate services are \r\ngrowing rapidly and are highly diverse in their practices and products. The decision-making context, level of user engagement and co\u0002production between scientists, practitioners and intended users are important determinants of the type of climate service developed \r\nand their utility for supporting adaptation, mitigation and risk management decisions. They require different types of user-producer \r\nengagement depending on what the service aims to deliver (high confidence), and these fall into three broad categories: website\u0002based services, interactive group activities and focused relationships."


id: e82ac5ddff6cc8df4f4dabf0b8cbdbe0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 38173
content:
"Realization of the full potential of climate services is often hindered by limited resources for the co-design and co-production process, \r\nincluding sustained engagement between scientists, service providers and users (high confidence). Further challenges relate to the \r\ndevelopment and provision of climate services, generation of climate service products, communication with users, and evaluation of \r\ntheir quality and socio-economic benefit. (Section TS.4.1) {1.2.3, 10.5.4, 12.6, Cross-Chapter Box 12.2, Glossary}"


id: c6bc0b016400fc388ecf52ae6dbc74fc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 32264
content:
"Box TS.12 | Multiple Lines of Evidence for Assessing Regional Climate Change and the \r\nInteractive Atlas"


id: bd5cd208c4897d9178646ba6427e95ec
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 30563
content:
"A key novel element in the AR6 is the Working Group I Atlas, which includes the Interactive Atlas (https://interactive\u0002atlas.ipcc.ch/). The Interactive Atlas provides the ability to explore much of the observational and climate model data \r\nused as lines of evidence in this assessment to generate regional climate information. {Atlas.2}"


id: a242a871af9d20b120a318e49bc1ff28
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 25777
content:
"Box TS.12, Figure 1 shows how the Interactive Atlas products, together with other lines of evidence, can be used to generate climate \r\ninformation for an illustrative example of the Mediterranean summer warming. The lines of evidence include the understanding of \r\nrelevant mechanisms, dynamic and thermodynamic processes and the effect of aerosols in this case (Box TS.12, Figure 1a); trends \r\nin observational datasets (which can have different spatial and temporal coverage; Box TS.12, Figure 1b, c); and attribution of these \r\ntrends and temperature projections from global and regional climate models at different resolutions, including single-model initial\u0002condition large ensembles (SMILEs; Box TS.12, Figure 1d, e). Taken together, this evidence shows there is high confidence that the "


id: a66ffdff47860669064a67a2bc0cf7c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26504
content:
"projected Mediterranean summer temperature increase will be larger than the global mean, with consistent results from CMIP5 and \r\nCMIP6 (Box TS.12, Figure 1e). However, CMIP6 results project both more pronounced warming than CMIP5 for a given emissions \r\nscenario and time period and a greater range of changes (Box TS.12, Figure 1d). {10.6.4, Atlas.2, Atlas.8.4}"


id: 62be2c50596665f89d3729f50a83c236
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14665
content:
"temperature is moderated or amplified by soil moisture feedback, \r\nsnow/ice-albedo feedback, regional forcing from land-use/land\u0002cover changes, forcing from aerosol concentrations, or decadal/\r\nmulti-decadal natural variability. Changes in local and remote \r\naerosol forcings lead to south-north gradients of the effective \r\nradiative forcing (hemispherical asymmetry). Along latitudes, \r\nit is more uniform, with strong amplification of the temperature \r\nresponse towards the Arctic (medium confidence). The decrease \r\nof SO2 emissions since the 1980s reduces the damping effect of \r\naerosols, leading to a faster increase in surface air temperature \r\nthat is most pronounced at mid- and high latitudes of the Northern \r\nHemisphere, where the largest emissions reductions have taken \r\nplace (medium confidence). {1.3, 3.4.1, 6.3.4, 6.4.1, 6.4.3, 8.3.1, \r\n8.3.2, Box 8.1, 10.4.2, 10.6, 11.1.6, 11.3}"


id: 915846fac48e49828b8f14ad5bfcfee
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22778
content:
"Anthropogenic forcing, including GHGs and aerosols, but \r\nalso regional land use and irrigation have all affected \r\nobserved regional climate changes (high confidence) and \r\nwill continue to do so in the future (high confidence), with \r\nvarious degrees of influence and response times, depending \r\non warming levels, the nature of the forcing and the relative \r\nimportance of internal variability. "


id: ec4850417266ecb18d75ea1f8f33ccb3
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 38935
content:
"Since the late 19th century, major modes of variability \r\n(MoVs) exhibited fluctuations in frequency and magnitude \r\nat multi-decadal time scales, but no sustained trends \r\noutside the range of internal variability (Table TS.4). An \r\nexception is the Southern Annular Mode (SAM), which has \r\nbecome systematically more positive (high confidence) and \r\nis projected to be more positive in all seasons, except for \r\nDecember-January-February (DJF), in high CO2 emissions \r\nscenarios (high confidence). The influence of stratospheric \r\nozone forcing on the SAM trend has been reduced since the \r\nearly 2000s compared to earlier decades, contributing to \r\nthe weakening of its positive trend as observed over 2000-\r\n2019 (medium confidence). "


id: 30c548ff40c0fc2358bf08c91ef992bb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5837
content:
"Multi-decadal dimming and brightening trends in incoming solar \r\nradiation at Earth's surface occurred at widespread locations (high \r\nconfidence). Multi-decadal variation in anthropogenic aerosol \r\nemissions are thought to be a major contributor (medium confidence), \r\nbut multi-decadal variability in cloudiness may also have played a \r\nrole. Volcanic eruptions affect regional climate through their spatially \r\nheterogeneous effect on the radiative budget as well as through \r\ntriggering dynamical responses by favouring a given phase from \r\nsome MoVs, for instance. {1.4.1, Cross-Chapter Box 1.2, 2.2.1, 2.2.2, \r\n3.7.1, 3.7.3, 4.3.1, 4.4.1, 4.4.4, Cross-Chapter Box 4.1, 7.2.2, 8.5.2, \r\n10.1.4, 11.1.6, 11.3.1}"


id: bb359c81e890bb2529f4e126f10c201e
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updated_at: 2023-04-19 13:21:31
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vector_id: 30154
content:
"In the near term, projected changes in most of the MoVs \r\nand related teleconnections will likely be dominated by \r\ninternal variability. In the long term, it is very likely that \r\nthe precipitation variance related to El Nino-Southern \r\nOscillation will increase. Physical climate storylines, \r\nincluding the complex interplay between climate drivers, \r\nMoVs, and local and remote forcing, increase confidence \r\nin the understanding and use of observed and projected \r\nregional changes. {2.4, 3.7, 4.3, 4.4, 4.5, 6.4, 8.3, 8.4, 10.3, \r\n10.4, 11.3}"


id: 3f3386436d2d7e56dea9c763276c7984
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8303
content:
"Historical urbanization affects the observed warming trends in cities \r\nand their surroundings (very high confidence). Future urbanization \r\nwill amplify the projected air temperature under different background \r\nclimates, with a strong effect on minimum temperatures that could \r\nbe as large as the global warming signal (very high confidence) \r\n(Box TS.14). Irrigation and crop expansion have attenuated increases \r\nin summer hot extremes in some regions, such as central North \r\nAmerica (medium confidence) (Box TS.6). {Box 10.3, 11.1.6, 11.3}"


id: d23787b5e947eac35ea5dcd5577a7fd1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34339
content:
"Modes of variability (Annex IV, Table TS.4) have existed for millennia \r\nor longer (high confidence), but there is low confidence in detailed \r\nreconstructions of most of them prior to direct instrumental records. \r\nMoVs are treated as a main source of uncertainties associated with \r\ninternal dynamics, as they can either accentuate or dampen, even \r\nmask, the anthropogenically forced responses. {2.4, 8.5.2, 10.4, 10.6, \r\n11.1.5, Atlas.3.1}"


id: 7dd20c291d0bc382cbf77a2294732636
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19308
content:
"While anthropogenic forcing has contributed to multi-decadal \r\nmean precipitation changes in several regions, internal variability \r\ncan delay emergence of the anthropogenic signal in long-term \r\nprecipitation changes in many land regions (high confidence). At the \r\nregional scale, the effect of human-induced GHG forcing on extreme "


id: d23034b3a4ebbdd0ec5ba025f5a712a1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34333
content:
"contributed to observed temporal evolution in the Atlantic Multi\u0002decadal Variability (AMV) and associated regional teleconnections, \r\nespecially since the 1960s, but there is low confidence in the \r\nmagnitude of this influence and the relative contributions of \r\nnatural and anthropogenic forcings. Internal variability is the \r\nmain driver of Pacific Decadal Variability (PDV) observed since \r\nthe start of the instrumental records (high confidence), despite \r\nsome modelling evidence for potential external influence. There is \r\nmedium confidence that the AMV will undergo a shift towards a \r\nnegative phase in the near term. {2.4, 3.7.6, 3.7.7, 8.5.2, 4.4.3}"


id: 50a8b9cadd413833fd77173f3dc1564d
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11464
content:
"Modes of decadal and multi-decadal variability over the Pacific \r\nand Atlantic Ocean exhibit no significant changes in variance \r\nover the period of observational records (high confidence). There \r\nis medium confidence that anthropogenic and volcanic aerosols "


id: a92a43daa742f7c1e4ca2c99c74af246
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26985
content:
"annual to decadal time scales (high confidence). The anthropogenic \r\nsignal in regional sea level change will emerge in most regions by \r\n2100 (medium confidence). {9.2.4, 9.6.1, 10.4.1, 10.4.2, 10.4.3}"


id: 22b3cbcd6dd45cd5a0d45437643bfc7a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3319
content:
"Anthropogenic forcing has been a major driver of regional mean \r\ntemperature change since 1950 in many sub-continental regions of \r\nthe world (virtually certain). At regional scales, internal variability \r\nis stronger, and uncertainties in observations, models and external \r\nforcing are all larger than at the global scale, hindering a robust \r\nassessment of the relative contributions of greenhouse gases, \r\nstratospheric ozone, and different aerosol species in most of the cases. \r\nMultiple lines of evidence, combining multi-model ensemble global \r\nprojections with those coming from single-model initial-condition \r\nlarge ensembles, show that internal variability is largely contributing \r\nto the delayed or absent emergence of the anthropogenic signal in \r\nlong-term regional mean precipitation changes (high confidence). \r\nInternal variability in ocean dynamics dominates regional patterns on "


id: 535d5ac2875c95b3a97172778a89ef46
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11940
content:
"Regional climate change is subject to the complex interplay between \r\nmultiple external forcings and internal variability. Time evolution \r\nof mechanisms operating at different time scales can modify the \r\namplitude of the regional-scale response of temperature, and \r\nboth the amplitude and sign of the response of precipitation, to \r\nanthropogenic forcing (high confidence). These mechanisms include \r\nnon-linear temperature, precipitation and soil moisture feedbacks; \r\nslow and fast responses of SST patterns; and atmospheric circulation \r\nchanges to increasing GHGs. Land-use and aerosol forcings and \r\nland-atmosphere feedback play important roles in modulating \r\nregional changes, for instance in weather and climate extremes (high \r\nconfidence). These can also lead to a higher warming of extreme "


id: 9df86351f15c2095a478325aa40e807c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 25027
content:
"temperatures compared to mean temperature (high confidence), \r\nand possibly cooling in some regions (medium confidence). The \r\nsoil moisture-temperature feedback was shown to be relevant for \r\npast and present-day heatwaves based on observations and model \r\nsimulations. {10.4.3, 11.1.6, 11.3.1}"


id: 4e66b1aa54f3a02fd875d080558038b0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11067
content:
"South-Eastern South America (SES) is one of the AR6 WGI reference \r\nregions (outlined with black thick contour in Figure TS.21a), and \r\nit is used here as an illustrative example of the interplay between \r\ndrivers of climate variability and change at regional scale. Austral \r\nsummer (DJF) precipitation positive trends have been observed \r\nover the region during 1950-2014. Drivers of this change include \r\nMoVs, such as AMV, ENSO, and PDV, as well as external forcing, \r\nlike GHG increases and ozone depletion together with aerosols (as \r\nillustrated in Figure TS.21a). Modes of variability and external forcing \r\ncollectively affect climate phenomena, such as the Hadley cell width \r\nand strength, Rossby waves activity emerging from the large-scale \r\ntropical SST anomalies, and the Southern Hemisphere polar vortex, "


id: 2e6eb4d9e9d279fca6922b56799079fd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5446
content:
"Global land monsoon precipitation decreased from the 1950s to the 1980s, partly due to anthropogenic aerosols, but \r\nhas increased since then in response to GHG forcing and large-scale multi-decadal variability (medium confidence). \r\nNorthern Hemispheric anthropogenic aerosols weakened the regional monsoon circulations in South Asia, East Asia \r\nand West Africa during the second half of the 20th century, thereby offsetting the expected strengthening of monsoon \r\nprecipitation in response to GHG-induced warming (high confidence). "


id: b516179abf48a7ef34edcb7a83f1c228
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29095
content:
"During the 21st century, global land monsoon precipitation is projected to increase in response to GHG warming in \r\nall time horizons and scenarios (high confidence). Over South and South East Asia, East Asia and the central Sahel, \r\nmonsoon precipitation is projected to increase, whereas over North America and the far western Sahel it is projected \r\nto decrease (medium confidence). There is low confidence in projected precipitation changes in the South American \r\nand Australian-Maritime Continent monsoons. At global and regional scales, near-term monsoon changes will be \r\ndominated by the effects of internal variability (medium confidence). {2.3, Cross-Chapter Box 2.4, 3.3, 4.4, 4.5, 8.2, \r\n8.3, 8.4, 8.5, Box 8.1, Box 8.2, 10.6}"


id: 7e88de6c2cb0ccb8fd8595a9e495ed1e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19413
content:
"Paleoclimate records indicate that during warm climates, like the mid-Pliocene Warm Period, monsoon systems were stronger \r\n(medium confidence). In the instrumental records, global summer monsoon precipitation intensity has likely increased since the \r\n1980s, dominated by Northern Hemisphere summer trends and large multi-decadal variability. Contrary to the expected increase of \r\nprecipitation under global warming, the Northern Hemisphere monsoon regions experienced declining precipitation from the 1950s \r\nto 1980s, which is partly attributable to the influence of anthropogenic aerosols (medium confidence) (Box TS.13, Figure 1). {2.3.1, \r\nCross-Chapter Box 2.4, 3.3.2, 3.3.3}"


id: b10ac6b0bbdcc8461e1f8512b4def5c9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28374
content:
"With continued global warming, it is likely that global land monsoon precipitation will increase during this century (Box TS.13, Figure 1), \r\nparticularly in the Northern Hemisphere, although the monsoon circulation is projected to weaken. A slowdown of the tropical circulation \r\nwith global warming can partly offset the warming-induced strengthening of precipitation in monsoon regions (high confidence). In the \r\nnear term, global monsoon changes are likely to be dominated by the effects of internal variability and model uncertainties (medium \r\nconfidence). In the long term, global monsoon rainfall change will feature a robust north-south asymmetry characterized by a greater \r\nincrease in the Northern Hemisphere than in the Southern Hemisphere and an east-west asymmetry characterized by enhanced Asian-\r\nAfrican monsoons and a weakened North American monsoon (medium confidence). {4.4.1, 4.5.1, 8.4.1}"


id: d7a62789ab44aec05115c88432579a05
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35248
content:
"Paleoclimate reconstructions indicate stronger monsoons in the Northern Hemisphere but weaker ones in the Southern Hemisphere \r\nduring warm periods, particularly for the South and South East Asian, East Asian, and North and South American monsoons, with \r\nthe opposite occurring during cold periods (medium confidence). It is very likely that Northern Hemispheric anthropogenic aerosols \r\nweakened the regional monsoon circulations in South Asia, East Asia and West Africa during the second half of the 20th century, "


id: 888adcd688d32da389b10e22743033f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21186
content:
"thereby offsetting the expected strengthening of monsoon precipitation in response to GHG-induced warming (Box TS.13, Figure 1). \r\nMultiple lines of evidence explain this contrast over South Asia, with the observed trends dominated by the effects of aerosols, while \r\nfuture projections are mostly driven by GHG increases. The recent partial recovery and enhanced intensity of monsoon precipitation \r\nover West Africa is related to the growing influence of GHGs with an additional contribution due to the reduced cooling effect of \r\nanthropogenic aerosols, emitted largely from North America and Europe (medium confidence). For other regional monsoons, that \r\nis, North and South America and Australia, there is low confidence in the attribution of recent changes in precipitation (Box TS.13, \r\nFigure 1) and winds. {2.3.1, 8.3.1, 8.3.2, Box 8.1, 10.6.3}"


id: 310dd0ef53ba95a173d897a149ad47db
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5878
content:
"Building the Assessment from Multiple Lines of Evidence\r\nLarge natural variability of monsoon precipitation across different time scales, found in both paleoclimate reconstructions and \r\ninstrumental measurements, poses an inherent challenge for robust quantification of future changes in precipitation at regional and \r\nsmaller spatial scales. At both global and regional scales, there is medium confidence that internal variability contributes the largest \r\nuncertainty related to projected changes, at least in the near term (2021-2040). A collapse of the Atlantic Meridional Overturning \r\nCirculation could weaken the African and Asian monsoons but strengthen the Southern Hemisphere monsoons (high confidence). \r\n{4.4.4, 4.5.1, Cross-Chapter Box 4.1, 8.5.2, 8.6.1, 9.2.3, 10.6.3}"


id: bc50308871ef9da7f5841e26e91c6e99
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 30376
content:
"Overall, long-term (2081-2100) future changes in regional monsoons like the South and South East Asian monsoon are generally \r\nconsistent across global (including high-resolution) and regional climate models and are supported by theoretical arguments. \r\nUncertainties in simulating the observed characteristics of regional monsoon precipitation are related to varying complexities of \r\nregional monsoon processes and their responses to external forcing, internal variability, and deficiencies in representing monsoon warm \r\nrain processes, organized tropical convection, heavy orographic rainfall and cloud-aerosol interactions. {8.3.2, 8.5.1, 10.3.3, 10.6.3}"


id: 9759d180ad18bbbbba5da0408e24d185
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23830
content:
"Relative sea level rise is very likely to virtually certain\r\n(depending on the region) to continue during the 21st \r\ncentury, contributing to increased coastal flooding in low\u0002lying areas (high confidence) and coastal erosion along \r\nmost sandy coasts (high confidence). Sea level will continue \r\nto rise beyond 2100 (high confidence) (Box TS.4). "


id: 885ebcb9fb41015fd5438f554ef37eee
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21155
content:
"Current climate in all regions is already distinct from the \r\nclimate of the early or mid-20th century with respect to \r\nseveral climatic impact-drivers (CIDs), resulting in shifting \r\nmagnitude, frequency, duration, seasonality and spatial \r\nextent of associated climate indices (high confidence). \r\nIt is very likely that mean temperatures have increased \r\nin all land regions and will continue to increase at rates \r\ngreater than the global average (high confidence). The \r\nfrequency of heat and cold extremes have increased and \r\ndecreased, respectively. These changes are attributed to \r\nhuman influence in almost all regions (medium to high \r\nconfidence) and will continue through the 21st century \r\n(high confidence). In particular, extreme heat would exceed \r\ncritical thresholds for health, agriculture and other sectors \r\nmore frequently by the mid 21st century with 2degC of global \r\nwarming (high confidence). "


id: 406296ff98069a6895a57d50fc7bf250
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8520
content:
"Every region of the world will experience concurrent \r\nchanges in multiple CIDs by mid-century or at 2degC global \r\nwarming and above (high confidence). Even for the current \r\nclimate, climate change-induced shifts in CID distributions \r\nand event probabilities, some of which have occurred over \r\nrecent decades, are relevant for risk assessments. {11.9, \r\n12.1, 12.2, 12.4, 12.5, Atlas.3-Atlas.11}"


id: 3565f46dfc42f1d3a221fc72e30424ea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6640
content:
"An overview of changes in regional CIDs (introduced in Section TS.1) \r\nis given in Table TS.5, which summarizes multiple lines of evidence \r\non regional climate change derived from observed trends, attribution \r\nof these trends and future projections. The level of confidence and "


id: d9133e024fe78a9359be5c9bff16689
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35489
content:
"multiple line\r\nSRES A1B, or a\r\nicate medium a\r\nTables 11.4-11\r\n Ice \r\nHeavy snowfall and ice storm\r\nHail\r\nSnow avalanche\r\nMedium confiof decrease "


id: 68fe82d91f2823c56f0b3a75e3f93ade
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15743
content:
"le TS.5 | Summary o\r\nectional changes. Th\r\nroximately encompass\r\nca is not an AR6 WGI \r\np\r\nrica\r\north Africa / \r\nahara / \r\nestern Africa / \r\nentral Africa / \r\north Eastern \r\nfrica / \r\nouth Eastern \r\nfrica / \r\nest Southern \r\nfrica / \r\nast Southern \r\nfrica / \r\nadagascar / \r\ne: There are several re\r\ny for observational y for attribution evi"


id: 9a797f3aefdfcf3ef057bf6c07a8dfd2
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 24422
content:
"4. Along sandy coasts and in the absence of sufficient sediment supply from terrestrial or offshore sources"


id: 183ff36a3649c9827eebbea962d7a98
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1469
content:
"1. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat."


id: 882b26169893dccd1ad9e9e340bddf9c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21109
content:
"4. Medium confidence of increase in the north and east and decrease in south and west\r\n5. Low confidence of increasing intensity, and high confidence of decreasing occurrence"


id: c466675483f00a0ae34674ede1646140
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31852
content:
"2. Tropical cyclones decrease in number but increase in intensity\r\n3. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat."


id: 606f653ce054f305bfc742aa0a872eb8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14273
content:
"4. Substantial parts of the North-Western South America, Northern South America and North-Eastern South America coasts are projected to prograde if present-day \r\nambient shoreline change rates continue"


id: 52ce464a35f69ec1324fe085cba4af83
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11839
content:
"2. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat"


id: debd3bb192b52250b9724acbd3604632
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 36448
content:
"1. Snow may increase in some high elevations and during the cold season and decrease in other seasons and at lower elevations\r\n2. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat."


id: feadcd42c22729d43e202d1874c8ad7b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 42192
content:
"1. Very high confidence in the direction of change, but low to medium confidence in the magnitude of change due to model uncertainty\r\n2. Decrease in eastern Pacific and southern Pacific subtropics, but increase in parts of western and equatorial Pacific; with seasonal variation in future changes\r\n3. High confidence in increase in extreme rain frequency and intensity in western tropical Pacific; low confidence in magnitude of change due to model bias\r\n4. Increase in southern Pacific"


id: 3b0df71e91dd5692774d1782268db6c6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7581
content:
"6. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat."


id: f73154dbb7aab4a9f1690fe2fff852f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40864
content:
"7. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat"


id: cf5ce196b269794bbdb71a9b83d107de
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33832
content:
"(a) World regions grouped into five clusters, each one based on a combination of changes in climatic impact-driver\r\nAssessed future changes: Changes refer to a 20-30 year period centred around 2050 and/or consistent with 2degC global warming compared to a similar p\r\nwithin 1960-2014 or 1850-1900."


id: 74b257f29660f85d5d554ba967bab1f6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17769
content:
"The height of the lighter shaded 'envelope' behind each bar represents the \r\nmaximum number of regions for which each CID is relevant. The envelope \r\nis symmetrical about the x-axis showing the maximum possible number of \r\nrelevant regions for CID increase (upper part) or decrease (lower part)."


id: 9a7184c9199d8604ca42f8ba14284ce5
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 24418
content:
"Climatic impact-drivers (CIDs) are physical climate system conditions (e.g., means, events, extremes) that affect an element of \r\nsociety or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a \r\nmixture of each across interacting system elements and regions. The CIDs are grouped into seven types, which are summarized \r\nunder the icons in sub-panels (i) and (ii). All regions are projected to experience changes in at least 5 CIDs. Almost all (96%) are \r\nprojected to experience changes in at least 10 CIDs and half in at least 15 CIDs. For many CID changes, there is wide \r\ngeographical variation, and so each region is projected to experience a specific set of CID changes. Each bar in the chart \r\nrepresents a specific geographical set of changes that can be explored in the WGI Interactive Atlas. "


id: 44df26ce30cb335a10d441f2f1c00166
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9343
content:
"Figure TS.22 | Synthesis of the geographical distribution of climatic impact-drivers changes and the number of AR6 WGI reference regions where they \r\nare projected to change. "


id: 6327e2b82fd289d461576476b7c838e9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14741
content:
"regions (high confidence). In many tropical regions, the number of \r\ndays per year where a heat index of 41degC is exceeded would increase \r\nby more than 100 days relative to the recent past under SSP5-8.5, \r\nwhile this increase will be limited to less than 50 days under SSP1-2.6 \r\n(high confidence) (Figure TS.6). The number of days per year where \r\ntemperature exceeds 35degC would increase by more than 150 days in \r\nmany tropical areas, such as the Amazon basin and South East Asia, \r\nby the end of century for the SSP5-8.5 scenario, while it is expected to \r\nincrease by less than 60 days in these areas under SSP1-2.6 (except \r\nfor the Amazon Basin) (high confidence) (Figure TS.24). {4.6.1, 11.3, \r\n11.9, 12.4, 12.5.2, Atlas}"


id: ef6d0c71612270718186f3729a8cba04
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39495
content:
"Warming trends observed in recent decades are projected to continue \r\nover the 21st century and over most land regions at a rate higher \r\nthan the global average (high confidence). For given global warming \r\nlevels, model projections from CMIP6 show future regional warming \r\nchanges that are similar to those projected by CMIP5. However, \r\nprojected regional warming in CMIP6 for given time periods and \r\nemissions scenarios has a wider range with a higher upper limit \r\ncompared to CMIP5 because of the higher climate sensitivity in some \r\nCMIP6 models and differences in the forcings. {Atlas.3-Atlas.11}"


id: d521681675c11745d723144d7fa361ca
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34820
content:
"Under RCP8.5/SSP5-8.5, it is likely that most land areas will experience \r\nfurther warming of at least 4degC compared to a 1995-2014 baseline \r\nby the end of the 21st century, and in some areas significantly more. \r\nAt increasing warming levels, extreme heat will exceed critical \r\nthresholds for health, agriculture and other sectors more frequently \r\n(high confidence), and it is likely that cold spells will become less \r\nfrequent towards the end of the century. For example, by the end \r\nof the 21st century, dangerous humid heat thresholds, such as the \r\nNational Oceanic and Atmospheric Administration (NOAA) heat index \r\n(HI) threshold of 41degC, will be exceeded much more frequently under \r\nthe SSP5-8.5 scenario than under SSP1-2.6 and will affect many "


id: c48d2e06369c10be9b736e84c806918
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31889
content:
"Wind: Mean wind speed has decreased over most land areas with \r\ngood observational coverage (medium confidence). It is likely that \r\nthe global proportion of major tropical cyclone (TC) intensities \r\n(Categories 3-5) over the past four decades has increased. The \r\nproportion of intense TCs, average peak TC wind speeds, and peak \r\nwind speeds of the most intense TCs will increase on the global scale \r\nwith increasing global warming (high confidence). {11.7.1}"


id: 9cc9fd88d9d110e7429a1de77a1d7453
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 24822
content:
"Figure TS.23 | Time period during which the signals of temperature change in observed data aggregated over the reference regions emerged from the \r\nnoise of annual variability in the respective aggregated data, using a signal-to-noise ratio of two as the threshold for emergence. The intent of this figure \r\nis to show, for the AR6 WGI reference regions, when a signal of annual mean surface temperature change emerged from the noise of annual variability in two global datasets \r\nand thus also provide some information on observational uncertainty. Emergence time is calculated for two global observational datasets: (a) Berkeley Earth and (b) CRUTEM5. \r\nRegions in the CRUTEM5 map are shaded grey when data are available over less than 50% of the area of the region. (Section TS.1.2.4) {Figure Atlas.11}"


id: 5bf2f3bfd1eb8e8a58faaaf63de17f4a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13441
content:
"Coastal and oceanic: There is high confidence that SST will \r\nincrease in all oceanic regions except the North Atlantic. Regional \r\nsea level change has been the main driver of changes in extreme \r\nsea levels across the quasi-global tide gauge network over the \r\n20th century (high confidence). With the exception of a few regions \r\nwith substantial land uplift, relative sea level rise is very likely to \r\nvirtually certain (depending on the region) to continue during the \r\n21st century, contributing to increased coastal flooding in low-lying \r\nareas (high confidence) and coastal erosion along most sandy \r\ncoasts (high confidence) over the 21st century. In the open ocean, \r\nacidification, changes in sea ice, and deoxygenation have already \r\nemerged in many areas (high confidence). Marine heatwaves are \r\nalso expected to increase around the globe over the 21st century \r\n(high confidence). (Section TS.2.4) {Box  9.2, 9.2.1.1, 9.6, 9.6.4, \r\n9.6.4.2, 12.4}"


id: 1d6c5fe5586810817ab30e0208e933bb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 2359
content:
"In addition to the main changes summarized above and in \r\nSection TS.4.3.1, additional details per CID are given below."


id: 65aa604b5f3dd5bc22f28165cd537e74
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15149
content:
"Heat and cold: Observed and projected increases in mean \r\ntemperature and a shift toward heat extreme characteristics are \r\nbroadly similar to the generic pattern described in Section TS.4.3.1. \r\n{2.3.1.1.2, 11.3, 11.9, 12.4.1.1, Atlas.4.2, Atlas.4.4}"


id: 2fc8be766e15a8ca8638cc18b590bd2a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5664
content:
"This section provides a continental synthesis of changes in CIDs, \r\nsome examples of which are presented in Figure TS.25."


id: 1a2d47d561ac37641bf34542497c450
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1800
content:
"Precipitation declines and aridity trends in Western Africa, Central \r\nAfrica, Southern Africa and the Mediterranean co-occur with \r\ntrends towards increased agricultural and ecological droughts in \r\nthe same regions (medium confidence). Trends towards increased \r\nhydrological droughts have been observed in the Mediterranean \r\n(high confidence) and Western Africa (medium confidence). These \r\ntrends correspond with projected regional increases in aridity and \r\nfire weather conditions (high confidence). {8.3.1.6, 8.4.1.6, 11.6, \r\n11.9, 12.4.1.2}"


id: 6ae029d26ab2c1c02019d7bae598aa21
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16087
content:
"Wind: Mean wind, extreme winds and the wind energy potential in \r\nNorth Africa and the Mediterranean are projected to decrease across \r\nall scenarios (high confidence). Over Western Africa and Southern \r\nAfrica, a future significant increase in wind speed and wind energy \r\npotential is projected (medium confidence). There is a projected \r\ndecrease in the frequency of tropical cyclones making landfall \r\nover Madagascar, East Southern Africa and East Africa (medium \r\nconfidence). {12.4.1.3}"


id: d61588c4d170e4dbf55fe221d61fe353
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34981
content:
"Snow and ice: There is high confidence that African glaciers and \r\nsnow have very significantly decreased in the last decades and that \r\nthis trend will continue in the 21st century. {12.4.1.4}"


id: 43a40e214ec82200260e9e54690650b9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9124
content:
"Additional regional changes in Africa, besides those \r\ndescribed in Section TS.4.3.1, include a projected decrease \r\nin total precipitation in the northernmost and southernmost \r\nregions (high confidence), with Western Africa having a west\u0002to-east pattern of decreasing-to-increasing precipitation \r\n(medium confidence). Increases in heavy precipitation that \r\ncan lead to pluvial floods (high confidence) are projected \r\nfor most African regions, even as increasing dry CIDs \r\n(aridity; hydrological, agricultural and ecological droughts; \r\nfire weather) are projected in the western part of Western \r\nAfrica, Southern Africa and Northern Africa and the \r\nMediterranean regions (medium to high confidence). {8.4, \r\n11.3, 11.6, 11.9, 12.4, Atlas.4}"


id: 4d9d0902d63c11e9d15300964d80d0e4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10933
content:
"Coastal and oceanic: Relative sea level has increased at a higher \r\nrate than GMSL around Africa over the last 3 decades. The present \r\nday 1-in-100-year extreme total water level (ETWL) is between \r\n0.1 m and 1.2 m around Africa, with values around 1 m or above \r\nalong the East and West Southern and Central Eastern Africa coasts. \r\nSatellite-derived shoreline retreat rates up to 1 m yr-1 have been \r\nobserved around the continent from 1984 to 2015, except in South \r\nEastern Africa, which has experienced a shoreline progradation \r\n(growth) rate of 0.1 m yr-1 over the same period. {12.4.1.5}"


id: 4ab8eaa24c2d485ba43c662ede0a5019
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10385
content:
"{2.3, 8.3, 8.4, 9.5, 9.6, 10.6, Box 10.4, 11.4, 11.5, 11.7, 11.9, \r\n12.4.2, Atlas.3.1, Atlas.5, Atlas.5.2, Atlas.5.3, Atlas.5.4, \r\nAtlas.5.5}"


id: 5a9fbea15edf84d69d490cd2fd9a04ea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13201
content:
"Due to the high climatological and geographical heterogeneity of \r\nAsia, some assessment findings below are summarized over five \r\nsub-continental areas comprising one or more of the AR6 WGI \r\nreference regions (Box TS.12): East Asia (EAS+ECA), North Asia \r\n(WSB+ESB+RFE), South Asia (SAS), South East Asia (SEA) and South \r\nWest Asia (ARP+WCA)."


id: b1ce221d520fb5f42d9636ca78a49261
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28501
content:
"In addition to the main changes summarized above and in Section \r\nTS.4.3.1, further details are given below."


id: e1d5b26ab403c72229dbce8c7140ed77
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37012
content:
"Heat and cold: Over all regions of Asia, observed and projected \r\nincreases in mean temperature and a shift toward heat extreme \r\ncharacteristics are broadly similar to the generic pattern described \r\nin Section TS.4.3.1. Over South East Asia, annual mean surface \r\ntemperature will likely increase by a slightly smaller amount than the \r\nglobal average. {Atlas.5.4.4}"


id: c575247a4a3b68a47618c0498c54f386
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 32048
content:
"Additional regional changes in Asia, besides those features \r\ndescribed in Section TS.4.3.1, include historical trends \r\nof annual precipitation that show considerable regional \r\ndifferences (high confidence). East Asian Monsoon \r\nprecipitation has changed, with drying in the north and \r\nwetting in the south since the 1950s, and annual mean \r\nprecipitation totals very likely have increased over \r\nmost territories of North Asia since the mid-1970s (high \r\nconfidence). South Asian summer monsoon precipitation \r\ndecreased over several areas since the mid-20th century \r\n(high confidence) but is likely to increase during the 21st \r\ncentury, with enhanced interannual variability. (Box TS.13)"


id: 7de14cf724194dd02da8a0ad107c00cd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19325
content:
"Wet and dry: Over East Asia, historical trends of annual precipitation \r\nshow considerable regional differences but with increases over north\u0002west China and South Korea (high confidence). Daily precipitation \r\nextremes have increased over part of the region (high confidence). \r\nExtreme hydrological drought frequency has increased in a region \r\nextending from south-west to north-east China, with projected \r\nincreases of agricultural and ecological drought for 4degC GWL and \r\nfire weather for 2degC and above (medium confidence). {8.3.2, 8.4.2, \r\n11.4.4, 11.4.5, 11.9, 12.4.2.2, Atlas.5.1.2}"


id: 5fe28343d5a3ce3baab36961a37f7879
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14179
content:
"Increases in precipitation and river floods are projected \r\nover much of Asia: in the annual mean precipitation in \r\nEast, North, South and South East Asia (high confidence); \r\nfor extremes in East, South, West Central, North and South \r\nEast Asia (high confidence) and Arabian Peninsula (medium \r\nconfidence); and for river floods in East, South and South \r\nEast Asia and East Siberia (medium confidence). Aridity \r\nin East and West Central Asia is projected to increase, \r\nespecially beyond the middle of the 21st century and global \r\nwarming levels beyond 2degC (medium confidence). Fire \r\nweather seasons are projected to lengthen and intensify \r\neverywhere except South East Asia, Tibetan Plateau and \r\nArabian Peninsula (medium confidence)."


id: 7e6d32093ba1929f2e34510c89405a81
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19402
content:
"Over North Asia, annual mean precipitation totals have very likely \r\nincreased, causing more intense flooding events, and there is \r\nmedium confidence that the number of dry days has decreased. \r\nConcurrently, total soil moisture is projected to decline extensively \r\n(medium confidence). {8.3.1.3, 8.4.1.6, 11.4.5, 11.5.2, 11.5.5, \r\n12.4.2.2, Atlas.5.2.2}"


id: 5e6df0d5ee0f0ad88b8ddfe365c36869
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13903
content:
"Over South Asia, the summer monsoon precipitation decreased \r\nover several areas since the mid-20th century (high confidence), \r\nwhile it increased in parts of the western HKH and decreased over \r\neastern-central HKH (medium confidence). The frequency of heavy \r\nprecipitation and flood events has increased over several areas \r\nduring the last few decades (medium confidence). {8.3.1.3, 8.3.2.4.1, \r\n8.4.1.5, 8.4.2.4.1, 10.6.3.3, 10.6.3.5, 10.6.3.6, 10.6.3.8, Cross\u0002Chapter Box 10.4, 11.4.1, 11.4.2, 11.4.5, 11.5.5, 12.4.2.2, Box 10.4, \r\nAtlas 5.3.2}"


id: 711f506245bb2f8f8f29d7527d935805
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17163
content:
"Surface wind speeds have been decreasing in Asia (high \r\nconfidence), but there is a large uncertainty in future \r\ntrends, with medium confidence that mean wind speeds \r\nwill decrease in North Asia, East Asia and Tibetan Plateau \r\nand that tropical cyclones will have decreasing frequency \r\nand increasing intensity overall in South East and East \r\nAsia."


id: 3cf4d8ccf269aed5b3102d694ab7be2a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7903
content:
"Over South East Asia, mean precipitation trends are not spatially \r\ncoherent or consistent across datasets and seasons (high confidence). \r\nMost of the region has experienced an increase in rainfall intensity \r\nbut with a reduced number of wet days (medium confidence). Rainfall \r\nis projected to increase in the northern parts of South East Asia and \r\ndecrease in areas in the Maritime Continent (medium confidence). \r\n{8.4.1, 11.4.2, 11.5.5, 11.9, 12.4.2.2, Atlas.3.1, Atlas.5.4.2, Atlas.5.4.4}"


id: 1bb5b3bd40bd94e78c25a3d5454a79a7
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 2061
content:
"Over North Asia, increases in permafrost temperature and \r\nits thawing have been observed over recent decades (high \r\nconfidence). Future projections indicate continuing decline \r\nin seasonal snow duration, glacial mass, and permafrost area \r\nby mid-century (high confidence). Snow-covered areas and \r\nsnow volumes will decrease in most regions of the Hindu \r\nKush Himalaya (HKH) during the 21st century, and snowline \r\nelevations will rise (high confidence) and glacier volumes \r\nare likely to decline with greater mass loss in higher CO2\r\nemissions scenarios. Heavy snowfall is increasing in East \r\nAsia and North Asia (medium confidence) but with limited \r\nevidence on future changes in hail and snow avalanches."


id: a1908b56358110b8751225aee0372232
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 25637
content:
"Over South West Asia, an observed annual precipitation decline \r\nover the Arabian Peninsula since the 1980s of 6.3 mm per decade \r\nis contrasted with observed increases between 1.3 mm and 4.8 mm \r\nper decade during 1960-2013 over the elevated part of eastern \r\nWest Central Asia (very high confidence), along with an increase of \r\nthe frequency and intensity of extreme precipitation. {Figure  8.19, \r\nFigure 8.20, 8.3.1.6, 8.4.1.6, 11.9, Table 11.2A, 12.4.2.2, Atlas.5.5}"


id: a7bbbe88eefe51ad2b2c88c6f39a583b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26726
content:
"Wind: Over East Asia, the terrestrial near-surface wind speed has \r\ndecreased and is projected to decrease further in the future (medium \r\nconfidence). Since the mid 1980's, there has been an increase in the \r\nnumber and intensification rate of intense TCs (medium confidence), \r\nwith a significant north-westward shift in tracks and a northward \r\nshift in their average latitude, increasing exposure over East China, \r\nthe Korean Peninsula and the Japanese Archipelago (medium \r\nconfidence). {11.7.1, 12.4.2.3}"


id: aa05090ec29337e60b1b750ac7753345
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27139
content:
"Additional regional changes in Australasia, besides those \r\nfeatures described in Section TS.4.3.1, include a significant \r\ndecrease in April to October rainfall in the south-west of \r\nthe state of Western Australia, observed from 1910 to 2019 \r\nand attributable to human influence (high confidence), \r\nwhich is very likely to continue in future. Agricultural \r\nand ecological droughts and hydrological droughts have \r\nincreased over Southern Australia (medium confidence), \r\nand meteorological droughts have decreased over Northern \r\nand Central Australia (medium confidence). Relative sea \r\nlevel has increased over the period 1993-2018 at a rate \r\nhigher than GMSL around Australasia (high confidence). \r\nSandy shorelines have retreated around the region, except \r\nin Southern Australia, where a shoreline progradation rate \r\nof 0.1 m yr-1 has been observed. "


id: 5d5d8c679b8f3df5e3d457926eedaed0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13714
content:
"Over North Asia, there is medium confidence for a decreasing trend \r\nin wind speed during 1979-2018 and for projected continuing \r\ndecreases of terrestrial near-surface wind speed. {2.3.1.4.4, 12.4.2.3}"


id: d5bc127e34718e5ce56c26f19a6c3c93
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34914
content:
"Over South East Asia, although there is no significant long-term trend \r\nin the number of TCs, fewer but more extreme TCs have affected the \r\nPhilippines during 1951-2013. {11.7.4, 12.4.2.3}"


id: 208f294f990d1c13bc7a999dcb818319
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 2952
content:
"Snow and ice: Over East Asia, decreases have been observed in the \r\nfrequency, and increases in the mean intensity, of snowfall in north\u0002western, north-eastern and south-eastern China and the eastern \r\nTibetan Plateau since the 1960s. Heavy snowfall is projected to \r\noccur more frequently in some parts of Japan (medium confidence). \r\n{12.4.2.4, Atlas.5.1.2}"


id: 96240698573bc2d339166ee8da943492
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23609
content:
"In the future, heavy precipitation and pluvial flooding are \r\nvery likely to increase over Northern Australia and Central \r\nAustralia, and they are likely to increase elsewhere in \r\nAustralasia for global warming levels (GWLs) exceeding 2degC \r\nand with medium confidence for a 2degC GWL. Agricultural and \r\necological droughts are projected to increase in Southern \r\nand Eastern Australia (medium confidence) for a 2degC GWL. \r\nFire weather is projected to increase throughout Australia \r\n(high confidence) and New Zealand (medium confidence). \r\nSnowfall is expected to decrease throughout the region \r\nat high altitudes in both Australia (high confidence) and \r\nNew Zealand (medium confidence), with glaciers receding \r\nin New Zealand (high confidence). {11.4, Table 11.6, 12.3, \r\n12.4.3, Atlas.6.4, Atlas.6.5}"


id: b927a3a00e6d34de0f6ba01282496740
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29779
content:
"Over North Asia, seasonal snow duration and extent have decreased \r\nin recent decades (high confidence), and maximum snow depth likely\r\nhas increased since the mid-1970s, particularly over the south of the \r\nRussian Far East. {2.3.2.5, 8.3.1.7.2, 9.5, 12.4.2.4, Atlas.5.2, Atlas.5.4}"


id: 4535c80a107b47d783fe2f5049dd496e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9405
content:
"Over South Asia, snow cover has reduced over most of the HKH since \r\nthe early 21st century, and glaciers have thinned, retreated, and lost \r\nmass since the 1970s (high confidence), although the Karakoram \r\nglaciers have either slightly gained mass or are in an approximately \r\nbalanced state (medium confidence). {8.3.1.7.1, Cross-Chapter \r\nBox 10.4}"


id: 87daae2527212c66fefab1de95489cd5
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21057
content:
"Over South West Asia, mountain permafrost degradation at high \r\naltitudes has increased the instability of mountain slopes in the past \r\ndecade (medium confidence). More than 60% of glacier mass in the \r\nCaucasus is projected to disappear under RCP8.5 emissions by the \r\nend of the 21st century (medium confidence). {9.5.1, 9.5.3, 12.4.2.4}"


id: b457098e002c7acd27dd1efbf1058aaf
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28965
content:
"Heat and cold: Observed and projected increases in mean \r\ntemperature and a shift toward heat extreme characteristics are \r\nbroadly similar to the generic pattern described in Section TS.4.3.1. \r\n{11.9, 12.4.3.1, Atlas.6}"


id: b7484348c876a10a6c759c161080e05
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29463
content:
"Wet and dry: There is medium confidence that heavy precipitation has \r\nincreased in Northern Australia since 1950. Annual mean precipitation \r\nis projected to increase in the south and west of New Zealand (medium \r\nconfidence) and is projected to decrease in south-west Southern \r\nAustralia (high confidence), Eastern Australia (medium confidence), and \r\nin the north and east of New Zealand (medium confidence) for a GWL \r\nof 2degC. There is medium confidence that river flooding will increase \r\nin New Zealand and Australia, with higher increases in Northern\r\nAustralia. Aridity is projected to increase with medium confidence in \r\nSouthern Australia (high confidence in south-west Southern Australia), \r\nEastern Australia (medium confidence) and in the north and east of \r\nNew Zealand (medium confidence) for GWLs around 2degC. {11.4, 11.9, \r\nTable 11.6, 12.4.3.2, Atlas.6.2}"


id: b3a649609299b426a262d4b7406a33e8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28849
content:
"Coastal and oceanic: Over the last three decades, relative sea \r\nlevel has increased at a rate higher than GMSL around Asia (high \r\nconfidence). Gross coastal area loss and shoreline retreat has been \r\nobserved over 1984-2015, but with localized shoreline progradation \r\nin the Russian Far East, East and South East Asia. {12.4.2.5}"


id: 3f57d2ad7a710d2e1de914e33a801550
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8336
content:
"Projections show that regional mean sea level continues to rise (high \r\nconfidence), ranging from 0.4-0.5 m under SSP1-2.6 to 0.8-1.0 m \r\nunder SSP5-8.5 for 2081-2100 relative to 1995-2014 (median \r\nvalues). This will contribute to more frequent coastal flooding and \r\nhigher ETWL in low-lying areas and coastal erosion along sandy \r\nbeaches (high confidence). There is high confidence that compound \r\neffects of climate change, land subsidence, and human factors will \r\nlead to higher flood levels and prolonged inundation in the Mekong \r\nDelta and other Asian coasts. {9.6.1, 9.6.3, 12.4.2.5}"


id: 62869cf4cb1d6e07c752c3c09257d6b4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14623
content:
"South America and Southern Central America (medium confidence). \r\nIn Northern South America and Southern Central America, aridity \r\nand agricultural and ecological droughts are increasing with \r\nmedium confidence. Fire weather is projected to increase over \r\nSouthern Central America and Southern South America with medium \r\nconfidence. {8.3.1.3, 8.4.2.4.5, 11.4.2, 11.9, Table 11.14, Table 11.15, \r\n12.4.4.2, Atlas.7.2.2, Atlas.7.2.4}"


id: b942b4bcf0e9f549631b44e56ab1d3e4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29801
content:
"under high CO2 emissions scenarios. TCs in north-eastern and north \r\nAustralia are projected to decrease in number (high confidence) but \r\nincrease in intensity except for 'east coast lows' (low confidence). \r\n{12.4.3.3}"


id: 1767bc2bb6eeeacbe946bfdd9e7dffa8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1338
content:
"Snow and ice: Observations in Australia show that the snow season \r\nlength has decreased by 5% in the last five decades. Furthermore, the \r\ndate of peak snowfall in Australia has advanced by 11 days over the \r\nlast 5 decades. Glacier ice volume in New Zealand has decreased by \r\n33% from 1977 to 2018. {12.4.3.4, Atlas.6.2}"


id: 95e07273deef833819a88664c36500dd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23565
content:
"Wind: Climate projections indicate an increase in mean wind speed \r\nand in wind power potential over the Amazonian region (Northern \r\nSouth America, South American Monsoon, North-Eastern South \r\nAmerica) (medium confidence). {12.4.4.3}"


id: 141116be1e96d6d42085d3b8028f79ba
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 748
content:
"Coastal and oceanic: Observed changes in marine heatwaves \r\n(MHWs) over the 20th century in the region show an increase in their \r\noccurrence frequency, except along the south-east coast of New \r\nZealand, an increase in duration per event, and the total number of \r\nMHW days per decade, with the change being stronger in the Tasman \r\nSea than elsewhere. The present day 1-in-100-year ETWL is between \r\n0.5-2.5 m around most of Australia, except the north-western \r\ncoast where 1-in-100-year ETWL can be as high as 6-7 m. {Box 9.1, \r\n12.3.1.5, 12.4.3.5}"


id: c5a1ef71d9dbcfb51c9b8003d1277558
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 32074
content:
"Snow and ice: Glacier volume loss and permafrost thawing will \r\nlikely continue in the Andes Cordillera under all climate scenarios, \r\ncausing important reductions in river flow and potentially high\u0002magnitude glacial lake outburst floods. {9.5.1.1, 12.4.4.4}"


id: bf3d4f0893fd424946c0dafbe4b4bebc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 30915
content:
"Coastal and oceanic: Around Central and South America, relative \r\nsea level has increased at a higher rate than GMSL in the South \r\nAtlantic and the subtropical North Atlantic, and at a rate lower than \r\nGMSL in the East Pacific over the last 3 decades. The present day \r\n1-in-100-year ETWL is highest in Southern and South-Western South \r\nAmerica subregions, where it can be as large as 5 to 6 m. Satellite \r\nobservations for 1984-2015 show shoreline retreat rates along the \r\nsandy coasts of Southern Central America, South-Eastern South \r\nAmerica and Southern South America, while shoreline progradation \r\nrates have been observed in North-Western South America and \r\nNorthern South America. Over the period 1982-2016, the coastlines \r\nexperienced at least one MHW per year, and more along the Pacific \r\ncoast of North Central America and the Atlantic coast of South\u0002Eastern South America. {12.4.4.5}"


id: 29d49fbd93dd76c052c1acec6582f959
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4586
content:
"Heat and cold: Observed and projected increases in mean \r\ntemperature and a shift toward heat extreme characteristics are \r\nbroadly similar to the generic pattern described in Section TS.4.3.1. \r\n{11.3.2, 11.3.5, Table  11.13, 12.4.4.1, Atlas.7.1.2, Atlas.7.2.2, \r\nAtlas.7.2.4}"


id: d9e3e2d1f4f65684ff86e390a81ca800
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35634
content:
"America and Northern Central America (from medium to\r\nhigh confidence). Severe wind storms, tropical cyclones \r\nand dust storms in North America are shifting toward more \r\nextreme characteristics (medium confidence), and both \r\nobservations and projections point to strong changes in the \r\nseasonal and geographic range of snow and ice conditions \r\nin the coming decades (very high confidence). General \r\nfindings for relative sea level, coastal flooding and erosion \r\nwill not apply for areas with substantial land uplift around \r\nthe Hudson Bay and Southern Alaska. {8.4, 11.4, 11.5, 11.7, \r\n11.9, 12.4, Atlas.9.4}"


id: 2bf6f31eadb24fd8a01621d3b10b997f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4985
content:
"Heat and cold: Observed and projected increases in mean \r\ntemperature and a shift toward heat extreme characteristics are \r\nbroadly similar to the generic pattern described in Section TS.4.3.1. \r\n{11.3, 11.9, 12.4.5.1, 12.5.2, Atlas.8.2, Atlas.8.4}"


id: 898bc5b4be0cb45dc1195da48ed569eb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21375
content:
"Wet and dry: There is medium confidence that annual mean \r\nprecipitation has increased in Northern Europe, West and Central \r\nEurope, and Eastern Europe since the early 20th century and \r\nhigh confidence for increases in extreme precipitation. In the \r\nEuropean Mediterranean, the magnitude and sign of observed land \r\nprecipitation trends depend on time period and exact study region \r\n(medium confidence). There is medium confidence that river floods \r\nwill decrease in Northern, Eastern and southern Europe for high \r\nwarming levels. {8.3.1.3, 11.3, 11.9, 12.4.5.2, Atlas.8.2, Atlas.8.4}"


id: 1a28aa27671ac0c57ab820f1c32aede5
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1794
content:
"Heat and cold: Observed and projected increases in mean \r\ntemperature and a shift toward heat extreme characteristics are \r\nbroadly similar to the generic pattern described in Section TS.4.3.1. \r\n{11.3, 11.9, 12.4.6.1, Atlas.9.2, Atlas.9.4}"


id: 8ed61ed373d8d9ff6c95a9743dee8e5f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22315
content:
"Wind: Mean wind speed over land has decreased (medium \r\nconfidence), but the role of human-induced climate change has not \r\nbeen established. There is high confidence that mean wind speeds \r\nwill decrease in Mediterranean areas and medium confidence for \r\nsuch decreases in Northern Europe for GWLs exceeding 2degC. The \r\nfrequency of Medicanes (tropical-like cyclones in the Mediterranean) \r\nis projected to decrease (medium confidence). {11.9, 12.4.5.3}"


id: 576c4e6cbaab8e7135cd799f11bbb768
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12645
content:
"Wet and dry: Annual precipitation increased over parts of Eastern \r\nand Central North America during 1960-2015 (high confidence) and \r\nhas decreased in parts of south-western United States and north\u0002western Mexico (medium confidence). River floods are projected to \r\nincrease for all North American regions other than Northern Central \r\nAmerica (medium confidence). {8.4.2.4, 11.4, 11.5, 11.9, 12.4.6.2, \r\nAtlas.9.2, Atlas.9.4}"


id: 94c59e9637bf4866cd114f166b237446
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23384
content:
"Snow and ice: In the Alps, snow cover will decrease below elevations \r\nof 1500-2000 m throughout the 21st century (high confidence). \r\nA reduction of glacier ice volume is projected in the European Alps \r\nand Scandinavia with high confidence and with medium confidence\r\nfor the timing and mass change rates. {9.5.2, 12.4.5.4}"


id: 59fab1995907d0b4eb1c997c4b98bc30
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13077
content:
"Agricultural and ecological drought increases have been observed in \r\nWestern North America (medium confidence), and aridity is projected \r\nto increase in the south-western United States and Northern Central \r\nAmerica, with lower summer soil moisture across much of the \r\ncontinental interior (medium confidence). {8.4.1, 11.6.2, 12.4.6.2}"


id: f7fdf7f41fb78de54003532ee24b3fa7
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41003
content:
"Coastal and oceanic: Over the last three decades, relative sea level \r\nhas increased at a lower rate than GMSL in the sub-polar North \r\nAtlantic coasts of Europe. The present-day 1-in-100-year ETWL is \r\nbetween 0.5-1.5 m in the Mediterranean basin and 2.5-5.0 m in \r\nthe western Atlantic European coasts, around the United Kingdom \r\nand along the North Sea coast, and lower at 1.5-2.5 m along the \r\nBaltic Sea coast. Satellite-derived shoreline change estimates over \r\n1984-2015  indicate  shoreline retreat rates of  around 0.5 m yr-1\r\nalong the sandy coasts of Central Europe and the Mediterranean \r\nand more or less stable shorelines in Northern Europe. Over the \r\nperiod 1982-2016, the coastlines of Europe experienced on average \r\nmore than 2.0 MHW per year, with the eastern Mediterranean and \r\nScandinavia experiencing 2.5-3 MHWs per year. {12.4.5.5}"


id: b5e7d1cca5ea16e6253e85fae504d67f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29226
content:
"Wind: Projections indicate a greater number of the most intense \r\nTCs, with slower translation speeds and higher rainfall potential for \r\nMexico's Pacific Coast, the Gulf Coast and the United States East \r\nCoast (medium confidence). Mean wind speed and wind power \r\npotential are projected to decrease in Western North America (high \r\nconfidence), with differences between global and regional models \r\nlending low confidence elsewhere. {11.4, 11.7, 12.4.6.3}"


id: 32dc5291eacfe226a6bf6416d9012dff
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6215
content:
"Snow and ice: It is likely that some high-latitude regions will \r\nexperience an increase in winter snow water equivalent due to the \r\nsnowfall increase prevailing over the warming trend. At sustained \r\nGWLs between 3degC and 5degC, nearly all glacial mass in Western \r\nCanada and Western North America will disappear (medium \r\nconfidence). {9.5.1, 9.5.3, 12.4.6.4, Atlas.9.4}"


id: 3c0a9b2b0e9a8a35ff3f5a052699fe02
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7754
content:
"Additional regional changes in North America, besides those \r\nfeatures described in Section TS.4.3.1, include changes \r\nin North American wet and dry CIDs, which are largely \r\norganized by the north-east (more wet) to south-west (more \r\ndry) pattern of mean precipitation change, although heavy \r\nprecipitation increases are widespread (high confidence). \r\nIncreasing evaporative demand will expand agricultural \r\nand ecological drought and fire weather (particularly in \r\nsummertime) in Central North America, Western North "


id: 6b0f0cda6b995531335e898a97460c32
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16129
content:
"Coastal and oceanic: Around North America, relative sea level has \r\nincreased over the last three decades at a rate lower than GMSL \r\nin the subpolar North Atlantic and in the East Pacific, while it has \r\nincreased at a rate higher than GMSL in the subtropical North Atlantic. \r\nObservations indicate that episodic coastal flooding is increasing \r\nalong many coastlines in North America. Shoreline retreat rates of \r\naround 1 m yr-1 have been observed during 1984-2015 along the \r\nsandy coasts of North-Western North America and Northern Central "


id: 9486aea6a6725f2fa6f68fe994f36684
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23339
content:
"Permafrost warming, loss of seasonal snow cover, and \r\nglacier melt will be widespread (high confidence). There is \r\nhigh confidence that both the Greenland and Antarctic ice \r\nsheets have lost mass since 1992 and will continue to lose \r\nmass throughout this century under all emissions scenarios. \r\nRelative sea level and coastal flooding are projected to \r\nincrease in areas other than regions with substantial land \r\nuplift (medium confidence). {2.3, 3.4, 4.3, 4.5, 7.4, 8.2, 8.4, \r\nBox 8.2, 9.5, 12.4.9, Atlas.11.1, Atlas.11.2}"


id: aff5243ea529c18f9927df05007eb04e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28194
content:
"America, while portions of the United States Gulf Coast have seen \r\na retreat rate approaching 2.5 m yr-1. Sandy shorelines along Eastern \r\nNorth America and Western North America have remained more or \r\nless stable during 1984-2014, but a shoreline progradation rate of \r\naround 0.5 m yr-1 has been observed in North-Eastern North America. \r\n{12.4.6.5}"


id: 5b82d431f2e15b14f710095c43c096dd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13345
content:
"Additional regional changes in Small Islands, besides those \r\nfeatures described in Section TS.4.3.1, include a likely\r\ndecrease in rainfall during boreal summer in the Caribbean \r\nand in some parts of the Pacific islands poleward of 20deg \r\nlatitude in both the Northern and Southern Hemispheres. \r\nThese drying trends will likely continue in coming decades. \r\nFewer but more intense tropical cyclones are projected \r\nstarting from a 2degC GWL (medium confidence). {9.6, 11.3, \r\n11.4, 11.7, 11.9, 12.4.7, Atlas.10.2, Atlas.10.4, Cross-Chapter \r\nBox Atlas.2}"


id: ad84d0ebd3d05db386667f80bb498934
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27769
content:
"Heat and cold: Changes in Antarctica showed larger spatial \r\nvariability, with very likely warming in the Antarctic Peninsula since \r\nthe 1950s and no overall trend in East Antarctica. Less warming \r\nand weaker polar amplification are projected as very likely over \r\nthe Antarctic than in the Arctic, with a weak polar amplification \r\nprojected as very likely by the end of the 21st century. {4.3.1, 4.5.1, \r\n7.4.4, 12.4.9.1, Atlas.11.1, Atlas.11.2}"


id: 2883ad7cba772245febc0b8ba9370464
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4336
content:
"Wet and dry: Recent decades have seen a general decrease in \r\nArctic aridity (high confidence), with increased moisture transport \r\nleading to higher precipitation, humidity and streamflow and a \r\ncorresponding decrease in dry days. Antarctic precipitation showed \r\na positive trend during the 20th century. The water cycle is projected \r\nto intensify in both polar regions, leading to higher precipitation \r\ntotals (and a shift to more heavy precipitation) and higher fraction \r\nof precipitation falling as rain. In the Arctic, this will result in higher \r\nriver flood potential and earlier meltwater flooding, altering seasonal \r\ncharacteristics of flooding (high confidence). A lengthening of the fire \r\nseason (medium confidence) and encroachment of fire regimes into \r\ntundra regions (high confidence) are projected. {8.2.3, 8.4.1, Box 8.2, \r\n9.4.1, 9.4.2, 12.4.9.2, Atlas.11.1, Atlas.11.2}"


id: d7c3e558b5429aa5bbd68ff8abae64ae
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35266
content:
"Heat and cold: It is very likely that most Small Islands have warmed \r\nover the period of instrumental records, and continued temperature \r\nincreases in the 21st century will further increase heat stress in these \r\nregions. {11.3.2, 11.9, 12.4.7.1, Atlas.10.2, Atlas.10.4, Cross-Chapter \r\nBox Atlas.2}"


id: e3cf8c8bcb0c0a71d788879e03bed872
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37367
content:
"Wet and dry: Observed and projected rainfall trends vary spatially \r\nacross the Small Islands. Higher evapotranspiration under a warming \r\nclimate can partially offset future increases or amplify future \r\nreductions in rainfall, resulting in increased aridity as well as more \r\nsevere agricultural and ecological drought in the Caribbean (medium \r\nconfidence). {11.4.2, 11.9, 12.4.7.2, Atlas.10.2, Atlas.10.4, Cross\u0002Chapter Box Atlas.2}"


id: 4ba46c266ec480ffcf9c55f27ac4d033
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10568
content:
"Wind: There is medium confidence in mean wind decrease over \r\nthe Russian Arctic and Arctic North-East North America, but low \r\nconfidence of changes in other Arctic regions and Antarctica. \r\n{12.4.9.3}"


id: 2a3fa7e8647dfff0c21b3be1b920ec53
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4645
content:
"Wind: Global changes indicate that Small Islands will face fewer \r\nbut more intense TCs, with spatial inconsistency in projections given \r\npoleward shifts in TC tracks (medium confidence). {11.7.1.2, 11.7.1.5, \r\n12.4.7.3}"


id: 9085368e949b13908929a7d6771bdb47
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22632
content:
"Snow and ice: Reductions in spring snow cover extent have \r\noccurred across the Northern Hemisphere since at least 1978 (very \r\nhigh confidence). Permafrost warming and thawing have been \r\nwidespread in the Arctic since the 1980s (high confidence), causing \r\nstrong heterogeneity in surface conditions. There is high confidence\r\nin future glacier- and ice-sheet loss, permafrost warming, decreasing \r\npermafrost extent and decreasing seasonal duration and extent of \r\nsnow cover in the Arctic. Decline in seasonal sea ice coverage along \r\nthe majority of the Arctic coastline in recent decades is projected to \r\ncontinue, contributing to an increase in coastal hazards (including \r\nopen water storm surge, coastal erosion and flooding). {2.3.2, 3.4.2, \r\n3.4.3, 9.4.1, 9.4.2, 9.5, 12.4.6, 12.4.9, Atlas.11.2}"


id: 3a4bd9c52c1e4e2d698376620fc5a0c7
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7461
content:
"Coastal and oceanic: Continued relative sea level rise is very likely \r\nin the ocean around Small Islands and, along with storm surges \r\nand waves, will exacerbate coastal inundation with the potential to \r\nincrease saltwater intrusion into aquifers in small islands. Shoreline \r\nretreat is projected along sandy coasts of most small islands (high \r\nconfidence). {9.6.3.3, 12.4.7.4, Cross-Chapter Box Atlas.2}"


id: f4bf3147fd030336f08ec132fad59a2f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40430
content:
"It is virtually certain that surface warming in the Arctic \r\nwill continue to be more pronounced than the global \r\naverage warming over the 21st century. An intensification \r\nof the polar water cycle will increase mean precipitation, \r\nwith precipitation intensity becoming stronger and more\r\nlikely to be rainfall rather than snowfall (high confidence). "


id: c504d215840eff34c39fd6a90f040b35
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31972
content:
"with lower confidence for those regions with substantial land uplift \r\n(Arctic North-East North America and Greenland). {12.4.9.5}"


id: cf3f066363c28947301548b41f944763
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33812
content:
"Some types of regions found in different continents face \r\ncommon climate challenges regardless of their location. \r\nThese include biodiversity hot spots that will very likely\r\nsee even more extreme heat and droughts, mountain areas \r\nwhere a projected raising in the freezing level height will \r\nalter snow and ice conditions (high confidence), and tropical \r\nforests that are increasingly prone to fire weather (medium \r\nconfidence). {8.4, Box 8.2, 9.5, 12.3, 12.4}"


id: 2009b9e8d011a7fc86292e06413bea14
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 2852
content:
"The Indian Ocean, western equatorial Pacific Ocean and \r\nwestern boundary currents have warmed faster than the \r\nglobal average (very high confidence), with the largest \r\nchanges in the frequency of marine heatwaves (MHWs) \r\nprojected in the western tropical Pacific and the Arctic \r\nOcean (medium confidence). The Pacific and Southern Ocean \r\nare projected to freshen and the Atlantic to become more \r\nsaline (medium confidence). Anthropogenic warming is very \r\nlikely to further decrease ocean oxygen concentrations, and \r\nthis deoxygenation is expected to persist for thousands \r\nof years (medium confidence). Arctic sea ice losses are \r\nprojected to continue, leading to a practically ice-free Arctic \r\nin September by the end of the 21st century under high \r\nCO2 emissions scenarios (high confidence). {2.3, 5.3, 9.2, 9.3, \r\nBox 9.2, 12.3.6, 12.4.8}"


id: e28961fb56cbe1c13ff03577eec87e4a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37156
content:
"Biodiversity hotspots located around the world will each face unique \r\nchallenges in CID changes. Heat, drought and length of dry season, \r\nwildfire weather, sea surface temperature and deoxygenation are \r\nrelevant drivers to terrestrial and freshwater ecosystems and have \r\nmarked increasing trends. {12.3, 12.4.10.1}"


id: ed7043b6f4a4837964016d5127fbb3da
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39138
content:
"Desert and semi-arid areas are strongly affected by CIDs such as \r\nextreme heat, drought and dust storms, with large-scale aridity \r\ntrends contributing to expanding drylands in some regions (high \r\nconfidence). {12.3, 12.4.10.3}"


id: f3fd2cee502071fe00c90b81627edf9a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40299
content:
"Average warming in mountain areas varies with elevation, but \r\nthe pattern is not globally uniform (medium confidence). Extreme \r\nprecipitation is projected to increase in major mountainous regions \r\n(medium to high confidence depending on location), with potential \r\ncascading consequences of floods, landslides and lake outbursts \r\nin all scenarios (medium confidence). {8.4.1.5, Box  8.2, 9.5.1.3, \r\n9.5.3.3, 9.5.2.3, Cross-Chapter Box 10.4, 11.5.5, 12.3, 12.4.1-12.4.6, \r\n12.4.10.4}"


id: e366a32717ae032620ed27a33fdd685f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37305
content:
"Ocean surface temperature: The Southern Ocean, the eastern \r\nequatorial Pacific, and the North Atlantic Ocean have warmed more \r\nslowly than the global average or slightly cooled. Global warming \r\nof 2degC above 1850-1900 levels would result in the exceedance of \r\nnumerous hazard thresholds for pathogens, seagrasses, mangroves, \r\nkelp forests, rocky shores, coral reefs and other marine ecosystems \r\n(medium confidence). {9.2.13, 12.4.8}"


id: b3cd8b10919a9184066d9b170735db92
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 28877
content:
"Most tropical forests are challenged by a mix of emerging warming \r\ntrends that are particularly large in comparison to historical variability \r\n(medium confidence). Water cycle changes bring prolonged drought, \r\nlonger dry seasons and increased fire weather to many tropical \r\nforests (medium confidence). {10.5, 12.3, 12.4}"


id: 47ff2dd465c1b33a17e8bde8a59d9bd9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9882
content:
"Marine heatwaves: Moderate increases in MHW frequency are \r\nprojected for mid-latitudes, and only small increases are projected \r\nfor the Southern Ocean (medium confidence). Under the SSP5-8.5 \r\nscenario, permanent MHWs (more than 360 days per year) are \r\nprojected to occur in the 21st century in parts of the tropical ocean, \r\nthe Arctic Ocean, and around 45degS; however, the occurrence of \r\nsuch permanent MHWs can be largely avoided under the SSP1-2.6 \r\nscenario. {Box 9.2, 12.4.8}"


id: 589a5311e183a96ee99990b612f56af9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12833
content:
"Ocean acidity: With the rising CO2 concentration, the ocean surface \r\npH has declined globally over the past four decades (virtually certain). \r\n{2.3.3.5, 5.3.3.2, 12.4.8}"


id: 91c6a0686adedb5abd3387f6414185ce
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22873
content:
"Ocean salinity: At the basin scale, it is very likely that the Pacific and \r\nthe Southern Ocean have freshened while the Atlantic has become \r\nmore saline. {2.3.3.2, 9.2.2.2, 12.4.8}"


id: 7d34c8a2f3def09ababe05a919ddcbed
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19205
content:
"Dissolved oxygen: In recent decades, low oxygen zones in ocean \r\necosystems have expanded. {2.3.4.2, 5.3.3.2, 12.4.8}"


id: cefdce2ee4b113c3e806dfc8485976f3
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33758
content:
"Sea ice: Arctic perennial sea ice is being replaced by thin, seasonal \r\nice, with earlier spring melt and delayed fall freeze up. There is no \r\nclear trend in the Antarctic sea ice area over the past few decades \r\nand low confidence in its future change. {2.3.2.1.1, 9.3.1.1, 12.4.8, \r\n12.4.9}"


id: d2bb61984cc6ae8c52b5b181e1d353e9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34424
content:
"With global warming, urban areas and cities will be affected by more frequent occurrences of extreme climate events, \r\nsuch as heatwaves, with more hot days and warm nights as well as sea level rise and increases in tropical cyclone \r\nstorm surge and rainfall intensity that will increase the probability of coastal city flooding (high confidence). {Box 10.3, \r\n11.3, 11.5, 12.3, 12.4}"


id: c1280126a6a9762e201cc45e02a4233e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31284
content:
"Urban areas have special interactions with the climate system, for instance in terms of heat islands and altering the water cycle, and \r\nthereby will be more affected by extreme climate events such as extreme heat (high confidence). With global warming, increasing \r\nrelative sea level compounded by increasing tropical cyclone storm surge and rainfall intensity will increase the probability of coastal \r\ncity flooding (high confidence). Arctic coastal settlements are particularly exposed to climate change due to sea ice retreat (high \r\nconfidence). Improvements in urban climate modelling and climate monitoring networks have contributed to understanding the \r\nmutual interaction between regional and urban climate (high confidence). {Box 10.3, 11.3, 11.5, 12.3, 12.4}"


id: c19cdf796cb90b9bb03512966c12aa2b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31366
content:
"Despite having a negligible effect on global surface temperature (high confidence), urbanization has exacerbated the effects of global \r\nwarming through its contribution to the observed warming trend in and near cities, particularly in annual mean minimum temperature \r\n(very high confidence) and increases in mean and extreme precipitation over and downwind of the city, especially in the afternoon \r\nand early evening (medium confidence). {2.3, Box 10.3, 11.3, 11.4, 12.3, 12.4}"


id: c10eeb37309141dfd90555ee4f5bcce8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31269
content:
"Combining climate change projections with urban growth scenarios, future urbanization will amplify (very high confidence) the \r\nprojected local air temperature increase, particularly by strong influence on minimum temperatures, which is approximately comparable \r\nin magnitude to global warming (high confidence). Compared to present day, large implications are expected from the combination \r\nof future urban development and more frequent occurrence of extreme climate events, such as heatwaves, with more hot days and \r\nwarm nights adding to heat stress in cities (very high confidence). {Box 10.2, 11.3, 12.4}"


id: a93a1de50cd73132e2ea37849e3aa4ea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26994
content:
"Both sea levels and air temperatures are projected to rise in most coastal settlements (high confidence). There is high confidence in \r\nan increase in pluvial flood potential in urban areas where extreme precipitation is projected to increase, especially at high global \r\nwarming levels. {11.4, 11.5, 12.4}"


id: 4d237cf1221e2d6249ecc29864384a22
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10846
content:
"Coordinating Lead Authors:\r\nDeliang Chen (Sweden), Maisa Rojas (Chile), Bjorn H. Samset (Norway)"


id: 6978279ec79a49586e535a26583a225a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15823
content:
"Anna  A.  Sorensson (Argentina), Peter Steinle (Australia), Thomas F. Stocker (Switzerland), \r\nMartina  Stockhause (Germany), Daithi Stone (New Zealand), Abigail Swann (United  States \r\nof America), Sophie  Szopa (France), Izuru Takayabu (Japan), Claudia Tebaldi (United  States \r\nof America), Laurent Terray (France), Peter W. Thorne (Ireland/United  Kingdom), Blair Trewin \r\n(Australia), Isabel Trigo (Portugal), Maarten K. van Aalst (The Netherlands), Bart van den Hurk \r\n(The Netherlands), Detlef van Vuuren (The Netherlands), Robert Vautard (France), Carolina Vera \r\n(Argentina), David Viner (United Kingdom), Axel von Engeln (Germany), Karina von Schuckmann \r\n(France/Germany), Xuebin Zhang (Canada)"


id: 8b57316cab0a9632be37adba5a23f18
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21677
content:
"Chen, D., M. Rojas, B.H. Samset, K. Cobb, A. Diongue Niang, P. Edwards, S. Emori, S.H. Faria, E. Hawkins, \r\nP. Hope, P.  Huybrechts, M. Meinshausen, S.K. Mustafa, G.-K. Plattner, and A.-M. Treguier, 2021: Framing, \r\nContext, and Methods. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group \r\nI  to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., \r\nP. Zhai, A. Pirani, S.L. Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, \r\nE. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekci, R. Yu, and B. Zhou (eds.)]. Cambridge \r\nUniversity Press, Cambridge, United Kingdom and New York, NY, USA, pp. 147-286, doi:10.1017/9781009157896.003."


id: 32cd188712671b15de4e7eb7f791521a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6205
content:
"evolving global efforts in climate change mitigation (efforts to limit \r\nclimate change) and adaptation (efforts to adapt to changes that \r\ncannot be avoided). In this context, WGI assesses, among other \r\ntopics, remaining cumulative carbon emissions budgets for a range \r\nof global warming levels, effects of long-lived and short-lived climate \r\nforcers, observed climate changes and their attribution to human \r\nforcing, and projected changes in sea level and climate extremes. \r\n{Cross-Chapter Box 1.1}"


id: 69e9265cbe272566ae403dc16e796db6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15900
content:
"Working Group I (WGI) of the Intergovernmental Panel on Climate \r\nChange (IPCC) assesses the current evidence on the physical science \r\nof climate change, evaluating knowledge gained from observations, \r\nreanalyses, paleoclimate archives and climate model simulations, \r\nas well as physical, chemical and biological climate processes. \r\nThis chapter sets the scene for the WGI Assessment, placing it in the \r\ncontext of ongoing global and regional changes, international policy \r\nresponses, the history of climate science and the evolution from \r\nprevious IPCC assessments, including the Special Reports prepared \r\nas part of this Assessment Cycle. This chapter presents key concepts \r\nand methods, relevant recent developments, and the modelling and \r\nscenario framework used in this Assessment."


id: a73419b8eefac6d9f6e37c1108ef01d9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26630
content:
"Global surface temperatures increased by about 0.1degC (likely\r\nrange -0.1degC to +0.3degC, medium confidence) between the period \r\naround 1750 and the 1850-1900 period, with anthropogenic \r\nfactors responsible for a warming of 0.0degC-0.2degC (likely range, \r\nmedium confidence). This assessed change in temperature before \r\n1850-1900 is not included in the AR6 assessment of global warming \r\nto date, to ensure consistency with previous IPCC assessment reports, \r\nand because of the lower confidence in the estimate. There was likely\r\na net anthropogenic forcing of 0.0-0.3 W m-2 in 1850-1900 relative \r\nto 1750 (medium confidence), with radiative forcing from increases in \r\natmospheric greenhouse gas concentrations being partially offset by \r\nanthropogenic aerosol emissions and land-use change. Net radiative \r\nforcing from solar and volcanic activity is estimated to be smaller \r\nthan +-0.1 W m-2 for the same period. {Cross-Chapter Box 1.2, 1.4.1, \r\nCross-Chapter Box 2.3}"


id: e291ad7adc66c88d9dad04dd06b350e1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37166
content:
"Natural climate variability can temporarily obscure or \r\nintensify anthropogenic climate change on decadal time \r\nscales, especially in regions with large internal interannual\u0002to-decadal variability. At the current level of global warming, \r\nan observed signal of temperature change relative to \r\nthe 1850-1900 baseline has emerged above the levels of \r\nbackground variability over virtually all land regions (high \r\nconfidence). Both the rate of long-term change and the amplitude of \r\ninterannual (year-to-year) variability differ between global, regional \r\nand local scales, between regions and across climate variables, \r\nthus influencing when changes become apparent. Tropical regions \r\nhave experienced less warming than most others, but also exhibit "


id: c0e2cb1f56d77932ea8b9faedacfb106
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31233
content:
"This report provides information of potential relevance to the \r\n2023 global stocktake. The five-yearly stocktakes called for in the \r\nParis Agreement will evaluate alignment among the Agreement's \r\nlong-term goals, its means of implementation and support, and "


id: 4bb11eb30db732c325a76fb3505b1263
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10574
content:
"ocean. While noting their remaining limitations, the WGI report uses \r\nthe most recent generation of reanalysis products alongside more \r\nstandard observation-based datasets. {1.5.2, Annex 1}"


id: ac49874c18ad42656fc6f9603dd57097
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27556
content:
"smaller interannual variations in temperature. Accordingly, the signal \r\nof change is more apparent in tropical regions than in regions with \r\ngreater warming but larger interannual variations (high confidence). \r\n{1.4.2, FAQ 1.2}"


id: 8023d430ca6eda6ff03ea1d0c59b87d4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19673
content:
"Since AR5, new techniques have provided greater confidence \r\nin attributing changes in climate and weather extremes \r\nto climate change. Attribution is the process of evaluating the \r\nrelative contributions of multiple causal factors to an observed \r\nchange or event. This includes the attribution of the causal factors \r\nof changes in physical or biogeochemical weather or climate \r\nvariables (e.g.,  temperature or atmospheric CO2) as done in WGI, \r\nor of the impacts of these changes on natural and human systems \r\n(e.g., infrastructure damage or agricultural productivity), as done in \r\nWGII. Attributed causes include human activities (such as emissions \r\nof greenhouse gases and aerosols, or land-use change), and changes \r\nin other aspects of the climate, or natural or human systems. \r\n{Cross-Working Group Box 1.1}"


id: ffb17c8cac22d99388d66f5bc0908f26
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 42379
content:
"AR6 has adopted a  unified framework of climate risk, \r\nsupported by an increased focus in WGI on low-likelihood, high\u0002impact outcomes. Systematic risk framing is intended to aid the \r\nformulation of effective responses to the challenges posed by current \r\nand future climatic changes and to better inform risk assessment and \r\ndecision-making. AR6 also makes use of the 'storylines' approach, \r\nwhich contributes to building a  robust and comprehensive picture \r\nof climate information, allows for a more flexible consideration and \r\ncommunication of risk, and can explicitly address low-likelihood, \r\nhigh-impact outcomes. {1.1.2, 1.4.4, Cross-Chapter Box 1.3}"


id: cf0ce2f943c42dc473ad39078645ed81
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33775
content:
"The construction of climate change information and \r\ncommunication of scientific understanding are influenced \r\nby the values of the producers, the users and their broader \r\naudiences. Scientific knowledge interacts with pre-existing \r\nconceptions of weather and climate, including values and beliefs \r\nstemming from ethnic or national identity, traditions, religion or lived \r\nrelationships to land and sea (high confidence). Science has values \r\nof its own, including objectivity, openness and evidence-based \r\nthinking. Social values may guide certain choices made during the \r\nconstruction, assessment and communication of information (high \r\nconfidence). {1.2.3, Box 1.1}"


id: ef187298b194992b5e94947028a69c43
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39436
content:
"Capabilities for observing the physical climate system have \r\ncontinued to improve and expand overall, but some reductions \r\nin observational capacity are also evident (high confidence). \r\nImprovements are particularly evident in ocean observing networks \r\nand remote-sensing systems, and in paleoclimate reconstructions \r\nfrom proxy archives. However, some climate-relevant observations \r\nhave been interrupted by the discontinuation of surface stations \r\nand radiosonde launches, and delays in the digitisation of records. \r\nFurther reductions are expected to result from the COVID-19 \r\npandemic. In  addition, paleoclimate archives such as mid-latitude \r\nand tropical glaciers, as well as modern natural archives used for \r\ncalibration (e.g.,  corals and trees), are rapidly disappearing due \r\nto a  host of pressures, including increasing temperatures (high \r\nconfidence). {1.5.1}"


id: 49819afdda51f8ec7eff9b2304935275
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10160
content:
"Reanalyses have improved since AR5 and are increasingly \r\nused as a  line of evidence in assessments of the state and \r\nevolution of the climate system (high confidence). Reanalyses, \r\nwhere atmosphere or ocean forecast models are constrained by \r\nhistorical observational data to create a  climate record of the \r\npast, provide consistency across multiple physical quantities and \r\ninformation about variables and locations that are not directly \r\nobserved. Since AR5, new reanalyses have been developed with \r\nvarious combinations of increased resolution, extended records, more \r\nconsistent data assimilation, estimation of uncertainty arising from \r\nthe range of initial conditions, and an improved representation of the "


id: 6fcff75e1a648b8982bef616a9c0e17f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16934
content:
"naturally forced changes (Chapter 3, Sections 1.2.1.1 and 1.4.1, and \r\nthe Cross-Working Group Box on Attribution). The core assessment \r\nconclusions from previous IPCC reports are confirmed or strengthened \r\nin this report, indicating the robustness of our understanding of the \r\nprimary causes and consequences of anthropogenic climate change."


id: 236992cea598d4f02d90b35330862daa
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3428
content:
"The role of the Intergovernmental Panel on Climate Change (IPCC) \r\nis to critically assess the scientific, technical and socio-economic \r\ninformation relevant to understanding the physical science and impacts \r\nof human-induced climate change and natural variations, including \r\nthe risks, opportunities and options for adaptation and mitigation. \r\nThis task is performed through a comprehensive assessment of the \r\nscientific literature. The robustness of IPCC assessments stems from \r\nthe systematic consideration and combination of multiple lines of \r\nindependent evidence. In addition, IPCC reports undergo one of the \r\nmost comprehensive, objective, open and transparent review and \r\nrevision processes ever employed for science assessments."


id: 6ec3c9e54b7991bc6b241668e501a7e9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16756
content:
"The WGI contribution to AR6 is focused on physical and biogeochemical \r\nclimate science information, with particular emphasis on regional \r\nclimate changes. These are relevant for mitigation, adaptation \r\nand risk assessment in the context of complex and evolving policy \r\nsettings, including the Paris Agreement, the global stocktake, \r\nthe Sendai Framework and the Sustainable Development Goals \r\n(SDGs) Framework."


id: d134816582647c11e06ccb1eb17615eb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34157
content:
"The core of this report consists of 12 chapters plus the Atlas \r\n(Figure  1.1), which can together be grouped into three categories \r\n(excluding this framing chapter):"


id: 8a5b7055befd509d4724cb75faba8ffd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21516
content:
"Starting with the First Assessment Report (FAR; IPCC, 1990a) the \r\nIPCC assessments have been structured into three Working Groups. \r\nWorking Group I (WGI) assesses the physical science basis of climate \r\nchange, Working Group II (WGII) assesses associated impacts, \r\nvulnerability and adaptation options, and Working Group III (WGIII) \r\nassesses mitigation response options. Each report builds on the \r\nearlier comprehensive assessments by incorporating new research \r\nand updating previous findings. The volume of knowledge assessed \r\nand the cross-linkages between the three Working Groups have \r\nsubstantially increased over time."


id: 5bc62650335dd068f05be933bf9e51c6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"Large-scale Information (Chapters 2, 3 and 4). These chapters \r\nassess climate information from global to continental or ocean-basin \r\nscales. Chapter 2 presents an assessment of the changing state of \r\nthe climate system, including the atmosphere, biosphere, ocean and \r\ncryosphere. Chapter 3 continues with an assessment of the human \r\ninfluence on this changing climate, covering the attribution of observed \r\nchanges, and introducing the fitness-for-purpose approach for the \r\nevaluation of climate models used to conduct the attribution studies. \r\nFinally, Chapter 4 assesses climate change projections, from the near "


id: 41050206bf1fff7de6f3b40653243d2c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"As part of its Sixth Assessment Cycle, from 2015 to 2022, the IPCC \r\nis producing three Working Group Reports, three targeted Special \r\nReports, a  Refinement to the 2006 IPCC Guidelines for National \r\nGreenhouse Gas Inventories, and a Synthesis Report. The AR6 Special \r\nReports covered the topics of Global Warming of 1.5degC (SR1.5; \r\nIPCC, 2018), Climate Change and Land (SRCCL; IPCC, 2019a) and \r\nThe Ocean and Cryosphere in a  Changing Climate (SROCC; IPCC, \r\n2019b). The SR1.5 and SRCCL are the first IPCC reports jointly \r\nproduced by all three Working Groups. This evolution towards a more \r\nintegrated assessment reflects a  broader understanding of the \r\ninterconnectedness of the multiple dimensions of climate change."


id: 126f772a0f6bdc997f1020862671eac1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"The Sixth Assessment Report (AR6) of the IPCC marks more than \r\n30  years of global collaboration to describe and understand, \r\nthrough expert assessments, one of the defining challenges of the \r\n21st century: human-induced climate change. Since the inception of \r\nthe IPCC in 1988, our understanding of the physical science basis \r\nof climate change has advanced markedly. The amount and quality of \r\ninstrumental observations and information from paleoclimate archives \r\nhave substantially increased. Understanding of individual physical, \r\nchemical and biological processes has improved. Climate model \r\ncapabilities have been enhanced, through the more realistic treatment \r\nof interactions among the components of the climate system, and \r\nimproved representation of the physical processes, in line with the \r\nincreased computational capacities of the world's supercomputers."


id: 77936c181461aa04bc64e70cf423319e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18239
content:
"This Report assesses both observed changes, and the components \r\nof these changes that are attributable to anthropogenic influence \r\n(i.e.,  human-induced), distinguishing between anthropogenic and "


id: 142b338265889889550d63e40b546732
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 762
content:
"Figure 1.1 | The structure of the AR6 WGI Report. Shown are the three pillars of \r\nthe AR6 WGI, its relation to the WGII and WGIII contributions, and the cross-working\u0002group AR6 Synthesis Report (SYR)."


id: 7b76600ad4626548e20cc2f57c17ad9f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18926
content:
"to the long term, including climate change beyond 2100, as well as \r\nthe potential for abrupt and 'low-likelihood, high-impact' outcomes."


id: aa97618ff419c052b0d7cc83f01ca7d6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
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content:
"Embedded in the chapters are Cross-Chapter Boxes that highlight \r\ncross-cutting issues. Each chapter also includes an Executive \r\nSummary (ES), and several Frequently Asked Questions (FAQs). \r\nTo enhance traceability and reproducibility of report figures and \r\ntables, detailed information on the input data used to create them, \r\nas well as links to archived code, are provided in the Input Data \r\nTables in chapter Supplementary Material. Additional metadata \r\non  the  model input datasets is provided via the report website \r\n(https://www.ipcc.ch/assessment-report/ar6/)."


id: fe182ac28341820e10e4904991c68844
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
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content:
"Process Understanding (Chapters 5, 6, 7, 8 and 9). These five\r\nchapters provide end-to-end assessments of fundamental Earth \r\nsystem processes and components: the carbon budget and \r\nbiogeochemical cycles (Chapter  5), short-lived climate forcers \r\nand their links to air quality (Chapter 6), the Earth's energy budget \r\nand climate sensitivity (Chapter  7), the water cycle (Chapter  8), \r\nand the ocean, cryosphere and sea level changes (Chapter  9). All \r\nthese chapters provide assessments of observed changes, including \r\nrelevant paleoclimatic information and understanding of processes \r\nand mechanisms as well as projections and model evaluation."


id: 478e4055c8399699f0e1a8552174b8f6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9806
content:
"The AR6 WGI Report includes a Summary for Policymakers (SPM)\r\nand a Technical Summary (TS). The integration among the three \r\nIPCC Working Groups is strengthened by the inclusion of the Cross\u0002Working-Group Glossary."


id: 9120a20693510d37ceff665550da3781
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22737
content:
"The AR6 WGI report, as a result of its scoping process, is structured \r\naround topics such as large-scale information, process understanding \r\nand regional information (Figure 1.1). This represents a rearrangement \r\nrelative to the structure of the WGI contribution to the IPCC Fifth \r\nAssessment Report (AR5; IPCC, 2013a), as summarized in Figure 1.2. \r\nThe AR6 approach aims at a  greater visibility of key knowledge \r\ndevelopments that are potentially relevant for policymakers, \r\nincluding climate change mitigation, regional adaptation planning \r\nbased on a risk management framework, and the global stocktake."


id: cc7d4ce1e250d5b9308aa8f76c1438ac
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"Two key subjects presented separately in AR5, paleoclimate and model \r\nevaluation, are now distributed among multiple AR6 WGI chapters. \r\nVarious other cross-cutting themes are also distributed throughout \r\nthis Report. A summary of these themes and their integration across \r\nchapters is described in Table 1.1."


id: 72904f5198a08099b0a3238437802dc4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 17397
content:
"Table 1.1 | Cross-cutting themes in AR6 WGI, and the main chapters that deal with them. Bold numbers in the table indicate the chapters that have extensive coverage."


id: e26a6c53a4bee8bd11d1601150d39fe0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 37129
content:
"Figure 1.2 | Main relations between AR5 WGI and AR6 WGI chapters. The left-hand column shows the AR5 WGI chapter categories. The central column lists the AR5 \r\nWGI chapters, with the colour code indicating their relation to the AR6 WGI structure shown in Figure 1.1: Large-Scale Information (purple), Process Understanding (gold), \r\nRegional Information (light blue) and Whole-Report Information (dark blue). AR5 WGI chapters depicted in white have their topics distributed over multiple AR6 WGI chapters \r\nand categories. The right-hand column explains where to find related information in the AR6 WGI report."


id: 68397649ee13780d5f256a280da9a842
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 15604
content:
"Box 7.1, are used to approximate large-scale climate responses of \r\ncomplex Earth System Models (ESMs) and have been used as tools to \r\nexplore the expected global surface air temperature (GSAT) response \r\nto multiple scenarios consistent with those assessed in WGI for the \r\nclassification of scenarios in WGIII. Chapter 6 provides information \r\nabout the impact of climate change on global air pollution, relevant \r\nfor WGII, including Cross-Chapter Box 6.1 on the implications of the \r\nrecent coronavirus pandemic (COVID-19) for climate and air quality. \r\nCross-Chapter Box  2.3 in Chapter  2  presents an integrated cross\u0002Working Group discussion of global temperature definitions, with \r\nimplications for many aspects of climate change science."


id: 647d47e3ff303002785d76ef88a47f6b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 14955
content:
"Integration of assessments across the chapters of the WGI Report, \r\nand with WGII and WGIII, occurs in a number of ways, including work \r\non a  common Glossary, risk framework (Cross-Chapter Box  1.3), \r\nscenarios and projections of future large-scale changes, and the \r\npresentation of results at various global warming levels (Section 1.6)."


id: b7a39a3a326eefd4409c11a482f734b8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29522
content:
"Chapters 8 to 12, and the Atlas, cover topics also assessed by WGII \r\nin several areas, including regional climate information and climate\u0002related risks. This approach produces a more integrated assessment \r\nof impacts of climate change across Working Groups. In particular, \r\nChapter 10 discusses the generation of regional climate information \r\nfor users, the co-design of research with users, and the translation \r\nof information into the user context (in particular directed towards \r\nWGII). Chapter 12 provides a direct bridge between physical climate \r\ninformation (climatic impact-drivers) and sectoral impacts and risk, \r\nfollowing the chapter organization of the WGII Assessment. Notably, \r\nCross-Chapter Box  12.1 draws a  connection to representative key \r\nrisks and Reasons for Concern (RFC)."


id: 77f8c9583c395c7b7f823bfeeab19130
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18314
content:
"In addition, Chapter 1 sets out a shared terminology on cross-cutting \r\ntopics, including climate risk, attribution and storylines, as well as \r\nan introduction to emissions scenarios, global warming levels and \r\ncumulative carbon emissions as an overarching topic for integration \r\nacross all three Working Groups."


id: 3f20cac77bb76eb3ffa443bf8491090c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8296
content:
"All these integration efforts are aimed at enhancing the bridges \r\nand 'handshakes' among Working Groups, enabling the final cross\u0002Working Group exercise of producing the integrated Synthesis Report."


id: d9efa6168c3b344aa8f96f002d77db3
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35643
content:
"The science assessed in Chapters 2 to 7, such as the carbon budget, \r\nshort-lived climate forcers (SLCFs) and emissions metrics, are topics \r\nin common with WGIII, and relevant for the mitigation of climate \r\nchange. This includes a  consistent presentation of the concepts of \r\ncarbon budget and net zero emissions targets within chapters, in \r\norder to support integration in the Synthesis Report. Emissions-driven \r\nemulators (simple climate models), summarized in Cross-Chapter "


id: 570b3ebf5f0e23fe4bdec9ef3b6b4312
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12568
content:
"system have continued, and these are assessed in full in later \r\nchapters. Here, we summarize changes to a  set of key large-scale \r\nclimate indicators over the modern era (1850 to present). We also \r\ndiscuss the changes in relation to the longer-term evolution of the \r\nclimate. These ongoing changes throughout the climate system form \r\na key part of the context of the present Report."


id: fbee804eb51c59a61282501126f887c8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41684
content:
"Special Reports prepared as part of the Sixth Assessment Cycle; \r\n(ii) to describe key concepts and methods, relevant developments \r\nsince AR5, and the modelling framework used in this Assessment; \r\nand (iii) together with the other chapters of this report, to provide \r\ncontext and support for the WGII and WGIII contributions to AR6, \r\nparticularly on climate information to support mitigation, adaptation \r\nand risk management."


id: 60de89eac79f8c3612b5c3ae9a3307be
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14340
content:
"The IPCC Sixth Assessment Cycle occurs in the context of increasingly \r\napparent climatic changes observed across the physical climate \r\nsystem. Many of these changes can be attributed to anthropogenic \r\ninfluences, with impacts on natural and human systems. The AR6 also \r\noccurs in the context of efforts in international climate governance \r\nsuch as the Paris Agreement, which sets a  long-term goal to hold \r\nthe increase in global average temperature to 'well below 2degC above \r\npre-industrial levels, and to pursue efforts to limit the temperature \r\nincrease to 1.5degC above pre-industrial levels, recognizing that this \r\nwould significantly reduce the risks and impacts of climate change.' \r\nThis section summarizes key elements of the broader context \r\nsurrounding the assessments made in the present report."


id: b562b0774b099d25979c5a08ebb8c1dd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29144
content:
"Figure  1.4 documents that the climate system is undergoing \r\na  comprehensive set of changes. It shows a  selection of key \r\nindicators of change through the instrumental era that are \r\nassessed and presented in the subsequent chapters of this report. \r\nAnnual mean values are shown as stripes, with colours indicating \r\ntheir value. The transitions from one colour to another over \r\ntime illustrate how conditions are shifting in all components of \r\nthe climate system. For these particular indicators, the observed \r\nchanges go beyond the yearly and decadal variability of the \r\nclimate system. In this Report, this is termed an 'emergence' of the \r\nclimate signal (Section 1.4.2 and FAQ 1.2)."


id: 105ba178bdc8f99e1cb1a6341492c094
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 69
content:
"Warming of the climate system is most commonly presented \r\nthrough the observed increase in global mean surface temperature \r\n(GMST). Taking a  baseline of 1850-1900, GMST change until \r\npresent (2011-2020) is 1.09degC [0.95 to 1.20] degC (Section  2.3 and \r\nCross-Chapter Box 2.3). This evolving change has been documented \r\nin previous assessment reports, with each reporting a  higher \r\ntotal global temperature change (Section  1.3 and Cross-Chapter \r\nBox  1.2). The  total change in global surface air temperature \r\n(GSAT) (Section  1.4.1 and Cross-Chapter Box  2.3) attributable \r\nto anthropogenic activities is assessed to be consistent with the \r\nobserved change in GSAT (Section 3.3).1"


id: f06586449ff2242e5ca2adc421d346fb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39675
content:
"The WGI contribution to AR5 (AR5 WGI; IPCC, 2013a) assessed \r\nthat 'warming of the climate system is unequivocal', and that since \r\nthe 1950s, many of the observed changes are unprecedented over \r\ndecades to millennia. Changes are evident in all components  of \r\nthe climate system: the atmosphere and the ocean have warmed, \r\namounts of  snow and ice have diminished, sea level has risen, \r\nthe ocean has acidified and its oxygen content has declined, and \r\natmospheric  concentrations of greenhouse gases (GHGs) have \r\nincreased (IPCC, 2013b). This Report documents that, since the AR5, \r\nchanges to the state of the physical and biogeochemical climate "


id: d40c0dc4b86e152472a9e2c2b6cd1046
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 34635
content:
"recent decade (2010-2019) was the lowest since the beginning of \r\nthe 20th century (Sections 2.3 and 9.5)."


id: 88bbd83d7cfb02608c11bb911bd47a4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 21218
content:
"Similarly, atmospheric concentrations of a  range of GHGs are \r\nincreasing. Carbon dioxide (CO2, shown in Figure 1.4 and Figure 1.5a, \r\nfound in AR5 and earlier reports to be the current strongest driver of \r\nanthropogenic climate change), has increased from 285.5 +- 2.1 ppm \r\nin 1850 to 409.9  +-  0.4  ppm in 2019; concentrations of methane \r\n(CH4), and nitrous oxide (N2O) have increased as well (Sections 2.2 \r\nand 5.2, and Annex V). These observed changes are assessed \r\nto be in line with known anthropogenic and natural emissions, \r\nwhen accounting for observed and inferred uptake by land, ocean \r\nand biosphere respectively (Section  5.2), and are a  key source of \r\nanthropogenic changes to the global energy balance (or radiative \r\nforcing; Sections 2.2 and 7.3)."


id: 4fda399663ef46798ad843d3d2c94caa
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11343
content:
"The global ocean has warmed unabatedly since at least 1970 \r\n(Sections 1.3, 2.3 and 9.2; SROCC, IPCC, 2019b). Figure 1.4 shows \r\nhow the averaged ocean heat content is steadily increasing, with \r\na total increase of [0.28 to 0.55] yottajoule (YJ; 1024 joule) between \r\n1971 and 2018 (Section 9.2). In response to this ocean warming, as \r\nwell as to the loss of mass from glaciers and ice sheets, the global \r\nmean sea level (GMSL) has risen by 0.20 [0.15 to 0.25] metres \r\nbetween 1900 and 2018. GMSL rise has accelerated since the late \r\n1960s (see Section 9.6)."


id: cbff8c53575dc8400fdd68b058bf6406
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33215
content:
"Overall, the changes in these selected climatic indicators have progressed \r\nbeyond the range of natural year-to-year variability (Chapters  2, 3, \r\n8 and 9, and Sections 1.2.1.2 and 1.4.2). The indicators presented in \r\nFigure 1.4 document a broad set of concurrent and emerging changes \r\nacross the physical climate system. All indicators shown here, along with \r\nmany others, are further presented in the coming chapters, together \r\nwith a rigorous assessment of the supporting scientific literature. Later \r\nchapters (Chapters 10, 11, 12 and Atlas) present similar assessments \r\nat the regional level, where observed changes do not always align with \r\nthe global mean picture shown here."


id: e3c0f5cf7278dd25851460cfe19489ac
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37357
content:
"The hydrological (or water) cycle is also changing and is assessed \r\nto be intensifying, through a higher exchange of water between the \r\nsurface and the atmosphere (Sections  2.3 and 8.3). The resulting \r\nregional patterns of changes to precipitation are, however, different \r\nfrom surface temperature change, and interannual variability is larger, \r\nas illustrated in Figure 1.4. Annual land area mean precipitation in \r\nthe Northern Hemisphere temperate regions has increased, while the \r\nsubtropical dry regions have experienced a decrease in precipitation \r\nin recent decades (Section 2.3)."


id: d909bce976ffc22a6bb20d466b765976
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35483
content:
"The cryosphere is undergoing rapid changes, with increased melting \r\nand loss of frozen water mass in most regions. This includes all \r\nfrozen parts of the globe, such as terrestrial snow, permafrost, sea \r\nice, glaciers, freshwater ice, solid precipitation, and the ice sheets \r\ncovering Greenland and Antarctica (Chapter 9; SROCC, IPCC, 2019b). \r\nFigure 1.4 illustrates how, globally, glaciers have been increasingly \r\nlosing mass for the last fifty years. The total glacier mass in the most "


id: 95892bbe26ba1834690acae0b83cb95e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23512
content:
"Paleoclimate archives (e.g., ice cores, corals, marine and lake sediments, \r\nspeleothems, tree rings, borehole temperatures, soils) permit the \r\nreconstruction of climatic conditions before the instrumental era. "


id: 6cc860a707868e72c9bacfc2aae00e80
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16416
content:
"changes in global mean temperature of a few degrees Celsius are \r\nassociated with increases in sea level of several tens of metres \r\n(Figure  1.5). During two extended warm periods (interglacials) of \r\nthe last 800 kyr, sea level is estimated to have been at least six \r\nmetres higher than today (Chapter  2; Dutton et al., 2015). During \r\nthe last interglacial, sustained warmer temperatures in Greenland \r\npreceded the peak of sea level rise (Figure 5.15 in Masson-Delmotte \r\net al., 2013). The paleoclimate record therefore provides substantial \r\nevidence directly linking warmer GMST to substantially higher GMSL."


id: 3a90505ad3885e63e30c5ef6fa94eb75
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7510
content:
"GMST will remain above present-day levels for many centuries even \r\nif net CO2 emissions are reduced to zero, as shown in simulations \r\nwith coupled climate models (Section  4.7.1; Plattner et al., 2008; \r\nSection 12.5.3 in Collins et al., 2013; Zickfeld et al., 2013; MacDougall \r\net al., 2020). Such persistent warm conditions in the atmosphere \r\nrepresent a  multi-century commitment to long-term sea level rise, \r\nsummer sea ice reduction in the Arctic, substantial ice-sheet melting, \r\npotential ice-sheet collapse, and many other consequences in all \r\ncomponents of the climate system (Section 9.4 and Figure 1.5; Clark \r\net al., 2016; Pfister and Stocker, 2016; H. Fischer et al., 2018)."


id: 726d216023126eee0832431ec91d95e6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17369
content:
"Paleoclimate records also show centennial- to millennial-scale \r\nvariations, particularly during the ice ages, which indicate rapid or \r\nabrupt changes of the Atlantic Meridional Overturning Circulation \r\n(AMOC; Section  9.2.3.1) and the occurrence of a 'bipolar seesaw' \r\n(opposite-phase surface temperature changes in both hemispheres; \r\nSection  2.3.3.4.1; Stocker and Johnsen, 2003; EPICA Community \r\nMembers, 2006; WAIS Divide Project Members et al., 2015; Lynch\u0002Stieglitz, 2017; Pedro et al., 2018; Weijer et al., 2019). This process \r\nsuggests that instabilities and irreversible changes could be triggered \r\nif critical thresholds are passed (Section  1.4.4.3). Several other \r\nprocesses involving instabilities are identified in climate models \r\n(Drijfhout et al., 2015), some of which may now be close to critical \r\nthresholds (Section 1.4.4.3; see also Chapters 5, 8 and 9 regarding \r\ntipping points; Joughin et al., 2014)."


id: 36eecce85fe6c286987d97828d2a4bdd
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
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content:
"Paleoclimatic information also provides a  long-term perspective \r\non rates of change of these three key indicators. In high-resolution \r\nreconstructions from polor ice cores, the rate of increase in \r\natmospheric CO2 observed over 1919-2019 CE is one order of \r\nmagnitude higher than the fastest CO2 fluctuations documented \r\nduring the Last Glacial Maximum and the last deglacial transition \r\n(Marcott et al., 2014, see Chapter 2, Section 2.2.3.2.1). Current multi\u0002decadal GMST exhibit a higher rate of increase than over the past \r\n2  kyr (Section  2.3.1.1.2; PAGES 2k Consortium, 2019), and in the \r\n20th  century GMSL rise was faster than during any other century \r\nover the past 3 kyr (Section 2.3.3.3)."


id: 352ea27e77f27d9b9009c52ab1ebc6fe
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 6606
content:
"Based on Figure 1.5, the reconstructed, observed and projected ranges \r\nof changes in the three key indicators can be compared. By the first \r\ndecade of the 20th  century, atmospheric CO2 concentrations had \r\nalready moved outside the reconstructed range of natural variation "


id: f90f9f4ee7203cbf01bf655bddcf253b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41182
content:
"Paleoclimate reconstructions also shed light on the causes of these \r\nvariations, revealing processes that need to be considered when \r\nprojecting climate change. The paleorecords show that sustained "


id: 78d07940bde8f77bd9e8db3b3ca922cc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
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content:
"over the past 800 kyr. On the other hand, GMST and GMSL were higher \r\nthan today during several interglacials of that period (Sections 2.3.1 \r\nand 2.3.3, and Figure 2.34). Projections for the end of the 21st century, \r\nhowever, show that GMST will have moved outside of its natural range \r\nwithin the next few decades, except for the strong mitigation scenarios \r\n(Section  1.6). There is a  risk that GMSL may potentially leave the \r\nreconstructed range of natural variations over the next few millennia \r\n(Section 9.6.3.5; Clark et al., 2016; SROCC, IPCC, 2019b). In addition, \r\nabrupt changes can not be excluded (Section 1.4.4.3)."


id: 5ebeac41b57a3b2e451a3e52d299b186
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
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content:
"The IPCC First Assessment Report (FAR, IPCC, 1990a) provided the \r\nscientific background for the establishment of the UNFCCC (UNFCCC, \r\n1992), which committed parties to negotiate ways to 'prevent \r\ndangerous anthropogenic interference with the climate system' (the \r\nultimate objective of the UNFCCC). The Second Assessment Report \r\n(SAR, IPCC, 1996) informed governments in negotiating the Kyoto \r\nProtocol (1997), the first major agreement focusing on mitigation \r\nunder the UNFCCC. The Third Assessment report (TAR, IPCC, \r\n2001a) highlighted the impacts of climate change and the need for \r\nadaptation, and introduced the treatment of new topics such as policy \r\nand governance in IPCC reports. The Fourth and Fifth Assessment \r\nReports (AR4, IPCC, 2007a; AR5, IPCC, 2013a) provided the scientific \r\nbackground for the second major agreement under the UNFCCC: the \r\nParis Agreement (2015), which entered into force in 2016."


id: 51da0056a3cc89f313037aef4b1448fb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11687
content:
"An important time period in the assessment of anthropogenic climate \r\nchange is the last 2 kyr. Since AR5, new global datasets have been \r\nproduced that aggregate aggregating local and regional paleorecords \r\n(PAGES 2k Consortium, 2013, 2017, 2019; McGregor et al., 2015; \r\nTierney et al., 2015; Abram et al., 2016; Hakim et al., 2016; Steiger \r\net al., 2018; Bronnimann et al., 2019b). Before the global warming \r\nthat began around the mid-19th century (Abram et al., 2016), a slow \r\ncooling in the Northern Hemisphere from roughly 1450-1850 CE is \r\nconsistently recorded in paleoclimate archives (PAGES 2k Consortium, \r\n2013; McGregor et al., 2015). While this cooling, primarily driven by \r\nan increased number of volcanic eruptions (Section 3.3.1; PAGES 2k \r\nConsortium, 2013; Owens et al., 2017; Bronnimann et al., 2019b), \r\nshows regional differences, the subsequent warming over the past \r\n150 years exhibits a global coherence that is unprecedented in the \r\nlast 2 kyr (Neukom et al., 2019)."


id: 11359a96fdc6df279d0f47c54f6c8d08
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 222
content:
"Parties to the PA commit to the goal of limiting global average \r\ntemperature increase to 'well below 2degC above pre-industrial levels, \r\nand to pursue efforts to limit the temperature increase to 1.5degC \r\nin order to significantly reduce the risks and impacts of climate \r\nchange'. In AR6, as in many previous IPCC reports, observations and \r\nprojections of changes in global temperature are expressed relative \r\nto 1850-1900 as an approximation for pre-industrial levels (Cross\u0002Chapter Box 1.2)."


id: d5fdc191dce895985b4da9562cab1156
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"The PA further addresses mitigation (Article  4) and adaptation to \r\nclimate change (Article 7), as well as loss and damage (Article 8), \r\nthrough the mechanisms of finance (Article  9), technology \r\ndevelopment and transfer (Article 10), capacity-building (Article 11) \r\nand education (Article 12). To reach its long-term temperature goal, \r\nthe PA recommends 'achieving a  balance between anthropogenic \r\nemissions by sources and removals by sinks of greenhouse gases in \r\nthe second half of this century', a state commonly described as 'net \r\nzero' emissions (Article 4) (Section 1.6 and Box 1.4). Each Party to the \r\nPA is required to submit a Nationally Determined Contribution (NDC) \r\nand pursue, on a voluntary basis, domestic mitigation measures with \r\nthe aim of achieving the objectives of its NDC (Article 4)."


id: d509725d515239829a3fb6f2f5ae23c3
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"The contexts of both policymaking and societal understanding about \r\nclimate change have evolved since AR5 was published (2013-2014). \r\nIncreasing recognition of the urgency of the climate change threat, \r\nalong with still-rising emissions and unresolved issues of mitigation \r\nand adaptation, including aspects of sustainable development, \r\npoverty eradication and equity, have led to new policy efforts. This \r\nsection summarizes these contextual developments and how they \r\nhave shaped, and been used during the preparation of this Report."


id: a576c2449bf5e66c8986ea0537d12b80
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"collective progress toward achieving the PA long-term goals. These \r\nprocesses will rely upon the assessments prepared during the IPCC \r\nSixth Assessment Cycle (e.g.,  Cross-Chapter Box  1.1; Schleussner \r\net al., 2016b)."


id: 99738f0f123b28f5f73dcb47f4be768a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 24224
content:
"Since AR5, the formal dialogue between the scientific and policy \r\ncommunities has been strengthened through a  new science-\r\npolicy interface, the Structured Expert Dialogue (SED). The SED was \r\nestablished by UNFCCC to support the work of its two subsidiary \r\nbodies, the Subsidiary Body for Scientific and Technological Advice \r\n(SBSTA) and the Subsidiary Body for Implementation (SBI). The first \r\nSED aimed to 'ensure the scientific integrity of the first periodic review' \r\nof the UNFCCC, the 2013-2015 review. The Mandate of the periodic \r\nreview is to 'assess the adequacy of the long-term (temperature) \r\ngoal in light of the ultimate objective of the convention' and the \r\n'overall progress made towards achieving the long-term global goal, \r\nincluding a consideration of the implementation of the commitments \r\nunder the Convention.'"


id: 2082a46a9e96f4132baed2468b1da741
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
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content:
"Cross-Chapter Box 1.1 | The WGI Contribution to AR6 and Its Potential Relevance for the \r\nGlobal Stocktake"


id: 6385eecd10521dc62ec2c9e405d63e48
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"Contributing Authors: Malte Meinshausen (Australia/Germany), Gian-Kasper Plattner (Switzerland), Aida Diongue-Niang (Senegal), \r\nFrancisco J. Doblas-Reyes (Spain), David Frame (New Zealand), Nathan P. Gillett (Canada), Helene T. Hewitt (United Kingdom), \r\nRichard G. Jones (United Kingdom), Hong Liao (China), Jochem Marotzke (Germany), James Renwick (New Zealand), Joeri Rogelj \r\n(United Kingdom, Belgium), Maisa Rojas (Chile), Sonia I. Seneviratne (Switzerland), Claudia Tebaldi (United States of America), \r\nBlair Trewin (Australia)"


id: 91d35e8252dbdf50127565f560275488
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22877
content:
"The PA further specifies that the stocktake shall be undertaken in a 'comprehensive and facilitative manner, considering mitigation, \r\nadaptation and the means of implementation and support, and in the light of equity and the best available science' (Article 14)."


id: 66e24a1eef094bd753884c18a29fda4f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 15366
content:
"The sources of input envisaged for the global stocktake include the 'latest reports of the Intergovernmental Panel on Climate Change' \r\nas a central source of information.4 The global stocktake is one of the key formal avenues for scientific inputs into the UNFCCC and PA \r\nnegotiation process alongside, for example, the Structured Expert Dialogues (SEDs) under the UNFCCC (Section 1.2.2).5"


id: db7976dbf3eacbe4efb3a532167de07
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"The WGI Assessment provides a  wide range of information with potential relevance for the global stocktake, \r\ncomplementing the IPCC AR6 Special Reports, the contributions from WGII and WGIII and the Synthesis Report. This \r\nincludes the state of GHG emissions and concentrations, the current state of the climate, projected long-term warming levels under \r\ndifferent scenarios, near-term projections, the attribution of extreme events, and remaining carbon budgets. Cross-Chapter Box 1.1, \r\nTable 1 provides pointers to the in-depth material that WGI has assessed and that may be relevant for the global stocktake."


id: 1d7889887b17fa2a845d1ac17093f093
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
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content:
"The following tabular overview of potentially relevant information from the WGI contribution for the global stocktake is \r\nstructured into three sections: the current state of the climate, the long-term future, and the near-term. These sections and \r\ntheir order align with the three questions of the Talanoa dialogue, launched during COP23, based on the Pacific concept of talanoa6: \r\n'Where are we', 'Where do we want to go' and 'How do we get there?'"


id: 771a0072598817c39e9b30c77478f4f
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 18153
content:
"Cross-Chapter Box 1.1, Table 1 | WGI assessment findings and their potential relevance for the global stocktake. The table combines information \r\nassessed in this report that could potentially be relevant for the global stocktake process. Section 1 focuses on the current state of the climate and its recent \r\npast. Section 2 focuses on long-term projections in the context of the PA's 1.5degC and 2.0degC goals and on progress towards net zero greenhouse gas emissions. \r\nSection 3 considers challenges and key insights for mitigation and adaptation in the near term from a WGI perspective. Further information on potential relevance of \r\nthe aspects listed here in terms of, for example, impacts and socio-economic aspects can be found in the WGII and WGIII reports"


id: d90e27706feb54da52c849270a0e0383
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35488
content:
"The Sendai Framework for Disaster Risk Reduction is a non-binding \r\nagreement to reduce risks associated with disasters of all scales, \r\nfrequencies and onset rates caused by natural or human-made \r\nhazards, including climate change. The SFDRR outlines targets and \r\npriorities for action including 'understanding disaster risk', along \r\nthe dimensions of vulnerability, exposure of persons and assets, \r\nand hazard characteristics. Chapter 12 assesses climate information \r\nrelevant to regional impact and risk assessment, with a  focus on \r\nclimate hazards and other aspects of climate that influence society \r\nand ecosystems and makes the link with Working Group II. AR6 \r\nadopts a  consistent risk- and solution-oriented framing (Cross\u0002Chapter Box  1.3) that calls for a  multidisciplinary approach and \r\ncross-Working Group coordination in order to ensure integrative \r\ndiscussions of major scientific issues associated with integrative risk \r\nmanagement and sustainable solutions (IPCC, 2017)."


id: c0f1e3bda933b3ac6d1ec4c63a927358
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"1.2.2.6 The Intergovernmental Science-Policy Platform \r\non Biodiversity and Ecosystem Services (IPBES)"


id: a1e9e3f63089291e079ca2d25fe44b50
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"Efforts to address climate change take place alongside and in the \r\ncontext of other major environmental problems, such as biodiversity \r\nloss. IPBES, established in 2012, builds on the IPCC model of \r\na science-policy interface and assessment. The Platform's objective \r\nis to 'strengthen the science-policy interface for biodiversity "


id: 2a03c6f803a70f1d05564386e6252d3c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 4612
content:
"and ecosystem services for the conservation and sustainable \r\nuse of biodiversity, long-term human well-being and sustainable \r\ndevelopment' (UNEP, 2012). The SROCC (IPCC, 2019b) and SRCCL \r\n(IPCC, 2019a) assessed the relations between changes in biodiversity \r\nand in the climate system. The rolling work programme of IPBES up \r\nto 2030 will address interlinkages among biodiversity, water, food \r\nand health. This assessment will use a nexus approach to examine \r\ninterlinkages between biodiversity and the above-mentioned issues, \r\nincluding climate change mitigation and adaptation. Furthermore, \r\nIPBES and IPCC will directly collaborate on biodiversity and climate \r\nchange under the rolling work programme."


id: f8966a82ecda66c900e3305bf84c03ef
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41096
content:
"Responses to climate change are facilitated when leaders, \r\npolicymakers, resource managers and their constituencies share \r\na  basic understanding of the causes, effects, and possible future \r\ncourse of climate change (SR1.5, IPCC, 2018; SRCCL, IPCC, 2019a). \r\nAchieving shared understanding is complicated, since scientific \r\nknowledge interacts with pre-existing conceptions of weather and \r\nclimate that have built up in diverse world cultures over centuries, \r\nand which are often embedded in strongly held values and beliefs \r\nstemming from ethnic or national identities, traditions, religions, and \r\nlived relationships to weather, land and sea (Van Asselt and Rotmans, \r\n1996; Rayner and Malone, 1998; Hulme, 2009, 2018; Green et al., \r\n2010; Jasanoff, 2010; Orlove et al., 2010; Nakashima et al., 2012; \r\nShepherd and Sobel, 2020). These diverse, more local understandings \r\ncan both contrast with and enrich the planetary-scale analyses of \r\nglobal climate science (high confidence)."


id: 2895f6cc04d3a7e19d4553d02f051c27
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 4351
content:
"The evolving governance context since AR5 challenges the IPCC to \r\nprovide policymakers and other actors with information relevant for \r\nboth adaptation to and mitigation of climate change, and for the loss \r\nand damage induced."


id: 98985c031e1b3cf8512c11724d34a292
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 24060
content:
"Furthermore, climate change itself is not uniform. Some regions face \r\nsteady, readily observable change, while others experience high \r\nvariability that masks underlying trends (Section 1.4.1); most regions \r\nare subject to hazards, but some may also experience benefits, \r\nat least temporarily (Chapters 11, 12 and Atlas). This non-uniformity \r\nmay lead to wide variation in public climate change awareness and \r\nrisk perceptions at multiple scales (Howe et al., 2015; Lee et al., 2015). \r\nFor example, short-term temperature trends, such as cold spells or \r\nwarm days, have been shown to influence public concern (Hamilton \r\nand Stampone, 2013; Zaval et al., 2014; Bohr, 2017)."


id: 802c057f1f28439d23b03dcdf6c8cb72
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19678
content:
"This section assesses how the process of communicating climate \r\ninformation has evolved since AR5. It summarizes key issues regarding \r\nscientific uncertainty addressed in previous IPCC assessments and \r\nintroduces the IPCC calibrated uncertainty language. Next it discusses \r\nthe role of values in problem-driven, multidisciplinary science \r\nassessments such as this one. The section introduces climate services \r\nand how climate information can be tailored for greatest utility in \r\nspecific contexts, such as the global stocktake. Finally, we briefly \r\nevaluate changes in media coverage of climate information since AR5, \r\nincluding the increasing role of Internet sources and social media."


id: f114856f4c8ec8ee5b0e434f663e580a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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"Given these manifold influences and the highly varied contexts \r\nof climate change communication, special care is required when \r\nexpressing findings and uncertainties, including IPCC assessments \r\nthat inform decision making. Throughout the IPCC's history, all three \r\nWorking Groups have sought to explicitly assess and communicate \r\nscientific uncertainty (Le Treut et al., 2007; Cubasch et al., 2013). "


id: 3ab55524189133e8e8c38d038a2b41aa
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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"communicating authors' expert judgments (Mastrandrea and Mach, \r\n2011). During the AR5 cycle, this calibrated uncertainty language was \r\nupdated and unified across all Working Groups (Mastrandrea et al., \r\n2010, 2011). Box 1.1 summarizes this framework as it is used in AR6."


id: 5bf6fc0f8f754495dc4bd4fd7974c2aa
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 13443
content:
"Over time, the IPCC has developed and revised a  framework to \r\ntreat uncertainties consistently across assessment cycles, reports, \r\nand Working Groups through the use of calibrated language (Moss \r\nand Schneider, 2000; IPCC, 2005). Since its First Assessment Report \r\n(FAR; IPCC, 1990a), the IPCC has specified terms and methods for "


id: 6805aa94e34787d7677e2a21ca0da681
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 15569
content:
"The AR6 follows the approach developed for AR5 (Box 1.1, Figure 1), as described in the 'Guidance Notes for Lead Authors of the IPCC \r\nFifth Assessment Report on Consistent Treatment of Uncertainties' (Mastrandrea et al., 2010). The uncertainty Guidance Note used \r\nin AR6 clarifies the relationship between the qualitative description of confidence and the quantitative representation of uncertainty \r\nexpressed by the likelihood scale. The calibrated uncertainty language emphasizes traceability of the assessment throughout the \r\nprocess. Key chapter findings presented in each chapter's Executive Summary are supported in the chapter text by a summary of the \r\nunderlying literature that is assessed in terms of evidence and agreement, confidence, and also likelihood, if applicable."


id: 491895334a5bb6cb8e70ceb14b6a6b75
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 10082
content:
"In all three Working Groups, author teams evaluate underlying scientific understanding and use two metrics to communicate the \r\ndegree of certainty in key findings. These metrics are:"


id: f66589d1f9663de4b7188c3617388dce
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40715
content:
"Throughout IPCC reports, the calibrated language indicating a formal confidence assessment is clearly identified by italics (e.g., medium \r\nconfidence). Where appropriate, findings can also be formulated as statements of fact without uncertainty qualifiers."


id: 5dd0c7e3447ed294053238dd44c63e73
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 13803
content:
"Box.1.1, Figure 1 (adapted from Mach et al., 2017) shows the idealized step-by-step process by which IPCC authors assess scientific \r\nunderstanding and uncertainties. It starts with the evaluation of the available evidence and agreement (steps 1-2). The following \r\nsummary terms are used to describe the available evidence: limited, medium, or robust; and the degree of agreement: low, medium, or \r\nhigh. Generally, evidence is most robust when there are multiple, consistent, independent lines of high-quality evidence."


id: 25f1ce56eb0b1eec6333497c12b6ead
created_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 3854
content:
"If the expert judgement of the author team concludes that there is sufficient confidence and quantitative/probabilistic evidence, \r\nassessment conclusions can be expressed with likelihood statements (steps 5-6). Unless otherwise indicated, likelihood statements \r\nare related to findings for which the authors' assessment of confidence is high or very high. Terms used to indicate the assessed \r\nlikelihood of an outcome include: virtually certain: 99-100% probability, very likely: 90-100%, likely: 66-100%, about as likely as not: \r\n33-66%, unlikely: 0-33%, very unlikely: 0-10%, exceptionally unlikely: 0-1%. Additional terms (extremely likely: 95-100%, more \r\nlikely than not >50-100%, and extremely unlikely 0-5%) may also be used when appropriate."


id: 11f080746ccc9b75b1ae75ccf1ab419f
created_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 343
content:
"Likelihood can indicate probabilities for single events or broader outcomes. The probabilistic information may build from statistical \r\nor modelling analyses, other quantitative analyses, or expert elicitation. The framework encourages authors, where appropriate, to \r\npresent probability more precisely than can be done with the likelihood scale, for example with complete probability distributions or \r\npercentile ranges, including quantification of tails of distributions, which are important for risk management (Sections 1.2.2 and 1.4.4; \r\nMach et al., 2017). In some instances, multiple combinations of confidence and likelihood are possible to characterize key findings"


id: 712f0cca9011353e58596cea6409ef73
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17171
content:
"Box 1.1, Figure 1 | The IPCC AR6 approach for characterizing understanding and uncertainty in assessment findings. This diagram illustrates the \r\nstep-by-step process authors use to evaluate and communicate the state of knowledge in their assessment (Mastrandrea et al., 2010). Authors present evidence/\r\nagreement, confidence, or likelihood terms with assessment conclusions, communicating their expert judgments accordingly. Example conclusions drawn from Report \r\nare presented in the box at the bottom of the figure. Figure adapted from Mach et al. (2017) ."


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vector_id: 24612
content:
"For example, a very likely statement might be made with high confidence, whereas a likely statement might be made with very high \r\nconfidence. In these instances, the author teams consider which statement will convey the most balanced information to the reader."


id: d4310006457f913763bbdb92f847a16a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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vector_id: 34663
content:
"Throughout this WGI Report, unless stated otherwise, uncertainty is quantified using 90% uncertainty intervals. The 90% uncertainty \r\ninterval, reported in square brackets [x to y], is estimated to have a 90% likelihood of covering the value that is being estimated. \r\nThe range encompasses the median value and there is an estimated 10% combined likelihood of the value being below the lower end \r\nof the range (x) and above its upper end (y). Often the distribution will be considered symmetric about the corresponding best estimate \r\n(as in the illustrative example in the figure), but this is not always the case. In this report, an assessed 90% uncertainty interval is \r\nreferred to as a 'very likely range'. Similarly, an assessed 66% uncertainty interval is referred to as a 'likely range'."


id: 74b2d9a5f0bbb9c6ff99c9f2940ba7c1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17770
content:
"for example, the transparency and traceability of expert judgements \r\nunderlying the assessment conclusions (Oppenheimer et al., 2016) \r\nand the context-dependent representations and interpretations \r\nof probability terms (Budescu et al., 2009, 2012; Janzwood, 2020). "


id: 189b5d136f1808584e352d100b001d19
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 1542
content:
"Considerable critical attention has focused on whether applying \r\nthe IPCC framework effectively achieves consistent treatment of \r\nuncertainties and clear communication of findings to users (Shapiro \r\net al., 2010; Adler and Hirsch Hadorn, 2014). Specific concerns include, "


id: 58cd753f81f1c37bf584f7828c53024b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 12868
content:
"Chapter  9  (Section  9.2.3) notes deep uncertainty in long-term \r\nprojections for sea level rise, and in processes related to marine ice\u0002sheet instability and marine ice cliff instability."


id: 60a2ad556f490a5c9418dfa3014b4118
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14299
content:
"Some suggested alternatives are impractical, such as always \r\nincluding numerical values along with calibrated language (Budescu \r\net al., 2014). Others, such as using positive instead of negative \r\nexpressions of low-to-medium probabilities, show promise but were \r\nnot proposed in time for adoption in AR6 (Juanchich et al., 2020). This \r\nreport therefore retains the same calibrated language used in AR5 \r\n(Box 1.1). Like previous reports, AR6 also includes FAQs that express \r\nits chief conclusions in plain language designed for lay readers."


id: f317047b4470361ad55878418cf28717
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
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content:
"The formal Principles Governing IPCC Work (1998, amended 2003, \r\n2006, 2012, 2013) specify that assessments should be 'comprehensive, \r\nobjective, open and transparent.' The IPCC assessment process seeks \r\nto achieve these goals in several ways: by evaluating evidence and \r\nagreement across all relevant peer-reviewed literature, especially that \r\npublished or accepted since the previous assessment; by maintaining \r\na  traceable, transparent process that documents the reasoning, \r\ndata and tools used in the assessment; and by maximizing the \r\ndiversity of participants, authors, experts, reviewers, institutions and \r\ncommunities represented, across scientific discipline, geographical "


id: b8cf298a93cbf201ef5505e0e4e9b7e6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 29719
content:
"location, gender, ethnicity, nationality and other characteristics. \r\nThe multi-stage review process is critical to ensure an objective, \r\ncomprehensive and robust assessment, with hundreds of scientists, \r\nother experts and governments providing comments to a series of \r\ndrafts before the report is finalized."


id: d7839919b6fa6ec4e6b564e5663444c8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35222
content:
"Since AR5, climate services have increased at multiple levels (local, \r\nnational, regional and global) to aid decision-making of individuals \r\nand organizations and to enable preparedness and early climate \r\nchange action. These services include appropriate engagement from \r\nusers and providers, are based on scientifically credible information \r\nand producer and user expertise, have an effective access mechanism, \r\nand respond to the users' needs (Glossary; Hewitt et al., 2012). \r\nA Global Framework for Climate Services (GFCS) was established in \r\n2009 by the World Meteorological Organization (WMO) in support \r\nof these efforts (Hewitt et al., 2012; Lucio and Grasso, 2016). \r\nClimate services are provided across sectors and time scales, from \r\nsub-seasonal to multi-decadal, and support co-design and co-"


id: 60c0566e0bb89696b72181ab8a645c7a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14317
content:
"In AR6, 'climate information' refers to specific information about the \r\npast, current or future state of the climate system that is relevant for \r\nmitigation, adaptation and risk management. Cross-Chapter Box 1.1 \r\nis an example of climate information at the global scale. It provides \r\nclimate change information with potential relevance for the global \r\nstocktake, and indicates where in AR6 this information may be found."


id: ef0f88da1d86bbe4a033f66dad0bdcb2
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"large social movements such as School Strikes for Climate gained \r\nworldwide attention (Thackeray et al., 2020). We thus assess that \r\nspecific characteristics of media coverage play a major role in climate \r\nunderstanding and perception (high confidence), including how IPCC \r\nassessments are received by the general public."


id: b2add9d1dd1ce8a9e9013229b69e32bc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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vector_id: 28675
content:
"production processes that involve climate information providers, \r\nresource managers, planners, practitioners and decision makers \r\n(Brasseur and Gallardo, 2016; Trenberth et al., 2016; C.D.  Hewitt \r\net al., 2017). For example, they may provide high-quality data on \r\ntemperature, rainfall, wind, soil moisture and ocean conditions, as \r\nwell as maps, risk and vulnerability analyses, assessments, and future \r\nprojections and scenarios. These data and information products may \r\nbe combined with non-meteorological data, such as agricultural \r\nproduction, health trends, population distributions in high-risk areas, \r\nroad and infrastructure maps for the delivery of goods, and other \r\nsocio-economic variables, depending on users' needs (WMO, 2020a). \r\nCross-Chapter Box 12.2 illustrates the diversity of climate services \r\nwith three examples from very different contexts."


id: e7c1500c63815f276fe231fb7b83f222
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 38082
content:
"The current landscape of climate services is assessed in detail \r\nin Chapter  12 (Section  12.6), with a  focus on multi-decadal \r\ntime scales relevant for climate change risk assessment. Other \r\ninformation relevant to improving climate services for decision\u0002making includes the assessment of methods to construct regional \r\ninformation (Chapter  10), as well as projections at the regional \r\nlevel (Atlas) relevant for impact and risk assessment in different \r\nsectors (Chapter 12)."


id: 25f7591319c01612996d9939fbd2e7de
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3857
content:
"Scientific understanding of the climate system's fundamental features \r\nis robust and well established. This section briefly presents the major \r\nlines of evidence in climate science (Figure  1.6). It illustrates their \r\nlong history and summarizes key findings from the WGI contribution \r\nto AR5, referencing previous IPCC assessments for comparison, \r\nwhere relevant. Box  1.2 summarizes major findings from three \r\nSpecial Reports already released during the IPCC Sixth Assessment \r\nCycle. This chapter's Appendix 1A summarizes the principal findings \r\nof all six IPCC WGI Assessment Reports, including the present Report, \r\nin a single table for ease of reference."


id: 63bf67228bc9054a9b5447ebbed17b70
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14838
content:
"Instrumental observations of the atmosphere, ocean, land, biosphere \r\nand cryosphere underpin all understanding of the climate system. \r\nThis section describes the evolution of instrumental data for major \r\nclimate variables at Earth's land and ocean surfaces, at altitude in \r\nthe atmosphere, and at depth in the ocean. Many data records exist, \r\nof varying length, continuity and spatial distribution; Figure 1.7 gives \r\na schematic overview of temporal coverage."


id: d905721fb51a123f96d341faa1e39e95
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35480
content:
"Instrumental weather observation at the Earth's surface dates to \r\nthe invention of thermometers and barometers in the 17th century. "


id: 325032084ca39206c07da6e00df03ac6
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6111
content:
"Figure 1.6 | Climate science milestones, between 1817 and 2021. Top: Milestones in observations. Middle: Curves of global surface air temperature (GMST) anomaly \r\nrelative to 1850-1900, using HadCRUT5 (Morice et al., 2021); atmospheric CO2 concentrations from Antarctic ice cores (Luthi et al., 2008; Bereiter et al., 2015); direct air \r\nmeasurements from 1957 onwards (see Figure 1.4 for details; Tans and Keeling, 2020). Bottom: Milestones in scientific understanding of the CO2-enhanced greenhouse effect. \r\nFurther details on each milestone are available in Section 1.3, and in Chapter 1 of AR4 (Le Treut et al., 2007)."


id: 3256e3723cb07c82eabb8f1772a6bb61
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6115
content:
"Heat-retaining properties of the atmosphere's constituent gases were \r\nclosely investigated in the 19th century. Foote (1856) measured solar \r\nheating of CO2 experimentally and argued that higher concentrations \r\nin the atmosphere would increase Earth's temperature. Water vapour, \r\nozone, CO2 and certain hydrocarbons were found to absorb longwave \r\n(infrared) radiation, the principal mechanism of the greenhouse effect \r\n(Tyndall, 1861). Nineteenth-century investigators also established the \r\nexistence of a natural biogeochemical carbon cycle. Carbon dioxide \r\nemitted by volcanoes is removed from the atmosphere through \r\na combination of silicate rock weathering, deep-sea sedimentation, \r\noceanic absorption, and biological storage in plants, shellfish, and \r\nother organisms. On multi-million-year time scales, the compression \r\nof fossil organic matter is stored as carbon as coal, oil and natural gas \r\n(Chamberlin, 1897, 1898; Ekholm, 1901)."


id: cdc6468f63a685e07f194090ab75d87d
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 33528
content:
"Arrhenius (1896) calculated that a  doubling of atmospheric CO2\r\nwould produce warming of 5degC-6degC, but in 1900 new measurements \r\nseemed to rule out CO2 as a  greenhouse gas due to overlap with \r\nthe absorption bands of water vapour (Angstrom, 1900; Very and \r\nAbbe, 1901). Further investigation and more sensitive instruments \r\nlater overturned Angstrom's conclusion (Fowle, 1917; Callendar, \r\n1938). Nonetheless, the major role of CO2 in the energy balance of \r\nthe atmosphere was not widely accepted until the 1950s (Callendar, \r\n1949; Plass, 1956, 1961; Manabe and Moller, 1961; Weart, 2008; \r\nEdwards, 2010). Revelle and Keeling established CO2 monitoring \r\nstations in Antarctica and Hawaii during the 1957-1958 International \r\nGeophysical Year (Revelle and Suess, 1957; Keeling, 1960). These \r\nstations have tracked rising atmospheric CO2 concentrations from "


id: a80f9edaffb57b9ad2f17fd841a01d9a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 26781
content:
"315  ppm in 1958 to 414  ppm in 2020. Ground-based monitoring \r\nof other GHGs followed. The Greenhouse Gases Observing Satellite \r\n(GOSat) was launched in 2009, and two Orbiting Carbon Observatory \r\nsatellite instruments have been in orbit since 2014."


id: cba8a295adf5b1302479050ed9fbd03e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 33155
content:
"The AR5 WGI highlighted 'the other CO2 problem' (Doney et al., 2009), \r\nthat is, ocean acidification caused by the absorption of some 20-30% \r\nof anthropogenic CO2 from the atmosphere and its conversion to \r\ncarbonic acid in seawater. The AR5 WGI assessed that the pH of \r\nocean surface water has decreased by 0.1 since the beginning of \r\nthe industrial era (high confidence), indicating approximately a 30% \r\nincrease in acidity (IPCC, 2013b)."


id: 603ed221afbcff3f487cc356b4fc0230
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 14235
content:
"With a  heat capacity about 1000 times greater than that of the \r\natmosphere, Earth's ocean stores the vast majority of energy \r\nretained by the planet. Ocean currents transport the stored heat \r\naround the globe and, over decades to centuries, from the surface \r\nto its greatest depths. The ocean's thermal inertia moderates \r\nfaster changes in radiative forcing on land and in the atmosphere, "


id: 8f08f4fe1a26e5c69735093bacd72dea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 22362
content:
"(Glacier Thickness Database (GlaThiDa), Gartner-Roer et al., 2014). \r\nIn summary, these data allowed AR5 WGI to assess that over the \r\nlast two decades, the Greenland and Antarctic ice sheets have been \r\nlosing mass, glaciers have continued to shrink almost worldwide, \r\nand Arctic sea ice and Northern Hemisphere spring snow cover have \r\ncontinued to decrease in extent (high confidence) (IPCC, 2013b)."


id: 4f080246aa01e809c695174a45429c1d
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 11192
content:
"the first systematic global measurements of the 700-2000 m layer. \r\nComparing the HMS Challenger data to data from Argo submersible \r\nfloats revealed global subsurface ocean warming on the centennial \r\nscale (Roemmich et al., 2012). The AR5 WGI assessed with high \r\nconfidence that ocean warming accounted for more than 90% of the \r\nadditional energy accumulated by the climate system between 1971 \r\nand 2010 (IPCC, 2013b). In comparison, warming of the atmosphere \r\ncorresponds to only about 1% of the additional energy accumulated \r\nover that period (IPCC, 2013a). Chapter 2 summarizes the ocean heat \r\ncontent datasets used in AR6 (Section 2.3.3.1 and Table 2.7)."


id: daccd09eb7918f395964db3681f28ba4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 35791
content:
"Paleoclimate studies reconstruct the evolution of Earth's climate \r\nover hundreds to billions of years using pre-instrumental historical \r\narchives, indigenous knowledge, and natural archives left behind \r\nby geological, chemical and biological processes (Figure  1.7). \r\nPaleoclimatology covers a  wide range of temporal scales, ranging \r\nfrom the human historical past (decades to millennia) to geological \r\ndeep time (millions to billions of years). Paleoclimate reference \r\nperiods are presented in Cross-Chapter Box 2.1."


id: 4ddcbf88f233206b8eddad8cafcf17ae
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10969
content:
"Historical climatology aids near-term paleoclimate reconstructions \r\nusing media such as diaries, almanacs and merchant accounts that \r\ndescribe climate-related events such as frosts, thaws, flowering \r\ndates, harvests, crop prices and droughts (Lamb, 1965, 1995; Le Roy \r\nLadurie, 1967; Brazdil et al., 2005). Meticulous records by Chinese \r\nscholars and government workers, for example, have permitted \r\ndetailed reconstructions of China's climate back to 1000 CE, and even \r\nbeyond (Louie and Liu, 2003; Ge et al., 2008). Climatic phenomena \r\nsuch as large-scale, regionally and temporally distributed warmer \r\nand cooler periods of the past 2000 years were reconstructed from \r\nEuropean historical records (Lamb, 1965, 1995; Le Roy Ladurie, 1967; \r\nNeukom et al., 2019)."


id: ab4df75d88009d98795cd4d2486280a8
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27366
content:
"Indigenous and local knowledge has played an increasing role \r\nin historical climatology, especially in areas where instrumental \r\nobservations are sparse. Peruvian fishermen named the periodic \r\nEl  Nino warm current in the Pacific, which was linked by later \r\nresearchers to the Southern Oscillation (Cushman, 2004). Inuit \r\ncommunities have contributed to climatic history and community\u0002based monitoring across the Arctic (Riedlinger and Berkes, 2001; "


id: fa3838130cf1436315b3cb94ba2f4610
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 41393
content:
"Gearheard et al., 2010). Indigenous Australian knowledge of climatic \r\npatterns has been offered as a complement to sparse observational \r\nrecords (Green et al., 2010; Head et al., 2014), such as those of sea\u0002level rise (Nunn and Reid, 2016). Ongoing research seeks to conduct \r\nfurther dialogue, utilize indigenous and local knowledge as an \r\nindependent line of evidence complementing scientific understanding, \r\nand analyse their utility for multiple purposes, especially adaptation \r\n(Laidler, 2006; Alexander et al., 2011; IPCC, 2019c). Indigenous and \r\nlocal knowledge is used most extensively by IPCC WGII."


id: 8e6b93549d66d363ca50fd1ddf51a213
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 22243
content:
"and Opdyke, 1973; Siddall et al., 2003; Lisiecki and Raymo, 2005; \r\nPast Interglacials Working Group of PAGES, 2016). These estimates \r\nhave bolstered the orbital cycles hypothesis (Hays et al., 1976; \r\nBerger, 1977, 1978). However, paleoclimatology of multi-million to \r\nbillion-year periods reveals that CH4, CO2, continental drift, silicate \r\nrock weathering and other factors played a greater role than orbital \r\ncycles in climate changes during ice-free 'hothouse' periods of Earth's \r\ndistant past (Frakes et al., 1992; Bowen et al., 2015; Zeebe et al., 2016)."


id: 710514d9184b94b457f3e8e02a327b08
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 17146
content:
"The AR5 WGI (IPCC, 2013b) used paleoclimatic evidence to put \r\nrecent warming and sea level rise in a  multi-century perspective \r\nand assessed that 1983-2012 was likely to have been the warmest \r\n30-year period of the last 1400 years in the Northern Hemisphere \r\n(medium confidence). The AR5 also assessed that the rate of sea level \r\nrise since the mid-19th century has been larger than the mean rate \r\nduring the previous two millennia (high confidence)."


id: 49d225e4fea4d260e797d8db842af9c4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 10224
content:
"Certain geological and biological materials preserve evidence of past \r\nclimate changes. These 'natural archives' include corals, trees, glacier \r\nice, speleothems (stalactites and stalagmites), loess deposits (dust \r\nsediments), fossil pollen, peat, lake sediment and marine sediment \r\n(Stuiver, 1965; Eddy, 1976; Haug et al., 2001; Wang et al., 2001; Jones \r\net al., 2009; Bradley, 2015). By the early 20th  century, laboratory \r\nresearch had begun to use tree rings to reconstruct precipitation \r\nand the possible influence of sunspots on climatic change (Douglass, \r\n1914, 1919, 1922). Radiocarbon dating, developed in the 1940s \r\n(Arnold and Libby, 1949), allows accurate determination of the age of \r\ncarbon-containing materials from the past 50,000 years; this dating \r\ntechnique ushered in an era of rapid progress in paleoclimate studies."


id: 7afd33a4f1ce3c614048c86f25b77568
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18837
content:
"The climate is a  globally interconnected system driven by solar \r\nenergy. Scientists in the 19th century established the main physical \r\nprinciples governing Earth's temperature. By 1822, the principle of \r\nradiative equilibrium (the balance between absorbed solar radiation \r\nand the energy Earth re-radiates into space) had been articulated, \r\nand the atmosphere's role in retaining heat had been likened to \r\na greenhouse (Fourier, 1822). The primary explanations for natural \r\nclimate change - greenhouse gases, orbital factors, solar irradiance, \r\ncontinental position, volcanic outgassing, silicate rock weathering, \r\nand the formation of coal and carbonate rock - were all identified by \r\nthe late 19th century (Fleming, 1998; Weart, 2008)."


id: 3026a247fcd09e58850325e453629f5b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 5732
content:
"Global reconstructions of sea surface temperature were developed \r\nfrom material contained in deep-sea sediment cores (CLIMAP Project \r\nMembers et al., 1976), providing the first quantitative constraints for \r\nmodel simulations of ice-age climates (e.g., Rind and Peteet, 1985). \r\nPaleoclimate data and modelling showed that the Atlantic Ocean \r\ncirculation has not been stable over glacial-interglacial time periods, \r\nand that many changes in ocean circulation are associated with \r\nabrupt transitions in climate in the North Atlantic region (Ruddiman \r\nand McIntyre, 1981; Broecker et al., 1985; Boyle and Keigwin, 1987; \r\nManabe and Stouffer, 1988)."


id: 1b5bd081603773feb6549457d38c9d73
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 1991
content:
"Natural drivers include changes in solar irradiance, ocean currents, \r\nnaturally occurring aerosols, and natural sources and sinks of \r\nradiatively active gases such as water vapour, CO2, CH4, and \r\nsulphur dioxide (SO2). Detailed global measurements of surface\u0002level solar irradiance were first conducted during the 1957-1958 \r\nInternational Geophysical Year (Landsberg, 1961), while top-of\u0002atmosphere irradiance has been measured by satellites since 1959 "


id: e7aa9de73eabbaf0bcd4e11f169a568b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 38064
content:
"By the early 20th century, cyclical changes in insolation due to the \r\ninteracting periodicities of orbital eccentricity, axial tilt and axial \r\nprecession had been hypothesized as a chief pacemaker of ice age-\r\ninterglacial cycles on multi-millennial time scales (Milankovitch, \r\n1920). Paleoclimate information derived from marine sediment \r\nprovides quantitative estimates of past temperature, ice volume and \r\nsea level over millions of years (Figure 1.5; Emiliani, 1955; Shackleton "


id: 9185641771d98e7cc2c5c4307ed33dc9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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index: climate_gpt_v2
vector_id: 22821
content:
"2010, 2013). The most important of these non-condensing gases \r\nis CO2 (a positive driver), released naturally by volcanism at about \r\n637 MtCO2 yr-1 in recent decades, or roughly 1.6% of the 37 GtCO2\r\nemitted by human activities in 2018 (Burton et al., 2013; Le Quere \r\net al., 2018). Absorption by the ocean and uptake by plants and soils \r\nare the primary natural CO2 sinks on decadal to centennial time \r\nscales (Section 5.1.2 and Figure 5.3)."


id: 76f8746cd5543ab4df79c8bdb6b261d0
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updated_at: 2023-04-19 13:21:31
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vector_id: 18136
content:
"(House  et al.,  1986). Measured changes in solar irradiance have \r\nbeen small and slightly negative since about 1980 (Matthes et al., \r\n2017). Water vapour is the most abundant radiatively active gas, \r\naccounting for about 75% of the terrestrial greenhouse effect, \r\nbut because its residence time in the atmosphere averages just \r\n8-10 days, its atmospheric concentration is largely governed by \r\ntemperature (van der Ent and Tuinenburg, 2017; Nieto and Gimeno, \r\n2019). As a result, non-condensing GHGs with much longer residence \r\ntimes serve as 'control knobs', regulating planetary temperature, \r\nwith water vapour concentrations as a feedback effect (Lacis et al., "


id: 3823c7613988e54bbadaf96477c72f2a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7081
content:
"Aerosols (tiny airborne particles) interact with climate in numerous \r\nways, some direct (e.g., reflecting solar radiation back into space) and "


id: e7dcef4c9de109e89ecc04624def4137
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 38104
content:
"(see Glossary), including widely used refrigerants and propellants, \r\nwere extremely potent greenhouse gases (Sections  2.2.4.3 and \r\n6.2.2.9; Ramanathan, 1975). When these chemicals were also \r\nfound to be depleting the stratospheric ozone layer, they were \r\nstringently and successfully regulated on a global basis by the 1987 \r\nMontreal Protocol on the Ozone Layer and successor agreements \r\n(Parson, 2003)."


id: a96d42db16283ea1c47b02b4a1dcc8a
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27033
content:
"All IPCC reports have assessed the total RF as positive when \r\nconsidering all sources. However, due to the considerable variability \r\nof both natural and anthropogenic aerosol loads, FAR characterized \r\ntotal aerosol RF as 'highly uncertain' and was unable even to \r\ndetermine its sign (positive or negative). Major advances in \r\nquantification of aerosol loads and their effects have taken place \r\nsince then, and IPCC reports since 1992 have consistently assessed "


id: 92310319049332a27531cc393004834e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22937
content:
"total forcing by anthropogenic aerosols as negative (IPCC, 1992, \r\n1995a, 1996). However, due to their complexity and the difficulty \r\nof obtaining precise measurements, aerosol effects have been \r\nconsistently assessed as the largest single source of uncertainty \r\nin estimating total RF (Stevens and Feingold, 2009; IPCC, 2013a). \r\nOverall, AR5 assessed that total aerosol effects, including cloud \r\nadjustments, resulted in a negative RF of -0.9 [-1.9 to -0.1] W m-2\r\n(medium confidence), offsetting a substantial portion of the positive \r\nRF resulting from the increase in GHGs (high confidence) (IPCC, \r\n2013b). Chapter 7 provides an updated assessment of the total and \r\nper-component RF for the WGI contribution to AR6."


id: 41994cb5f4711bf76b42d6eda1334288
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8731
content:
"Understanding the global climate system requires both theoretical \r\nunderstanding and empirical measurement of the major forces \r\nand factors that govern the transport of energy and mass (air, water and \r\nwater vapour) around the globe; the chemical and physical properties \r\nof the atmosphere, ocean, cryosphere and land surfaces; and the \r\nbiological and physical dynamics of natural ecosystems, as well as \r\nthe numerous feedbacks (both positive and negative) among these \r\nprocesses. Attributing climatic changes or extreme weather events \r\nto human activity (Cross-Working Group Box: Attribution) also \r\nrequires an understanding of the many ways that human activities \r\nmay affect the climate, along with statistical and other techniques \r\nfor separating the 'signal' of anthropogenic climate change from the \r\n'noise' of natural climate variability (Section 1.4.2). This inter- and \r\ntrans-disciplinary effort requires contributions from many sciences."


id: 8f72df9ed91afbd1d74f3322c009b101
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 22449
content:
"In the 1960s similar approaches to modelling the weather were used \r\nto model the climate, but with much longer runs than daily forecasting \r\n(Smagorinsky et al., 1965; Manabe and Wetherald, 1967). Simpler \r\nstatistical and one- and two-dimensional modelling approaches \r\ncontinued in tandem with the more complex general circulation \r\nmodels (GCMs; Manabe and Wetherald, 1967; Budyko, 1969; Sellers, \r\n1969). The first coupled atmosphere-ocean model (AOGCM) with \r\nrealistic topography appeared in 1975 (Bryan et al., 1975; Manabe \r\net al., 1975). Rapid increases in computer power enabled higher \r\nresolutions, longer model simulations, and the inclusion of additional \r\nphysical processes in GCMs, such as aerosols, atmospheric chemistry, \r\nsea ice, and snow."


id: f188b0e25b9b488d07250dd5a768192
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 39878
content:
"Due to the complexity of many interacting processes, ranging \r\nin scale from the molecular to the global, and occurring on time \r\nscales from seconds to millennia, attribution makes extensive use \r\nof conceptual, mathematical, and computer simulation models. \r\nModelling allows scientists to combine a vast range of theoretical \r\nand empirical understanding from physics, chemistry and other \r\nnatural sciences, producing estimates of their joint consequences \r\nas simulations of past, present or future states and trends (Nebeker, \r\n1995; Edwards, 2010, 2011)."


id: a4499d107920017d799bfd1d296ae390
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 26097
content:
"In addition to radiative transfer (discussed above in Section 1.3.3), \r\nforces and factors such as thermodynamics (energy conversions), \r\ngravity, surface friction, and the Earth's rotation govern the planetary\u0002scale movements or 'circulation' of air and water in the climate \r\nsystem. The scientific theory of climate began with Halley (1686), \r\nwho hypothesized vertical atmospheric circulatory cells driven by \r\nsolar heating, and Hadley (1735), who showed how the Earth's \r\nrotation affects that circulation. Ferrel (1856) added the Coriolis \r\nforce to existing theory, explaining the major structures of the global \r\natmospheric circulation. In aggregate, prevailing winds and ocean \r\ncurrents move energy poleward from the equatorial regions where \r\nthe majority of incoming solar radiation is received."


id: 83b380954667d99e19293bc07bc5aee9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20313
content:
"Since climate models vary along many dimensions, such as grid \r\ntype, resolution, and parameterizations, comparing their results \r\nrequires special techniques. To address this problem, the climate "


id: 6b1f3f959d1b27d0426077e899a745c1
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 16140
content:
"Climate models provide the ability to simulate these complex \r\ncirculatory processes, and to improve the physical theory of climate \r\nby testing different mathematical formulations of those processes. "


id: c171368de748b4207c4943c331627ad5
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 31338
content:
"consistent with the AR5 WGI assessed likely range of equilibrium \r\nclimate sensitivity (ECS) [1.5degC to 4.5degC] to within estimated \r\nuncertainties (on ECS, see Section  1.3.5; IPCC, 2013a). Similarly, \r\nover the period 1993-2010, when observations of all sea level \r\ncomponents were available, AR5 WGI assessed the observed global \r\nmean sea level rise to be consistent with the sum of the observed \r\ncontributions from ocean thermal expansion (due to warming) \r\ncombined with changes in glaciers, the Antarctic and Greenland ice \r\nsheets, and land-water storage (high confidence). Verification that \r\nthe terms of these budgets balance over recent decades provides \r\nstrong evidence for our understanding of anthropogenic climate \r\nchange (Cross-Chapter Box 9.1)."


id: 23f38864fa3a5483beda34fd5cfb964c
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3508
content:
"It was recognized in IPCC AR5 that information about the near term \r\nwas increasingly relevant for adaptation decisions. In response, AR5 \r\nWGI made a specific assessment for how global surface temperature \r\nwas projected to evolve over the next two decades, concluding that \r\nthe change for the period 2016-2035 relative to 1986-2005 will likely \r\nbe in the range of 0.3degC-0.7degC (medium confidence), assuming no \r\nmajor volcanic eruptions or secular changes in total solar irradiance \r\n(IPCC, 2013b). The AR5 was also the first IPCC assessment report \r\nto assess 'decadal predictions' of the climate, where the observed \r\nstate of the climate system was used as a starting point for forecasts \r\nseveral years ahead. The AR6 examines updates to these decadal \r\npredictions (Section 4.4.1)."


id: aa499fea0714d4e66529d4ae69125e51
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27191
content:
"A key indicator of climate understanding is whether theoretical climate \r\nsystem budgets or 'inventories', such as the balance of incoming and \r\noutgoing energy at the surface and at the top of the atmosphere, \r\ncan be quantified and balanced observationally. The global energy \r\nbudget, for example, includes energy retained in the atmosphere, \r\nupper ocean, deep ocean, ice, and land surface. Church et al. (2013) \r\nassessed in AR5 with high confidence that independent estimates of \r\neffective radiative forcing (ERF), observed heat storage, and surface \r\nwarming combined to give an energy budget for the Earth that is "


id: 750c9ffe53048086f687cfb4a618d72e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 17827
content:
"The assessments and predictions for the near-term evolution of global \r\nclimate features are largely independent of future CO2 emissions \r\npathways. However, AR5 WGI assessed that limiting climate change \r\nin the long-term future will require substantial and sustained \r\nreductions of GHG emissions (IPCC, 2013b). This assessment results \r\nfrom decades of research on understanding the climate system and "


id: 3c7554c92d35346635836259b784a9cf
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 7828
content:
"The 1979 Charney NRC report estimated ECS at 3degC, stating the range \r\nas 2degC-4.5degC, based on 'consistent and mutually supporting' model \r\nresults and expert judgment (NRC, 1979). ECS is defined in IPCC \r\nassessments as the global surface air temperature (GSAT) response \r\nto CO2 doubling (from pre-industrial levels) after the climate has \r\nreached equilibrium (stable energy balance between the atmosphere \r\nand ocean). Another quantity, transient climate response (TCR), was \r\nlater introduced as the change in GSAT, averaged over a  20-year \r\nperiod, at the time of CO2 doubling in a scenario of concentration \r\nincreasing at 1% per year. Calculating ECS from historical or \r\npaleoclimate temperature records, in combination with energy \r\nbudget models, has produced estimates both lower and higher than \r\nthose calculated using GCMs and ESMs; in this Report, these are \r\nassessed in Chapter 7, Section 7.5.2."


id: 368ecf0fd49e5cc7a2a49ec18d870f58
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6832
content:
"its perturbations, and projecting climate change into the future. Each \r\nIPCC report has considered a range of emissions scenarios, typically \r\nincluding a scenario in which societies choose to continue on their \r\npresent course, as well as several others reflecting socio-economic \r\nand policy responses that may limit emissions and/or increase the \r\nrate of CO2 removal from the atmosphere. Climate models are used \r\nto project the outcomes of each scenario. However, future human \r\nclimate influence cannot be precisely predicted because GHG and \r\naerosol emissions, land use, energy use and other human activities \r\nmay change in numerous ways. Common emissions scenarios used in \r\nthe WGI contribution to AR6 are detailed in Section 1.6."


id: e4bb792454e948f13b113ef11fdee020
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37525
content:
"Based on model results and steadily increasing CO2 concentrations \r\n(Bolin and Bischof, 1970; SMIC, 1971; Meadows et al., 1972), \r\nconcerns about future 'risk of effects on climate' were addressed in \r\nRecommendation 70 of the Stockholm Action Plan, resulting from \r\nthe 1972 United Nations Conference on the Human Environment \r\n(UN, 1973). Numerous other scientific studies soon amplified these \r\nconcerns (summarized in Schneider (1975) and Williams (1978); see \r\nalso Nordhaus (1975, 1977). In 1979, a US National Research Council \r\n(NRC) group led by Jule Charney reported on the 'best present \r\nunderstanding of the carbon dioxide/climate issue for the benefit of \r\npolicymakers', initiating an era of regular and repeated large-scale \r\nassessments of climate science findings."


id: 9450d96ffc6b96ca73bc7907c36cfe62
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 23304
content:
"ECS is typically characterized as most relevant on centennial time \r\nscales, while TCR was long seen as a more appropriate measure of \r\nthe 50-100-year response to gradually increasing CO2. However, \r\nrecent studies have raised new questions about how accurately both \r\nquantities are estimated by GCMs and ESMs (Grose et al., 2018; \r\nMeehl et al., 2020; Sherwood et al., 2020). Further, as climate models \r\nevolved to include a full-depth ocean, the time scale for reaching full \r\nequilibrium became longer and new methods to estimate ECS had to \r\nbe developed (Gregory et al., 2004; Meehl et al., 2020; Meinshausen \r\net al., 2020). Because of these considerations, as well as new \r\nestimates from observation-based, paleoclimate, and emergent\u0002"


id: 7d017650f4cad319213336f868589ac4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 19178
content:
"Table 1.2 | Estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) from successive major scientific assessments since \r\n1979. No likelihood statements are available for reports prior to 2001 because those reports did not use the IPCC calibrated uncertainty language. The assessed range of \r\nECS differs from the range derived from general circulation model (GCM) and Earth system model (ESM) results because assessments take into account other evidence, other \r\ntypes of models, and expert judgment. The AR6 definition of ECS differs from previous reports, now including all long-term feedbacks except those associated with ice sheets. \r\nAR6 estimates of ECS are derived primarily from process understanding, historical observations and emergent constraints, informed by (but not based on) GCM and ESM model \r\nresults. CMIP6 is the 6th phase of the Coupled Model Intercomparison Project (Section 7.5.5 and Box 7.1)."


id: f54df4978d2e270e45371d7fe2ac7dde
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40527
content:
"constraints studies (Sherwood et al., 2020), the AR6 definition of ECS \r\nhas changed from previous reports; it now includes all feedbacks \r\nexcept those associated with ice sheets. Accordingly, unlike previous \r\nreports, the AR6 assessments of ECS and TCR are not based primarily \r\non GCM and ESM model results (see Section 7.5.5 and Box. 7.1 for \r\na full discussion)."


id: e5e705df065dc62fdbafe1817613460
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 37747
content:
"significant reductions of warming due to short-lived climate forcers \r\n(SLCFs) could reduce the level at which temperature stabilizes once CO2\r\nemissions reach net zero, and also reduce the long-term global warming \r\ncommitment by reducing radiative forcing from SLCFs (Chapter 5)."


id: 10a20b22f1f7fc1e2b593d4200ffb659
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 110
content:
"In summary, major lines of evidence  - observations, paleoclimate, \r\ntheoretical understanding and natural and human drivers - have been \r\nstudied and developed for over 150  years. Methods for projecting \r\nclimate futures have matured since the 1950s and attribution \r\nstudies since the 1980s. We conclude that understanding of the \r\nprincipal features of the climate system is robust and well established."


id: 357adb453dab10a072418394d3be16ce
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 6658
content:
"Today, other sensitivity terms are sometimes used, such as 'transient \r\nclimate response to emissions' (TCRE, defined as the ratio of warming \r\nto cumulative CO2 emissions in a  CO2-only simulation) and 'Earth \r\nsystem sensitivity' (ESS), which includes multi-century Earth system \r\nfeedbacks such as changes in ice sheets."


id: 243771ab7b33bd11b3f894933b29ce31
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 3562
content:
"Table 1.2 shows estimates of ECS and TCR for major climate science \r\nassessments since 1979. The table shows that despite some variation \r\nin the range of GCM and (for the later assessments) ESM results, \r\nexpert assessment of ECS changed little between 1979 and the \r\npresent Report. Based on multiple lines of evidence, AR6 has narrowed \r\nthe likely range of ECS to 2.5degC-4.0degC (Chapter 7, Section 7.5.5)."


id: 2cb8d99239c8f7876e7bcee990aacceb
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 5130
content:
"Although these studies generally showed good agreement between \r\npast projections and subsequent observations, this type of analysis is \r\ncomplicated because the scenarios of future radiative forcing used in \r\nearlier projections do not precisely match the actual radiative forcings \r\nthat subsequently occurred. Mismatches between the projections \r\nand subsequent observations could be due to incorrectly projected \r\nradiative forcings (e.g.,  aerosol emissions, GHG concentrations or \r\nvolcanic eruptions that were not included), an incorrectly modelled \r\nresponse to those forcings, or both. Alternatively, agreement \r\nbetween projections and observations could be fortuitous due to \r\na  compensating balance of errors, for example, too low climate \r\nsensitivity but too strong radiative forcings."


id: b851f3f2ce5836757b75f5486e48ab44
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29641
content:
"From the close link between cumulative emissions and warming it \r\nfollows that any given level of global warming is associated with \r\na total budget of GHG emissions, especially CO2 as it is the largest long\u0002lived contributor to radiative forcing (Allen et al., 2009; Collins et al., \r\n2013; Rogelj et al., 2019). Higher emissions in earlier decades imply \r\nlower emissions later on to stay within the Earth's carbon budget. \r\nStabilizing the anthropogenic influence on global surface temperature \r\nthus requires that CO2 emissions and removals reach net zero once the \r\nremaining carbon budget is exhausted (Cross-Chapter Box 1.4)."


id: b6320bb28347d359993cc5a0fa2b4a4
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29279
content:
"One approach to partially correct for mismatches between the \r\nforcings used in the projections and the forcings that actually occurred \r\nis described by Hausfather et al. (2020). Model projections of global \r\nsurface temperature and estimated radiative forcings were taken \r\nfrom several historical studies, along with the baseline 'no-policy' \r\nscenarios from the first four IPCC assessment reports. These model \r\nprojections of temperature and radiative forcing are then compared \r\nto (i) the observed change in temperature through time over the \r\nprojection period, and (ii) the observed change in temperature \r\nrelative to the observationally estimated radiative forcing over the \r\nprojection period (Figure 1.9; data from Hausfather et al., 2020). "


id: b91d30562dfe2be7accb9ba825f59d0
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 29771
content:
"Past, present and future emissions of CO2 therefore commit the world to \r\nsubstantial multi-century climate change, and many aspects of climate \r\nchange would persist for centuries even if emissions of CO2 were \r\nstopped immediately (IPCC, 2013b). According to AR5, a large fraction \r\nof this change is essentially irreversible on a multi-century to millennial \r\ntime scale, barring large net removal ('negative emissions') of CO2 from \r\nthe atmosphere over a  sustained period through as yet unavailable \r\ntechnological means (Chapters 4 and 5l; IPCC, 2013a, 2018). However, "


id: 4066bf51d9b85b44ea835dffb29c1345
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8524
content:
"the world. Regional projections were given for the best estimate of 1.8degC \r\nof global warming by 2030, compared to a baseline of 1850-1900, and \r\nwere assigned low confidence. The FAR also suggested that regional \r\ntemperature changes should be scaled by -30% to +50% to account \r\nfor the uncertainty in projected global warming."


id: 4c90d6bd9b2519e51f51ae391d2c04ea
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 10732
content:
"The regional projections presented in FAR are compared to \r\nthe observed temperature change in the period since 1990 \r\n(Figure  1.10), following Grose et al. (2017). Subsequent observed \r\ntemperature change has tracked within the FAR projected range \r\nfor the best estimate of regional warming in the Sahel, South Asia \r\nand southern Europe. Temperature change has tracked at or below \r\nthis range for the central North America and Australia regions, \r\nyet remains within the range reduced by 30% to generate FAR's \r\nlower global warming estimate. This is consistent with the smaller \r\nobserved estimate of radiative forcing compared to the FAR central \r\nestimate. Note that the projections assessed in Chapter  4  of this \r\nReport suggest that global temperatures will be around 1.2degC-1.8degC \r\nabove 1850-1900 levels by 2030, a range which is also lower than \r\nthe FAR central estimate."


id: ac4282701bb37fb6d5204db8fce2db09
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 27550
content:
"In addition to global surface temperature, past regional projections \r\ncan be evaluated. For example, FAR (IPCC, 1990a) presented a series \r\nof temperature projections for 1990-2030 for several regions around "


id: 857a2df3e216cc312994fed25eded905
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 20622
content:
"observations, allowing for regional-scale climate variability and \r\ndifferences in projected and actual forcings. There is medium \r\nconfidence that the spatial warming pattern has been reliably \r\nprojected in past IPCC reports (limited evidence, high agreement)."


id: 769966bffac6ec55c2a40b208b01a069
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 18084
content:
"Overall, there is medium confidence that past projections of global \r\ntemperature are consistent with subsequent observations, especially \r\nwhen accounting for the difference in radiative forcings used and \r\nthose which actually occurred (limited evidence, high agreement). \r\nThe FAR regional projections are broadly consistent with subsequent "


id: f66d3610df72bb1fd88419b189a4eb0b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 40723
content:
"The Sixth Assessment Cycle started with three Special Reports. The Special Report on Global Warming of 1.5degC (SR1.5, IPCC, 2018), \r\ninvited by the Parties to the UNFCCC in the context of the Paris Agreement, assessed current knowledge on the impacts of global \r\nwarming of 1.5degC above pre-industrial levels and related global greenhouse gas (GHG) emissions pathways. The Special Report on \r\nClimate Change and Land (SRCCL, IPCC, 2019a) addressed GHG fluxes in land-based ecosystems, land use and sustainable land \r\nmanagement in relation to climate change adaptation and mitigation, desertification, land degradation and food security. The Special \r\nReport on the Ocean and Cryosphere in a Changing Climate (SROCC, IPCC, 2019b) assessed new literature on observed and projected \r\nchanges of the ocean and the cryosphere, and their associated impacts, risks and responses."


id: 48008d59fa74c1a42b0732096e648a8b
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 9885
content:
"The SR1.5 and SRCCL were produced through a collaboration between the three IPCC Working Groups, SROCC by only Working \r\nGroups I and II. Here we focus on key findings relevant to the physical science basis covered by WGI."


id: 4037a1502fad1a33e23795dc73d49d30
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"With respect to the ocean, SROCC assessed that it is virtually certain that the ocean has warmed unabated since 1970 and has taken \r\nup more than 90% of the excess heat contributed by global warming. The rate of ocean warming has likely more than doubled since \r\n1993. Over the period 1982-2016, marine heatwaves have very likely doubled in frequency and are increasing in intensity (very high \r\nconfidence). In addition, the surface ocean acidified further (virtually certain) and loss of oxygen occurred from the surface to a depth \r\nof 1000 m  (medium confidence). The Report expressed medium confidence that the Atlantic Meridional Overturning Circulation \r\n(AMOC) weakened in 2004-2017 relative to 1850-1900."


id: 75965e90555818e54bc332d1d53f42cd
created_at: 2023-04-19 13:21:31
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content:
"The SROCC assessed that anthropogenic climate change has increased observed precipitation (medium confidence), winds (low \r\nconfidence), and extreme sea level events (high confidence) associated with some tropical cyclones. It also found evidence for an \r\nincrease in the annual global proportion of Category 4 or 5 tropical cyclones in recent decades (low confidence)."


id: 9f47f152059446e66e81daeb5a9647cc
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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vector_id: 25248
content:
"The SRCCL stated that the land is simultaneously a source and sink of CO2, due to both anthropogenic and natural drivers. It estimates \r\nwith medium confidence that agriculture, forestry and other land use (AFOLU) activities accounted for around 13% of CO2, 44% of \r\nCH4, and 82% of N2O emissions from human activities during 2007-2016, representing 23% (12.0 +- 3.0 GtCO2 equivalent yr-1) of \r\nthe total net anthropogenic emissions of GHGs. The natural response of land to human-induced environmental change - such as \r\nincreasing atmospheric CO2 concentration, nitrogen deposition and climate change - caused a net CO2 sink equivalent of around 29% \r\nof total CO2 emissions (medium confidence); however, the persistence of the sink is uncertain due to climate change (high confidence)."


id: b9f94f4e61efa626a6e72b29bf51c387
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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vector_id: 29944
content:
"The SRCCL also assessed how changes in land conditions affect global and regional climate. It found that changes in land cover have \r\nled to both a net release of CO2, contributing to global warming, and an increase in global land albedo, causing surface cooling. \r\nHowever, the report estimated that the resulting net effect on globally averaged surface temperature was small over the historical \r\nperiod (medium confidence)."


id: 40b74e341bcfe8643437601e209652f9
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
content_type: text
index: climate_gpt_v2
vector_id: 8570
content:
"The SROCC found that the carbon content of Arctic and boreal permafrost is almost twice that of the atmosphere (medium confidence), \r\nand assessed medium evidence with low agreement that thawing northern permafrost regions are currently releasing additional \r\nnet CH4 and CO2."


id: f841536b310e838cb710f28d86e4ca0e
created_at: 2023-04-19 13:21:31
updated_at: 2023-04-19 13:21:31
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content:
"jg\r\nThe SR1.5 concluded that global warming is likely to reach 1.5degC between 2030 and 2052 if it continues to increase at the current rate \r\n(high confidence). However, even though warming from anthropogenic emissions will persist for centuries to millennia and will cause \r\nongoing long-term changes, past emissions alone are unlikely to raise global surface temperature to 1.5degC above 1850-1900 levels."


id: b5e2086bae85861fc58a10cfca161e6d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 29223
content:
"The SR1.5 also found that reaching and sustaining net zero anthropogenic CO2 emissions and reducing net non-CO2 radiative forcing \r\nwould halt anthropogenic global warming on multi-decadal time scales (high confidence). The maximum temperature reached is then \r\ndetermined by (i) cumulative net global anthropogenic CO2 emissions up to the time of net zero CO2 emissions (high confidence) and (ii) \r\nthe level of non-CO2 radiative forcing in the decades prior to the time that maximum temperatures are reached (medium confidence)."


id: dd7c88e8bedf53ca5def5739653ae0cf
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 36233
content:
"Furthermore, climate models project robust differences in regional climate characteristics between the present day and a  global \r\nwarming of 1.5degC, and between 1.5degC and 2degC, including mean temperature in most land and ocean regions and hot extremes in most \r\ninhabited regions (high confidence). There is medium confidence in robust differences in heavy precipitation events in several regions \r\nand the probability of droughts in some regions."


id: be48efe9e87b069c749ffb302b1e4d7d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 30744
content:
"The SROCC projected that over the 21st century, the ocean will transition to unprecedented conditions, with increased temperatures \r\n(virtually certain), further acidification (virtually certain), and oxygen decline (medium confidence). Marine heatwaves are projected to \r\nbecome more frequent (very high confidence) as are extreme El Nino and La Nina events (medium confidence). The AMOC is projected"


id: c2d0aea65a3d8335e738a6ccd4f178d6
created_at: 2023-04-19 13:21:32
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vector_id: 31550
content:
"to weaken during the 21st century (very likely), but a collapse is deemed very unlikely (albeit with medium confidence due to known \r\nbiases in the climate models used for the assessment)."


id: 4d2c94bb8b5de2b967bd62a646cce0e4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 10856
content:
"pygg\r\nThe SR1.5 focused on emissions pathways and system transitions consistent with 1.5degC global warming over the 21st century. Building \r\nupon the understanding from AR5 WGI of the quasi-linear relationship between cumulative net anthropogenic CO2 emissions since \r\n1850-1900 and maximum global mean temperature, the Report assessed the remaining carbon budgets compatible with the 1.5degC \r\nor 2degC warming goals of the Paris Agreement. Starting from year 2018, the remaining carbon budget for a one-in-two (50%) chance \r\nof limiting global warming to 1.5degC is about 580 GtCO2, and about 420 GtCO2 for a two-in-three (66%) chance (medium confidence)."


id: fd69dfa12d1223b854b8bc053decb22a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 41940
content:
"At  constant 2017 emissions, these budgets would be depleted by about the years 2032 and 2028, respectively. Using GMST \r\ninstead of GSAT gives estimates of 770 GtCO2 and 570 GtCO2, respectively (medium confidence). Each budget is further reduced by \r\napproximately 100 GtCO2 over the course of this century when permafrost and other less well represented Earth system feedbacks \r\nare taken into account."


id: 219801d6202e169e838f81d39c22de7d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 3121
content:
"It is concluded that all emissions pathways with no or limited overshoot of 1.5degC imply that global net anthropogenic CO2 emissions \r\nwould need to decline by about 45% from 2010 levels by 2030, reaching net zero around 2050, together with deep reductions in \r\nother anthropogenic emissions, such as methane and black carbon. To limit global warming to below 2degC, CO2 emissions would have \r\nto decline by about 25% by 2030 and reach net zero around 2070."


id: 6b7b181b01e3b54a8a90529f7e33c011
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 16212
content:
"First, anomalies are often used when combining data from multiple \r\nlocations, because the absolute values can vary over small spatial scales \r\nwhich are not densely observed or simulated, whereas anomalies are \r\nrepresentative for much larger scales (e.g., for temperature; Hansen \r\nand Lebedeff, 1987). Since their baseline value is zero by definition, \r\nanomalies are also less susceptible to biases arising from changes \r\nin the observational network. Second, the seasonality in different \r\nclimate indicators can be removed using anomalies to more clearly \r\ndistinguish variability from long-term trends."


id: 809fb2314f409f5bb15b7a69201d0f83
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 19758
content:
"Several baselines or reference periods are used consistently \r\nthroughout AR6 WGI. Baseline refers to a  period against which \r\ndifferences are calculated, whereas reference period is used more \r\ngenerally to indicate a  time period of interest, or a  period over \r\nwhich some relevant statistics are calculated (Glossary). Variations \r\nin observed and simulated climate variables over time are often \r\npresented as 'anomalies', that is, the differences relative to a baseline, \r\nrather than using the absolute values. This is done for several reasons."


id: 64782062c9fd5d77ff76147237f923ef
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 14952
content:
"variable being considered, the rates of change of the variable and the \r\npurpose of the chosen period, but is usually 20 to 50  years long. \r\nThe World Meteorological Organization (WMO) uses 30-year periods \r\nto define 'climate normals', which indicate conditions expected to be \r\nexperienced in a given location."


id: 2ec28245b8fef548913f9e267dbfe676
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 5503
content:
"For some variables, such as precipitation, anomalies are often \r\nexpressed as percentages in order to more easily compare changes \r\nin regions with very different climatological means. However, \r\nfor situations where there are important thresholds (e.g.,  phase \r\ntransitions around 0degC) or for variables which can only take \r\na particular sign or be in a fixed range (e.g., sea ice extent or relative \r\nhumidity), absolute values are normally used."


id: bf9a8bc8ec643ed43115dc53da739b07
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 30975
content:
"For AR6 WGI, the period 1995-2014 is used as a baseline to calculate \r\nthe changes in future climate using model projections and also as \r\na 'modern' or 'recent past' reference period when estimating past \r\nobserved warming. The equivalent period in AR5 was 1986-2005, and \r\nin SR1.5, SROCC and SRCCL it was 2006-2015. The primary reason for \r\nthe different choice in AR6 is that 2014 is the final year of the historical \r\nCMIP6 simulations. These simulations subsequently assume different \r\nemissions scenarios and so choosing any later baseline end date \r\nwould require selecting a particular emissions scenario. For certain \r\nassessments, the most recent decade possible (e.g., 2010-2019 or \r\n2011-2020, depending on the availability of observations) is also \r\nused as a reference period (Cross-Chapter Box 2.3)."


id: 6b79dcad771ab6988377cf2eb472c77
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 16211
content:
"The choice of a  baseline period has important consequences for \r\nevaluating both observations and simulations of the climate, \r\nfor  comparing observations with simulations, and for presenting \r\nclimate projections. There is usually no perfect choice of baseline \r\nas many factors have to be considered and compromises may be \r\nrequired (Hawkins and Sutton, 2016). It is important to evaluate the \r\nsensitivity of an analysis or assessment to the choice of the baseline."


id: 4d4056402d0a8db4922249ba595691dd
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 10872
content:
"For example, the collocation of observations and reanalyses within the \r\nmodel ensemble spread depends on the choice of the baseline, and \r\nuncertainty in future projections of climate is reduced if using a more \r\nrecent baseline, especially for the near term (Figure 1.11). The length \r\nof an appropriate baseline or reference period depends on the "


id: 7c7ae7026ededb235845f9f83d8e947f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 19100
content:
"Figure  1.12 shows changes in observed global mean surface \r\ntemperature (GMST) relative to 1850-1900 and illustrates "


id: ad90b2eb608b089cb1d6796e39f103a5
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 27779
content:
"observed global warming levels for a  range of reference periods \r\nthat are either used in AR6 or were used in previous IPCC reports. \r\nThis allows changes to be calculated between different periods \r\nand compared to previous assessments. For example, AR5 assessed \r\nthe change in GMST from the 1850-1900 baseline to 1986-2005 \r\nreference period as 0.61 [0.55  to  0.67]  degC, whereas it is now \r\nassessed to be 0.69 [0.52 to 0.82] degC using improved GMST datasets \r\n(Cross-Chapter Box 2.3)."


id: 9a84b6e3793c88d3eee698453ba78e42
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 24428
content:
"either direction, with low confidence in the sign of any differences \r\n(see Cross Chapter Box 2.3 for details). "


id: 9b0372310ff67faa0dde7daaaabf9b62
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 24521
content:
"Three future reference periods are used in AR6 WGI for presenting \r\nprojections: near term (2021-2040), mid-term (2041-2060) and \r\nlong-term (2081-2100; Figure  1.11). In AR6, 20-year reference \r\nperiods are considered long enough to show future changes in \r\nmany variables when averaging over ensemble members of multiple \r\nmodels, and short enough to enable the time dependence of changes \r\nto be shown throughout the 21st century. Projections with alternative \r\nrecent baselines (such as 1986-2005 or the current WMO climate\u0002normal period of 1981-2010) and a wider range of future reference \r\nperiods are presented in the Interactive Atlas. Note that 'long term' \r\nis also sometimes used in a more general sense to refer to durations \r\nof centuries to millennia when examining past climate, as well as \r\nfuture climate change beyond the year 2100. Cross-Chapter Box 2.1 \r\ndiscusses the paleo-reference periods used in AR6."


id: 2f3cb4132a9f819c745f803b3267bf82
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 5576
content:
"The commonly used metric for global surface warming tends to be \r\nGMST but, as shown in Figure 1.11, climate model simulations tend to \r\nuse global surface air temperature (GSAT). Although GMST and GSAT \r\nare closely related, the two measures are physically distinct. GMST is \r\na combination of land surface air temperature (LSAT) and sea surface \r\ntemperature (SST), whereas GSAT is surface air temperatures over \r\nland, ocean and ice. A  key development in AR6 is the assessment \r\nthat long-term changes in GMST and GSAT differ by at most 10% in "


id: c9b8fca8ad707ee010ffcebd765b4aae
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Contributing Authors: Ed Hawkins (United Kingdom), Paul Edwards (United States of America), Piers Forster (United Kingdom), \r\nDarrell S. Kaufman (United States of America), Jochem Marotzke (Germany), Malte Meinshausen (Australia/Germany), Maisa Rojas \r\n(Chile), Bjorn H. Samset (Norway), Peter Thorne (Ireland/United Kingdom)"


id: e7ebca33b9176d90bfc1a466b746e42f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 38115
content:
"Owens et al., 2017; Hamilton et al., 2018). It is likely that there was a net anthropogenic forcing of 0.0-0.3 Wm-2 in 1850-1900 relative \r\nto 1750 (medium confidence). The net radiative forcing from changes in solar activity and volcanic activity in 1850-1900, compared \r\nto the period around 1750, is estimated to be smaller than +-0.1 W m-2, but note there were several large volcanic eruptions between \r\n1750 and 1850 (Cross-Chapter Box 1.2, Figure 1)."


id: 65ae4d7bd3eda388699d7fb01b525b09
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 15152
content:
"Combining these different sources of evidence, we assess that from the period around 1750 to 1850-1900 there was a change in \r\nglobal temperature of around 0.1 [-0.1 to +0.3] degC (medium confidence), with an anthropogenic component in a likely range of \r\n0.0degC-0.2degC (medium confidence)."


id: 2ceb98c08cdee8ea1bbe7eb09df9709f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 5172
content:
"Climatic changes since the pre-industrial era are a combination of \r\nlong-term anthropogenic changes and natural variations on time \r\nscales from days to decades. The relative importance of these two \r\nfactors depends on the climate variable or region of interest. Natural \r\nvariations consist of both natural radiatively forced trends (e.g., due \r\nto volcanic eruptions or solar variations) and 'internal' fluctuations of \r\nthe climate system which occur even in the absence of any radiative \r\nforcings. The internal 'modes of variability', such as the El Nino-\r\nSouthern Oscillation (ENSO) and the North Atlantic Oscillation (NAO), \r\nare discussed further in Annex IV."


id: 1fef0ec1d21f3efa22ae6d38bc7ee195
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 2830
content:
"Natural variations in both weather and longer time scale phenomena \r\ncan temporarily mask or enhance any anthropogenic trends \r\n(e.g.,  Deser et al., 2012; Kay et al., 2015). These effects are more \r\nimportant on small spatial and temporal scales but can also occur on \r\nthe global scale (Cross-Chapter Box 3.1)."


id: 21db6b14568ccbd7b3be8d52c82f50dd
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 3180
content:
"Since AR5, many studies have examined the role of internal variability \r\nthrough the use of 'large ensembles'. Each such ensemble consists of \r\nmany different simulations by a single climate model for the same \r\ntime period and using the same radiative forcings. These simulations \r\ndiffer only in their phasing of the internal climate variations (also "


id: 6177811df14f18e49140a5821dc30640
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 14444
content:
"Natural climate variations can temporarily mask or \r\nenhance anthropogenic climatic changes over a \r\ndecade or more, especially for smaller regions and \r\nshorter averaging periods."


id: b074f6567603dd1bdad0d802581df95d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 28279
content:
"the construction of 'observation-based large ensembles', which \r\nare alternate possible realizations of historical observations that \r\nretain the statistical properties of observed regional weather \r\n(e.g., McKinnon and Deser, 2018)."


id: 977507dfe76d11766f827c6c88b77405
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 23858
content:
"In the 1930s it was noted that temperatures were increasing at both \r\nlocal and global scales (Figure  1.8; Kincer, 1933; Callendar, 1938). \r\nAt the time it was unclear whether the observed changes were \r\npart of a  longer-term trend or a  natural fluctuation; the 'signal' \r\nhad not yet clearly emerged from the 'noise' of natural variability. \r\nNumerous studies have since focused on the emergence of changes \r\nin temperature using instrumental observations (e.g., Madden and \r\nRamanathan, 1980; Wigley and Jones, 1981; Mahlstein et al., 2011, \r\n2012; Lehner and Stocker, 2015; Lehner et al., 2017) and paleo\u0002temperature data (e.g., Abram et al., 2016)."


id: 9b6e0ba5f322f9a24b9d6291994bdee5
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 24599
content:
"Since the IPCC Third's Assessment Report in 2001, the observed \r\nsignal of climate change has been unequivocally detected at the \r\nglobal scale (Section 1.3), and this signal is increasingly emerging \r\nfrom the noise of natural variability on smaller spatial scales and \r\nin a range of climate variables (FAQ 1.2). In this Report emergence "


id: fd5d08685f797dc66d8d1d732e6fc26d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 41931
content:
"(Section  11.2.5); and the emergence of climatic impact-drivers for \r\nAR6 regions and many climate variables is assessed in Chapter 12 \r\n(Section 12.5.2)."


id: 515a43497bade9b23a4fc28a393b5fd2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 11592
content:
"Related to the concept of emergence is the detection of change \r\n(Chapter  3). Detection of change is defined as the process of \r\ndemonstrating that some aspect of the climate, or a system affected \r\nby climate, has changed in some defined statistical sense, often using \r\nspatially aggregating methods that try to maximize S/N, such as \r\n'fingerprints' (e.g., Hegerl et al., 1996), without providing a reason \r\nfor that change. An identified change is detected in observations if its \r\nlikelihood of occurrence by chance due to internal variability alone is \r\ndetermined to be small, for example, <10% (Glossary)."


id: fac3d49e509c9c40f1f5a36255b28b2a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 41494
content:
"When evaluating and analysing simulations of the physical climate \r\nsystem, several different sources of uncertainty need to be considered \r\n(e.g., Hawkins and Sutton, 2009; Lehner et al., 2020). Broadly, these \r\nsources are: uncertainties in radiative forcings (both those observed \r\nin the past and those projected for the future); uncertainty in the \r\nclimate response to particular radiative forcings; internal and \r\nnatural variations of the climate system (which may be somewhat \r\npredictable); and interactions among these sources of uncertainty."


id: 24ffbb77145f16b6b2a6a07b2bbd4c76
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 3710
content:
"An example of observed emergence in surface air temperatures is \r\nshown in Figure 1.14. Both the largest changes in temperature and \r\nthe largest amplitude of year-to-year variations are observed in the \r\nArctic, with lower latitudes showing less warming and smaller year-to\u0002year variations. For the six example regions shown in Figure 1.14, the \r\nemergence of changes in temperature is more apparent in Northern \r\nSouth America, East Asia and Central Africa, than for northern North \r\nAmerica or Northern Europe. This pattern was predicted by Hansen \r\net al. (1988) and noted in subsequent observations by Mahlstein et al. \r\n(2011) (Sections 10.3.4.3 and 12.5.2). Overall, tropical regions show \r\nearlier emergence of temperature changes than at higher latitudes \r\n(high confidence)."


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vector_id: 27683
content:
"Ensembles of climate simulations (Section  1.5.4.2), such as \r\nthose produced as part of the sixth phase of the Coupled Model \r\nIntercomparison Project (CMIP6), can be used to explore these \r\ndifferent sources of uncertainty and estimate their magnitude. \r\nRelevant experiments with climate models include both historical \r\nsimulations constrained by past radiative forcings, and projections \r\nof future climate which are constrained by specified drivers, such \r\nas GHG concentrations, emissions, or radiative forcings. (The term \r\n'prediction' is usually reserved for estimates of the future climate \r\nstate which are also constrained by the observed initial conditions of \r\nthe climate system, analogous to a weather forecast.)"


id: 59558fbdc52b051858d17cb4dedcd8c2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 12953
content:
"Future radiative forcing is uncertain due to as-yet-unknown societal \r\nchoices that will determine future anthropogenic emissions; this is \r\nconsidered 'scenario uncertainty'. The RCP and SSP scenarios, which \r\nform the basis for climate projections assessed in this Report, are \r\ndesigned to span a plausible range of future pathways (Section 1.6) \r\nand can be used to estimate the magnitude of scenario uncertainty, but \r\nthe real world may also differ from any one of these example pathways."


id: f77b5bde7de38f956dc38bb3416341ed
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 40916
content:
"Annex IV) are unpredictable on time scales longer than a few years \r\nahead and are a source of uncertainty for understanding how the \r\nclimate might become in a particular decade, especially regionally. \r\nThe increased use of 'large ensembles' of complex climate model \r\nsimulations to sample this component of uncertainty is discussed \r\nabove in Section 1.4.2.1 and further in Chapter 4."


id: 2c7514124c63088ff7de155255188630
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 5086
content:
"It is plausible that there are interactions between radiative forcings \r\nand climate variations, such as influences on the phasing or \r\namplitude of internal or natural climate variability (Zanchettin, 2017). \r\nFor example, the timing of volcanic eruptions may influence Atlantic \r\nMulti-decadal Variability (e.g., Ottera et al., 2010; Birkel et al., 2018) \r\nor ENSO (e.g.,  Maher et al., 2015; Khodri et al., 2017; Zuo et al., \r\n2018), and anthropogenic aerosols may influence decadal modes of \r\nvariability in the Pacific (e.g., Smith et al., 2016). In addition, melting \r\nof glaciers and ice caps due to anthropogenic influences has been \r\nspeculated to increase volcanic activity (e.g., a specific example for \r\nIceland is discussed in Swindles et al., 2018)."


id: 71bb21fd2d9a9906858260d3255e412
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 17254
content:
"Not all of these listed sources of uncertainty are of the same type. \r\nFor example, internal climate variations are an intrinsic uncertainty \r\nthat can be estimated probabilistically, and could be more precisely \r\nquantified, but cannot usually be reduced. However, advances in \r\ndecadal prediction offer the prospect of narrowing uncertainties in \r\nthe trajectory of the climate for a few years ahead (Section 4.2.3; \r\ne.g., Meehl et al., 2014; Yeager and Robson, 2017)."


id: e424ff0a00b97bbd48bd655fe548ab2d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 37441
content:
"Other sources of uncertainty, such as model response uncertainty, \r\ncan in principle be reduced, but are not amenable to a frequency\u0002based interpretation of probability, and Bayesian methods to \r\nquantify the uncertainty have been considered instead (e.g., Tebaldi, \r\n2004; Rougier, 2007; Sexton et al., 2012). The scenario uncertainty \r\ncomponent is distinct from other uncertainties, given that future \r\nanthropogenic emissions can be considered as the outcome of a set \r\nof societal choices (Section 1.6.1)."


id: 746df508c80d4c912ab94404b127cc07
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 17716
content:
"For climate model projections it is possible to approximately quantify \r\nthe relative amplitude of various sources of uncertainty (e.g., Hawkins \r\nand Sutton, 2009; Lehner et al., 2020). A range of different climate \r\nmodels are used to estimate the model response uncertainty to \r\na  particular emissions pathway, and multiple pathways are used \r\nto estimate the scenario uncertainty. The unforced component \r\nof internal variability can be estimated from individual ensemble \r\nmembers of the same climate model (Section  1.5.4.8; e.g.,  Deser \r\net al., 2012; Maher et al., 2019)."


id: da3ca0418de271145331166124773cc2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 35694
content:
"Even without any anthropogenic radiative forcing, there would still \r\nbe uncertainty in projecting future climate because of unpredictable \r\nnatural factors such as variations in solar activity and volcanic \r\neruptions. For projections of future climate, such as those presented \r\nin Chapter  4, the uncertainty in these factors is not normally \r\nconsidered. However, the potential effects on the climate of large \r\nvolcanic eruptions (Cross-Chapter Box 4.1; Zanchettin et al., 2016; \r\nBethke et al., 2017) and large solar variations (Feulner and Rahmstorf, \r\n2010; Maycock et al., 2015) are studied. On longer time scales, orbital \r\neffects and plate tectonics also play a role."


id: ef90bc113867b2d7c8aaf0485f3d6e86
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 39529
content:
"Figure 1.15 illustrates the relative size of these different uncertainty \r\ncomponents using a 'cascade of uncertainty' (Wilby and Dessai, 2010), \r\nwith examples shown for global mean temperature, Northern South \r\nAmerican annual temperatures and East Asian summer precipitation \r\nchanges. For global mean temperature, the role of internal variability \r\nis small, and the total uncertainty is dominated by emissions scenario \r\nand model response uncertainties. Note that there is considerable "


id: d5c16687d1ead0976c615dc69c6186e9
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 34919
content:
"Further, even in the absence of any anthropogenic or natural changes \r\nin radiative forcing, Earth's climate fluctuates on time scales from \r\ndays to decades or longer. These 'internal' variations, such as those \r\nassociated with modes of variability (e.g.,  ENSO, Pacific Decadal \r\nVariability (PDV), or Atlantic Multi-decadal Variability (AMV); "


id: b5024004d2c403b6dbbba532be3b1792
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 29081
content:
"overlap between individual simulations for different emissions \r\nscenarios, even for the mid-term (2041-2060). For example, the \r\nslowest-warming simulation for SSP5-8.5 produces less mid-term \r\nwarming than the fastest-warming simulation for SSP1-1.9. For the \r\nlong term, emissions scenario uncertainty becomes dominant."


id: b477ce6217054ba65c91e565d040fe5e
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 28993
content:
"Since AR5 there have been developments in how to consider and \r\ndescribe future climate outcomes which are considered possible but \r\nvery unlikely, highly uncertain, or potentially surprising. To examine \r\nsuch futures there is a  need to move beyond the usual likely or \r\nvery likely assessed ranges and consider low-likelihood outcomes, \r\nespecially those that would result in significant impacts if they \r\noccurred (e.g., Sutton, 2018; Sillmann et al., 2021). This section briefly \r\noutlines some of the different approaches used in the AR6 WGI."


id: 87f420af3edcd9269ee48e749ceac6fe
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 21073
content:
"In the AR6, certain low-likelihood outcomes are described and \r\nassessed because they may be associated with high levels of \r\nrisk, and  the greatest risks may not be associated with the most \r\nlikely outcome. The aim of assessing these possible futures is to \r\nbetter inform risk assessment and decision-making. Two types are \r\nconsidered: (i) low-likelihood high-warming (LLHW) scenarios, which \r\ndescribe the climate in a  world with very high climate sensitivity; \r\nand (ii) low-likelihood, high-impact outcomes that have a  low "


id: 5092fa1915fb09f6a0bf0a0c94a03d72
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 11448
content:
"approaches have been used to better inform risk assessment and \r\ndecision-making, to assist understanding of regional processes, and \r\nrepresent and communicate climate projection uncertainties more \r\nclearly. The aim is to help build a cohesive overall picture of potential \r\nclimate change pathways that moves beyond the presentation of \r\ndata and figures (Glossary; Flottum and Gjerstad, 2017; Moezzi et al., \r\n2017; Dessai et al., 2018; T.G. Shepherd et al., 2018)."


id: 9378e727595aaf15e14d6b0145b650b8
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
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content:
"An illustrative example of how low-likelihood outcomes can produce \r\nsignificant additional risks is shown in Figure  1.16. The Reasons \r\nfor Concern (RFCs) produced by the IPCC AR5 WGII define the \r\nadditional risks due to climate change at different global warming \r\nlevels. These have been combined with Chapter  4  assessments of \r\nprojected global temperature for different emissions scenarios (SSPs; \r\nSection  1.6), and Chapter  7  assessments about ECS. For example, \r\neven following an intermediate emissions scenario could result in \r\nhigh levels of additional risk if ECS is at the upper end of the very \r\nlikely range. However, not all possible low-likelihood outcomes \r\nrelate to ECS, and AR6 considers these issues in more detail than \r\nprevious IPCC assessment reports (see Table 1.1 and Section 1.4.4.2 \r\nfor some examples)."


id: 12cd583272a57f084421e72325182ee9
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 515
content:
"As societies are increasingly experiencing the impacts of climate \r\nchange-related events, the climate science community is developing \r\nclimate information tailored for particular regions and sectors. There \r\nis a  growing focus on explaining and exploring complex physical \r\nchains of events or on predicting climate under various future \r\nsocio-economic developments. Since AR5, 'storylines' or 'narratives' "


id: dcb058aa78f55044bbdbf2fb2df725a5
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 36086
content:
"climate change alone; instead, such decisions will normally take into \r\naccount socio-economic factors as well (Shepherd, 2019)."


id: 57a5f2300f2f9340facfca12751ccfea
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 12688
content:
"would affect regional precipitation and other climate variables, and \r\ndiscuss the various climate drivers that could cause such a circulation \r\nresponse (James et al., 2015; Zappa and Shepherd, 2017; Mindlin \r\net al., 2020). Physical climate storylines can also help frame the \r\ncausal factors of extreme weather events (Shepherd, 2016) and then \r\nbe linked to event attribution (Section  11.2.2 and Cross-Working \r\nGroup Box: Attribution)."


id: 1e5fac98e8b8055b3d70754b14e73863
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 2543
content:
"Storyline approaches can be used to communicate and contextualize \r\nclimate change information in the context of risk for policymakers \r\nand practitioners (Box  10.2; e.g.,  de Bruijn et al., 2016; Dessai \r\net al., 2018; Scott et al., 2018; Jack et al., 2020). They can also help \r\nin assessing risks associated with LLHI events (Weitzman, 2011; \r\nSutton, 2018), because they consider the 'physically self-consistent \r\nunfolding of past events, or of plausible future events or pathways' \r\n(Shepherd et al., 2018), which would be masked in a  probabilistic \r\napproach. These aspects are important as the greatest risk need \r\nnot be associated with the highest-likelihood outcome, and in fact \r\nwill often be associated with low-likelihood outcomes. The storyline \r\napproach can also acknowledge that climate-relevant decisions in \r\na risk-oriented framing will rarely be taken on the basis of physical "


id: 48de573d1ce1515be813f7843a287f2b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 10034
content:
"Contributing Authors: Andy Reisinger (New Zealand), Maisa Rojas (Chile), Aida Diongue-Niang (Senegal), Maarten K. van Aalst \r\n(The  Netherlands), Mathias Garschagen (Germany), Mark Howden (Australia), Margot Hurlbert (Canada), Katharine Mach \r\n(United States of America), Sawsan Khair Elsied Abdel Rahim Mustafa (Sudan), Brian O'Neill (United States of America), Roque Pedace \r\n(Argentina), Jana Sillmann (Norway/Germany), Carolina Vera (Argentina), David Viner (United Kingdom)"


id: 6ed9000ea0afb9a3d4be043f1aced9fd
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 16772
content:
"The IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX; \r\nIPCC, 2012) presented a framework for assessing risks from climate change, which linked hazards (due to changes in climate) with \r\nexposure and vulnerability (Cardona et al., 2012). This framework was further developed by AR5 WGII (IPCC, 2014b), while AR5 WGI \r\nfocussed only on the hazard component of risk. As part of AR6, a cross-Working Group process expanded and refined the concept of \r\nrisk to allow for a consistent risk framing to be used across the three IPCC Working Groups (IPCC, 2019b; Box 2 in Abram et al., 2019; \r\nReisinger et al., 2020)."


id: c95c4ef3840a6e5f04e364e0ed453dd0
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 32749
content:
"The potential for adverse consequences for human or ecological systems, recognizing the diversity of values and objectives \r\nassociated with such systems. In the context of climate change, risks can arise from potential impacts of climate change \r\nas well as human responses to climate change. Relevant adverse consequences include those on lives, livelihoods, health \r\nand well-being, economic, social and cultural assets and investments, infrastructure, services (including ecosystem services), \r\necosystems and species."


id: f19e589527b4b3a16b27c2a2869a9f8c
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 39892
content:
"In the context of climate change impacts, risks result from dynamic interactions between climate-related hazards with the \r\nexposure and vulnerability of the affected human or ecological system to the hazards. Hazards, exposure and vulnerability \r\nmay each be subject to uncertainty in terms of magnitude and likelihood of occurrence, and each may change over time and \r\nspace due to socio-economic changes and human decision-making (see also risk management, adaptation and mitigation)."


id: 5533843aed68969b4f35f27a95335496
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 12263
content:
"In the context of climate change responses, risks result from the potential for such responses not achieving the intended \r\nobjective(s), or from potential trade-offs with, or negative side-effects on, other societal objectives, such as the Sustainable \r\nDevelopment Goals (SDGs) (see also risk trade-off). Risks can arise, for example, from uncertainty in implementation, \r\neffectiveness or outcomes of climate policy, climate-related investments, technology development or adoption, and \r\nsystem transitions."


id: f679d6a7a1011d2acacbe561d7b47e5
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 40733
content:
"Exposure: The presence of people; livelihoods; species or ecosystems; environmental functions, services, and resources; infrastructure; \r\nor economic, social, or cultural assets in places and settings that could be adversely affected."


id: cfa304f6c441be0a1dd1711665234a40
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 33888
content:
"Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements \r\nincluding sensitivity or susceptibility to harm and lack of capacity to cope and adapt."


id: 8a89975ca8b5132ba01f7ad11f79ae4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 21547
content:
"Hazard: The potential occurrence of a natural or human-induced physical event or trend that may cause loss of life, injury, or other health \r\nimpacts, as well as damage and loss to property, infrastructure, livelihoods, service provision, ecosystems and environmental resources."


id: 19d96ea616e9eb0f116d9e61b534c565
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Impacts: The consequences of realized risks on natural and human systems, where risks result from the interactions of climate-related \r\nhazards (including extreme weather/climate events), exposure, and vulnerability. Impacts generally refer to effects on lives, livelihoods, \r\nhealth and well-being, ecosystems and species, economic, social and cultural assets, services (including ecosystem services), and \r\ninfrastructure. Impacts may be referred to as consequences or outcomes and can be adverse or beneficial."


id: 4e179b35039b1426d805ea6185e4dfaf
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Risk in AR6 WGI\r\nThe revised risk framing clarifies the role and contribution of WGI to risk assessment. 'Risk' in IPCC terminology applies only to human \r\nor ecological systems, not to physical systems on their own."


id: 26c6e750b3a2231c576d9ad085e0ef9f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 3975
content:
"Climatic impact-drivers (CIDs): CIDs are physical climate system conditions (e.g., means, events, extremes) that affect an element \r\nof society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral or a mixture \r\nof each across interacting system elements and regions."


id: 4f85dddfd6292d1f71a4b587233f1cf2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"In AR6, WGI uses the term 'climatic impact-drivers' to describe changes in physical systems rather than 'hazards', because the term \r\nhazard already assumes an adverse consequence. The terminology of 'climatic impact-driver' therefore allows WGI to provide a more \r\nvalue-neutral characterization of climatic changes that may be relevant for understanding potential impacts, without pre-judging \r\nwhether specific climatic changes necessarily lead to adverse consequences, as some could also result in beneficial outcomes \r\ndepending on the specific system and associated values. Chapter 12 and the Atlas assess and provide information on climatic impact\u0002drivers for different regions and sectors to support and link to the WGII assessment of the impacts and risks (or opportunities) related \r\nto the changes in the climatic impact-drivers. Although CIDs can lead to adverse or beneficial outcomes, focus is given to CIDs \r\nconnected to hazards, and hence inform risk."


id: 2e77dcdc1eea8fcff168ec9805332720
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index: climate_gpt_v2
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content:
"'Extremes' are a category of CID, corresponding to unusual events with respect to the range of observed values of the variable. \r\nChapter 11 assesses changes in weather and climate extremes, their attribution and future projections."


id: e924e582eb1194053e105447a9a9a953
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updated_at: 2023-04-19 13:21:32
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content:
"Information provided by WGI may or may not be relevant to understand risks related to climate change responses. For example, the \r\nrisk to a company arising from emissions pricing, or the societal risk from reliance on an unproven mitigation technology, is not directly \r\ndependent on actual or projected changes in climate but arise largely from human choices. However, WGI climate information may be \r\nrelevant to understand the potential for maladaptation, such as the potential for specific adaptation responses not achieving the desired \r\noutcome or having negative side effects. For example, WGI information about the range of sea level rise can help inform understanding \r\nof whether coastal protection, accommodation, or retreat would be the most effective risk management strategy in a particular context. "


id: 5782ea67612e2fa43a72abbf370347ea
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"From a WGI perspective, low-likelihood, high-impact outcomes and the concept of deep uncertainty are also relevant for risk assessment."


id: d473f02df93cf692f4fe495acce14c55
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Low-likelihood, high-impact (LLHI) outcomes: Outcomes/events whose probability of occurrence is low or not well known \r\n(as in the context of deep uncertainty) but whose potential impacts on society and ecosystems could be high. To better inform risk \r\nassessment and decision-making, such low-likelihood outcomes are considered if they are associated with very large consequences \r\nand may therefore constitute material risks, even though those consequences do not necessarily represent the most likely outcome."


id: e187bdc61598b2bad11d66decb62fc07
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updated_at: 2023-04-19 13:21:32
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content:
"The AR6 WGI Report provides more detailed information about these types of events compared to AR5 (Table 1.1, Section 1.4.4)."


id: ff8d03df9578c5fc60e403a55db03c38
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 42361
content:
"Recognizing the need for assessing and managing risk in situations of high uncertainty, SROCC advanced the treatment of situations \r\nwith deep uncertainty (Section 1.2.3; IPCC, 2019b; Box 5 in Abram et al., 2019). A situation of deep uncertainty exists when experts or \r\nstakeholders do not know or cannot agree on: (i) appropriate conceptual models that describe relationships among key driving forces \r\nin a system; (ii) the probability distributions used to represent uncertainty about key variables and parameters; and/or (iii) how to \r\nweigh and value desirable alternative outcomes (Abram et al., 2019). The concept of deep uncertainty can complement the IPCC \r\ncalibrated uncertainty language and thereby broaden the communication of risk."


id: 9abde2969e4780821f75f2aa110660aa
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 24464
content:
"et al., 2015; Bathiany et al., 2020). In such simulations, tipping points \r\noccur in narrow regions of parameter space (e.g., CO2 concentration \r\nor temperature increase), and for specific climate background states. \r\nThis makes them difficult to predict using Earth system models (ESMs) \r\nrelying on parmeterizations of known processes. In some cases, \r\nit is possible to detect forthcoming tipping points through time\u0002series analysis that identifies increased sensitivity to perturbations \r\nas the tipping point is approached (e.g.,  'critical slowing-down', \r\nScheffer et al., 2012)."


id: a1a5d804af0ab1fbb1d825addb4f2a9
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content:
"An 'abrupt change' is defined in this report as a change that takes \r\nplace substantially faster than the rate of change in the recent history \r\nof the affected component of a  system (Glossary). In some cases, \r\nabrupt change occurs because the system state actually becomes \r\nunstable, such that the subsequent rate of change is independent of \r\nthe forcing. We refer to this class of abrupt change as a 'tipping point',\r\ndefined as a critical threshold beyond which a system reorganizes, \r\noften abruptly and/or irreversibly (Glossary; Lenton et al., 2008). \r\nSome of the abrupt climate changes and climate tipping points \r\ndiscussed in this Report could have severe local climate responses, \r\nsuch as extreme temperature, droughts, forest fires, ice-sheet loss \r\nand collapse of the thermohaline circulation (Sections 4.7.2, 5.4.9, \r\n8.6 and 9.2.3)."


id: 27257ba3e6bf4a29f0477e71f7d5bafa
created_at: 2023-04-19 13:21:32
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content:
"Some suggested climate tipping points prompt transitions from one \r\nsteady state to another (Figure 1.17). Transitions can be prompted \r\nby perturbations such as climate extremes which force the system \r\noutside of its current well of attraction in the stability landscape; \r\nthis is called noise-induced tipping (Figure  1.17a,b; Ashwin et al., \r\n2012). For example, the tropical forest dieback seen in some ESM \r\nprojections is accelerated by longer and more frequent droughts over \r\ntropical land (Good et al., 2013)."


id: da29f074a301ad8060be4a0f2cfb61a7
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 35678
content:
"There is evidence of abrupt changes in Earth's history, and some of \r\nthese events have been interpreted as tipping points (Dakos et al., \r\n2008). Some of these are associated with significant changes in the \r\nglobal climate, such as deglaciations in the Quaternary (past 2.5 \r\nmillion years) and rapid warming at the Palaeocene-Eocene Thermal \r\nMaximum (around 55.5 million years ago; Bowen et al., 2015; Hollis \r\net al., 2019). Such events changed the planetary climate for tens to \r\nhundreds of thousands of years, but at a rate that is actually much \r\nslower than projected anthropogenic climate change over this \r\ncentury, even in the absence of tipping points."


id: f36983944288a77e1b16d3fafaa7ea8a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Alternatively, transitions from one state to another can occur if \r\na  critical threshold is exceeded; this is called 'bifurcation tipping' \r\n(Figure  1.17c,d; Ashwin et al., 2012). The new state is defined as \r\n'irreversible' on a  given time scale if the recovery from this state \r\ntakes substantially longer than the time scale of interest, which is \r\ndecades to centuries for the projections presented in this report. \r\nA well-known example is the modelled irreversibility of the ocean's \r\nthermohaline circulation in response to North Atlantic changes such \r\nas freshwater input from rainfall and ice-sheet melt (Rahmstorf \r\net al., 2005; Alkhayuon et al., 2019), which is assessed in detail in \r\nChapter 9 (Section 9.2.3)."


id: 4347655274559ad6bc5f50fd021c8808
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Such paleoclimate evidence has even fuelled concerns that \r\nanthropogenic GHGs could tip the global climate into a permanent \r\nhot state (Steffen et al., 2018). However, there is no evidence of such \r\nnon-linear responses at the global scale in climate projections for \r\nthe next century, which indicates a near-linear dependence of global \r\ntemperature on cumulative GHG emissions (Sections 1.3.5, 5.5 and \r\n7.4.3.1). At the regional scale, abrupt changes and tipping points, such \r\nas Amazon rainforest dieback and permafrost collapse, have occurred \r\nin projections with Earth System Models (Section  4.7.3; Drijfhout "


id: b2b96f54b736e15c3c8d375179d00395
created_at: 2023-04-19 13:21:32
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content:
"The tipping point concept is most commonly framed for systems \r\nin which the forcing changes relatively slowly. However, this is not \r\nthe case for most scenarios of anthropogenic forcing projected for \r\nthe 21st century. Systems with inertia lag behind rapidly increasing \r\nforcing, which can lead to the failure of early warning signals or "


id: 556b5e1f263caef3f034f1c8a14f0aa4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 12303
content:
"even the possibility of temporarily overshooting a bifurcation point \r\nwithout provoking tipping (Ritchie et al., 2019)."


id: 7725b37b6ccda12af8ec4d6736e79721
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 18160
content:
"among humans or other species, such as the COVID-19 pandemic \r\n(Cross-Chapter Box 6.1; Forster et al., 2020; Le Quere et al., 2020). \r\nThe discovery of the hole in the ozone layerwas also a surprise even \r\nthough some of the relevant atmospheric chemistry was known at \r\nthe time. The term 'unknown unknowns' (Parker and Risbey, 2015) \r\nis also sometimes used in this context to refer to events that cannot \r\nbe anticipated with present knowledge or were of an unanticipated \r\nnature before they occurred."


id: e526887da25d78254482222c0b98e514
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 37615
content:
"'Surprises' are a class of risk that can be defined as low-likelihood \r\nbut well-understood events: they are events that cannot be predicted \r\nwith current understanding. The risk from such surprises can be \r\naccounted for in risk assessments (Parker and Risbey, 2015). Examples \r\nrelevant to climate science include: a  series of major volcanic \r\neruptions or a nuclear war, either of which would cause substantial \r\nplanetary cooling (Robock et al., 2007; Mills et al., 2014); significant \r\n21st century sea level rise due to marine ice sheet instability (MISI; \r\nBox 9.4); the potential for collapse of the stratocumulus cloud decks \r\n(Schneider et al., 2019) or other substantial changes in climate \r\nfeedbacks (Section  7.4); and unexpected biological epidemics "


id: 884eff17f0d29f1b10e1c06e9c22d443
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Contributing Authors: Pandora Hope (Australia), Wolfgang Cramer (France/Germany), Gregory M. Flato (Canada), Katja Frieler \r\n(Germany), Nathan P. Gillett (Canada), Christian Huggel (Switzerland), Jan Minx (Germany), Friederike Otto (United Kingdom/\r\nGermany), Camille Parmesan (France, United Kingdom/United States of America), Joeri Rogelj (United Kingdom/Belgium), Maisa Rojas \r\n(Chile), Sonia I. Seneviratne (Switzerland), Aimee B.A. Slangen (The Netherlands), Daithi Stone (New Zealand), Laurent Terray (France), \r\nMaarten K. van Aalst (The Netherlands), Robert Vautard (France), Xuebin Zhang (Canada)"


id: e0fd44a389714430ff4b92f152c0a69b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 36850
content:
"Changes in the climate system are becoming increasingly apparent, as are the climate-related impacts on natural and human systems. \r\nAttribution is the process of evaluating the contribution of one or more causal factors to such observed changes or events. Typical \r\nquestions addressed by the IPCC include: 'To what extent is an observed change in global temperature induced by anthropogenic GHG \r\nand aerosol concentration changes, or influenced by natural variability?' and 'What is the contribution of climate change to observed \r\nchanges in crop yields, which are also influenced by changes in agricultural management?' Changes in the occurrence and intensity of \r\nextreme events can also be attributed, addressing questions such as: 'Have human GHG emissions increased the likelihood or intensity \r\nof an observed heatwave?'"


id: 30c47fceed19067b74810f6f8d382997
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"This Cross-Working Group Box briefly describes why attribution studies are important. It also describes some new developments in the \r\nmethods used in those studies and provides recommendations for interpretation."


id: 13053d3570b9566f2beb5f2124b07d77
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 554
content:
"Attribution studies serve to evaluate and communicate linkages associated with climate change, for example: between the human\u0002induced increase in GHG concentrations and the observed increase in air temperature or extreme weather events (AR6 WGI \r\nChapters 3, 10 and 11); or between observed changes in climate and changing species distributions and food production (AR6 WGII \r\nChapters 2 and others, summarized in WGII Chapter 16; e.g., Verschuur et al., 2021); or between climate change mitigation policies \r\nand atmospheric GHG concentrations (AR6 WGI Chapter 5; AR6 WGIII Chapter 14). As such, they support numerous statements made \r\nby the IPCC (AR6 WGI Section 1.3 and Appendix 1A; IPCC, 2013b, 2014b)."


id: bb984dd8cf9310af4d0c81e2d2164559
created_at: 2023-04-19 13:21:32
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content:
"Attribution assessments can also serve to monitor mitigation and assess the efficacy of applied climate protection policies (AR6 WGI \r\nSection 4.6.3; e.g., Nauels et al., 2019; Banerjee et al., 2020), inform and constrain projections (WGI Section 4.2.3; Gillett et al., 2021; \r\nRibes et al., 2021) or inform the loss and damages estimates and potential climate litigation cases by estimating the costs of climate \r\nchange (Huggel et al., 2015; Marjanac et al., 2017; Frame et al., 2020). These findings can thus inform mitigation decisions as well as \r\nrisk management and adaptation planning (e.g., CDKN, 2017)."


id: eaeddf847bbbb74659ee17063850f69
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"There are many attribution approaches, and several methods are detailed below. In physical and biological systems, attribution often \r\nbuilds on the understanding of the mechanisms behind the observed changes and numerical models are used, while in human systems \r\nother methods of evidence-building are employed. Confidence in the attribution can be increased if more than one approach is used \r\nand the model is evaluated as fit-for-purpose (WGI Section 1.5, WGI Section 3.8, WGI Section 10.3.3.4; Hegerl et al., 2010; Vautard \r\net al., 2019; Otto et al., 2020; Philip et al., 2020). The final step includes appropriate communication of the attribution assessment and \r\nthe accompanying confidence in the result (e.g., Lewis et al., 2019)."


id: ede8d7b01b42f3d4874cb303ab410edb
created_at: 2023-04-19 13:21:32
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content:
"ratio (WGI Section 5.2.1.1). Decomposition approaches can be used to attribute emissions underlying those changes to various drivers \r\nsuch as population, energy efficiency, consumption or carbon intensity (Hoekstra and van den Bergh, 2003; Raupach et al., 2007; Rosa \r\nand Dietz, 2012). Combined with attribution of their climate outcomes, the attribution of the sources of GHG emissions can inform \r\nthe attribution of anthropogenic climate change to specific countries or actors (Matthews, 2016; Otto et al., 2017; Skeie et al., 2017; \r\nNauels et al., 2019), and in turn inform discussions on fairness and burden sharing (WGIII Chapter 14)."


id: 67e0f555ed545be35612297f0d863cc9
created_at: 2023-04-19 13:21:32
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content:
"Specific regional conditions and responses may simplify or complicate attribution on those scales. For example, some human forcings, \r\nsuch as regional land-use change or aerosols, may enhance or reduce regional signals of change (WGI Sections 10.4.2, 11.1.6 and \r\n11.2.2; Lejeune et al., 2018; Undorf et al., 2018; Boe et al., 2020; Thiery et al., 2020). In general, regional climate variations are larger \r\nthan the global mean climate, adding additional uncertainty to \r\nattribution (e.g., in regional sea level change, WGI Section 9.6.1). \r\nThese statistical limitations may be reduced by 'process-based \r\nattribution', focusing on the physical processes known to \r\ninfluence the response to external forcing and internal variability \r\n(WGI Section 10.4.2).\r\nAttribution in the IPCC\r\nThe process of evaluating the contribution of one or more causal \r\nfactors to observed changes or events"


id: 248452c04db5bcc915c0e4dc2f103d8b
created_at: 2023-04-19 13:21:32
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content:
"Cross-Working Group Box: Attribution, Figure 1 | Schematic of the \r\nsteps to develop an attribution assessment, and the purposes of \r\nsuch assessments. Methods and systems used to test the attribution \r\nhypothesis or theory include: model-based fingerprinting; other \r\nmodel-based methods; evidence-based fingerprinting; process\u0002based approaches; empirical or decomposition methods; and the \r\nuse of multiple lines of evidence. Many of the methods are based on the \r\ncomparison of the observed state of a system to a hypothetical counterfactual \r\nworld that does not include the driver of interest to help estimate the causes of \r\nthe observed response."


id: 7959c5d1f37c8b579d790c680962e41a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"The attribution of observed changes to climate-related drivers \r\nacross a  diverse set of sectors, regions and systems is part of \r\neach chapter in the WGII contribution to AR6 and is synthesized \r\nin WGII Chapter  16 (Section  16.2). The number of attribution "


id: b96a4da767c7b667dc88f70b83b21f24
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 29834
content:
"studies on climate change impacts has grown substantially since AR5, generally leading to higher confidence levels in attributing the \r\ncauses of specific impacts. New studies include the attribution of changes in socio-economic indicators such as economic damages \r\ndue to river floods (e.g., Schaller et al., 2016; Sauer et al., 2021), the occurrence of heat-related human mortality (e.g., Vicedo-Cabrera \r\net al., 2018; Sera et al., 2020) or economic inequality (e.g., Diffenbaugh and Burke, 2019)."


id: 5b55587c5b3f015d95fe16b61934fd55
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 13312
content:
"Impact attribution does not always involve attribution to anthropogenic climate forcing. However, a  growing number of studies \r\ninclude this aspect (e.g., Frame et al. (2020) for the attribution of damages induced by Hurricane Harvey; or Diffenbaugh and Burke \r\n(2019) for the attribution of economic inequality between countries; or Schaller et al. (2016) for flood damages)."


id: 7a89a31af8486efb155405693d5f7ff3
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"The AR5 assessed regional-scale detection and attribution and \r\nassessed key regional climate phenomena and their relevance for \r\nfuture regional climate projections. This report shows that past \r\nand future climate changes and extreme weather events can be \r\nsubstantial on local and regional scales (Chapters 8-12 and Atlas), \r\nwhere they may differ considerably from global trends, not only in \r\nintensity but even in the direction of change (e.g., Fischer et al., 2013)."


id: cfa5381628d344e19dcdf41f511a340b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Although the evolution of global climate trends emerges as the \r\nnet result of regional phenomena, average or aggregate estimates \r\noften do not reflect the intensity, variability and complexity of \r\nregional climate changes (Stammer et al., 2018; Shepherd, 2019). \r\nA fundamental aspect of the study of regional climate changes is the \r\ndefinition of characteristic climate zones, clusters or regions, across \r\nwhich the emergent climate change signal can be properly analysed \r\nand projected (see Atlas). Suitable sizes and shapes of such zones \r\nstrongly depend not only on the climate variable and process of \r\ninterest, but also on relevant multi-scale feedbacks."


id: dd09b48d82fa2d99df613f4412f76074
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content:
"There are several approaches to the classification of climate \r\nregions. When climate observation data was sparse and limited, the "


id: e7affa61ab77f6fb02b1cc49060c2048
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updated_at: 2023-04-19 13:21:32
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content:
"climate projections for 2030 were presented for five sub-continental \r\nregions (see Section 1.3.6 for an assessment of those projections). \r\nIn subsequent reports, there has been a growing emphasis on the \r\nanalysis of regional climate, including two special reports: one on \r\nregional impacts (IPCC, 1998) and another on extreme events "


id: 69856cd7424d4744cf0824d787d55339
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content:
"(SREX, IPCC, 2012). A  general feature of previous IPCC reports is \r\nthat the number and coverage of climate regions vary according to \r\nthe subject and across Working Groups. Such varied definitions have \r\nthe advantage of optimizing the results for a particular application \r\n(e.g., national boundaries are crucial for decision-making, but they "


id: caff15fea76c8a4646ba1a887ade200b
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content:
"rarely delimit distinctive climate regions), whereas variable definitions \r\nof regions may have the disadvantage of hindering multidisciplinary \r\nassessments and comparisons between studies or Working Groups."


id: 67ac7e0e26bdab99348b2d425a077460
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"(Figure 1.18c), based on the nine continental domains defined in AR5 \r\nWGII Part B (Hewitson et al., 2014). These are classical geopolitical \r\ndivisions of Africa, Asia, Australasia, Europe, North America, Central \r\nand South America, plus Small Islands, Polar Regions, and the \r\nOcean. In AR6 WGI, five hybrid zones (Caribbean-Small Islands, East \r\nEurope-Asia, European Arctic, North American Arctic, and Northern \r\nCentral America) are also identified, which are assessed in more \r\nthan one Continental Region. Additional consistency with WGIII is \r\npursued in Chapter  6  through the use of sub-continental domains \r\nwhich essentially form a  subset of the Continental Set of Regions \r\n(Figure 1.18c and Section 6.1)."


id: ec1e6b4878477b840ab32bc3e00e94a0
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"In this Report, regional climate change is primarily addressed through \r\nthe introduction of four classes of regions (unless otherwise explicitly \r\nmentioned and justified). The first two are the unified WGI Reference \r\nSets of (i) Land Regions and (ii) Ocean Regions, which are used \r\nthroughout the Report. These are supplemented by additional sets \r\nof (iii) Typological Regions - used in Chapters 5, 8-12 and Atlas - \r\nand (iv) Continental Regions, which are mainly used for linking \r\nChapters 11, 12 and Atlas with Working Group II (Figure 1.18). All \r\nfour classes of regions are defined and described in detail in the \r\nAtlas. Here we summarize their basic features."


id: d6a7d51d46a0d6e1def18422aef626dd
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vector_id: 35069
content:
"This section presents a selection of key developments since AR5 of \r\nthe capabilities underlying the lines of evidence used in the present \r\nreport: observational data and observing systems (Section  1.5.1); \r\nnew developments in reanalyses (Section  1.5.2); climate models \r\n(Section  1.5.3); and modelling techniques, comparisons and \r\nperformance assessments (Section 1.5.4). For brevity, we focus on the \r\ndevelopments that are of particular importance to the conclusions \r\ndrawn in later chapters, though we also provide an assessment of \r\npotential losses of climate observational capacity."


id: 8522c5403a80f4bef27f0a93e44bb1d3
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Progress in climate science relies on the quality and quantity of \r\nobservations from a range of platforms: surface-based instrumental \r\nmeasurements, aircraft, radiosondes and other upper-atmospheric \r\nobservations, satellite-based retrievals, ocean observations, and \r\npaleoclimatic records. An historical perspective to these types of \r\nobservations is presented in Section 1.3.1."


id: 3689178e33053feeddc5a5ad503e8d9d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"The starting point for defining the AR6 Reference Sets of Land Regions \r\nwas the collection of 26 regions introduced in SREX (IPCC, 2012). \r\nThe SREX collection was then revised, reshaped, complemented and \r\noptimized to reflect the recent scientific literature and observed \r\nclimate-change trends, giving rise to the novel AR6 Reference Set of \r\n46 Land Regions. Additionally, AR6 introduces a new Reference Set \r\nof 15 Ocean Regions (including 3 Hybrid Regions that are treated as \r\nboth: land and ocean), which complete the coverage of the whole \r\nEarth (Iturbide et al., 2020)."


id: 41e9fae1f3f0e9831a114c38071308c8
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content:
"Particular aspects of regional climate change are described by \r\nspecialized domains called Typological Regions (Figure 1.18b). These \r\nregions cover a  wide range of spatial scales and are defined by \r\nspecific features, called typologies. Examples of typologies include: \r\ntropical forests, deserts, mountains, monsoon regions and megacities, \r\namong others. Typological Regions are powerful tools to summarize \r\ncomplex aspects of climate defined by a  combination of multiple \r\nvariables. For this reason, they are used in many chapters of AR6 WGI \r\nand WGII (e.g., Chapters 8-12 and Atlas)."


id: e66637b5decf34ccde61c45968a2d9a4
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vector_id: 37842
content:
"as well as new and/or emerging observational platforms that play \r\na key role in AR6. We then discuss potential near-term losses in key \r\nobservational networks due to climate change or other adverse \r\nhuman-caused influence."


id: c045b6cba6e0a7ee06b416987283844c
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 31131
content:
"Two distinctly different but important remote-sensing systems can \r\nprovide information about temperature and humidity since the \r\nearly 2000s. Global navigation satellite systems (e.g.,  GPS), radio \r\noccultation and limb soundings provide information, although only \r\ndata for the upper troposphere and lower stratosphere are suitable \r\nto support climate change assessments (Angerer et al., 2017; \r\nScherllin-Pirscher et al., 2017; Gleisner et al., 2020; Steiner et al., \r\n2020). These measurements complement those from the Atmospheric \r\nInfrared Sounder (AIRS; Chahine et al., 2006). AIRS has limitations \r\nin cloudy conditions, although these limitations have been partly \r\nsolved using new methods of analysis (Blackwell and Milstein, 2014; \r\nSusskind et al., 2014). These new data sources now have sufficiently \r\nlong records to strengthen the analysis of atmospheric warming in \r\nChapter 2 (Section 2.3.1.2)."


id: e93f46d43923135cdb903dcf7a31b5fe
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content:
"Observations of the ocean have expanded significantly since AR5, \r\nwith expanded global coverage of in situ ocean temperature and \r\nsalinity observations, in situ ocean biogeochemistry observations, \r\nand satellite retrievals of a variety of EOVs. Many recent advances "


id: 13c906a6cdb960af66673e8ca8c34fa2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 693
content:
"are extensively documented in a  compilation by Lee et al. (2019). \r\nBelow we discuss those most relevant for the current assessment."


id: cccfe45254d18db73fb22f1b327a83bf
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 33365
content:
"Argo is a global network of nearly 4000 autonomous profiling floats \r\n(Roemmich et al., 2019), delivering detailed constraints on the \r\nhorizontal and vertical structure of temperature and salinity across \r\nthe global ocean. Argo has greatly expanded since AR5, including \r\nbiogeochemistry and measurements deeper than 2000 m  (Jayne \r\net al., 2017), and the longer time series enable more rigorous climate \r\nassessments of direct relevance to estimates of ocean heat content \r\n(Sections  2.3.3.1 and 7.2.2.2). Argo profiles are complemented by \r\nanimal-borne sensors in several key areas, such as the seasonally ice\u0002covered sectors of the Southern Ocean (Harcourt et al., 2019)."


id: 8f639e2da1d7008a185201b9f08f145b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 22437
content:
"Improvements have also been made in the monitoring of permafrost. \r\nThe Global Terrestrial Network for Permafrost (GTN-P; Biskaborn \r\net al., 2015) provides long-term records of permafrost temperature \r\nand active layer thickness at key sites to assess their changes over \r\ntime. Substantial improvements to our assessments of large-scale \r\nsnow changes come from intercomparison and blending of several \r\ndatasets, for snow water equivalent (Mortimer et al., 2020) and \r\nsnow cover extent (Mudryk et al., 2020), and from bias corrections \r\nof combined datasets using in situ data (Sections 2.3.2.5 and 9.5.2; \r\nPulliainen et al., 2020)."


id: d625b399050300337f6d8475e4424d1f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 34993
content:
"Most basin-scale arrays of moored ocean instruments have \r\nexpanded since AR5, providing decades-long records of the ocean \r\nand atmosphere properties relevant for climate, such as the El Nino-\r\nSouthern Oscillation (Chen et al., 2018), deep convection (de Jong \r\net al., 2018) or transports through straits (Woodgate, 2018). Key \r\nbasin-scale arrays include transport-measuring arrays in the Atlantic \r\nOcean, continuing (McCarthy et al., 2020) or newly added since AR5 \r\n(Lozier et al., 2019), supporting the assessment of regional ocean \r\ncirculation (Section  9.2.3). Tropical ocean moorings in the Pacific, \r\nIndian and Atlantic oceans include new sites, improved capability for \r\nreal-time transmission, and new oxygen and CO2 sensors (Bourles \r\net al., 2019; Hermes et al., 2019; Smith et al., 2019)."


id: c51d37e368328717b82684432e5010b6
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 31990
content:
"A decade of observations of sea-surface salinity is now available via \r\nthe SMOS and SMAP satellite retrievals, providing continuous and \r\nglobal monitoring of surface salinity in the open ocean and coastal \r\nareas for the first time (Section  9.2.2.2; Vinogradova et al., 2019; \r\nReul et al., 2020)."


id: 123eb788fdfeaa31a6da63aa20148e91
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 406
content:
"The global network of tide gauges, complemented by a  growing \r\nnumber of satellite-based altimetry datasets, allows for more robust \r\nestimates of global and regional sea level rise (Sections  2.3.3.3 \r\nand 9.6.1.3). Incorporating vertical land motion derived from the \r\nGlobal Positioning System (GPS), the comparison with tide gauges \r\nhas allowed the correction of a drift in satellite altimetry series over \r\nthe period 1993-1999 (Watson et al., 2015; Chen et al., 2017), thus \r\nimproving our knowledge of the recent acceleration of sea level rise \r\n(Chapter  2, Section  2.3.3.3). These datasets, combined with Argo \r\nand observations of the cryosphere, allow a consistent closure of the \r\nglobal mean sea level budget (Cross-Chapter Box 9.1; WCRP Global \r\nSea Level Budget Group, 2018)."


id: 1a267630ca66c810915d41e3a7f4baa4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 1792
content:
"For the cryosphere, there has been much recent progress in \r\nsynthesizing global datasets covering larger areas and longer time \r\nperiods from multi-platform observations. For glaciers, the Global \r\nTerrestrial Network for Glaciers, which combines data on glacier \r\nfluctuations, mass balance and elevation change with glacier outlines \r\nand ice thickness, has expanded and provided input for assessing \r\nglobal glacier evolution and its role in sea level rise (Sections 2.3.2.3 \r\nand 9.5.1; Zemp et al., 2019). New data sources include archived \r\nand declassified aerial photographs and satellite missions, and high\u0002"


id: 456d5712a2beded902c2d6dfd6bf81bd
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 9433
content:
"The ability to estimate changes in global land biomass has improved \r\ndue to the use of different microwave satellite data (Liu et al., 2015) \r\nand in situ forest census data and co-located lidar, combined with \r\nthe Moderate Resolution Imaging Spectroradiometer (MODIS; \r\nBaccini et al., 2017). This has allowed for improved quantification "


id: 3edf855fc88be654c63a2dae8c22b4bc
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 8247
content:
"Ongoing efforts have expanded the number of large-scale, tree \r\nring-based drought reconstructions that span the last centuries \r\nto millennium at annual resolution (Chapter  8; Cook et al., 2015; \r\nStahle et al., 2016; Aguilera-Betti et al., 2017; Morales et al., 2020). \r\nLikewise, stalagmite records of oxygen isotopes have increased in \r\nnumber, resolution and geographic distribution since AR5, providing \r\ninsights into regional-to-global-scale hydrological change over the \r\nlast centuries to millions of years (Chapter  8; Cheng et al., 2016; \r\nDenniston et al., 2016; Comas-Bru and Harrison, 2019). A new global \r\ncompilation of water isotope-based paleoclimate records spanning \r\nthe last 2000 years (PAGES Iso2K) lays the groundwork for quantitative \r\nmulti-proxy reconstructions of regional- to global-scale hydrological \r\nand temperature trends and extremes (Konecky et al., 2020)."


id: 3025be478bd33ca7a803a239c936b0bd
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 5731
content:
"of land temperature (Duan et al., 2019), carbon stocks and human\u0002induced changes due to deforestation (Chapter  2, Section  2.2.7). \r\nTime series of Normalized Difference Vegetation Index (NDVI) \r\nfrom MODIS and other remote-sensing platforms is widely applied \r\nto assess the effects of climate change on vegetation in drought\u0002sensitive regions (Atampugre et al., 2019). New satellite imaging \r\ncapabilities for meteorological observations, such as the advanced \r\nmultispectral imager aboard Himawari-8 (Bessho et al., 2016), also \r\nallow for improved monitoring of challenging quantities such as \r\nseasonal changes of vegetation in cloudy regions (Section 2.3.4.3; \r\nMiura et al., 2019)."


id: 6e36fe66e2f39c72dac8b983ab647db2
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 16654
content:
"In the ocean, efforts are underway to coordinate observations of \r\nbiologically relevant EOVs around the globe (Muller-Karger et al., \r\n2018; Canonico et al., 2019) and to integrate observations across \r\ndisciplines (e.g., the Global Ocean Acidification Observing Network, \r\nGOA-ON; Tilbrook et al., 2019). A  large number of coordinated \r\nfield campaigns during the 2015/2016 El Nino event enabled \r\nthe collection of short-lived biological phenomena such as coral \r\nbleaching and mortality caused by a months-long ocean heatwave \r\n(Hughes et al., 2018); beyond this event, coordinated observations of \r\ncoral reef systems are increasing in number and quality (Obura et al., \r\n2019). Overall, globally coordinated efforts focused on individual \r\ncomponents of the biosphere (e.g., the Global Alliance of Continuous \r\nPlankton Recorder Surveys, GACS; Batten et al., 2019) contribute to \r\nimproved knowledge of the ways in which marine ecosystems are \r\nchanging (Section 2.3.4.2)."


id: d4e34b7ba88b883253ac8ccfd86fc7ac
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 34769
content:
"Recent advances in the reconstruction of climate extremes - aside \r\nfrom temperature and drought - include expanded datasets of past \r\nEl Nino-Southern Oscillation extremes (Section  2.4.2; e.g.,  Barrett \r\net al., 2018; Freund et al., 2019; Grothe et al., 2020) and other modes \r\nof variability (Hernandez et al., 2020), hurricane activity (e.g., Burn \r\nand Palmer, 2015; Donnelly et al., 2015), jet stream variability (Trouet \r\net al., 2018) and wildfires (e.g., Taylor et al., 2016)."


id: e5fb092d0027f592f652ed51747469d5
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 37755
content:
"New datasets as well as recent data compilations and syntheses \r\nof sea level over the last millennia (Kopp et al., 2016; Kemp et al., \r\n2018), the last 20 kyr (Khan et al., 2019), the last interglacial period \r\n(Section 2.3.3.3: Dutton et al., 2015), and the Pliocene (Cross-Chapter \r\nBox  2.4; Dumitru et al., 2019; Grant et al., 2019) help constrain \r\nsea level variability and its relationship to global and regional \r\ntemperature variability, and to estimates of contributions to sea level \r\nchange from different sources on centennial to millennial time scales \r\n(Section 9.6.2)."


id: 5c2c767ad96a517e0e98bb5ac154849d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 13472
content:
"Given widespread evidence for decreases in global biodiversity in \r\nrecent decades  - and that these decreases are related to climate \r\nchange and other forms of human disturbance (IPBES, 2019) - a new \r\ninternational effort to identify a set of Essential Biodiversity Variables \r\n(EBVs) is underway (Pereira et al., 2013; Navarro et al., 2017)."


id: e977689aead4e560aee70a18c4cc4a70
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 38430
content:
"Reconstructions of paleo ocean pH (Section 2.3.3.5) have increased \r\nin number and accuracy, providing new constraints on ocean pH \r\nacross the last centuries (e.g.,  Wu et al., 2018), the last glacial \r\ncycles (e.g.,  Moy et al., 2019), and the last several million years \r\n(e.g., Anagnostou et al., 2020). Such reconstructions inform processes \r\nand act as benchmarks for Earth system models of the global carbon \r\ncycle over the recent geologic past (Section 5.3.1), including previous \r\nhigh-CO2 warm intervals such as the Pliocene (Cross-Chapter Box 2.4). \r\nParticularly relevant to such investigations are reconstructions of \r\natmospheric CO2 (Honisch et al., 2012; Foster et al., 2017) that span \r\nthe past millions to tens of millions of years."


id: 3b32c0ffe753d19d6e4d388c516d8b10
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 7601
content:
"In summary, the observational coverage of ongoing changes to the \r\nclimate system is improved at the time of AR6, relative to what was \r\navailable for AR5 (high confidence)."


id: 496110cdf439a5758665623367b8a37f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 10128
content:
"Major paleoreconstruction efforts completed since AR5 include \r\na  variety of large-scale, multi-proxy temperature datasets and \r\nassociated reconstructions spanning the last 2000  years (PAGES \r\n2k Consortium, 2017, 2019; Neukom et al., 2019), the Holocene \r\n(Kaufman et al., 2020), the Last Glacial Maximum (Cleator et al., 2020; \r\nTierney et al., 2020b), the mid-Pliocene Warm Period (McClymont \r\net al., 2020), and the Early Eocene Climatic Optimum (Hollis et al., \r\n2019). Newly compiled borehole data (Cuesta-Valero et al., 2019), \r\nas well as advances in statistical applications to tree ring data, \r\nresult in more robust reconstructions of key indices such as Northern \r\nHemisphere temperature over the last millennium (e.g., Wilson et al., \r\n2016; Anchukaitis et al., 2017). Such reconstructions provide a new \r\ncontext for recent warming trends (Chapter 2) and serve to constrain \r\nthe response of the climate system to natural and anthropogenic \r\nforcing (Chapters 3 and 7)."


id: 45f02d707734d3a3c9fecc1fc150d09d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 9530
content:
"Constraints on the timing and rates of past climate changes have \r\nimproved since AR5. Analytical methods have increased the precision \r\nand reduced sample-size requirements for key radiometric dating \r\ntechniques, including radiocarbon (Gottschalk et al., 2018; Lougheed \r\net al., 2018) and uranium-thorium dating (Cheng et al., 2013). More \r\naccurate ages of many paleoclimate records are also facilitated \r\nby recent improvements in the radiocarbon calibration datasets \r\n(IntCal20, Reimer et al., 2020). A  recent compilation of global \r\ncosmogenic nuclide-based exposure dates (Balco, 2020b) allows for \r\na  more rigorous assessment of the evolution of glacial landforms \r\nsince the Last Glacial Maximum (Balco, 2020a)."


id: 3728fdff6abfa8f6212c49c6b4e66c2b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 6921
content:
"Advances in paleoclimate data assimilation (Section  10.2.3.2) \r\nleverage the expanded set of paleoclimate observations to create \r\nphysically consistent gridded fields of climate variables for data\u0002rich intervals of interest (e.g.,  over the last millennium, (Hakim \r\net al., 2016) or last glacial period (Cleator et al., 2020; Tierney et al., \r\n2020b)). Such efforts mirror advances in our understanding of the \r\nrelationship between proxy records and climate variables of interest, \r\nas formalized in so-called proxy system models (e.g., Tolwinski-Ward \r\net al., 2011; Dee et al., 2015; Dolman and Laepple, 2018)."


id: 1f74a728135ad3631931b0b0855b71d0
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 2740
content:
"(Liu et al., 2021). Concern has been raised about potential leakage \r\nfrom 5G network transmissions into the operating frequencies of \r\npassive sensors on existing weather satellites, which could adversely \r\ninfluence their ability to remotely observe water vapour in the \r\natmosphere (Yousefvand et al., 2020)."


id: ac1a0fa546e5f3b71bb62385dd1ed972
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 27517
content:
"Overall, the number, temporal resolution and chronological accuracy \r\nof paleoclimate reconstructions have increased since AR5, leading \r\nto improved understanding of climate system processes (or Earth \r\nsystem processes) (high confidence)."


id: 9865f7e3ee604ed3cd6fbfe00e0aae98
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 24022
content:
"Surface-based networks have reduced in their coverage or range of \r\nvariables measured due to COVID-19 and other factors. Over land, \r\nseveral factors, including the ongoing transition from manual to \r\nautomatic observations of weather, have reduced the spatial coverage \r\nof certain measurement types, including rainfall intensity, radiosonde \r\nlaunches and pan evaporation, posing unique risks to datasets used \r\nfor climate assessment (WMO, 2017; Lin and Huybers, 2019). Ship\u0002based measurements, which are important for ocean climate and \r\nreanalyses through time (Smith et al., 2019), have been in decline \r\ndue to the number of ships contributing observations. There has also \r\nbeen a decline in the number of variables recorded by ships, but an \r\nincrease in the quality and time-resolution of others (e.g., sea level \r\npressure, Kent et al., 2019)."


id: 4e6c2a8cb6ce1162c8661c67b631f9a4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 11073
content:
"In summary, while the quantity, quality and diversity of climate \r\nsystem observations have grown since AR5, the loss or potential loss \r\nof several critical components of the observational network is also \r\nevident (high confidence)."


id: 172e55c25a08468b394caa2e7353ed66
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 1295
content:
"Certain satellite frequencies are used to detect meteorological \r\nfeatures that are vital to climate change monitoring. These can be \r\ndisturbed by certain radio communications (Anterrieu et al., 2016), \r\nalthough scientists work to remove noise from the signal (Oliva \r\net al., 2016). For example, water vapour in the atmosphere naturally \r\nproduces a weak signal at 23.8 gigahertz (GHz), which is within the \r\nrange of frequencies of the 5G cellular communications network "


id: 33044ba4d4e7ee3d03ede81f56d322b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 6242
content:
"Reanalyses are usually the output of a  model (e.g.,  a  numerical \r\nweather prediction model) constrained by observations using data \r\nassimilation techniques, but the term has also been used to describe \r\nobservation-based datasets produced using simpler statistical "


id: ca7f730f7a4d4e459b5912530c63b007
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 32967
content:
"et al., 2001). Older reanalyses have a number of limitations, which \r\nhave to be accounted for when assessing the results of any study \r\nthat uses them."


id: 7be2834c898f0e1c6b22373121f3ce41
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 19005
content:
"methods and models (Annex I: Observational Products). This section \r\nfocuses on the model-based methods and their recent developments."


id: 8758996b2b50d34536e90fe3026bb11e
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 20974
content:
"Reanalyses complement datasets of observations in describing \r\nchanges through the historical record and are sometimes considered \r\nas 'maps without gaps' because they provide gridded output in \r\nspace and time, often global, with physical consistency across \r\nvariables on sub-daily time scales, and information about sparsely \r\nobserved variables (such as evaporation; Hersbach et al., 2020). They \r\ncan be globally complete, or regionally focussed and constrained \r\nby boundary conditions from a global reanalysis (Section 10.2.1.2). \r\nThey can also provide feedback about the quality of the observations \r\nassimilated, including estimates of biases and critical gaps for some \r\nobserving systems."


id: a4b566452a1539fb659e8c711275f10b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 26196
content:
"ERA5 provides hourly atmospheric fields at about 31 km resolution \r\non 137 levels in the vertical, as well as land-surface variables and \r\nocean waves. It is available from 1979 onwards and is updated in \r\nnear-real time, with plans to extend back to 1950. A  10-member \r\nensemble is also available at coarser resolution, allowing uncertainty \r\nestimates to be provided (e.g.,  Section  2.3). MERRA-2 includes \r\nmany updates from the earlier version, including the assimilation of \r\naerosol observations, several improvements to the representation \r\nof the stratosphere, including ozone, and improved representations \r\nof cryospheric processes. All of these improvements increase the \r\nusefulness of these reanalyses (Section 7.3; Hoffmann et al., 2019)."


id: 4c9321bc497ea999f4c5e0ff3acc1a34
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 10736
content:
"Many early reanalyses are described in Box 2.3 of Hartmann et al. \r\n(2013). These were often limited by the underlying model, the data \r\nassimilation schemes and observational issues (Thorne and Vose, \r\n2010; Zhou et al., 2018). Observational issues include the lack of \r\nunderlying observations in some regions, changes in the observational \r\nsystems over time (e.g.,  spatial coverage, introduction of satellite \r\ndata), and time-dependent errors in the underlying observations or in \r\nthe boundary conditions, which may lead to stepwise biases in time. \r\nThe assimilation of sparse or inconsistent observations can introduce \r\nmass or energy imbalances (Valdivieso et al., 2017; Trenberth et al., \r\n2019). Further limitations and some efforts to reduce the implications \r\nof these observational issues are detailed below."


id: 2a1b2e57096d6d0caa01b5350c034b61
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 4618
content:
"Models of atmospheric composition and emissions sources and \r\nsinks allow the forecast and reanalysis of constituents such as O3, \r\ncarbon monoxide (CO), nitrogen oxides (NOx) and aerosols. The \r\nCopernicus Atmosphere Monitoring Service (CAMS) reanalysis shows \r\nimprovement against earlier atmospheric composition reanalyses, \r\ngiving greater confidence for its use to study trends and evaluate \r\nmodels (Section 7.3; e.g., Inness et al., 2019)."


id: 9853f44dfb22d4386f27c2eb95001138
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 24008
content:
"The methods used in the development of reanalyses have progressed \r\nsince AR5 and, in some cases, this has important implications for \r\nthe information they provide on how the climate is changing. Annex \r\nI  includes a  list of reanalysis datasets used in AR6. Recent major \r\ndevelopments in reanalyses include the assimilation of a wider range \r\nof observations, higher spatial and temporal resolution, extensions \r\nfurther back in time, and greater efforts to minimize the influence of \r\na temporally varying observational network."


id: d20b6719f26e19e3d5682f9de29a13b4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 34308
content:
"Extensive improvements have been made in global atmospheric \r\nreanalyses since AR5. The growing demand for high-resolution \r\ndata has led to the development of higher-resolution atmospheric \r\nreanalyses, such as the Modern-Era Retrospective Analysis for \r\nResearch and Applications, version 2 (MERRA-2; Gelaro et al., 2017) \r\nand ERA5 (Hersbach et al., 2020). There is a  focus on ERA5 here \r\nbecause it has been assessed as of high enough quality to present \r\ntemperature trends alongside more traditional observational datasets \r\n(Section 2.3.1.1) and is also used in the Interactive Atlas."


id: fdd419296aaa3ee2d515ff9cb7c7a65f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 42016
content:
"Precipitation is not usually assimilated in reanalyses and, depending \r\non the region, reanalysis precipitation can differ from observations \r\nby more than the observational error (Zhou and Wang, 2017; Sun \r\net al., 2018; Alexander et al., 2020; Bador et al., 2020), although \r\nthese studies did not include ERA5. Assimilation of radiance \r\nobservations from microwave imagers which, over ice-free ocean \r\nsurfaces, improve the analysis of lower-tropospheric humidity, \r\ncloud liquid water and ocean-surface wind speed have resulted \r\nin improved precipitation outputs in ERA5 (Hersbach et al., 2020). \r\nGlobal averages of other fields, particularly temperature, from ERA\u0002Interim and JRA-55 reanalyses continue to be consistent over the last \r\n20 years with surface observational data sets that include the polar \r\nregions (Simmons and Poli, 2015), although biases in precipitation "


id: 5e74c8e1645207c3393a7281b913b41f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Atmospheric reanalyses that were assessed in AR5 are still being \r\nused in the literature, and results from ERA-Interim (about 80 km \r\nresolution, production stopped in August 2019; Dee et al., 2011), the \r\nJapanese 55-year Reanalysis (JRA-55; Ebita et al., 2011; Kobayashi \r\net al., 2015; Harada et al., 2016) and Climate Forecast System \r\nReanalysis (CFSR; Saha et al., 2010) are assessed in AR6. Some \r\nstudies still also use the NCEP/NCAR reanalysis, particularly because \r\nit extends back to 1948 and is updated in near-real time (Kistler "


id: f16ccacf89c4c5cee6ac5aede9d1bd35
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 39862
content:
"and radiation can influence temperatures regionally (Zhou et al., \r\n2018). The global average surface temperature from MERRA-2 is far \r\ncooler in recent years than temperatures derived from ERA-Interim \r\nand JRA-55, which may be due to the assimilation of aerosols and \r\ntheir interactions (Section 2.3)."


id: 7ad38d88905eaaff0f451f6a33dad202
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 18812
content:
"in the atmospheric forcing from atmospheric reanalyses \r\n(see  Section  1.5.2.1.3); and improvements in the data quantity \r\nand quality available for assimilation (e.g.,  Lellouche et al., 2018; \r\nHeimbach et al., 2019), particularly due to Argo observations (Annex \r\nI; Zuo et al., 2019)."


id: cf32ca94185444caf1ac4c3a33acd9f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 33801
content:
"A number of regional atmospheric reanalyses (Section  10.2.1.2) \r\nhave been developed, such as COSMO-REA (Wahl et al., 2017), and \r\nthe Australian Bureau of Meteorology Atmospheric high-resolution \r\nRegional Reanalysis for Australia (BARRA; Su et al., 2019). Regional \r\nreanalyses can add value to global reanalyses due to the lower \r\ncomputational requirements, and can allow multiple numerical \r\nweather prediction models to be tested (e.g.,  Kaiser-Weiss et al., \r\n2019). There is some evidence that these higher-resolution reanalyses \r\nbetter capture precipitation variability than global lower-resolution \r\nreanalyses (Jermey and Renshaw, 2016; Cui et al., 2017). They are \r\nfurther assessed in Section 10.2.1.2 and used in the Interactive Atlas."


id: b4ecbae8680cc28e06fc2e62eda33988
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 29074
content:
"In summary, the improvements in atmospheric reanalyses, and the \r\ngreater number of years since the routine ingestion of satellite data \r\nbegan, relative to AR5, mean that there is increased confidence in \r\nusing atmospheric reanalysis products alongside more standard \r\nobservation-based datasets in AR6 (high confidence)."


id: 649c04ef4cbde4feffd98682ff634a5f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 14979
content:
"While there are still limitations in their representation of oceanic \r\nfeatures, ocean reanalyses add value to products based only on \r\nobservation, and are used to inform assessments in AR6 (Chapters 2, \r\n3, 7 and 9). Reanalyses of the atmosphere or ocean alone may not \r\naccount for important atmosphere-ocean coupling, motivating the \r\ndevelopment of coupled reanalyses (Laloyaux et al., 2018; Schepers \r\net al., 2018; Penny et al., 2019), but these are not assessed in AR6."


id: b9a49db32aa8ce4b1f943502e0e382d7
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 29872
content:
"Since AR5, ocean reanalyses have improved due to: increased \r\nmodel resolution (Zuo et al., 2017; Lellouche et al., 2018; Heimbach \r\net al., 2019); improved physics (Storto et al., 2019); improvements "


id: 2a01a4fcf9f84758d85a8b54a74cb106
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 4611
content:
"This section summarizes major developments in these different types \r\nof models since AR5. Past IPCC reports have made use of multi-model \r\nensembles generated through various phases of the World Climate \r\nResearch Programme (WCRP) Coupled Model Intercomparison \r\nProject (CMIP). Analysis of the latest CMIP Phase 6 (CMIP6; Eyring \r\net al., 2016) simulations constitute a key line of evidence supporting \r\nthis Assessment Report (Section  1.5.4). The key characteristics of \r\nmodels participating in CMIP6 are listed in Annex II: Models."


id: 983d236e191f95b9bb4cf15a0d71a94
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 23995
content:
"cycles, ecosystem structure and ecosystem functioning, and \r\nto provide initial conditions for further model experiments or \r\ndownscaling (Chapter 2)."


id: d007549ea669eba26e51557cc647e263
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 33954
content:
"The growing interest in longer-term climate forecasts (from seasonal \r\nto multi-year and decadal) means that reanalyses are now more \r\nroutinely being used to develop the initial state for these forecasts, \r\nsuch as for the Decadal Climate Prediction Project (DCPP; Boer et al., \r\n2016). Ocean reanalyses are now being used routinely in the context \r\nof climate monitoring, (e.g.,  the Copernicus Marine Environment \r\nMonitoring Service Ocean State Report; von Schuckmann et al., 2019)."


id: 7f469a7dc529ed6d27b97ab59303db40
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 19547
content:
"In summary, reanalyses have improved since AR5 and can \r\nincreasingly be used as a  line of evidence in assessments of the \r\nstate and evolution of the climate system (high confidence). \r\nReanalyses provide consistency across multiple physical quantities, \r\nand information about variables and locations that are not directly \r\nobserved. Since AR5, new reanalyses have been developed with \r\nvarious combinations of increased resolution, extended records, \r\nmore consistent data assimilation, estimation of uncertainty arising \r\nfrom the range of initial conditions, and an improved representation \r\nof the atmosphere or ocean system. While noting their remaining \r\nlimitations, this Report uses the most recent generation of reanalysis \r\nproducts alongside more standard observation-based datasets."


id: be7d5bac9b0ae5f55b3d7fe50b78824f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 30774
content:
"The number of vertical levels in the atmosphere of global models \r\nhas increased (Figure 1.19), partly to enable simulations to include \r\nhigher levels in the atmosphere and better represent stratospheric \r\nprocesses (Charlton-Perez et al., 2013; Kawatani et al., 2019). Half \r\nthe modelling groups now use 'high-top' models with a  top level \r\nabove the stratopause (a pressure of about 1 hPa). The number of \r\nvertical levels in the ocean models has also increased in order to \r\nachieve finer resolution over the water column and especially in the \r\nupper mixed layer and to better resolve the diurnal cycle (Section 3.5 \r\nand Annex II; Bernie et al., 2008)."


id: eb7f35a34a0321c2a226d4894cbfae8e
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"A wide range of numerical models is widely used in climate science to \r\nstudy the climate system and its behaviour across multiple temporal \r\nand spatial scales. These models are the main tools available to \r\nlook ahead into possible climate futures under a range of scenarios \r\n(Section  1.6). Global Earth system models (ESMs) are the most \r\ncomplex models that contribute to AR6. At the core of each ESM is \r\na GCM (general circulation model) representing the dynamics of the \r\natmosphere and ocean. ESMs are complemented by regional models \r\n(Section 10.3.1) and by a hierarchy of models of lower complexity. "


id: 26aa5b32435f48bc6e8ff861b98d1416
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 3962
content:
"Despite the documented progress of higher resolution, the \r\nmodel evaluation carried out in subsequent chapters shows that \r\nimprovements between CMIP5 and CMIP6 remain modest at the \r\nglobal scale (Section  3.8.2; Bock et al., 2020). Lower resolution \r\nalone does not explain all model biases, for example, a low blocking \r\nfrequency (Davini and D'Andrea, 2020) or a  wrong shape of the \r\nIntertropical Convergence Zone (Tian and Dong, 2020). Model \r\nperformance depends on model formulation and parameterizations \r\nas much as on resolution (Chapters 3, 8 and 10)."


id: 7ab165153bb888f70ccd4f6ebc11c098
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Atmospheric models include representations of physical processes \r\nsuch as clouds, turbulence, convection and gravity waves that are \r\nnot fully represented by grid-scale dynamics. The CMIP6 models \r\nhave undergone updates in some of their parameterization schemes \r\ncompared to their CMIP5 counterparts, with the aim of better \r\nrepresenting the physics and bringing the climatology of the models \r\ncloser to newly available observational datasets. Most notable \r\ndevelopments are to schemes involving radiative transfer, cloud "


id: c4fb79c64d3c3ec903513fa4b9f417f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 31965
content:
"microphysics, and aerosols, in particular a more explicit representation \r\nof the aerosol indirect effects through aerosol-induced modification \r\nof cloud properties. Broadly, aerosol-cloud microphysics has been \r\na  key topic for the aerosol and chemistry modelling communities \r\nsince AR5, leading to improved understanding of the climate \r\ninfluence of short-lived climate forcers, but they remain the single \r\nlargest source of spread in ESM calculations of climate sensitivity \r\n(Meehl et al., 2020), with numerous parameterization schemes in \r\nuse (Section 6.4; Gettelman and Sherwood, 2016; Zhao et al., 2018; \r\nGettelman et al., 2019). The treatment of droplet size and mixed\u0002phase clouds (liquid and ice) was found to lead to changes in the \r\nclimate sensitivity (Glossary) of some models between AR5 and AR6 \r\n(Section  7.4; Bodas-Salcedo et al., 2019; Gettelman et al., 2019; \r\nZelinka et al., 2020)."


id: 8273f0055273e7fe38deec82fb2c1137
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
content_type: text
index: climate_gpt_v2
vector_id: 20074
content:
"When developing climate models, choices have to be made in a number \r\nof areas. Besides model formulation and resolution, parameterizations \r\nof unresolved processes also involve many choices as, for each of \r\nthese, several parameters can be set. The acceptable range for these \r\nparameters is set by mathematical consistency (e.g.,  convergence \r\nof a  numerical scheme), physical considerations (e.g.,  energy \r\nconservation), observations, or a  combination of factors. Model \r\ndevelopers choose a set of parameters that both falls within this range \r\nand mimics observations of individual processes or their statistics."


id: 6730e49b6219129eb4ad259ba4049eff
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 15430
content:
"Sea level rise is caused by multiple processes acting on multiple time \r\nscales: ocean warming, glaciers and ice-sheet melting, change in \r\nwater storage on land, and glacial isostatic adjustment (Box 9.1) but \r\nno single model can represent all these processes (Section 9.6). In \r\nthis Report, the contributions are computed separately (Figure 9.28) \r\nand merged into a  common probabilistic framework and updated \r\nfrom AR5 (Section 9.6; Church et al., 2013; Kopp et al., 2014)."


id: 433b611f99285efe50cc527b72fe90b7
created_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 9040
content:
"Another notable development since AR5 is the inclusion of stochastic \r\nparameterizations of sub-grid processes in some comprehensive \r\nclimate models (Sanchez et al., 2016). Here, the deterministic \r\ndifferential equations that govern the dynamical evolution of the \r\nmodel are complemented by knowledge of the stochastic variability \r\nin unresolved processes. While not yet widely implemented, the \r\napproach has been shown to improve the forecasting skill of weather \r\nmodels, to reduce systematic biases in global models (Berner et al., \r\n2017; Palmer, 2019) and to influence simulated climate sensitivity \r\n(Strommen et al., 2019)."


id: 351b3d5b171b194b89e15a19ccfeca65
created_at: 2023-04-19 13:21:32
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content:
"independently such that all collective behaviour is emergent, is an \r\nopen question (Schmidt et al., 2017; Burrows et al., 2018)."


id: be82287a986102ad6fa304122ad9c28b
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 30780
content:
"Regional tuning targets include: the AMOC, the Southern Ocean \r\ncirculation, and temperature profiles in ocean basins (Golaz et al., \r\n2019; Sellar et al., 2019); regional land properties and precipitations \r\n(Mauritsen et al., 2019; Yukimoto et al., 2019) ; latitudinal distribution \r\nof radiation (Boucher et al., 2020); spatial contrasts in TOA radiative \r\nfluxes or surface fluxes; and stationary waves in the Northern \r\nHemisphere (Schmidt et al., 2017; Yukimoto et al., 2019)."


id: 7fb16629d65af06bacf316b1a4c16783
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Even with some core commonalities of approaches to model tuning, \r\npractices can differ, such as the use of initial drift from initialized \r\nforecasts, the explicit use of the transient observed record for the \r\nhistorical period, or the use of the present-day radiative imbalance at \r\nthe TOA as a tuning target rather than an equilibrated pre-industrial \r\nbalance. The majority of CMIP6 modelling groups report that they \r\ndo not tune their model for the observed trends during the historical \r\nperiod (23 out of 29 groups), nor for ECS (25 out of 29). ECS and \r\nTCR are thus emergent properties for a  large majority of models. \r\nThe effect of tuning on model skill and ensemble spread in CMIP6 is \r\nfurther discussed in Section 3.3."


id: 6b4187db61edbebc64306a76a9703a1e
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 16170
content:
"The need for accurate climate information at the regional scale is \r\nincreasing (Section  10.1). High-resolution global climate models, \r\nsuch as those taking part in HighResMIP, provide more detailed "


id: 47566579276e1f51f046c827615fe0c7
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 9759
content:
"Figure 1.20 | World map showing the increased diversity of modelling centres contributing to CMIP and CORDEX. Climate models are often developed by \r\ninternational consortia. One such consortium, EC-Earth, is shown as an example under the label 8 EU Cities (involving SMHI, Sweden; KNMI, The Netherlands; DMI, Denmark; \r\nAEMET, Spain; Met Eireann, Ireland; CNR-ISAC, Italy; Instituto de Meteorologia, Portugal; and FMI, Finland). There are too many such collaborations to display all of them on \r\nthis map. More complete information about institutions contributing to CORDEX and CMIP6 is found in Annex II."


id: 38d195152c506cfc6e58da545e108900
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 7200
content:
"The number of climate centres or consortia that carry out global \r\nclimate simulations and projections has grown from 11 in the \r\nfirst CMIP to 19 in CMIP5 and 28 for CMIP6 (Section  1.5.4.2 and \r\nAnnex II). Regional climate models participating in the Coordinated \r\nRegional Downscaling Experiment (CORDEX) are more diverse than \r\nthe global ESMs (Section 1.5.4.3 and Annex II) and engage an even \r\nwider international community (Figure 1.20)."


id: eff52e92139b7385ddf54e24f50a710f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 39597
content:
"EMICs have been used extensively in past IPCC reports, providing \r\nlong-term integrations on paleoclimate and future time scales, \r\nincluding stabilization pathways and a  range of commitment \r\nscenarios, with perturbed physics ensembles and sensitivity studies, \r\nor with simulations targeting the uncertainty in global climate-\r\ncarbon cycle systems (e.g., Meehl et al., 2007b; Collins et al., 2013). "


id: 5d61f5f63d9981e50477f8cf889b06c6
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Current emulators and SCMs include the generic impulse response \r\nmodel outlined in Chapter  8  of AR5 (AR5-IR; Supplementary \r\nMaterial 8.SM.11 of Myhre et al., 2013), two-layer models (Held \r\net al., 2010; Rohrschneider et al., 2019; Nicholls et al., 2020), and \r\nhigher-complexity approaches that include upwelling, diffusion and \r\nentrainment in the ocean component (e.g.,  MAGICC Version 5.3 \r\n(Raper et al., 2001; Wigley et al., 2009); Version 6/7 (Meinshausen \r\net al., 2011a); OSCAR (Gasser et al., 2017); CICERO SCM (Skeie et al., \r\n2017); FaIR (Millar et al., 2017a; Smith et al., 2018); and a range of \r\nstatistical approaches (Schwarber et al., 2019; Beusch et al., 2020b). \r\nAn example of recent use of an emulator approach is an early \r\nestimate of the climate implications of the COVID-19 lockdowns \r\n(Cross-Chapter Box 6.1; Forster et al., 2020)."


id: cdf13114b6a5fdc01f9fb1123f287e35
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updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 33566
content:
"heterogeneous forcers such as black carbon more adequately (Stjern \r\net al., 2017), provide an appropriate representation of the forcing-\r\nfeedback framework (e.g., Sherwood et al., 2015), investigate new \r\nparameterizations of ocean heat uptake, and implement better \r\nrepresentations of volcanic aerosol-induced cooling (Gregory \r\net al., 2016a)."


id: 5d4f6f8b851a83e1e33ce455a18c1f3d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 13696
content:
"MAGICC (Wigley et al., 2009; Meinshausen et al., 2011a) and \r\nFaIR (Smith et al., 2018) were used in IPCC SR1.5 (IPCC, 2018) to \r\ncategorize mitigation pathways into classes of scenarios that peak \r\nnear 1.5degC, overshoot 1.5degC, or stay below 2degC. The SR1.5 (Rogelj \r\net al., 2018b) concluded that there was high agreement on the \r\nrelative temperature response of pathways, but medium agreement\r\non the precise absolute magnitude of warming, introducing a level of \r\nimprecision in the attribution of a single pathway to a given category."


id: 996a64b9d6ef657f0d4cd2039604ec02
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 24215
content:
"Since AR5, simplified climate models have been developed further, and \r\ntheir use is increasing. Different purposes motivating development \r\ninclude: being as simple as possible for teaching purposes (e.g., a two\u0002layer energy balance model); being as comprehensive as possible to \r\nallow for propagation of uncertainties across multiple Earth system \r\ndomains (MAGICC and others); or focusing on higher-complexity \r\nrepresentation of specific domains (e.g.,  OSCAR). The common \r\ntheme motivating many models is to improve parameterizations \r\nthat reflect the latest findings in complex ESM interactions - such \r\nas the nitrogen cycle addition to the carbon cycle, or tropospheric \r\nand stratospheric ozone exchange - with the aim of emulating their \r\nglobal mean temperature response. Also, within the simple models \r\nthat have a  rudimentary representation of spatial heterogeneity \r\n(e.g., four-box simple climate models), the ambition is to represent "


id: b4a027ae06d7997af11619713d5ed05e
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"In this Report, there are two notable uses of simple climate \r\nmodels. One is the connection between the assessed range of \r\nECS in Chapter  7, and the projections of future global surface air \r\ntemperature (GSAT) change in Chapter 4, which is done via a two\u0002layer model based on Held et al. (2010). It is also used as input to \r\nsea level projections in Chapter 9. The other usage is the transfer of \r\nEarth system assessment knowledge to WGIII, via a set of models \r\n(MAGICC, FaIR, CICERO-SCM) specifically tuned to represent the WGI \r\nassessment. For an overview of the uses, and an assessment of the \r\nrelated Reduced Complexity Model Intercomparison Project (RCMIP), \r\nsee Nicholls et al. (2020) and Cross-Chapter Box 7.1."


id: a09d32577ba5be37000962ce9aadfa58
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updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 25465
content:
"Emissions metrics compare the radiative forcing, temperature change, or other climate effects arising from emissions of CO2 against \r\nthose from emissions of non-CO2 radiative forcing agents (such as CH4 or N2O). They have been discussed in the IPCC since the First \r\nAssessment Report and are used as a means of aggregating emissions and removals of different gases and placing them on a common \r\n('CO2 equivalent', or 'CO2-eq') scale."


id: 6b62c4e011068acb1982fe6fa5eea6df
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 16193
content:
"AR5 included a thorough assessment of common pulse emissions metrics, and how these address various indicators of future climate \r\nchange (Myhre et al., 2013). Most prominently used are the global warming potentials (GWPs), which integrate the calculated radiative \r\nforcing contribution following an idealized pulse (or one-time) emission, over a chosen time horizon (IPCC, 1990a), or the global \r\ntemperature change potential (GTP), which considers the contribution of emissions to the global-mean temperature at a specific time \r\nafter emission. Yet another metric is the global precipitation change potential (GPP), used to quantify the precipitation change per unit \r\nmass of emission of a given forcing agent (Shine et al., 2015)."


id: f16b55451bf953461309b004cc304ebe
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Each Party shall use the 100-year time-horizon global warming potential (GWP) values from the IPCC Fifth Assessment Report, \r\nor 100-year time-horizon GWP values from a subsequent IPCC assessment report as agreed upon by the 'Conference of the \r\nParties serving as the meeting of the Parties to the Paris Agreement' (CMA), to report aggregate emissions and removals of \r\nGHGs, expressed in CO2-eq. Each Party may in addition also use other metrics (e.g., global temperature potential) to report \r\nsupplemental information on aggregate emissions and removals of GHGs, expressed in CO2-eq."


id: 353e43391754303c8617e59f149d3af6
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updated_at: 2023-04-19 13:21:32
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vector_id: 6613
content:
"Since AR5, improved knowledge of the radiative properties, lifetimes and other characteristics of emitted species, and the response of \r\nthe climate system, have led to updates to the numerical values of a range of metrics (Table 7.15). Another key development is a set \r\nof metrics that compare a pulse emission of CO2 (as considered by GWP and GTP) to step-changes of emission rates for short-lived \r\ncomponents (i.e., also considering emissions trends). Termed GWP* (which also includes a pulse component) and combined global"


id: 6cd460101789a15db6429f5622564e9a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"temperature change potential (CGTP), these metrics allow the construction of a  near-linear relationship between global surface \r\ntemperature change and cumulative CO2 and CO2-eq emissions of both short- and long-lived forcing agents (Allen et al., 2016; Cain \r\net al., 2019; Collins et al., 2020). For example, the temperature response to a sustained methane reduction has a similar behaviour to \r\nthe temperature response to a pulse CO2 removal (or avoided emission)."


id: f596fb0fc9b3f0d4225084d3210c4301
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"In this Report, recent scientific developments underlying emissions metrics, as relevant for WGI, are assessed in full in Section 7.6. \r\nIn particular, see Box 7.3, which discusses the choice of metric for different usages, and Section 7.6.1, which treats the challenge \r\nof comparing the climate implication of emissions of short-lived and long-lived compounds. Also, the choice of metric is of key \r\nimportance when defining and quantifying net zero GHG emissions (Box 1.4 and Section 7.6.2). Chapter 6 applies metrics to attribute \r\nGSAT change to short-lived climate forcer (SLCF) and long-lived GHG emissions from different sectors and regions (Section 6.6.2)."


id: c7d45477571cc5d8c93859670db47116
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 32461
content:
"The metrics assessed in this Report are also used, and separately assessed, by WGIII. See Cross-Chapter Box  2  and Annex B  in \r\nChapter 2 of the WGIII contribution to AR6."


id: 2ba77926e1b768e0535d67ee3e29adf4
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 4938
content:
"Numerical models, however complex, cannot be a  perfect \r\nrepresentation of the real world. Results from climate modelling \r\nsimulations constitute a key line of evidence for the present Report, \r\nwhich requires considering the limitations of each model simulation. \r\nThis section presents recent developments in techniques and \r\napproaches to robustly extract, quantify and compare results from \r\nmultiple, independent climate models, and how their performance \r\ncan be assessed and validated."


id: b210e4954f6c70d3a8a5ab80062458d6
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Together, the three ensemble methods (MMEs, ICEs, PPEs) allow \r\ninvestigation of climate model uncertainty arising from internal \r\nvariability, initial and internal boundary conditions, model \r\nformulations and parameterizations (Parker, 2013). Figure  1.21 \r\nillustrates the different ensemble types. Recent studies have also \r\nstarted combining multiple ensemble types or using ensembles in \r\ncombination with statistical analytical techniques. For example, \r\nMurphy et al. (2018) combine MMEs and PPEs to give a  fuller \r\nassessment of modelling uncertainty. Wagman and Jackson (2018) \r\nuse PPEs to evaluate the robustness of MME-based emergent \r\nconstraints. Sexton et al. (2019) study the robustness of ICE "


id: 96780608b2950a003c0458cac0bc4c4f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 23675
content:
"Recently, the ICE technique has been extended to atmosphere-only \r\nsimulations (Mizuta et al., 2017), single-forcer influences such as \r\nvolcanic eruptions (Bethke et al., 2017), regional modelling (Mote \r\net al., 2015; Fyfe et al., 2017; Schaller et al., 2018; Leduc et al., 2019), \r\nand to attribution of extreme weather events using crowdsourced \r\ncomputing (climateprediction.net; Massey et al., 2015)."


id: 601141a6c80eafd2fdd4096e1847c92c
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 14208
content:
"ICEs can also be used to evaluate climate model parameterizations, \r\nif models are initialized appropriately (Phillips et al., 2004; Williams \r\net al., 2013), mostly within the framework of seamless weather and \r\nclimate predictions (e.g.,  Palmer et al., 2008; Hurrell et al., 2009; \r\nBrown et al., 2012). Initializing an atmospheric model in hindcast \r\nmode and observing the biases as they develop permits testing of the \r\nparameterized processes, by starting from a known state rather than \r\none dominated by quasi-random short-term variability (Williams \r\net al., 2013; Ma et al., 2014; Vanniere et al., 2014). However, single\u0002model initial-conditions ensembles cannot cover the same degrees of \r\nfreedom as a multi-model ensemble, because model characteristics \r\nsubstantially affect model behaviour (Flato et al., 2013)."


id: e97868bbe093a26ebd3991d1b576ecad
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"A third common modelling technique is the perturbed parameter \r\nensemble (PPE; note that the abbreviation also sometimes refers to \r\nthe sub-category 'perturbed physics ensemble'). These methods are \r\nused to assess uncertainty based on a single model, with individual \r\nparameters perturbed to reflect the full range of their uncertainty \r\n(Murphy et al., 2004; Knutti et al., 2010; Lee et al., 2011; Shiogama \r\net al., 2014). Statistical methods can then be used to detect which \r\nparameters are the main causes of uncertainty across the ensemble. \r\nPPEs have been used frequently in simpler models, such as EMICs, and \r\nare being applied to more complex models. A caveat of PPEs is that the \r\nestimated uncertainty will depend on the specific parameterizations \r\nof the underlying model and may well be an underestimation of \r\nthe 'true' uncertainty. It is also challenging to disentangle forced \r\nresponses from internal variability using a PPE alone."


id: b1bf09315063b4529779c3869063e089
created_at: 2023-04-19 13:21:32
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content:
"approaches by identifying parameters and processes responsible for \r\nmodel errors at the two different time scales."


id: c1ef894f4a770dd541c3b2f16f3a6aba
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 31421
content:
"Overall, we assess that increases in computing power and the \r\nbroader availability of larger and more varied ensembles of model \r\nsimulations have contributed to better estimations of uncertainty in \r\nprojections of future change (high confidence). Note, however, that \r\ndespite their widespread use in climate science today, the cost of \r\nthe ensemble approach in human and computational resources, and \r\nthe challenges associated with the interpretation of multi-model \r\nensembles, has been questioned (Palmer and Stevens, 2019; Touze\u0002Peiffer et al., 2020)."


id: 20698d23a1a171a2aa9d100e8d838a21
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
vector_id: 2921
content:
"The Coupled Model Intercomparison Project (CMIP) provides \r\na  framework to compare the results of different GCMs or ESMs \r\nperforming similar experiments. Since its creation in the mid-1990s, it \r\nhas evolved in different phases, involving all major climate modelling \r\ncentres in the world (Figure 1.20). The results of these phases have \r\nplayed a key role in previous IPCC reports, and the present Report \r\nassesses a  range of results from CMIP5 that were not published \r\nuntil after the AR5, as well as the first results of the 6th phase of "


id: 710c31cfed4250691c4e910291ea147d
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 17149
content:
"Figure  1.22 |  Structure of CMIP6, the 6th phase of the Coupled Model \r\nIntercomparison Project. The centre shows the common DECK (Diagnostic, \r\nEvaluation and Characterization of Klima) and historical experiments that all \r\nparticipating models must perform. The outer circles show the topics covered by the \r\nendorsed (red) and other MIPs (orange). See Table 1.3 for explanation of the MIP \r\nacronyms. Figure is adapted from Eyring et al. (2016)."


id: ee6690d8e63bd299db7a1b87301465a6
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"CMIP (CMIP6; Eyring et al., 2016). The CMIP6 experiment design is \r\nsomewhat different from previous phases. It now consists of a limited \r\nset of DECK (Diagnostic, Evaluation and Characterization of Klima) \r\nsimulations and an historical simulation that must be performed by \r\nall participating models, as well as a wide range of CMIP6-Endorsed \r\nmodel intercomparison projects (MIPs) covering specialized topics \r\n(Figure 1.22; Eyring et al., 2016). Each MIP activity consists of a series \r\nof model experiments, documented in the literature (Table 1.3) and in \r\nan online database (es-doc.org; Annex II; Pascoe et al., 2020)."


id: 78b42cc95876c57da4f9335690e46f26
created_at: 2023-04-19 13:21:32
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content:
"simulations on common domains and under common experimental \r\nconditions in a  similar way to the CMIP effort. Dynamical and \r\nstatistical downscaling techniques can provide higher-resolution \r\nclimate information than is available directly from global climate \r\nmodels (Section  10.3). These techniques require evaluation and \r\nquantification of their performance before they can be considered \r\nappropriate as usable regional climate information or be used in \r\nsupport of climate services. CORDEX simulations have been provided \r\nby a range of regional downscaling models for 14 regions, together \r\ncovering much of the globe (Figure Atlas.7), and they are used \r\nextensively in the AR6 WGI Atlas (Atlas.1.4 and Annex II)."


id: 31dc307f0b3af519c83a2902d3a0924a
created_at: 2023-04-19 13:21:32
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"In support of AR6, CORDEX has undertaken a  new experiment \r\n(CORDEX-CORE) in which regional climate models downscale \r\na common set of global model simulations, performed at a coarser \r\nresolution, to a spatial resolution spanning from 12-25 km over most \r\nof the CORDEX domains (Box Atlas.1). CORDEX-CORE represents \r\nan improved level of coordinated intercomparison of downscaling \r\nmodels (Remedio et al., 2019)."


id: 7668a6376e410cbcd52cb1693dd6d486
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"For the first time in CMIP, a  range of comprehensive evaluation \r\ntools are now available that can run alongside the commonly used \r\ndistributed data platform - Earth System Grid Federation (ESGF; see \r\nAnnex II) - to produce comprehensive results as soon as the model \r\noutput is published to the CMIP archive."


id: 972b388f1df628994e010bfda35746e0
created_at: 2023-04-19 13:21:32
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content:
"For instance, the Earth System Model Evaluation Tool (ESMValTool; \r\nEyring et al., 2020; Lauer et al., 2020; Righi et al., 2020) is used by \r\na number of chapters. It is an open-source community software tool \r\nthat includes a large variety of diagnostics and performance metrics \r\nrelevant for coupled Earth system processes, such as for the mean, \r\nvariability and trends, and it can also examine emergent constraints \r\n(Section 1.5.4.7). ESMValTool also includes routines provided by the \r\nWMO Expert Team on Climate Change Detection and Indices for the \r\nevaluation of extreme events (Min et al., 2011; Sillmann et al., 2013) \r\nand diagnostics for key processes and variability. Another example \r\nof an evaluation tool is the CLIVAR 2020 ENSO metrics package \r\n(Planton et al., 2021)."


id: c07202807dfbd66a906e5d705b14141f
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"Beyond the DECK and the historical simulations, the CMIP6-Endorsed \r\nMIPs aim to investigate how models respond to specific forcings, \r\ntheir potential systematic biases, their variability, and their responses \r\nto detailed future scenarios such as the Shared Socio-economic \r\nPathways (SSPs; Section 1.6). Table 1.3 lists the 23 CMIP6-Endorsed \r\nMIPs and key references. Results from a range of these MIPs, and \r\nmany others outside of the most recent CMIP6 cycle, will be assessed \r\nin the following chapters (also shown in Table  1.3). References to \r\nall the CMIP6 datasets used in the report are found in Annex II, \r\nTable AII.10."


id: a68942905c8de564928f537cc2e09135
created_at: 2023-04-19 13:21:32
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content:
"These tools are used in several chapters of this report for the creation \r\nof the figures that show CMIP results. Together with the Interactive \r\nAtlas, they allow for traceability of key results, and an additional level \r\nof quality control on whether published figures can be reproduced. \r\nIt also provides the capability to update published figures with, as \r\nmuch as possible, the same set of models in all figures, and to assess \r\nmodel improvements across different phases of CMIP (Section 3.8.2)."


id: d5f67244f8eaf7c8b518d7144fb8c29
created_at: 2023-04-19 13:21:32
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content:
"These new developments are facilitated by the definition of common \r\nformats for CMIP model output (Balaji et al., 2018) and the availability \r\nof reanalyses and observations in the same format as CMIP output \r\n(obs4MIPs; Ferraro et al., 2015). The tools are also used to support \r\nroutine evaluation at individual model centres and simplify the \r\nassessment of improvements in individual models or generations \r\nof model ensembles (Eyring et al., 2019). Note, however, that while \r\ntools such as ESMValTool can produce an estimate of overall model "


id: fbf36c404be2c3b63a2cc0c3a328910
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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content:
"The Coordinated Regional Downscaling Experiment (CORDEX; \r\nGutowski Jr. et al., 2016) is an intercomparison project for regional \r\nmodels and statistical downscaling techniques, coordinating "


id: 68dd9531961266eb50bf0aa23a2e10b9
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 15718
content:
"Model Intercomparison Project Observational Simulator (COSP; \r\nSwales et al., 2018) has been released which makes use of a collection \r\nof observation proxies or satellite simulators. Related approaches \r\nin this rapidly evolving field include simulators for Arctic Ocean \r\nobservations (Burgard et al., 2020) and measurements of aerosol \r\nobservations along aircraft trajectories (Watson-Parris et al., 2019)."


id: 8180785925a4dfdececaf673071db4df
created_at: 2023-04-19 13:21:32
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"performance, dedicated model evaluation still needs to be performed \r\nwhen analysing projections for a particular purpose, such as assessing \r\nchanging hazards in a given region. Such evaluation is discussed in \r\nthe next section, and in greater detail in later chapters of this Report."


id: 8e91ab1f19864213e53aa2cbfa2bd26b
created_at: 2023-04-19 13:21:32
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content:
"In this Report, model evaluation is performed in the individual \r\nchapters, rather than in a separate chapter as was the case for AR5. \r\nThis applies to the model types discussed above, and also to dedicated \r\nmodels of subsystems that are not (or not yet) part of usual climate \r\nmodels, for example, glacier or ice-sheet models (Annex II). Further \r\ndiscussions are found in Chapter 3 (attribution), Chapter 5 (carbon \r\ncycle), Chapter 6 (short-lived climate forcers), Chapter 8 (water cycle), \r\nChapter  9  (ocean, cryosphere and sea level), Chapter  10 (regional \r\nscale information) and the Atlas (regional models)."


id: baabdfe80ed51e4df4cf9a052123098a
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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index: climate_gpt_v2
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content:
"Techniques used for evaluating process-based climate models against \r\nobservations were assessed in AR5 (Flato et al., 2013), and have \r\nprogressed rapidly since (Eyring et al., 2019). The most widely used \r\ntechnique is to compare climatologies (long-term averages of specific \r\nclimate variables) or time series of simulated (process-based) model \r\noutput with observations, considering the observational uncertainty. \r\nA further approach is to compare the results of process-based models \r\nwith those from statistical models. In addition to a comparison of \r\nclimatological means, trends and variability, AR5 already made \r\nuse of a  large set of performance metrics for a  quantitative \r\nevaluation of the models."


id: b3e48de4f10b06bdf3ceb8455813b62b
created_at: 2023-04-19 13:21:32
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content:
"An emergent constraint is the relationship between an uncertain \r\naspect of future climate change and an observable feature of the \r\nEarth System, evident across an ensemble of models (Allen and \r\nIngram, 2002; Mystakidis et al., 2016; Wenzel et al., 2016; Hall et al., \r\n2019; Winkler et al., 2019). Complex Earth system models (ESMs) \r\nsimulate variations on time scales from hours to centuries, telling \r\nus how aspects of the current climate relate to its sensitivity to \r\nanthropogenic forcing. Where an ensemble of different ESMs \r\ndisplays a  relationship between a  short-term observable variation \r\nand a  longer-term sensitivity, an observation of the short-term "


id: 72bd4e6da90a7b452913b6a02565e547
created_at: 2023-04-19 13:21:32
updated_at: 2023-04-19 13:21:32
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vector_id: 17429
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"Since AR5, a  range of studies has investigated model agreement \r\nwith observations well beyond large-scale mean climate properties \r\n(e.g., Bellenger et al., 2014; Covey et al., 2016; Pendergrass and Deser, \r\n2017; Goelzer et al., 2018; Beusch et al., 2020a), providing information \r\non the performance of recent model simulations across multiple \r\nvariables and components of the Earth system (e.g.,  Anav et al., \r\n2013; Guan and Waliser, 2017). Based on such studies, this Report \r\nassesses model improvements across different CMIP DECK, CMIP6 \r\nhistorical and CMIP6-Endorsed MIP simulations, and of differences \r\nin model performance between different classes of models, such as \r\nhigh- versus low-resolution models (see e.g., Section 3.8.2)."


