# document

id: f23f94fb32c0641b7e0dd750e07c2450
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 40016
content:
"[...] extreme event of strengthening trade winds are potentially a result \r of natural internal variability, a role of anthropogenic contribution \r has not been ruled out. Nevertheless, the CMIP5 models indicate no \r general change in trends into the future (Figure 6.7), giving more \r weight to natural internal variability as an explanation. "


id: 1c046a85b77a45e5f36e534640ab5eb5
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 2114
content:
"In the Indian Ocean, water exits the Indonesian Seas mostly \r flowing westward along with the South Equatorial Current, and \r some supplying the Leeuwin Current. The South Equatorial Current \r feeds the heat and biogeochemical signatures from the Indian \r Ocean into the Agulhas Current, which transports it further into the \r Atlantic Ocean. Observations of Mozambique Channel inflow from \r 2003-2012 measured a mean transport of 16.7 x 106\r  m3 s-1 with \r a maximum in austral winter, and IOD related interannual variability \r of 8.9 x 106\r  m3 s-1 (Ridderinkhof et al. 2010). A multidecadal proxy, \r from three years of mooring data and satellite altimetry, suggests \r that the Agulhas Current has been broadening since the early 1990s \r due to an increase in eddy kinetic energy (Beal and Elipot, 2016). \r Numerical model experiments suggest an intensification of the \r Agulhas leakage since the 1960s, which has contributed to the \r [...]"


id: 540ca8bc532ff6d01c9c9090e7971f87
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 12060
content:
"[...] warming in the upper 300 m of the tropical Atlantic Ocean (Lubbecke \r et al. 2015). Agulhas leakage is found to covary with the AMOC on \r decadal and multi-decadal timescales and has likely contributed \r to the AMOC slowdown (Biastoch et  al. 2015; Kelly et  al. 2016). \r Meanwhile, climate projections indicate that Agulhas leakage is likely\r to strengthen and may partially compensate the AMOC slowdown \r projected by coarse-resolution climate models (Loveday et al. 2015)."


id: 55ccd85d617f6e1ad4456b7d56f4dc96
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 12366
content:
"Among the number of potential causes of this decadal variability in \r surface global temperature, a prolonged negative phase of the Pacific \r Decadal Oscillation/Interdecadal Pacific Oscillation (PDO/IPO) was \r suggested as a contributor. Because of the magnitude and duration of \r this Pacific-centred variability (Figure 6.7), it is identified as an extreme \r decadal climate event. One line of research has explored the role of \r the warm tropical Atlantic decadal variability in forcing the trade wind \r trends and associated cooling Pacific SST trends (Kucharski et al. 2011; \r McGregor et al. 2014; Li et al. 2016b). It appears that climate models may \r misrepresent this link due to tropical Atlantic biases (Kajtar et al. 2018; \r McGregor et al. 2018) and thus potentially underestimate global mean \r temperature decadal variability. Nevertheless, there is no indication \r that such an underestimation of global temperature variability is \r [...]"


id: b87250edbe819960a4a5ceb00d78176a
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 29660
content:
"[...] evident in the models (Flato et al. 2013; Marotzke and Forster, 2015). \r The impact of modes of natural variability on global mean temperature \r decadal variability remains an active area of research."


id: 9ed5f5b55e1da5eca118419908251588
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 25165
content:
"The Pacific cooling pattern may have significant impacts on \r terrestrial carbon uptake via teleconnections. The reduced ecosystem \r respiration due to the smaller warming over land has significantly \r accelerated the net biome productivity and therefore increased \r the terrestrial carbon sink (Ballantyne et al. 2017) and paused the \r growth rate of atmospheric CO2 despite increasing anthropogenic \r carbon emissions (Keenan et al. 2016). During the 2000s, the global \r ocean carbon sink has also strengthened (Fay and McKinley, 2013; \r Landschutzer et al. 2014; Majkut et al. 2014; Landschutzer et al. 2015; \r Munro et al. 2015), reversing a trend of stagnant or declining carbon \r uptake during the 1990s. It has been suggested that the upper ocean \r overturning circulation has weakened during the 2000s thereby \r decreasing the outgassing of natural CO2, especially in the Southern \r Ocean (Landschutzer et  al. 2015), and enhanced the global ocean \r [...]"


id: c3f0ba3c85919cfad0a1d280f6f4ace9
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 31753
content:
"[...] CO2 sink (DeVries et al. 2017). How this is connected to the global \r warming slowdown is currently unclear. "


id: ffe0f7ff4356bb537e9c990712c8f729
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 42413
content:
"During the last interglacial warm period, palaeo-data suggest that the \r AMOC may have been weaker (Govin et al. 2012) and also show proxy \r record evidences of instabilities (Galaasen et al. 2014). Based on an \r AMOC reconstruction using SST fingerprints, it has been suggested \r that the AMOC may have experienced around 3 +- 1 x 106\r  m3 s-1\r of weakening (about 15% decrease) since the mid-20th century \r (Caesar et al. 2018). Such a trend in AMOC was also suspected in \r a former study using Principal Component Analysis of SST (Dima and \r Lohmann, 2010). Palaeo-proxies also highlight that the historical era \r may exhibit an unprecedented low AMOC over the last 1,600 years \r (Sherwood et  al. 2011; Rahmstorf et  al. 2015; Thibodeau et  al. \r 2018; Thornalley et al. 2018). Nevertheless, these proxy records are \r indirect measurements of the AMOC so that considerable uncertainty \r remains concerning these results. Moreover, the exact mechanisms \r [...]"


id: 922573d83e7174ad984074e0cfcc727
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
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content:
"[...] to explain such a long-term weakening are not fully understood \r and some reconstructions show a weakening starting very early \r in the historical era, when the level of anthropogenic perturbation \r and warming was very low. Climate model simulations (Figure 6.8) \r do show a weakening over the historical era, but this weakening \r is mainly occurring over the recent decades. Climate projections \r exhibit a weakening of around 1.4 +- 1.4 x 106\r  m3 s-1 for present \r day (2006-2015) minus pre-industrial (1850-1900), highlighting \r that anthropogenic warming may have already forced an AMOC \r weakening. Nevertheless, no proper detection and attribution of the \r on-going changes has been led so far due to still limited observational \r evidences. Thus, we conclude that there is medium confidence that the \r AMOC has weakened over the historical era but there is insufficient \r evidence to quantify a likely range of the magnitude of the change."


id: cbdcc5d40b760681d0be70bd4dc3d5f9
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 33192
content:
"Considerable effort has been dedicated in the last decades to \r improve the observation system of the large-scale ocean circulation \r (e.g., Argo and its array of about 3,800 free-drifting profiling floats), \r including the AMOC through dedicated large-scale observing arrays \r (at 16oN (Send et  al. 2011) and 26oN (McCarthy et  al. 2015b), in \r the subpolar gyre (SPG) (Lozier et al. 2017), between Portugal and \r the tip of Greenland (Mercier et al. 2015), at 34.5oS (Meinen et al. \r 2013), among others). The strength of the AMOC at 26oN has been \r continuously estimated since 2004 with an annual mean estimate \r of 17 +- 1.9 x 106\r  m3 s-1 over the 2004-2017 period (Smeed \r et al. 2018). The AMOC at 26oN has been 2.7 x 106\r  m3 s-1 weaker \r in 2008-2017 than in the first four years of measurement (Smeed \r et al. 2018). However, the record is not yet long enough to determine \r if there is a long-term decline of the AMOC. McCarthy et al. (2012) \r [...]"


id: 5d1103ced36d7e085c6737249a14fa17
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 13641
content:
"[...] reported a 30% reduction in the AMOC in 2009-2010, followed by \r a weaker minimum a year later. Analysis of forced ocean models \r suggests such events may occur once every two or three decades "


id: 317c34c2c231d5c18268144f9c31f9e5
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 5947
content:
"Evaluation of AMOC variations in the CMIP5 database has been \r further analysed in this report (Figure 6.8) using almost twice as \r many models as in AR5 (IPCC, 2013). The AR5 assessment of a very \r unlikely AMOC collapse has been confirmed, although one model \r (FGOALS-s2) does show such a collapse (e.g., decrease larger than \r 80% relative to present day) before the end of the century for RCP8.5 \r scenario (Figure 6.8). Now based on up to 27 model simulations, the \r decrease of the AMOC is assessed to be of -2.1 +- 2.6 x 106 m3\r  s-1\r (-11 +- 14%, likely range) in 2081-2100 relative to present day \r (2006-2015) for RCP2.6 scenario and  -5.5  +-  2.7 x 106\r  m3 s-1\r (-32 +-  14%) for RCP8.5 scenario, in line with a process-based \r probabilistic assessment (Schleussner et al. 2014). Furthermore, the \r uncertainty in AMOC changes has been shown to be mainly related \r to the spread in model responses rather than scenarios (RCP4.5 and \r [...]"


id: 27255119d252ff10f2c750be3f405
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 4048
content:
"[...] RCP8.5) or internal variability uncertainty (Reintges et  al. 2017). \r This behaviour is very different from the uncertainty in global SST "


id: edd5cfb456da71ee3b09eadf735313af
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 39205
content:
"Concerning the question of the reversibility of the AMOC, a few \r ramp-up/ramp-down simulations have been performed to evaluate \r it for transient time scales (a few centuries, while millennia will be \r necessary for a full steady state). Results usually show a reversibility \r of the AMOC (Jackson et al. 2014; Sgubin et al. 2015) although the \r timing and amplitude is highly model dependent (Palter et al. 2018). \r A hysteresis behaviour of the AMOC in response to freshwater \r release has been found in a few climate models (Hawkins \r et al. 2011; Jackson et al. 2017) even at the eddy resolving resolution \r (Mecking et al. 2016; Jackson and Wood, 2018). This is in line with \r the possibility of tipping point in the AMOC system. The biases of \r present-day models in representing the transport at 30oS (Deshayes \r et  al. 2013; Liu et  al. 2017a; Mecking et  al. 2017) or the salinity \r in the tropical era (Liu  et  al. 2014b) may considerably affect the \r [...]"


id: 3939c9d62d318d6b21d5c2d6a55bf6ee
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 7278
content:
"[...] sensitivity of the models to freshwater release, but more on the \r multi-centennial time scale. "


id: 97542876ff3eeca40b9dc96e004b6724
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 23825
content:
"The different potential impacts of large changes in the Atlantic \r Ocean circulation are summarised in Figure 6.10. Based on variability \r analysis, it has been shown that a decrease in the AMOC strength has \r impacts on storm track position and intensity in the North Atlantic \r (Gastineau et al. 2016), with a potential increase in the number of \r winter storms hitting Europe (Woollings et al. 2012; Jackson et al. \r 2015), although some uncertainty remains with respect to the models \r considered (Peings et al. 2016). The influence on the Arctic sea ice \r cover has also been evidenced at the decadal scale, with a  lower \r AMOC limiting the retreat of Arctic sea ice (Yeager et  al. 2015; \r Delworth and Zeng, 2016). The climatic impacts could be substantial \r over Europe (Jackson et al. 2015), where an AMOC weakening can \r lead to high pressure over the British Isles in summer (Haarsma et al. \r 2015), reminiscent of a negative summer NAO, inducing an increase \r [...]"


id: b17d5debc67f9025b0106ae4436446ee
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 28449
content:
"[...] in precipitation in Northern Europe and a decrease in Southern \r Europe. In winter, the response of atmospheric circulation may \r help to reduce the cooling signature over Europe (Yamamoto and \r Palter, 2016), notably through an enhancement of warming maritime \r effect due to a stronger storm track (Jackson et  al. 2015), driving \r more powerful storms in the North Atlantic (Hansen et al. 2016). The \r observed extreme low AMOC in 2009-2010, which was followed by \r a reduction in ocean heat content to the north (Cunningham et al. \r 2013), has been possibly implicated in cold European weather events \r in winter 2009-2010 and December 2010 (Buchan et  al. 2014) \r although a robust attribution is missing. In summer, cold anomalies \r in the SPG, like the one occurring during the so-called cold blob in \r 2015 (Josey et al. 2018), have been suspected to potentially enhance \r the probability of heatwaves over Europe in summer (Duchez et al. \r [...]"


id: 979988bf907d74ad2a7c540bb292a503
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 23886
content:
"[...] 2016). Nevertheless, considerable uncertainties remain with regard \r to this aspect due to the lack of historical observations before 2004 \r and due to poor model resolution of small-scale processes related \r to frontal dynamics around the Gulf Stream region (Vanniere et al. \r 2017). In addition, oceanic changes in the Gulf Stream region may \r occur in line with AMOC weakening (Saba et al. 2016) with potential \r rapid warming due to a northward shift of the Gulf Stream. However, \r these changes are largely underestimated in coarse resolution \r models (Saba et al. 2016) . In North America, a negative phase of the \r AMV, reminiscent of a weakening of the AMOC, lowers agricultural \r production in a few Mexican coastal states (Azuz-Adeath et al. 2019).\r Changes in ocean circulation can also strongly impact sea level \r in the regions bordering the North Atlantic (McCarthy et  al. \r 2015a; Palter et al. 2018). A collapse of the AMOC or of the SPG \r [...]"


id: 7ea58f05e43ab6315c17dde3e98d74d0
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 19439
content:
"associated expansion of the cryosphere around the North Atlantic, \r which increases surface albedo (Rugenstein et  al. 2013; Winton \r et  al.  2013), as well as cloud cover variations and modifications \r in water vapour content (Trossman et al. 2016). As the uptake of \r excess heat occurs preferentially in regions with delayed warming \r (Winton et  al. 2013; Frolicher et  al. 2015; Armour et  al. 2016), \r a potential large reduction of the AMOC may shift the uptake of \r excess heat from the low to the high latitudes (Rugenstein et al. \r 2013; Winton et al. 2013), where the atmosphere is more sensitive \r to external forcing (Winton et al. 2010; Rose et al. 2014; Rose and \r Rayborn, 2016; Rugenstein et al. 2016). A decrease in AMOC may \r also decrease the subduction of anthropogenic carbon to deeper \r waters (Zickfeld et al. 2008; Winton et al. 2013; Randerson et al. \r 2015; Rhein et al. 2017). A potential impact of methane emissions \r [...]"


id: b332fcbf0c42d8308929b1319b75ff12
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
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vector_id: 28769
content:
"[...] has also been highlighted for past Heinrich events during which \r massive icebergs discharge in the North Atlantic may have led to \r large AMOC disruptions. Large increases (>100 ppb) in methane \r production have been associated with these events (Rhodes et al. \r 2015) potentially due to increased wetland production in the SH, \r related to teleconnections of the North Atlantic with tropical area \r (Ringeval et al. 2013; Zurcher et al. 2013). All these different effects \r indicate a potentially positive feedback of the AMOC on the carbon \r cycle (Parsons et  al. 2014), although other elements from the \r terrestrial biosphere may limit its strength or even reverse its sign \r (Bozbiyik et al. 2011). "


id: 8c9a7d72ec18fa563b91c6c617afe6b0
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 21924
content:
"Changes in Atlantic Ocean circulation can also strongly impact \r marine life and can be seen at all levels of different ecosystems. \r For instance, changes in the abundance and distribution of \r species in response to circulation changes in the SPG have been \r documented amongst plankton (Hatun et  al. 2009), fish (Payne \r et  al. 2012; Miesner and Payne, 2018), seabirds (Descamps et  al. \r 2013) and top predators such as tuna, billfish and pilot whales \r (Hatun et al. 2009; MacKenzie et al. 2014). Nutrient concentrations \r in the northeast Atlantic have also been shown to be limited by \r the recent weakening of the SPG, with concomitant ecosystem \r impacts (Johnson et  al. 2013; Hatun et  al. 2016). The influence \r of SPG circulation also extends to ecosystems beyond from the \r immediate area, and has a clear impact on the productivity of cod \r (Gadus morhua) in the Barents Sea, for example (Arthun et al. 2017; \r Arthun et al. 2018). On a broader scale, changes in the AMOC are an \r [...]"


id: 1f2216dca95fedb4aef3ac213e7a291
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 2685
content:
"[...] important driver of AMV, which has also been linked to substantial \r changes in marine ecosystems on both sides of the North Atlantic \r (Alheit et al. 2014; Nye et al. 2014). Recent AMOC weakening is also \r suspected to explain large marine deoxygenation in the northwest \r coastal Atlantic (Claret et al. 2018). In addition, a recent study using \r a marine productivity proxy from Greenland ice cores suggest that \r net primary productivity has decreased by 10 +- 7% in the subarctic \r Atlantic over the past two centuries possibly related to changes \r in AMOC (Osman et al. 2019). Finally, a model study investigated \r the impact of mitigation by reversing the forcing from a RCP8.5 \r scenario from 2100 and found that global marine net productivity \r may recover very rapidly and even overshoot contemporary values \r at the end of the reversal, highlighting the potential benefit of \r mitigation (John et al. 2015)."


id: a84302205048c6d3d01f0c985f546c37
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 26823
content:
"Decadal prediction systems can help fill this gap. Skilful prediction of \r AMOC variation has been demonstrated on the multi-annual scale \r (Matei et  al. 2012) and retrospective prediction experiments have \r demonstrated that the large changes in the SPG seen in the mid-1990s \r could have been foreseen several years in advance (Wouters et  al. \r 2013; Msadek et al. 2014). The World Climate Research Programme's \r grand challenge of launching decadal predictions every year (Kushnir \r et al. 2019) is an important step towards anticipating rapid changes \r in the near term and can drive decadal-scale climate services. For \r example, a few studies have already shown that small variations \r anticipated by decadal predictions (e.g., Sheen et  al. 2017) can be \r useful for the development of climate services, notably for agriculture \r in south and east Africa (Nyamwanza et al. 2017). Decadal predictions \r also match the decision making time horizons of many users of the \r [...]"


id: c41107b7657daa012ff797e7f9fe84e5
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 31777
content:
"[...] ocean (Tommasi et al. 2017b) and are expected to play an increasingly \r important role in this sector in the future (Payne et al. 2017)."


id: a196c79e0aee53dd0180e04390e8093f
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 25646
content:
"Over the last decade, several efforts have been made to address \r long-term shoreline change driven by the cascading impact of SLR, \r waves and MSL. Ranasinghe et al. (2012) presented the Probabilistic \r Coastline Recession model, which provides probabilistic estimates of \r coastline recession in response to both storms and SLR in the 21st \r century. Dune recession is estimated for each storm considering \r the recovery between storms, which is obtained empirically. More \r recently, Toimil et  al. (2017) developed a methodology to address \r shoreline change over this century due to the action of waves, storm \r surges, astronomical tides in combination with SLR. The methodology \r considers the generation of thousands of multi-variate hourly time \r series of waves and storm surges to reconstruct future shoreline \r evolution probabilistically, which enables estimates of extreme \r recessions and long-term coastline change to be obtained. The model \r [...]"


id: 434f5604850be1cc18ae858814cd4f1c
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 9054
content:
"[...] proposed by Vitousek et al. (2017) integrates longshore and cross\u0002shore transport induced by GCM-projected waves and SLR, which \r allows it to be applied to both long and pocket sandy beaches. The \r analysis provides only one instance of what coastline change over \r the 21st century may be."


id: e17d0b6c76563af71b56890ebe99a193
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 36941
content:
"Compound events and cascading impacts are examples of deep \r uncertainty because data deficiency often prevents the assessment \r of probabilities and consequences of the risks from compound \r events. Furthermore, climate drivers that contribute to compound \r events could cross tipping points in the future (e.g., Cai et al. 2016; \r Cross-Chapter Box 4 in Chapter 1). Concepts and methods for \r addressing compound events and cascading impacts have a solid \r foundation in disaster risk reduction frameworks (Scolobig, 2017) \r where they may be assessed with scenarios, risk mapping, and \r participatory governance (Marzocchi et  al. 2012; Komendantova \r et  al. 2014). However, these approaches have tended to not \r consider the effects of climate change, rather considering hazards \r and vulnerability as stationary entities (Gallina et al. 2016). Trends \r in geophysical and meteorological extreme events and their \r interaction with more complex social, economic and environmental \r [...]"


id: af26b77a2a3ed35f1a50de7213f34b1c
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 28059
content:
"[...] vulnerabilities overwhelm existing governance and institutional \r capacities (Shimizu and Clark, 2015) because of the aggregated \r cascading impacts. "


id: 3e250a276db8e11f713d77be7417ed55
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 8107
content:
"Understanding regions where changes in the climate system could \r increase the likelihood or severity of multiple hazards is relevant \r to understanding compound events (Figure 6.1). Several recent \r studies have highlighted coastal regions that are becoming more \r susceptible to multiple hazards from changes in regional climate. \r Warming and poleward expansion of the warm western boundary \r current regions (WBCs; Yang et al. 2016a) together with intensified \r cyclogenesis in these WBC regions; the Gulf Stream (Booth et al. \r 2012), the Kuroshio (Hirata et  al. 2016) and the East Australian \r Current (EAC; Pepler et  al. 2016a) can increase the likelihood of \r multiple hazards. These include increased rates of SLR (Brunnabend \r et al. 2017; Zhang et al. 2017b) together with increases in severe \r rainfall, storm surges and associated flooding (Thompson et al. 2013; \r Oey and Chou, 2016; Pepler et al. 2016a). WBCs have undergone an \r [...]"


id: 72a376452e910348bf99555f77950c34
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 17411
content:
"[...] intensification and poleward expansion in all but the Gulf Stream \r where the weakening of the AMOC cancelled this effect (Seager \r and Simpson, 2016; Yang et al. 2016a). "


id: 42d47bf7e75fca0ed4f1178242deb0a2
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 8949
content:
"The management of compound events and cascading impacts in \r the context of governance poses challenges, partly because it is \r place dependent and heavily influenced by local parameters such \r as hazard experience and cultural values. Moreover, in some cases, \r people perceive that their community or country is less affected than \r others, leading to a 'spatial optimism bias' that delays or reduces \r the scope of actions (Nunn et al. 2016). In other cases it is unclear \r who will take responsibility when compound events and cascading \r impacts occur (Scolobig, 2017), although for some compound risks \r (e.g., na-tech disasters - when natural hazards trigger technological \r disasters), the private sector cooperates with governments to \r manage and respond to risks (Krausmann et al. 2017). Considerable \r variations exist among and inside countries. The level of engagement \r depends on the process of cascading impacts and the role of \r [...]"


id: 8f484f732634e4ed9523105c8752445d
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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"[...] governance arrangement at the country level (Lawrence et  al. \r 2018), countries' capacity to develop integrated risk and disaster \r frameworks and regulations, viable multi-stakeholder and public\u0002private partnership in the case of multiple technological and natural \r hazards (Gerkensmeier and Ratter, 2018), the initiatives of local \r governments to exercise compound risk operations, and experience \r in interagency cooperation (Scolobig, 2017). The importance of local \r knowledge and traditional practices in disaster risk prevention and \r reduction is widely recognised (Hiwasaki et al. 2014; Hilhorst et al. \r 2015; Audefroy and Sanchez, 2017) (high confidence). The need to \r strengthen DRM is evident and can be improved and communicated \r effectively by integrating local knowledge such as Inuit's indigenous \r knowledge and local knowledge in Alaska (Pearce et al. 2015; Cross\u0002Chapter Box  3 in Chapter 1) since it is easier for communities to \r [...]"


id: 3aeea1ffb9ee05c7a796e1bb803e5593
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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"Impacts of compound events also have significant multi-effects in \r the societal system. Cascading impacts are particularly driven by \r the loss or (temporary) disruption of critical infrastructure (Pescaroli \r and Alexander, 2018), such as communications, transport, and \r power supply, on housing, dams and flood protection; as well as \r health provision. Repeated extreme and compound events are \r leading to critical transitions in social systems (Kopp et  al. 2016) \r which may cause the disruption of (local) communities, creating \r cascading impacts consisting of short-term impacts as well as long\u0002lasting economic effects, and in some cases migration. When the \r responses of the economic sector to short term weather variations \r are applied to long term-climate projections, risks associated with \r climate change on different sectors are projected to result in an \r average 1.2% of decrease of US GDP per degree Celsius of warming. \r [...]"


id: a740e5591c80173770d50b21af32f7fa
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"[...] Furthermore, broad geographical discrepancies generate a  large \r transfer of value northwards and westwards with the expected \r consequence of increased economic inequality (Hsiang et al. 2017). \r The severity and intensity of the cascading impacts also depend \r on the affected societies' vulnerability and resilience. For example, \r the intensity and influence of compound events are dependent \r on the size and scale of the affected society and the percentage \r of economy or GDP impacted (Handmer et al. 2012 in IPCC SREX). \r Smaller countries and especially small islands face the challenge of \r being unable to 'hedge' the risk through geographical redistribution \r (see Cross-Chapter Box 9). "


id: 43d180f139e72d1a5bead4871e4f0ec6
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
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content:
"Impacts from the natural system can descend into a cascade of \r disasters. For example, in 2005, Hurricane Katrina led to heavy \r flooding in the coastal area, dike breaches, emergency response \r failures, chaos in evacuation (traffic jams) and social disruption. \r Flooding in Thailand in 2011 led to the closure of many factories \r which not only impacted on the country's economy but impaired \r the global automobile and electronic industry (Kreibich et  al. \r 2014). Female-owned establishments are more challenged with \r failures than businesses owned by men due to less experience, \r shorter duration and smaller size of businesses (Haynes et al. 2011; \r Marshall et al. 2015). The impact of compound events on ecosystems \r can also, in the long run, have devastating impacts on societal \r systems, for example, impacts from tropical storms can lead to coral \r degradation, which leads to increased wave impact and subsequent \r [...]"


id: 10d7d135fc8425fe17198964ce1d4e58
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 152
content:
"Cai et  al. (2016) consider five interacting, stochastic, potential \r climate tipping points: reorganisation of the AMOC; disintegration \r of the GIS; collapse of the WAIS; dieback of the Amazon Rain Forest; \r and shift to a more persistent El Nino regime. The deep uncertainties \r associated with the likelihood of each of these tipping points and the \r dependence of them on the state of the others is addressed through \r expert elicitation. There is limited evidence, but high agreement that \r present costs of carbon are clearly underestimated. Double (Lemoine \r and Traeger, 2016), triple (Ceronsky et al. 2011), to eightfold (Cai et al. \r 2016) increase of the carbon price are suggested, depending on the \r working hypothesis. Cai et al. (2016) indicate that with the prospect \r of multiple interacting tipping points, the present social cost of \r carbon increases from 15 to 116 USD per tonne of CO2, and conclude \r that stringent efforts are needed to reduce CO2 emission if these \r [...]"


id: 53ebe4ea5855d149669a2639c3024137
created_at: 2023-04-19 13:22:32
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content:
"The compound events caused many impacts on natural systems, agriculture, infrastructure and communities. Additional emergency \r services from outside the state were needed to deal with the fires. The MHW caused disease outbreaks in farmed shellfish, mortality \r in wild shellfish and species found further south than previously recorded. The energy sector experienced a severe cascade of impacts \r due to climate stressors and system inter-dependencies. The combination of drought, fires, floods and MHW reduced output from the\r agriculture, forestry, fishing and energy sectors and reduced the State of Tasmania gross state product (GSP) to 1.3%, well below the \r anticipated growth of 2.5%. To address the energy shortages, Tasmania's four largest industrial energy users, responsible for 60% \r of Tasmania's electricity usage, agreed to a series of voluntary load reductions of up to 100 MW on a sustained basis, contributing \r [...]"


id: a193f64cce5846ad238fcc96403103aa
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content:
"[...] to a 1.7% reduction in the output of the manufacturing sector (Eslake, 2016). The total cost of the fires and floods was assessed at "


id: dd7d5bbb2bc37b0a55b2fa8381423c01
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 36235
content:
"The Coral Triangle is under the combined threats of mean warming, ocean acidification, temperature and sea level \r variability (often associated with both El Nino and La Nina), coastal development and overfishing, leading to reduced \r ecosystem services and loss of biodiversity. The Coral Triangle covers 4 million square miles of ocean and coastal waters in \r Southeast Asia and the Pacific, in the area surrounding Indonesia, Malaysia, Papua New Guinea, the Philippines, Timor Leste and \r the Solomon Islands. It is the centre of the highest coastal marine biodiversity in the world due to its geological setting, physical \r environment, and an array of ecological and evolutionary processes which makes it a conservation priority. Together with mangroves \r and seagrass beds, the 605 species of corals including 15 regional endemics (Veron et al. 2011) provide ecosystem services to over 100 \r [...]"


id: a740f5dbe04ba0b902d022285b4dc0de
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"[...] million people from diverse and rich cultures, in particular for food, building materials and coastal protection. "


id: a3602f34efc834a38a5867cff4975de7
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 25951
content:
"Risks from compound events include increase in sea surface temperature (SST), SLR and increased human activities. The increasing trend \r in SSTs was estimated to be 0.1oC per decade between 1960 and 2007 (Kleypas et al. 2015) but increased to 0.2oC per decade from 1985 \r to 2006 (Penaflor et al. 2009), an estimation comparable with that in the South China Sea (Zuo et al. 2015). However, waters in \r the northern and eastern parts are warming faster than the rest of the region, and this variability is increased by local parameters \r linked to the complex bathymetry and oceanography of the region (Kleypas et al. 2015). Areas in the eastern part have experienced \r more thermal stress events, and these appear to be more likely during La Nina events, which generate heat pulses in the region,\r leading to bleaching events, some of them already triggered by El Nino Southern Oscillation (ENSO) events. In the Coral Triangle, El \r [...]"


id: 3dc4994ee4431e8b8935ee4b3038d1c4
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index: climate_gpt_v2
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content:
"[...] Nino events have a relative cooling effect, while La Nina events are accompanied by warming (Penaflor et al. 2009). The 1997-1998 \r El Nino was followed by a strong La Nina so that degree heating weeks (DHW) values in many parts of the region were greater than \r four, which caused widespread coral bleaching (DHW values greater than zero indicate there is thermal stress, while DHW values of \r 4 and greater indicate the existence of sufficient thermal stress to produce significant levels of coral bleaching; Kayanne, 2017). \r However, in Indonesia, the 2015-2016 El Nino event had impacted shallow water reefs well before high SSTs could trigger any coral \r bleaching (Ampou et al. 2017). Sea level in Indonesia had been at its lowest in the past 12 years following this El Nino event and \r this had affected corals living in shallow waters. Substantial mortality was likely caused by higher daily aerial exposure during \r [...]"


id: feefbde2c227c8a0cfec6c0b2b79a772
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content:
"[...] low tides and warmer SST associated with shallow waters. Another climate change-associated impact in the Coral Triangle is ocean \r acidification. Although less exposed than other reefs at higher latitudes (van Hooidonk et al. 2013), changes in pH are expected to \r affect coral calcification (DeCarlo et al. 2017), with an impact on coral reef fisheries (Speers et al. 2016)."


id: 5dec4f173f1b7da504fb4aeb438c1589
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"At least 68 people died from the direct effects of Harvey in Houston (Blake and Zelinsky, 2018). The Houston metropolitan area \r was devastated with the release of about 4.6 million pounds of contaminants from petrochemical plants and refineries. Irma caused \r 44 direct deaths (Cangialosi et al. 2018) and wiped out housing, schools, fisheries and livestock in Barbuda, Antigua, St. Martin \r and the British Virgin Islands (ACAPS et al. 2017). Maria caused 31 direct deaths in Dominica, two in Guadeloupe and around 65 \r in Puerto Rico (Pasch et al. 2018), and completely vacated Barbuda. Maria destroyed almost all power lines, buildings and 80% \r of crops in Puerto Rico (Rexach et al. 2017; Rossello, 2017), and damaged pharmaceutical industries that provided 33% of Puerto\r Rico's gross domestic product (GDP) causing shortages of some medical supplies in the USA (Sacks et al. 2018). The effects of Maria \r [...]"


id: f353a1ed8cd002a5e13da8832a7a788c
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content:
"[...] are expected to increase the poverty rate by 14% because of unemployment in tourism and agriculture sectors for more than a year \r in Dominica (The Government of the Commonwealth of Dominica, 2017), and resulted in outmigration to neighboring countries or \r the USA (ACAPS et al. 2017; Rossello, 2017). These economic and social consequences are indicative of the cascading impact of the \r 2017 hurricanes. The post-disaster reconstruction plan is to renovate telecommunications, develop climate resilient building plans and \r emergency coordination (Rossello, 2017; The Government of the Commonwealth of Dominica, 2017)."


id: e0ac0b30965ac4791fcf5efd432365b6
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 36782
content:
"(Weaver et  al. 2013). Examples include the inclusion of rapid SLR \r for assessing coastal impacts and adaptation options (Ranger et al. \r 2013; Haasnoot et  al. 2018; see Sections 6.4 and 6.7). Decision \r analysis frameworks such as 'Robust Decision Making', 'Decision \r Scaling', 'Assess Risk of Policy', 'Info-gap', 'Dynamic Adaptation \r Policy Pathways', 'Dynamic Adaptive Pathways Planning', 'Multi\u0002Criteria Decision Analysis', 'Real Options Analysis' and 'Context-First' \r accommodate a wide range of uncertainties with subsequent socio\u0002ecological impact (Weaver et al. 2013). The central question remains, \r however, how one can overcome path dependencies which may \r cause technical lock-ins in the current system. Monitoring systems \r of climatic and derived variables, in order to predict necessary shifts \r in adaptation policies are in development (Haasnoot et  al. 2015). \r However, these frameworks have so far been mostly applied to more \r [...]"


id: f39ef971f768de9411029d9d9c717e60
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
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content:
"Since AR5, growing discussions have advocated for transformative \r adaptation, implying that they support fundamental societal shift \r towards sustainability and climate-resilient development pathways \r (Moloney et  al. 2017; IPCC, 2018; Morchain, 2018). Successful \r adaptation to abrupt change and extreme events incorporates \r climate change concerns and the impact of climate extremes on \r vulnerable populations taking into account community participation \r and local knowledge (Tozier de la Poterie and Baudoin, 2015). These \r interventions reduce risk and enhance resilience, and contribute to \r the SDGs and social justice (Mal et al. 2018). Temporal scales denote \r before and after abrupt changes and extreme events (prevention and \r post-event response), long- and short-term adaptation measures, and \r the lag time between forecast, warning and event (Field et al. 2012; \r IPCC, 2012). Spatial dimensions include local risk management and \r [...]"


id: f4cbcd994d4ce1c8e332a480ee1b8572
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 40437
content:
"[...] adaptation as well as regional and international coordination to \r prepare for unexpected extremes tackling the impacts at multiple \r geographic scales (Devine-Wright, 2013; Barnett et  al. 2014; \r Lyth et al. 2016; Barange et al. 2018). "


id: beb53f0551d3121a062486150df10132
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 30817
content:
"Request for the use of 'actionable' information and communication \r based on climate science and modelling will increase (McNie, 2007; \r Moser and Boykoff, 2013). Such information can only be effective \r when it is perceived as 'credible, salient, and legitimate' (Paton, 2007; \r Paton, 2008; Dilling et al. 2015). Since SREX (IPCC, 2012), there is \r medium confidence that trust in the information and the institution \r (Hardin, 2002; Townley and Garfield, 2013) that governs extreme \r events and abrupt change (Malka et al. 2009; Birkmann et al. 2011; \r Schoenefeld and McCauley, 2016) is important. Trust in expert and \r scientific knowledge helps people make sense of climate change \r impact and engage with adaptation measures (Moser and Boykoff, \r 2013; Yeh, 2016). Without such knowledge, people have little \r recourse to believe and evaluate relevant information (Braten et al. \r 2011). Individuals who trust their government can be complacent and \r [...]"


id: cc3938ce9cc0396a42c7b70379c45ea
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content:
"[...] do not prepare for the consequences of extremes (Simpson, 2012; \r Edmondson and Levy, 2019), and shift the responsibility to the \r government (Edmondson and Levy, 2019). Familiarity with and \r information about hazards, community characteristics, as well as \r the relationship between people and government agencies influence \r the level of trust (Paton, 2007)."


id: dc91780e43cb1cd652f79f3d4205f191
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 36069
content:
"Decision making about abrupt change or extreme events is not \r autonomous; it is constrained by formal and informal institutional \r processes such as regulatory structures, property rights, as well as \r culture, traditions and social norms (Field et al. 2012; IPCC, 2012). \r Efforts in various countries and large cities to improve resilience \r and adaptation are growing, and these efforts are linked to a global \r network of research, information and best practices (e.g., Aerts et al. \r 2014). In both northern and southern high latitudes, extreme climatic \r conditions and remoteness from densely populated regions constrain \r human choices. The question is whether responses to extremes \r and abrupt changes require approaches that are different from \r the anticipatory management of adaptation to changes in climate \r and weather extremes. While there are several impact studies on \r extreme events and abrupt change, very few focus on the necessity of \r [...]"


id: 637de2aa511639439e81d9b6bcb0dec
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updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 14797
content:
"[...] dedicated individual, governmental or business adaptive responses \r (Tol et al. 2006; Anthoff et al. 2010; Anthoff et al. 2016)."


id: 8afec988e5c3fd6d07a54ff102f91f46
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 21623
content:
"Recent literature shows that there are crucial differences between the \r ethical challenges of mitigation and those of adaptation (Wallimann\u0002Helmer, 2015; Wallimann-Helmer, 2016) in their dealings with Loss \r and Damage (L&D); and the ongoing analysis disputes how to \r distribute responsibilities between mitigation and adaptation based \r on climate justice criteria (Wallimann-Helmer et al. 2019). The Warsaw \r International Mechanism on L&D under the United Nations Framework \r Convention on Climate Change (UNFCCC) addresses irreversible \r changes and limits to adaptation at the global scale (see also Cross\u0002Chapter Box 1 in Chapter 1). This is in contrast to national and local \r policies, addressing impacts and adaptation. Within the SROCC report, \r several of the documented and projected irreversible or unavoidable \r and thus residual impacts beyond adaptation would potentially fall \r under this category (e.g., Warner and van der Geest, 2013; Huggel \r [...]"


id: 377521e19bcac5f5353698ec72cdc334
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updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 6968
content:
"[...] et al. 2019; Mechler et al. 2019), including impacts from SLR, land \r erosion and reduced freshwater resources on small islands, changes \r in high mountains and cryosphere changes, as well as changes in \r ocean species and resources. Apart from climate hazards, risks for \r L&D are also determined by increasing exposure and vulnerability "


id: 5c42f76e6dfbb4209faae5d1ea6230b5
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 13486
content:
"and Climate Change Adaptation\r Governance for effective adaptation defined as changes in practice, \r process and structure (Smit et al. 2001) considers equity, legitimacy \r and co-benefits (Patterson et  al. 2018) appropriate to the issue \r (Young, 2002). Countries, sectors and localities place different values \r and perspectives on these categories, and they can change over time \r (Plummer et al. 2017; see Cross-Chapter Boxes 1 and 2 in Chapter 1). \r Transformative governance embraces a wider application of climate \r change-induced mitigation and adaptation strategies to generate \r fundamental change. It is society-wide and goes beyond the goals \r of climate change policies and measures (IPCC, 2013; Patterson et al. \r 2018). It is distinguished from conventional strategies and solutions, \r as it includes both natural and human systems and intertwines with \r the SDGs (Fleurbaey et al. 2014; Tabara et al. 2019). Transformational \r [...]"


id: 496ed566ce67954eea7df8629e4194ed
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content:
"[...] adaptation is also needed when incremental adaptation to extreme \r events and abrupt changes is insufficient (Kates et  al. 2012). \r Planned retreat from SLR and climate refugees illustrate the need for \r transformative governance as the current coastal and risk management \r regimes do not have the capacity to handle these issues adequately. \r Inclusion of bilateral and regional agreements related to climate\u0002induced migration (McAdam, 2011), land use planning frameworks to \r respond to policy, institutional and cultural implications of migration \r (Matthews and Potts, 2018), and identification of beneficiaries of \r managed retreat (Hino et al. 2017) along with positive opportunities \r for migrants to diversify income and avoid being in harm's way \r (Gemenne, 2015) are steps towards transformative governance. \r Retreat and migration entail local responses that include indigenous \r and local knowledges and perspectives that can be applied to solve \r [...]"


id: 1a882082e3ae6d9a8cf33dce177c93a9
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content:
"[...] these issues (Farbotko and Lazrus, 2012; Hilhorst et al. 2015; Tharakan, \r 2015; Iloka, 2016; Nunn et al. 2016; see also Cross-Chapter Boxes 2 \r and 5 in Chapter 1). Another example is the Polar region which has \r started to pursue transformative governance given the potential for \r increased tourism and cooperation that require changed governance \r structure (see  Sections 3.5.2; 3.5.5 and Table 3.7 in Chapter 3). \r Accountability for transformations and transitions has been identified \r as a crucial factor to support responsible action and strengthen \r climate governance (Edmondson and Levy, 2019)."


id: 52055b113af9ef65de531b89e3f3f11e
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 11705
content:
"Under the same L&D mechanism, risk transfer mechanisms and \r insurance have been suggested as a specific adaptation policy option. \r Several forms of 'climate change' insurance have been proposed \r recently, but their potential for adaptation has met with criticism, \r importantly because of the costs of formal insurance and other risk \r transfer options, as well as issues with sustainability given the lack \r of loss prevention and adaptation (Surminski et al. 2016; Linnerooth\u0002Bayer et  al. 2019). A compensation mechanism for low-lying small \r islands inclusive of L&D proposal is in progress (Adelman, 2016). \r Insurance (see also Section 4.4.4) can help absorb extreme shocks for \r both individuals, using traditional insurance and parametric insurance. \r Sovereign insurance mechanisms can help governments absorb large \r losses (Linnerooth-Bayer et  al. 2019), but eventually they need to \r be coupled with other incentives for adaptation and risk reduction \r [...]"


id: b61427e69c2549c078933ddd03cff657
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 29255
content:
"There is a consensus that investing in disaster risk reduction has \r economic benefits, although there is medium evidence about the \r range of the estimated benefits which varies from a global estimate \r of two to four dollars saved for each dollar invested (Kull et al. 2013; \r Mechler, 2016) to about 400 EUR per invested 1 EUR in the case \r of flood early warning systems in Europe (Pappenberger et  al. \r 2015). The US Federal Emergency Management Agency indicated \r that a  1%  increase in annual investment in flood management \r decreases flood damage by 2.1% (Davlasheridze et  al. 2017). \r Conserving ecosystems that provide services for risk reduction also \r has monetary benefits. Wetlands have been observed to reduce \r damages during storms. Wetlands and floodplains in Otter Creek \r (Vermont, USA) reduced damages caused by storms by 54-78% and \r 84-95%, respectively, for Tropical Storm Irene (Watson et al. 2016). \r For the whole of the USA, wetlands provide 23.2 billion USD yr-1\r [...]"


id: 748c84907d618da0d5bb4814ea9458d0
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content:
"[...] in storm protection services and the loss of 1 hectare of wetland is \r estimated to correspond to an average 33,000 USD increase in storm \r damage from specific storms (Costanza et  al. 2008). Engineered \r structures are also expected to reduce risks. In Europe, to maintain \r the coastal flood loss constant relative to the size of the economy, \r flood defence structures need to be able to protect coastal areas for \r a projected increase of sea level between 0.5-2.5 m. Without these \r risk reduction actions, the expected damages from coastal floods \r could increase by two or three degrees of magnitude compared to \r the present (Vousdoukas et al. 2018). Although risk reduction actions \r are generally considered an effective way to reduce the damages by \r shifting the loss-exceedance curve, cost-benefit analysis of disaster \r risk reduction actions faces several challenges, including its limited \r role in informing decisions, spatial and temporal uncertainty scales, \r [...]"


id: fb3c615be0cf53f41da76572b4ebe5c
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updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 41576
content:
"[...] and discounting and choice of discount rate that affect cost-benefit \r analysis results heavily (Mechler, 2016)."


id: 53f3aa047a2cd22215012f519f78fd29
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 12041
content:
"Though discourse abounds related to transformative governance, it \r falls short of its ideal in climate change action plans as it is unclear \r whether communities have the capacity to engage in substantive \r change to build low-carbon and resilient communities (Burch et al. \r 2014). The results of a study on the USA by Tang and Dessai (2012) \r indicate that climate adaptation and mitigation plans' treatment \r of extreme climate conditions and disaster preparedness is limited. \r Moreover, risk communication with the public is part of an integrated \r disaster warning system, but behavioural response to disaster \r warnings are often governed by personal beliefs about the nature of \r the hazard; and ultimately swaying individual decisions to comply with \r or ignore the warning message (Mayhorn and McLaughlin,  2014). \r New approaches such as the 'first mile' of early warning systems, \r built on the specific needs from beneficiary communities instead \r [...]"


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updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 11063
content:
"[...] of on technological progress, are being implemented (Zommers \r et al. 2017); but they have not yet been assessed. "


id: b4c34ae12ee05ace084c9a3289baa3a8
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"Coupling disaster risk reduction and management with climate \r change adaptation effort - following the set targets of UNFCCC \r and the Sendai Framework - has shown progress since SREX and \r AR5 (e.g., Lawrence and Saunders, 2017). Substantial literature \r exists on the topic, but there is little assessment of practices on the \r ground in the implementation of integrated disaster management \r and climate change adaptation (Nalau et al. 2016) including health \r (Banwell et  al. 2018). Mainstreaming disaster risk reduction and \r climate change adaptation within and across sectors is considered \r essential to ensure administrative coordination and coherence \r across sectoral plans and policies (Shimizu and Clark, 2015) \r (medium confidence). Financial and technological support and \r capacity building especially related to public works, savings or loans \r enable households to build assets and improve livelihoods (Ulrichs \r [...]"


id: 4445f7f9c5a911c5cc25b1b84c2b561a
created_at: 2023-04-19 13:22:32
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"[...] et al. 2019). No assessment is available so far of the efficiency and \r effectiveness of mainstreaming especially related to the integration \r of climate change adaptation and disaster risk reduction, let alone \r for abrupt and extreme impacts."


id: a70b0da7a2a46aaa4e4018d3179ac67e
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"Case studies of integration note major problems, for example, weak \r coordination among government agencies (Seidler et al. 2018); lack \r of data and user-friendly information to guide decision making \r at the local level (Jones et  al. 2017) and the need for the central \r governmental support for data availability (Putra et  al. 2018); \r fragmentation due to competing local objectives (Forino et  al. \r 2017); dependence on regional and international frameworks in \r the absence of a national framework (Rivera and Wamsler, 2014); \r limited availability of formal training in integration (Hemstock et al. \r 2017); and turf wars between responsible government agencies \r (Nemakonde and Van Niekerk, 2017). The case of Pacific islands \r such as Vanuatu is indicative of these problems. Though they have \r coupled disaster risk reduction with climate change adaptation, \r problems manifest in relationships, responsibilities, capacity and \r [...]"


id: 4f4e2282d615d1e2e2496453e17c2a45
created_at: 2023-04-19 13:22:32
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content:
"[...] expectations between government agencies and other actors \r (e.g., international donors and non-governmental organisations), as \r analysed by Vanuatu's response to the Category 5 TC Pam (Nalau \r et  al. 2017). Some solutions are proposed such as getting all the \r actors on the same page and focusing on reducing vulnerability to \r longer-term environmental hazards (Schipper et al. 2016); focussing \r on specific goals, objectives and strategies (Organization of American \r States, 2014); assigning a single department to handle integration \r (APEC,  2016); and citing real-life decision examples in national \r guidelines (Bell et  al. 2017). Place-based responses also entail \r the inclusion and the acknowledgement of indigenous and local \r knowledge for an enhanced resilience pathway (Hilhorst et al. 2015; \r Tharakan, 2015; Iloka, 2016; Nunn et al. 2016). "


id: 3faa422089061251bcb8932b2d52d1c0
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
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content:
"Knowledge gaps limit the identification of the most relevant actions \r to achieve and pursue climate-resilient development pathways. \r Since SREX and AR5, there is little research on indirect impacts of \r climatic extremes on ecosystems and consequences on poverty and \r livelihoods critical to the SDGs. For example, adaptation solutions \r and limitations, including governance challenges, for the ocean do \r not include extreme events (Sections 5.5.2 and 5.5.3 in Chapter 5). \r Further, there is only scant literature on L&D, including non-economic \r impacts, resulting from well-documented processes such as MHWs \r (Section 6.4), SLR impacts on low-lying coasts (Section 4.3), and \r cryosphere changes (Section 2.3; Chapter 3) (high confidence). \r Limited information is available concerning the cost-benefit and \r effectiveness of risk-reduction measures. Coupling risk transfer and \r insurance mechanisms with risk reduction measures, for example, \r [...]"


id: 982934bfd51d7bfd74c082cbb243584a
created_at: 2023-04-19 13:22:32
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content:
"Reducing GHG emissions is the main action to limit global warming to acceptable levels and reduce the \r occurrence of extreme events and abrupt changes. However, in addition to mitigation, a variety of measures \r and risk management strategies supports adaptation to future risks. Future risks linked to abrupt changes \r are strongly influenced by local conditions and different characteristics of the events themselves and evolve \r differently depending on the circumstances. One major factor for adaptation is whether the extreme events \r will simply amplify the known impacts or whether they will cause completely new conditions, which may be \r related to a tipping point. Another essential factor is whether an extreme event or abrupt change will happen \r in isolation or in conjunction with other events, in a chain of cascading impacts or as part of a compound risk \r where several events happen at the same time so that impacts can multiply each other. Also, impacts are heavily \r [...]"


id: 6161f84eb1f2baf49b2d1fa3cbca7ada
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"[...] aggravated by increasing exposure and changes in vulnerability, for example reducing the availability of food, \r water and energy supply, and not just the occurrence of extremes themselves. "


id: cc58e2df4f9030304beb023bec3e3b47
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"Successful management of extreme events and abrupt changes in the ocean and cryosphere involves all available \r resources and governance approaches, including among others land-use and spatial planning, indigenous \r knowledge and local knowledge. The management of the risks to ecosystems include their preservation, the \r sustainable use of resources and the recognition of the value of ecosystem services. There are three general \r approaches that, alone or in combination, can enable communities to adapt to these events: retreat from the \r area, accommodation to new conditions and protection. All have advantages and limitations and their success \r will depend on the specific circumstances and the community's level of adaptability. But only transformative \r governance that integrates a variety of strategies and benefits from institutional change helps to address \r larger risks posed by compound events. Integrating risk-reduction approaches into institutional practices and \r [...]"


id: b84d9748bc97e2552e6a6680d9967aa0
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vector_id: 29638
content:
"[...] inclusive decision making that builds on the respective competences of different government agencies and other \r stakeholders can support management of these extremes. A change of lifestyles and livelihoods might further \r support the adaptation to new conditions."


id: c8a5a4b696c5c98dae564e872a743407
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"Ocean and cryosphere changes already impact Low-Lying Islands and Coasts (LLIC), including Small \r Island  Developing States (SIDS), with cascading and compounding risks. Disproportionately higher risks \r are  expected  in the course of the 21st century. Reinforcing the findings of the IPCC Special Report on \r Global Warming of 1.5oC, vulnerable human communities, especially those in coral reef environments and polar \r regions, may exceed adaptation limits well before the end of this century and even in a low greenhouse gas \r emission pathway (high confidence1). Depending on the effectiveness of 21st century mitigation and adaptation \r pathways under all emission scenarios, most of the low-lying regions around the world may face adaptation \r limits beyond 2100, due to the long-term commitment of sea level rise (medium confidence). LLIC host around \r 11% of the global population, generate about 14% of the global Gross Domestic Product and comprise many world cultural \r [...]"


id: c7ba3ee8eacc62d851e7dffa53b30ed7
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
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content:
"[...] heritage sites. LLIC already experience climate-related ocean and cryosphere changes (high confidence), and they share both \r commonalities in their exposure and vulnerability to climate change (e.g., low elevation, human disturbances to terrestrial \r and marine ecosystems), and context-specificities (e.g., variable ecosystem climate sensitivities and risk perceptions by \r populations). Options to adapt to rising seas, e.g., range from hard engineering to ecosystem-based measures, and from \r securing current settings to relocating people, built assets and activities. Effective combinations of measures vary across \r geographies (cities and megacities, small islands, deltas and Arctic coasts), and reflect the scale of observed and projected \r impacts, ecosystems' and societies' adaptive capacity, and the existence of transformational governance (high confidence) \r {Sections 3.5.3, 4.4.2 to 4.4.5, 5.5.2, 6.8, 6.9, Cross-Chapter Box 2 in Chapter 1}."


id: 2a766477a493ca15d35dafd0c8262ec1
created_at: 2023-04-19 13:22:32
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content:
"LLIC are already experiencing the impacts of climate-related changes to the ocean and cryosphere, for both extreme events \r and slow onset changes (Sections 4.3.3, 5.3.1 to 5.3.6, 6.2, 6.8, 6.9), due to their low elevation, narrow ecological zonation, \r climate sensitive ecosystems and natural resources, as well as increasing anthropogenic pressures (Sections 1.5, 4.3.2). \r High levels of impacts to coastal morphology, ecosystems and dependent human communities are detectable today and \r disproportionately higher risks are expected in the course of the 21st century (medium evidence, high agreement) (Sections \r 4.3.4, 5.3.7), even under a low emission pathway compatible with a 1.5oC global warming (Hoegh-Guldberg et al., 2018; IPCC, \r 2018). The magnitude of projected impacts (i.e., risks; Cross-Chapter Box 2 in Chapter 1) will depend on future greenhouse \r gas emissions and the associated climate changes, as well as on other drivers such as population movement into risk-prone \r [...]"


id: 29ca8479206ceda3dbf21b2efc44f09f
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content:
"Climate-related hazards - LLIC are subject to the same climate-related hazards as other islands and coasts (overview in Wong \r et al., 2014), for both extreme events, for example, marine heat waves, tropical and extratropical storms, associated storm \r surges, and heavy precipitation; and slow onset changes, for example, retreat of glaciers and  ice  sheets, sea ice and \r permafrost thaw, sea level rise, and ocean warming and acidification (Sections 1.4, 2.2, 3.2 to 3.4, 4.2, 5.2, 6.2 to 6.6, \r Box 6.1). Table CB9.1 summarises the SROCC updates of these hazards, which often combine to explain part of observed \r climate impacts and projected risks. For example, accelerating sea level rise will combine with  storm surges, tides and \r waves to generate to extreme sea level events that affect flooding (Section 4.3.3.2), shoreline changes (Section 4.3.3.3) and \r salinisation of soils, groundwater and surface waters (Section 4.3.3.4). Sea level rise will also combine with ocean warming to \r [...]"


id: ede6886b9c213af8e5909bfd785fddf4
created_at: 2023-04-19 13:22:32
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content:
"[...] accelerate permafrost thawing in the Arctic (Sections 3.4.1.2, 3.4.2.2). Ocean acidification will combine with ocean warming \r and deoxygenation to impact benthic and pelagic organisms, associated ecosystems (e.g., coral reefs, oyster beds) and top \r predators, with subsequent impacts on species' abundance and distribution, and the ecosystem services benefiting human \r societies (Sections 4.3.3.5, 5.2.2, 5.3.1 to 5.3.6, 5.4.1, 6.4.2, 6.5.2, 6.6.2, 6.7.2, 6.8.2). Importantly, LLIC are at risk for \r multi-metre sea level rise projected post-2100 under Representative Concentration Pathway (RCP)8.5 and restricted to 1-2 \r m in 2300 under RCP2.6 (Section 4.2.3.5)."


id: 10088c22eaf8bd9a1bf0db0780ac97f6
created_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
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"Highly context-specific territorial and societal dynamics have resulted in major changes at the coast, for instance the growing \r concentration of people and assets in risk prone coastal areas (Section 4.3.2.2), and the degradation of coastal ecosystem \r services such as coastal protection and healthy conditions for coastal fisheries and aquaculture (Section 4.3.2.3, 5.4.1.3, \r 5.4.2.2.2). Local drivers of exposure and vulnerability include, for example, coastal squeeze, inadequate land use planning, \r changes in construction modes, sand mining and unsustainable resource extraction (e.g.,  in the Comoros; Betzold and \r Mohamed, 2016; Ratter et al., 2016), as well as loss of Indigenous Knowledge and Local Knowledge (IK and LK; Cross-Chapter \r Box 4 in Chapter 1). For example, the loss of IK and LK-based practices and associated cultural heritage limits both the ability \r [...]"


id: 21ace14a1f1849fbedd09bc342445a8e
created_at: 2023-04-19 13:22:32
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content:
"[...] to recognise and respond to ocean and cryosphere related risk and the empowerment of local communities (high confidence) \r (Section  4.3.2.4.2). Population growth in medium-to-mega coastal cities is also of concern. For the year 2000, the Low \r Elevation Coastal Zones (LECZ, highest elevation up to 10 m above sea level) were estimated to host around 625 million \r people (Lichter et al., 2011; Neumann et al., 2015), with the vast majority (517 million) living in non-developed contexts. \r By 2100, the LECZ population may increase to as much as 1.14 billion under a Shared Socioeconomic Pathway (SSP) where \r countries focus on domestic, or even regional issues (SSP3; Jones and O'Neill, 2016). Poor planning can combine with coastal \r population growth and climate-related ocean change to create maladaptation (Juhola et al., 2016; Magnan et al., 2016). "


id: a91ab2788ef146c365a8cb3d6b57128
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updated_at: 2023-04-19 13:22:32
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content:
"jpgpj\r Coastal cities and megacities - Coastal cities, especially megacities with over 10 million inhabitants, are at serious risk from \r climate-related ocean and cryosphere changes (Abadie, 2018). Over half of today's global population lives in cities and \r megacities, many of which are located in LLIC, including New York City, Tokyo, Jakarta, Mumbai, Shanghai, Lagos and Cairo \r (Figure CB9.1). Without substantial adaptation interventions, and based on the compounding effects of future growth in \r population and assets, sea level rise and continued subsidence, future flood losses in the 136 largest coastal cities are \r projected to rise from 6 billion USD yr-1 at present to 1 trillion USD yr-1 in 2050 (Hallegatte et al., 2013; Sections 4.3.3.2 \r and 6.3.3). In addition to important impacts on coastal megacities and large port cities, small and mid-sized cities are also \r [...]"


id: c2a235a9fd5716453bf2729c61f84ac3
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content:
"[...] considered highly vulnerable because of fast growth rates and low political, human and financial capacities for risk reduction \r compared to larger cities (Birkmann et al., 2016; Box 4.2)."


id: af920649c19bd42de48b3eea9d356510
created_at: 2023-04-19 13:22:32
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vector_id: 28127
content:
"impact of TCs, storm surge and ocean acidification in small islands contributing to loss and damage (Moser and Hart, 2015; \r Noy and Edmonds, 2016). For example, Category 5 TC Pam devastated Vanuatu in 2015 with 449.4 million USD in losses for \r an economy with a GDP of 758 million USD (Government of Vanuatu, 2015; Handmer and Iveson, 2017). Kiribati, Papua New \r Guinea, Solomon Islands and Tuvalu were all impacted by the TC Pam system (IFRC, 2018). In 2016, TC Winston caused 43 \r deaths in Fiji and losses of more than one third of the GDP (Government of Fiji, 2016; Cox et al., 2018). In 2017, Hurricanes \r Maria and Irma swept through 15 Caribbean countries, causing major damages and casualties across numerous islands. \r Rebuilding in three countries alone - Dominica, Barbuda and the British Virgin Islands - will cost an estimated 5 billion USD \r (UNDP, 2017). The Post-Disaster Needs Assessment for Dominica concluded that hurricane Maria resulted in total damages \r [...]"


id: b85783f7f13ea8de1a53714601f5d56c
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content:
"[...] amounting to 226% of 2016 GDP (The Government of the Commonwealth of Dominica, 2017). In 2018, Category 4 TC Gita \r struck the Pacific islands of Eua and Tongatapu, impacting 80% of the population of Tonga through destruction of buildings, \r crops and infrastructure, and resulting in 165 million USD of losses with a national GDP of 461 million USD (Government of \r Tonga, 2018). Effective early warning systems, in some Caribbean islands, have reduced the impact (WMO, 2018). Projected \r changes in extreme weather include increased intensity of TCs with increased wind speed and rainfall, together with reduced \r translational speed creating greater destruction from individual storms and  counteracting the decreased frequency of \r occurrence (Sections 6.3 and 6.8)."


id: 5c72334ff3f25781bff6999774018d66
created_at: 2023-04-19 13:22:32
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content:
"SIDS are home to 65 million people (UN-OHRLLS, 2015). More than 80% of small island residents live near the coast where \r flooding and coastal erosion already pose serious problems (Nurse et al., 2014) and since the IPCC 5th Assessment Report \r (AR5) and the Special Report on Global Warming of 1.5oC (SR1.5), there is consensus on the increasing threats to island \r sustainability in terms of land, soils and freshwater availability. As a result, there is growing concern that some island nations \r as a whole may become uninhabitable due to rising sea levels and climate change, with implications for relocation, sovereignty \r and statehood (Burkett, 2011; Gerrard and Wannier, 2013; Yamamoto and Esteban, 2014; Donner, 2015). For example, at the \r island scale, recent studies (e.g., on Roi-Namur Island, Marshall Islands; Storlazzi et al., 2018) estimate some atoll islands to \r [...]"


id: a9a1e36252015e2a3f2768c3d9970187
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vector_id: 27062
content:
"[...] become uninhabitable before the middle of the 21st century due to the exacerbation of wave-driven flooding by sea level \r rise, compromising soil fertility and the integrity of freshwater lenses (Cheriton et al., 2016). The literature also discusses the \r future of atoll island shoreline. Atoll islands are not 'static landforms' (high confidence) and they experience both erosion \r (Section 4.3.3.3) and accretion of land. In the Solomon Islands, where rates of sea level rise exceed the global average at \r 7-10 mm yr-1 (Becker et al., 2012), a study of 33 reef islands showed five vegetated islands had disappeared and six islands \r were concerned with severe shoreline erosion (Albert et al., 2016). In Micronesia, a study showed the disappearance of \r several reef islands, severe erosion in leeward reef edge islands and coastal expansion in mangrove areas (Nunn et al., 2017). \r [...]"


id: b9041e1cae5c187482a0973f73a8e056
created_at: 2023-04-19 13:22:32
updated_at: 2023-04-19 13:22:32
content_type: text
index: climate_gpt_v2
vector_id: 29754
content:
"[...] In Tuvalu, with sea level rise of ~15 cm between 1971 and 2014, small islands decreased in land area while larger populated \r islands maintained or increased land area with the exception of the remote island of Nanumea (Kench et al., 2018). Positive \r shoreline and surface area changes over the recent decades to century have been observed for atoll islands in the Pacific \r and Indian oceans (McLean and Kench, 2015; Albert et al., 2016; Kench et al., 2018; Duvat, 2019). Out of 709 islands studied, \r 73.1% had stable surface area, 15.5% increased and 11.4% decreased in size over the last 40-70 years (Duvat, 2019). It has, \r however, been argued that the capacity of some atoll islands to maintain their land area by naturally adjusting to sea level \r rise could be reduced in the coming decades (low evidence, high agreement). Indeed, the projected combination of higher \r [...]"


id: b400bfb8128b81303f829a51e41ca503
created_at: 2023-04-19 13:22:32
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content:
"[...] rates of sea level rise (Sections 4.2.3.2, 4.2.3.3 and 4.2.3.5), increased wave energy (Albert et al., 2016; see also Section 6.3), \r changes in storm wave direction (Harley et al., 2017), as well as the impacts of ocean warming and acidification on the reef \r system (Quataert et al., 2015; Hoegh-Guldberg et al., 2018), is expected to shift the balance towards more frequent flooding \r and increased erosion (Sections 4.3.3, 5.3.3). "


id: d91fbd09421ea8f7b7b7fab1e7812cab
created_at: 2023-04-19 13:22:32
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content:
"Deltas - In a context of natural subsidence exacerbated by high human disturbances to sediment supply, for example, due \r to fresh water exploitation or damming and land use change upstream from the coast (Kondolf et al., 2014), marine flooding \r is already affecting deltas around the world (Brown et al., 2018; Section 4.3.3.4, Box 4.1). An estimated 260,000 km2 of delta \r area have been temporarily submerged over the 1990s-2000s (Syvitski et al., 2009; Wong et al., 2014). The recurrence of El \r Nino associated floods in the San Juan River delta, Colombia, led to the relocation of several villages, including El Choncho, \r San Juan de la Costa, Charambira and Togoroma (Correa and Gonzalez, 2000). The intrusion of saline or brackish water due \r to relative sea level rise in combination with storm surges and natural and human-induced subsidence, results in increasing \r [...]"


id: 8177b131e6cc730613f94d078053437e
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"[...] residual salinity, as already reported in the Delaware Estuary, USA (Ross et al., 2015), in the Ebro Delta, Spain (Genua-Olmedo \r et al., 2016) and in the Mekong Delta, Vietnam (Smajgl et al., 2015; Gugliotta et al., 2017). This affects livelihoods, for \r example., freshwater fish habitat in Bangladesh (Dasgupta et al., 2017; Section 4.3.3.4.2). Increased salinity limits drinking \r water supply (Wilbers et al., 2014), with associated repercussions for the abundance and toxicity of cholera vibrio (Vibrio \r cholerae) as shown in the Ganges Delta (Batabyal et al., 2014). Local agriculture is also at risk. Oilseed, sugarcane and jute \r cultivation have already ceased due to high salinity levels in coastal Bangladesh (Khanom, 2016) and dry-season crops are "


id: 52182d45824bca0631315c4b01c2561d
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content:
"Arctic coasts - Climate-related ocean and cryosphere changes combine to negatively impact not only the economy \r and life-styles of the Arctic coastal communities, but also the local cultural identity, self-sufficiency, IK and LK and related \r skills (Lacher, 2015; Sections 3.4.3, 4.3.2.4.2). Changes in fish and seabird populations amplified by climate change have an \r impact on ecosystems and livelihoods in Arctic island communities such as in Norway's Lofoten archipelago (Dannevig and \r Hovelsrud, 2016; Kaltenborn et al., 2017). Another concern relates to coastal erosion, for example triggered by permafrost \r thaw (Gunther et al., 2013; Jones et al., 2018), and which already affects 178 Alaskan communities, with 26 in a very critical \r situation, such as Newtok, Shishmaref, Kivilina and northwestern coastal communities on the Chukchi Sea (Bronen and \r Chapin III, 2013). Noteworthy, erosion does not affect all Arctic coastlines: many of them are located in areas that experience \r [...]"


id: b6555b11e8ceb373eee9f2840cc4dcb0
created_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
vector_id: 29297
content:
"[...] rapid glacial-isostatic adjustment (GIA) uplift (James et al., 2015; Forbes et al., 2018) and have low sensitivity to extreme sea \r levels and sea level rise. An additional factor unique to the Arctic coasts compared to other LLIC is the decrease in seasonal \r sea ice extent (Section 3.2.1, 4.3.4.2.1), that both reduces the physical protection of the land (Overeem et al., 2011; Fang \r et al., 2018), for example, from wave action, and allows for greater open water fetch producing stronger wind-generated \r waves in the open water (Lantuit et al., 2011). In combination with a decreased stability of permafrost - another specificity \r of polar regions (Romanovsky et al., 2010) - and sea level rise, seasonal sea ice extent reduction results in shoreline erosion \r (Gibbs and Richmond, 2017; Jones et al., 2018), with associated impacts on coastal settlements (Table 3.4). However, as \r [...]"


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created_at: 2023-04-19 13:22:32
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content:
"[...] mentioned above, local geomorphology and geology in the Arctic is as important as  permafrost and sea ice extent for \r determining current and future erosion (Lantuit et al., 2011). "


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"Considering a sea level rise scenario range of 25-123 cm - all RCPs; wider range of sea level rise scenarios than the likely\r range of AR5 but relatively consistent with the range of projections assessed in this report (Section  4.2.3.2) - and no \r adaptation, Hinkel et al. (2014) estimated annual losses from future marine flooding to amount to 0.3-9.3% of global GDP in \r 2100. Noteworthy, coastal protection will inevitably have economic costs (DiSegni and Shechter, 2013), whether it involves \r hard coastal protection (Hinkel et al., 2018), ecosystem-based approaches (Narayan et al., 2016; Pontee et al., 2016) or \r a combination of both (Schoonees et al., 2019). Coastal agriculture (e.g., rice crops; Smajgl et al., 2015; Genua-Olmedo et al., \r 2016), and fisheries and aquaculture will also be seriously impacted (Sections 4.3.3.6.1, 4.3.3.6.3, 5.4.1). For example, it is \r [...]"


id: cd6b081a46686c9a6428c2b0436c02a0
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"[...] expected that the marine fisheries revenues of 89% of the world's fishing countries will be negatively affected by mid-century \r under RCP8.5 (Hilmi et al., 2015). The fact that more than 90% of the world's rural poor are located in the LECZ of 15 \r developing countries (Barbier, 2015) and that these regions are highly dependent on fish for their dietary consumption, raises \r a serious concern about future food security (FAO et al., 2017; Section 5.4.2.1.2). But not all regions are equally threatened, "


id: 1f5bcffb17f2bf695312cd1e5b60d6c6
created_at: 2023-04-19 13:22:32
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"Coastal tourism could be affected in various ways by ocean- and cryosphere-related changes (Hoegh-Guldberg et al., 2018; \r Sections 4.3.3.6.2, 5.4.2.1.3). Coastal infrastructure and facilities, such as harbours and resorts (e.g., in Ghana; Sagoe-Addy \r and Appeaning Addo, 2013), are prone to storm waves. For coral reefs for recreational activities and tourism (especially diving \r and snorkelling), Chen et al. (2015) estimated that the global economic impact of the expected decline in reef coverage \r (between 6.6 and 27.6% under RCPs 2.6 and 8.5, respectively) will range from 1.9 to 12.0 billion USD yr-1. The future appeal \r of tourism destinations will partly depend on sea surface temperature, including induced effects such as an increase in \r invasive species, e.g., jellyfishes (Burge et al., 2014; Weatherdon et al., 2016) and lion fish in the Northwest Atlantic, the Gulf \r [...]"


id: f2b4e9d22ea25da02cfecac9111560c6
created_at: 2023-04-19 13:22:32
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"[...] of Mexico and the Caribbean (Albins, 2015; Johnston et al., 2015; Holdschlag and Ratter, 2016). It will also depend on how \r tourists and tourism developers perceive the risks induced by ocean-related changes (e.g., Shakeela et al., 2013; Davidson \r and Sahli, 2015). This will combine with the influence of changes in climatic conditions in tourists' areas of origin (Bujosa \r and Rossello, 2013; Amelung and Nicholls, 2014; Hoegh-Guldberg et al., 2018) and of non-climatic components such as \r accommodation and travel prices. Importantly, estimating the effects on global-to-local tourism flows remains challenging \r (Rossello-Nadal, 2014; Wong et al., 2014)."


id: 15c2214c9826bdeb2c0b1ea246775646
created_at: 2023-04-19 13:22:32
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"A wide range of coastal adaptation measures are currently implemented in LLIC worldwide (Sections 1.6.2, 2.3.7, 3.5.2, \r 3.5.3, 4.4.3, 5.5.2, 6.9, Figure 1.2, Box 5.4), including the installation of major infrastructure such as armouring of coasts \r (e.g., seawalls, groynes, revetments and rip-raps), soft engineering (e.g., beach nourishment and dune restoration), reclamation \r works to build new lands seaward and upwards, ecosystem-based measures (e.g., vegetation planting and coral farming), \r community-based approaches (e.g., social networks, education campaigns and economic diversification) and institutional \r innovations (e.g., marine protected areas and evacuation plans). The effectiveness of the measures to reduce risks depends \r on both local context-specificities (Gattuso et al., 2018) and the magnitude and timing of local climate impacts. However, \r there is still a gap in on-the-ground evidence, good practices and guidelines to evaluate the observed and projected benefits \r [...]"


id: 71b09418976fcd16df3e46fc1aa1d072
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content:
"[...] of each type of measures applied in various contexts, for example, to decide whether nature-based options represent low- to \r no-regret solutions, or not a solution at all. "


id: fba42c1bc2b4b29ecd3ee0c02180eea6
created_at: 2023-04-19 13:22:32
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content:
"Protection with hard coastal defences is commonly used to prevent inundation from extreme water levels and wave overtopping \r (Section 4.4.2.2). In environments such as megacities, adequately engineered hard coastal defences are considered to be \r successful options and an efficient adaptation option in the long run (Hinkel et al., 2018). However, such measures can \r also lead to detrimental effects, such as erosion exacerbation by seawalls reflecting wave energy and jetties disrupting \r cross-shore sediment transport. Adaptation labelled measures 'may [thus] lead to increased risk of adverse climate-related \r outcomes, increased vulnerability to climate change, or diminished welfare' (Noble et al., 2014: 857) and  therefore be \r maladaptive (Barnett and O'Neill, 2013; Juhola et al., 2016; Magnan et al., 2016). As a result, alternatives have emerged, \r such as ecosystem-based design measures including coconut fibre blankets (David et al., 2016), plantations of seagrass (Paul \r [...]"


id: 7246c5a1c94b8b9537e82bf1231591d7
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content:
"[...] and Gillis, 2015), artificial reefs made from bio-rock materials (Beetham et al., 2017; Goreau and Prong, 2017) and bamboo \r breakwaters (David et al., 2016). While restoration operations are often rather associated to conservation practices, they \r can have co-benefits in terms of coastal protection services (Section 4.3.2.3). For example, soft protection systems used in \r 69 studies were found to exhibit effectiveness in reducing wave heights at 70% for coral reefs, 62-79% for salt marshes, \r 36% for seagrass meadows and 31% for mangroves (Narayan et al., 2016). Arguing that coral reefs can provide comparably \r higher wave attenuation benefits to artificial defences such as breakwaters, Ferrario et al. (2014) conclude that reef defences \r for reducing coastal hazards can be enhanced cost effectively on the order of 1/10th. Coral reefs are, however, at very \r [...]"


id: af3027c1b9406f3e4f34b98810bc10dc
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"[...] high risk from climate change (Hoegh-Guldberg et al., 2018; Section 5.3.4), which challenges the duration of such benefits. "


id: 40b5b4c2d170a3affed395c39d6f246d
created_at: 2023-04-19 13:22:32
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index: climate_gpt_v2
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content:
"While human migration and relocation are expected to be a growing challenge for LLIC (medium evidence, high agreement) \r (Adger et al., 2014; Birk and Rasmussen, 2014; Milan and Ruano, 2014; Thomas, 2015; Sections 3.5.3.5, 4.4.2.4, 6.3.4, \r Table 3.4; Hajra et al., 2017; Stojanov et al., 2017), recent studies advocate for considering these options as adaptation to \r climate-related changes in the ocean and cryosphere (Shayegh et al., 2016; Allgood and McNamara, 2017; Hauer, 2017; \r Morrison, 2017; Perumal, 2018; Section 4.4.2.4). Such a view is, however, convoyed by discussions on related costs and \r impacts on the wellbeing of the people who are relocated (Null and Herzer Risi, 2016). Coastal retreat is underway in various \r LLIC around the world, for example, in Alaska and the US (Bronen, 2015; Ford et al., 2015; Logan et al., 2016; Hino et al., \r 2017), Guatemala (Milan and Ruano, 2014), Western Colombia (Correa and Gonzalez, 2000), the Caribbean (Apgar et al., \r [...]"


id: d841105c83a0c5db344207112b2bf4bf
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"[...] 2015; Rivera-Collazo et al., 2015) and Vietnam (Collins et al., 2017). Noteworthy, environmentally-induced relocation is not \r necessarily new, for example, in the Pacific (Nunn, 2014; Boege, 2016). The Gilbertese people from Kiribati moved to the \r Solomon Islands during the 1950s-1960s, as a result of long periodic droughts and subsequent environmental degradation \r (Birk and Rasmussen, 2014; Albert et al., 2016; Tabe, 2016; Weber, 2016). In the Solomon Islands, the relocation of the Taro \r Township (Choiseul Province) as a result of rising sea level and coastal erosion is already underway (Haines and McGuire, 2014; \r Haines, 2016). In Fiji, the relocation of Vunidogoloa village as a result of sea level rise and coastal erosion was successfully \r carried out in 2014 (McNamara and Des Combes, 2015). In Alaska, some communities (e.g., Newtok) responded to changing \r [...]"


id: 6440ca3774e9fb5e7d61032efbf0bb4
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content:
"[...] environmental and livelihood conditions due to permafrost thaw with self-initiated relocation efforts. Subsequently, Alaska \r state funding has been allocated to assist them (Bronen, 2015; Hamilton et al., 2016). Conflict escalation is a serious concern \r in the resettlement areas, between newcomers and locals, or between different groups of newcomers, particularly under \r conditions of land scarcity, high population density and (perceived) inequality (Connell and Lutkehaus, 2017; Boege, 2018). \r The obstacles thus extend well beyond the cost of relocation itself because of the multi-dimensional impacts on people's \r lives. Relocation also concerns economic activities, as illustrated with shellfish aquaculture relocation in the west coast of the \r US due to ocean acidification-driven crises (Cooley et al., 2016). "


id: 133b9ad4966cfbf1a9e6058cf09bc421
created_at: 2023-04-19 13:22:32
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content:
"For all interventions, adaptation is fully recognised as being a societal challenge, and not merely a question of technological \r solutions (medium evidence, high agreement) (Jones and Clark, 2014; McCubbin et al., 2015; Gerkensmeier and Ratter, \r 2018). Enhancing adaptation implies various sociopolitical and economic framings, coping capacities and cross-scale social \r and economic impacts (Sections 4.4.3, 4.4.5, Cross-Chapter Box 3 in Chapter 1). As a result, community-based decision \r making, sustainable spatial planning and new institutional arrangements gain increasing attention (Sections 4.4.4). Such \r approaches can involve working with local informal and formal institutions (Barron et al., 2012), enhancing risk ownership \r by communities through participative approaches (McEwen et al., 2017), establishing collaborative community networks \r (Hernandez-Gonzalez et al., 2016), and better integrating LLIC communities' IK and LK (see McMillen et al., 2014; Cross-Chapter \r [...]"


id: 4f5181314883615245e40afeb81e0cb
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"[...] Box 4 in Chapter 1). Small island communities, in particular, can strengthen their adaptive capacities by building on relatively \r high degrees of social capital, that is, dense social networks, collective action, reciprocity and relations of trust (Petzold and \r Ratter, 2015; Barnett and Waters, 2016; Petzold, 2016; Kelman, 2017; Section 4.3.2.4.3). The aim of all these approaches is \r both to facilitate the effective implementation of adaptive action, and create widespread acceptance of adaptation policies \r by stakeholders and local populations."


id: 198a35838f508b42e02422a2195c0ce5
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"Participatory scenario building processes, collaborative landscape planning and co-design of ecosystem-based management for \r LLIC resilience are underway along with promising approaches to actively engage all levels of society in the exploration of \r future adaptation scenarios. Experiences are reported for the German North Sea coast (Karrasch et al., 2017), Tenerife Island \r in the Atlantic Ocean (Hernandez-Gonzalez et al., 2016) and Pacific island communities (Burnside-Lawry et al., 2017). While \r adaptation labelled measures currently applied 'on the ground' are mainly reactive and short-term, long-term approaches \r are emerging (Noble et al., 2014; Wong et al., 2014), as illustrated by the development of 'adaptation pathways' - that is, \r long-term adaptation strategies based upon decision cycles that, over time, explore and sequence a set of possible actions \r [...]"


id: 5cf94897978bba0f7ca5213214b050ff
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"[...] based on alternative external, uncertain developments (Haasnoot et al., 2013; Barnett et al., 2014; Wise et al., 2014; Werners \r et al., 2015; Hermans et al., 2017; Section  4.4.4.3.4). Key expected benefits are an improved consideration of both the \r evolving nature of vulnerability (Denton et al., 2014; Dilling et al., 2015; Duvat et al., 2017; Fawcett et al., 2017) and climate \r change uncertainty (O'Brien et al., 2012; Brown et al., 2014; Noble et al., 2014), as well as better anticipation of the risks of \r maladaptation (Magnan et al., 2016). Practical applications of adaptation pathways in LLIC are occurring, for example, in "


id: 179fe6964f25ea56a91c63f27833d66e
created_at: 2023-04-19 13:22:32
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"LLIC are particularly at risk from climate-related changes to the ocean and the cryosphere, whether they are urban or \r rural, continental or island, at any latitude and regardless of level of development (high confidence). Over the course of the \r 21st century, they are expected to experience both increasing risks (high confidence) and limits to ecological and societal \r adaptation (de Coninck et al., 2018; Djalante et al., 2018; Section 4.3.4.2, Figure 6.2, Figure CB9.2; Hoegh-Guldberg et al., \r 2018), which has the potential to significantly increase the level of loss and damage experienced by local coastal livelihoods \r (e.g., fishing, logistics or tourism) (Djalante et al., 2018). However, there are still important research gaps on residual risks and \r adaptation limits, given that these limits can be reached due to the intensity of the hazards and/or to the high vulnerability \r [...]"


id: 66e64e8f3d0c56d704d986812b817f97
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content:
"[...] of a given system, and can be ecological, technological, economic, social, cultural, political or institutional. In addition, ocean \r and cryosphere changes have the potential to accumulate in compound events and cause cascades of impacts through \r economic, environmental and social processes (medium evidence, high agreement) (Sections 6.8.2 to 6.8.3, Box 6.1). This is \r the case when coastal flooding and riverine inundation occur together, for example, during the 2012 Superstorm Sandy in \r New York City, USA (Rosenzweig and Solecki, 2014); the 2014 cyclone Bejisa in Reunion Island, France (Duvat et al., 2016), \r and the 2017 Hurricane Harvey in Houston, USA (Emanuel, 2017). Cascade effects far beyond the extent of the original \r impacts bring the risk in LLIC of slowing down and reversing overall development achievements, particularly on poverty \r reduction (low evidence, medium agreement) (Hallegatte et al., 2016). Global time series analysis of risk and vulnerability \r [...]"


id: e057746ef810b38e1cf99aa1deea1e39
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content:
"[...] trends show that many Pacific island states have fallen behind the global average in terms of progress made in the reduction \r of social vulnerability towards natural hazards over the past years (Feldmeyer et al., 2017). These findings may well be \r indicative of the situation for other LLIC (medium confidence) (Hay et al., 2019). "


id: 3f9a04c99b04bf13ae57395a29476ded
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content:
"protection and ecosystem-based adaptation will reach significant limits by 2100 in the case of a  1  m  rise in sea level, \r suggesting the need for research into the crossing of environmental and/or anthropogenic tipping points (Sections 6.2). \r The SROCC report confirms that high risk to various geographies (Arctic communities remote from regions of rapid positive \r glacial-isostatic adjustment, megacities, urban atoll islands and large tropical agricultural deltas) are to be expected before \r a 1 m rise in global mean sea level (Section 4.3.4.2.1). More broadly, this report suggests, first, that the drivers and timing \r of the future habitability of LLIC will vary from one case to another (Manley et al., 2016; Hay et al., 2018). Second, future \r storylines of risks will also critically depend on the multi-decadal effectiveness of coastal nations' and communities' responses \r [...]"


id: 73835b36ee96f5ac34b475af405e6566
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content:
"[...] (medium evidence, high agreement). This will, in turn, partly depend on transformation of risk management regimes in order \r to harness these potentials and shift course towards climate-resilient development pathways (low evidence, high agreement) \r (Solecki et al., 2017)."


id: 4f70d9a4d5c059a143242147b1c14ab7
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content:
"The journey of this report reflects extraordinary efforts by all \r contributors under exceptional circumstances. The COVID-19 \r pandemic, which started during the review of the Second Order \r Draft, disrupted the process. However, the early response of Working \r Group I, through the hard work of the authors, review editors, chapter \r scientists, the Technical Support Unit, and Bureau members, made \r it possible to deliver a report that meets the most stringent science \r quality standards, thanks to the in-depth, broad review process, with \r an exhaustive, robust, rigorous and transparent assessment of the \r latest state of climate science knowledge. We commend the additional \r efforts taken, including by all reviewers from the research community \r and government representatives who adapted to a new way of working \r to complete this vital report. Our particular appreciation goes to the \r Working Group I Co-Chairs Valerie Masson-Delmotte and Panmao Zhai \r [...]"


id: 5eba23ae905458fa652062f42366815e
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"[...] for their leadership throughout the process. Their extraordinary efforts \r ensured that this robust and clear report is available to the world today."


id: f1a68166ec911c6f33e72ed1dbe41390
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"The introduction (Chapter 1) of the Report frames the WGI \r assessment within the broader AR6 and global climate policy \r context and introduces the key concepts, lines of evidence, and \r major developments. The remainder of the Report is structured in \r three segments. The first segment focuses on large-scale climate \r change (Chapters 2-4). These chapters provide an updated and \r comprehensive assessment of knowledge about the current state \r of the climate system, human influence and projections of future \r change on key large-scale indicators of the climate system. Chapter 2 \r assesses observed large-scale changes in the climate system in the \r long-term paleoclimate context. Chapter 3 updates the assessment \r of human influence on the climate system, considering natural \r variability, model performance and detection and attribution. \r Chapter 4 covers global climate projections spanning time horizons \r from the near term (2021-2040) to the mid-term (2041-2060), long \r [...]"


id: 121bcc3be10fa6927f4e40020688ee0b
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updated_at: 2023-04-19 13:22:33
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"oxide and the assessment of carbon and other biogeochemical \r feedbacks. Chapter  6 assesses changes in the emissions and \r abundances of individual SLCFs, how these changes affect \r Earth's energy balance through radiative forcing and feedback in \r the climate system, the implications of changing climate on air \r quality, and the implications of SLCF mitigation for climate and \r for air quality. Chapter 7 addresses Earth's energy budget through \r advances in observations, understanding and quantification of \r effective radiative forcing, and the assessment of feedbacks and \r climate sensitivity. Chapter 8 assesses observed and projected \r changes in the global water cycle, the physical understanding of \r the complexity of its response to multiple drivers, and implications \r for water availability. The physical processes underlying global \r and regional changes in the ocean, cryosphere and sea level and \r the understanding of observed and projected future changes since \r [...]"


id: b595b9601d00db3ac2ab9db25c2a1d28
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"[...] the AR5 and Special Report on the Ocean and Cryosphere in a \r Changing Climate are assessed in Chapter 9."


id: e1a18d65a7ad01d07647a390402eafa1
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content:
"The final four chapters of the Report (Chapters 10-12 and the Atlas) \r are dedicated to the assessment and distillation of regional climate \r information from multiple lines of evidence at sub-continental to \r local scales (including urban climate), building on information from \r previous chapters on large-scale climate and process understanding, \r with a focus on recent and projected regional changes in mean \r climate, extremes, and climatic impact-drivers. Chapter 10 assesses \r the foundations of how regional climate information is distilled from \r multiple lines of evidence and the interplay between anthropogenic \r causes and internal variability at regional scales. Chapter 11 addresses \r changes in weather and climate extremes on global and regional \r scales, including observed changes and their attribution, as well as \r projected changes. Chapter 12 assesses the climatic conditions that \r may lead to impacts and risks across the world's regions. Changes \r [...]"


id: 433c1d354e17e82a5d2d1a083f522606
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"[...] in mean climate at regional scales, in particular observed trends and \r their attribution and projected future changes in temperature \r and precipitation, are assessed in the Atlas chapter."


id: 68fab1bd543250c8ebb079fcf3b93ef3
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updated_at: 2023-04-19 13:22:33
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"The preparation of the WGI AR6 report was also informed by \r recommendations from several IPCC expert meetings. The first \r meeting focused on assessing climate information for regions \r (in 2018, co-organized by WGI and WGII, and hosted at ICTP, Trieste, \r Italy), which provided a scoping of the Interactive Atlas. A  second \r meeting focused on short-lived climate forcers (in 2018, co-organized \r by TFI and WGI, and hosted by the World Meteorological Organization \r in Geneva, Switzerland), which identified science advances in the \r understanding of emissions and climate effects of SLCFs and needs \r for improvements in emission inventories and methodologies. A \r third meeting on mitigation, sustainability, and climate stabilization \r scenarios (in 2019, organized by WGIII in Addis Ababa, Ethiopia), led \r to cross-WG coordination related to scenarios. Recommendations \r for clarity and readability from the 2016 IPCC Expert Meeting \r [...]"


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"[...] on Communication (organized by the IPCC Secretariat in Oslo, \r Norway) were taken into account in developing technical guidance, \r training and resources provided to authors and in particular for the \r preparation of the text and figures of the Frequently Asked Questions \r and the Summary for Policymakers."


id: 16bd4dd461dba53fc841f2624d4cc51e
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vector_id: 1212
content:
"Richard P. Allan (United Kingdom), Paola A. Arias (Colombia), Sophie Berger (France/Belgium), Josep G. \r Canadell (Australia), Christophe Cassou (France), Deliang Chen (Sweden), Annalisa Cherchi (Italy), Sarah \r L. Connors (France/United Kingdom), Erika Coppola (Italy), Faye Abigail Cruz (Philippines), Aida Diongue\u0002Niang (Senegal), Francisco J. Doblas-Reyes (Spain), Herve Douville (France), Fatima Driouech (Morocco), \r Tamsin L. Edwards (United Kingdom), Francois Engelbrecht (South Africa), Veronika Eyring (Germany), \r Erich Fischer (Switzerland), Gregory M. Flato (Canada), Piers Forster (United Kingdom), Baylor Fox\u0002Kemper (United States of America), Jan S. Fuglestvedt (Norway), John C. Fyfe (Canada), Nathan P. Gillett \r (Canada), Melissa I. Gomis (France/Switzerland), Sergey K. Gulev (Russian Federation), Jose Manuel \r Gutierrez (Spain), Rafiq Hamdi (Belgium), Jordan Harold (United Kingdom), Mathias Hauser (Switzerland), \r [...]"


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"[...] Ed Hawkins (United Kingdom), Helene T. Hewitt (United Kingdom), Tom Gabriel Johansen (Norway), \r Christopher Jones (United Kingdom), Richard G. Jones (United Kingdom), Darrell S. Kaufman (United \r States of America), Zbigniew Klimont (Austria/Poland), Robert E. Kopp (United States of America), Charles \r Koven (United States of America), Gerhard Krinner (France/Germany, France), June-Yi Lee (Republic of \r Korea), Irene Lorenzoni (United Kingdom/Italy), Jochem Marotzke (Germany), Valerie Masson-Delmotte \r (France), Thomas K. Maycock (United States of America), Malte Meinshausen (Australia/Germany), Pedro \r M.S. Monteiro (South Africa), Angela Morelli (Norway/Italy), Vaishali Naik (United States of America), \r Dirk Notz (Germany), Friederike Otto (United Kingdom/Germany), Matthew D. Palmer (United Kingdom), \r Izidine Pinto (South Africa/Mozambique), Anna Pirani (Italy), Gian-Kasper Plattner (Switzerland), \r [...]"


id: 373b4cc84ccfc61b06e7337564b4be80
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"[...] Krishnan Raghavan (India), Roshanka Ranasinghe (The Netherlands/Sri Lanka, Australia), Joeri Rogelj \r (United Kingdom/Belgium), Maisa Rojas (Chile), Alex C. Ruane (United States of America), Jean-Baptiste \r Sallee (France), Bjorn H. Samset (Norway), Sonia I. Seneviratne (Switzerland), Jana Sillmann (Norway/\r Germany), Anna A. Sorensson (Argentina), Tannecia S. Stephenson (Jamaica), Trude Storelvmo (Norway), \r Sophie Szopa (France), Peter W. Thorne (Ireland/United Kingdom), Blair Trewin (Australia), Robert Vautard \r (France), Carolina Vera (Argentina), Noureddine Yassaa (Algeria), Sonke Zaehle (Germany), Panmao Zhai \r (China), Xuebin Zhang (Canada), Kirsten Zickfeld (Canada/Germany)"


id: 8bf3f4a9ab48065656721a74aef0e672
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"Krishna M. AchutaRao (India), Bhupesh Adhikary (Nepal), Edvin Aldrian (Indonesia), Kyle Armour (United \r States of America), Govindasamy Bala (India/United States of America), Rondrotiana Barimalala (South \r Africa/Madagascar), Nicolas Bellouin (United Kingdom/France), William Collins (United Kingdom), \r William D. Collins (United States of America), Susanna Corti (Italy), Peter M. Cox (United Kingdom), \r Frank J. Dentener (EU/The Netherlands), Claudine Dereczynski (Brazil), Alejandro Di Luca (Australia, \r Canada/Argentina), Alessandro Dosio (Italy), Leah Goldfarb (France/United States of America), Irina \r V. Gorodetskaya (Portugal/Belgium, Russian Federation), Pandora Hope (Australia), Mark Howden \r (Australia), A.K.M Saiful Islam (Bangladesh), Yu Kosaka (Japan), James Kossin (United States of America), \r Svitlana Krakovska (Ukraine), Chao Li (China), Jian Li (China), Thorsten Mauritsen (Germany/Denmark), \r [...]"


id: 5ffa0a9e53e3d9df1d092f347ff9410e
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"[...] Sebastian Milinski (Germany), Seung-Ki Min (Republic of Korea), Thanh Ngo Duc (Vietnam), Andy \r Reisinger (New Zealand), Lucas Ruiz (Argentina), Shubha Sathyendranath (United Kingdom/Canada, \r Overseas Citizen of India), Aimee B. A. Slangen (The Netherlands), Chris Smith (United Kingdom), Izuru \r Takayabu (Japan), Muhammad Irfan Tariq (Pakistan), Anne-Marie Treguier (France), Bart van den Hurk \r (The Netherlands), Karina von Schuckmann (France/Germany), Cunde Xiao (China)"


id: 523b96c55fa265c149f810436ea405e8
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"Panel (b) Evidence from attribution studies, which synthesize information from climate models and observations. The panel shows temperature \r change attributed to: total human influence; changes in well-mixed greenhouse gas concentrations; other human drivers due to aerosols, ozone and land-use \r change (land-use reflectance); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges.\r Panel (c) Evidence from the assessment of radiative forcing and climate sensitivity. The panel shows temperature changes from individual components \r of human influence: emissions of greenhouse gases, aerosols and their precursors; land-use changes (land-use reflectance and irrigation); and aviation contrails. \r Whiskers show very likely ranges. Estimates account for both direct emissions into the atmosphere and their effect, if any, on other climate drivers. For aerosols, \r [...]"


id: 780410b0723c940e978594b05680311
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"[...] both direct effects (through radiation) and indirect effects (through interactions with clouds) are considered. \r {Cross-Chapter Box 2.3, 3.3.1, 6.4.2, 7.3}"


id: 6fb6883e9c9604d20d2758c3eee7e4f7
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content:
"IPCC AR6 WGI reference regions: North America: NWN (North-Western North America, NEN (North-Eastern North America), WNA \r (Western North America), CNA (Central North America), ENA (Eastern North America), Central America: NCA (Northern Central America), \r SCA (Southern Central America), CAR (Caribbean), South America: NWS (North-Western South America), NSA (Northern South America), NES \r (North-Eastern South America), SAM (South American Monsoon), SWS (South-Western South America), SES (South-Eastern South America), \r SSA (Southern South America), Europe: GIC (Greenland/Iceland), NEU (Northern Europe), WCE (Western and Central Europe), EEU (Eastern \r Europe), MED (Mediterranean), Africa: MED (Mediterranean), SAH (Sahara), WAF (Western Africa), CAF (Central Africa), NEAF (North Eastern \r Africa), SEAF (South Eastern Africa), WSAF (West Southern Africa), ESAF (East Southern Africa), MDG (Madagascar), Asia: RAR (Russian \r [...]"


id: 614ea32b6fdddd3e3d1d39384efe96ce
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"[...] Arctic), WSB (West Siberia), ESB (East Siberia), RFE (Russian Far East), WCA (West Central Asia), ECA (East Central Asia), TIB (Tibetan Plateau), \r EAS (East Asia), ARP (Arabian Peninsula), SAS (South Asia), SEA (South East Asia), Australasia: NAU (Northern Australia), CAU (Central \r Australia), EAU (Eastern Australia), SAU (Southern Australia), NZ (New Zealand), Small Islands: CAR (Caribbean), PAC (Pacific Small Islands)"


id: 7230bc668dd2762e76a182a5fb896351
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"The IPCC AR6 WGI inhabited regions are displayed as hexagons with identical size in their approximate geographical location (see legend for regional acronyms). \r All assessments are made for each region as a whole and for the 1950s to the present. Assessments made on different time scales or more local spatial scales might \r differ from what is shown in the figure. The colours in each panel represent the four outcomes of the assessment on observed changes. Striped hexagons (white \r and light-grey) are used where there is low agreement in the type of change for the region as a whole, and grey hexagons are used when there is limited data and/\r or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium confidence in the observed change. The confidence \r level for the human influence on these observed changes is based on assessing trend detection and attribution and event attribution literature, and it is indicated \r [...]"


id: ae70ac46c4706c47a5cd93ec6d734948
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"[...] by the number of dots: three dots for high confidence, two dots for medium confidence and one dot for low confidence (single, filled dot: limited agreement; single, \r empty dot: limited evidence)."


id: 4751fd606de98cfb8510f38207e04786
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"Box SPM.1.1: This Report assesses the climate response to five illustrative scenarios that cover the range of possible future \r development of anthropogenic drivers of climate change found in the literature. They start in 2015, and include scenarios22\r with high and very high GHG emissions (SSP3-7.0 and SSP5-8.5) and CO2 emissions that roughly double from current \r levels by 2100 and 2050, respectively, scenarios with intermediate GHG emissions (SSP2-4.5) and CO2 emissions remaining \r around current levels until the middle of the century, and scenarios with very low and low GHG emissions and CO2 emissions \r declining to net zero around or after 2050, followed by varying levels of net negative CO2 emissions23 (SSP1-1.9 and \r SSP1-2.6), as illustrated in Figure SPM.4. Emissions vary between scenarios depending on socio-economic assumptions, \r levels of climate change mitigation and, for aerosols and non-methane ozone precursors, air pollution controls. Alternative \r [...]"


id: 4c5602207a5f9dcb912c44d7908a9cfe
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"[...] assumptions may result in similar emissions and climate responses, but the socio-economic assumptions and the feasibility \r or likelihood of individual scenarios are not part of the assessment. \r {1.6, Cross-Chapter Box 1.4, TS.1.3} (Figure SPM.4)"


id: c482d2d34c3a31bb87b351ea05eef654
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"Box SPM.1.2: This Report assesses results from climate models participating in the Coupled Model Intercomparison Project \r Phase 6 (CMIP6) of the World Climate Research Programme. These models include new and better representations of \r physical, chemical and biological processes, as well as higher resolution, compared to climate models considered in previous \r IPCC assessment reports. This has improved the simulation of the recent mean state of most large-scale indicators of climate \r change and many other aspects across the climate system. Some differences from observations remain, for example in \r regional precipitation patterns. The CMIP6 historical simulations assessed in this Report have an ensemble mean global \r surface temperature change within 0.2degC of the observations over most of the historical period, and observed warming is \r within the very likely range of the CMIP6 ensemble. However, some CMIP6 models simulate a warming that is either above \r [...]"


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"Panel (b) Warming contributions by groups of anthropogenic drivers and by scenario are shown as the change in global surface \r temperature (degC) in 2081-2100 relative to 1850-1900, with indication of the observed warming to date. Bars and whiskers represent median values \r and the very likely range, respectively. Within each scenario bar plot, the bars represent: total global warming (degC; 'total' bar) (see Table SPM.1); warming \r contributions (degC) from changes in CO2 ('CO2' bar) and from non-CO2 greenhouse gases (GHGs; 'non-CO2 GHGs' bar: comprising well-mixed greenhouse \r gases and ozone); and net cooling from other anthropogenic drivers ('aerosols and land use' bar: anthropogenic aerosols, changes in reflectance due to \r land-use and irrigation changes, and contrails from aviation) (see Figure SPM.2, panel c, for the warming contributions to date for individual drivers). The \r [...]"


id: e7c73a527f70b8e5e17f098dff9970e7
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"[...] best estimate for observed warming in 2010-2019 relative to 1850-1900 (see Figure SPM.2, panel a) is indicated in the darker column in the 'total' bar. \r Warming contributions in panel (b) are calculated as explained in Table SPM.1 for the total bar. For the other bars, the contribution by groups of drivers is \r calculated with a physical climate emulator of global surface temperature that relies on climate sensitivity and radiative forcing assessments.\r {Cross-Chapter Box 1.4; 4.6; Figure 4.35; 6.7; Figures 6.18, 6.22 and 6.24; 7.3; Cross-Chapter Box 7.1; Figure 7.7; Box TS.7; Figures TS.4 and TS.15}"


id: 3e18285085ae8c28986d1cab8edeb5cb
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"Panel (a) Comparison of observed and simulated annual mean surface temperature change. The left map shows the observed changes in annual \r mean surface temperature in the period 1850-2020 per degC of global warming (degC). The local (i.e., grid point) observed annual mean surface temperature changes \r are linearly regressed against the global surface temperature in the period 1850-2020. Observed temperature data are from Berkeley Earth, the dataset with \r the largest coverage and highest horizontal resolution. Linear regression is applied to all years for which data at the corresponding grid point is available. The \r regression method was used to take into account the complete observational time series and thereby reduce the role of internal variability at the grid point level. \r White indicates areas where time coverage was 100 years or less and thereby too short to calculate a reliable linear regression. The right map is based on model \r [...]"


id: 4b819491bad76384c8127bd7e402f94c
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"[...] simulations and shows change in annual multi-model mean simulated temperatures at a global warming level of 1degC (20-year mean global surface temperature \r change relative to 1850-1900). The triangles at each end of the colour bar indicate out-of-bound values, that is, values above or below the given limits."


id: 5be6e6be088cd9b62573c2a74db32f93
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"In panel (c), high positive percentage changes in dry regions may correspond to small absolute changes. In panel (d), the unit is the standard deviation \r of interannual variability in soil moisture during 1850-1900. Standard deviation is a widely used metric in characterizing drought severity. A projected \r reduction in mean soil moisture by one standard deviation corresponds to soil moisture conditions typical of droughts that occurred about once every six years \r during 1850-1900. In panel (d), large changes in dry regions with little interannual variability in the baseline conditions can correspond to small absolute \r change. The triangles at each end of the colour bars indicate out-of-bound values, that is, values above or below the given limits. Results from all models \r reaching the corresponding warming level in any of the five illustrative scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are averaged. \r [...]"


id: a90b517e36fce30ab073499b5c0475ca
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"[...] Maps of annual mean temperature and precipitation changes at a global warming level of 3degC are available in Figure 4.31 and Figure 4.32 in Section 4.6.\r Corresponding maps of panels (b), (c) and (d), including hatching to indicate the level of model agreement at grid-cell level, are found in Figures 4.31, 4.32 and \r 11.19, respectively; as highlighted in Cross-Chapter Box Atlas.1, grid-cell level hatching is not informative for larger spatial scales (e.g., over AR6 reference regions) \r where the aggregated signals are less affected by small-scale variability, leading to an increase in robustness."


id: e1592fc351c470f4e76225c945d3b163
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"was exceeded on average once in a decade during the 1850-1900 reference period. Agricultural and ecological drought events are defined as the annual \r average of total column soil moisture below the 10th percentile of the 1850-1900 base period. These extremes are defined on model grid box scale. For hot \r temperature extremes and extreme precipitation, results are shown for the global land. For agricultural and ecological drought, results are shown for drying regions \r only, which correspond to the AR6 regions in which there is at least medium confidence in a projected increase in agricultural and ecological droughts at the 2degC \r warming level compared to the 1850-1900 base period in the Coupled Model Intercomparison Project Phase 6 (CMIP6). These regions include Western North \r America, Central North America, Northern Central America, Southern Central America, Caribbean, Northern South America, North-Eastern South America, South \r [...]"


id: 6f172d8d2242a009072e82c6e2edb42d
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"[...] American Monsoon, South-Western South America, Southern South America, Western and Central Europe, Mediterranean, West Southern Africa, East Southern \r Africa, Madagascar, Eastern Australia, and Southern Australia (Caribbean is not included in the calculation of the figure because of the too-small number of full land \r grid cells). The non-drying regions do not show an overall increase or decrease in drought severity. Projections of changes in agricultural and ecological droughts \r in the CMIP Phase 5 (CMIP5) multi-model ensemble differ from those in CMIP6 in some regions, including in parts of Africa and Asia. Assessments of projected \r changes in meteorological and hydrological droughts are provided in Chapter 11. \r In the 'frequency' section, each year is represented by a dot. The dark dots indicate years in which the extreme threshold is exceeded, while light dots are years \r [...]"


id: f21a64cce105db398149203be7285e91
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"[...] when the threshold is not exceeded. Values correspond to the medians (in bold) and their respective 5-95% range based on the multi-model ensemble from \r simulations of CMIP6 under different Shared Socio-economic Pathway scenarios. For consistency, the number of dark dots is based on the rounded-up median. \r In the 'intensity' section, medians and their 5-95% range, also based on the multi-model ensemble from simulations of CMIP6, are displayed as dark and \r light bars, respectively. Changes in the intensity of hot temperature extremes and extreme precipitation are expressed as degree Celsius and percentage. As for \r agricultural and ecological drought, intensity changes are expressed as fractions of standard deviation of annual soil moisture. \r {11.1; 11.3; 11.4; 11.6; 11.9; Figures 11.12, 11.15, 11.6, 11.7, and 11.18}"


id: c0d4598959999c58edf5a08fc78151c9
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"The bar chart illustrates the projected amount of cumulative anthropogenic CO2 emissions (GtCO2) between 1850 and 2100 remaining in the atmosphere (grey \r part) and taken up by the land and ocean (coloured part) in the year 2100. The doughnut chart illustrates the proportion of the cumulative anthropogenic \r CO2 emissions taken up by the land and ocean sinks and remaining in the atmosphere in the year 2100. Values in % indicate the proportion of the cumulative \r anthropogenic CO2 emissions taken up by the combined land and ocean sinks in the year 2100. The overall anthropogenic carbon emissions are calculated by \r adding the net global land-use emissions from the CMIP6 scenario database to the other sectoral emissions calculated from climate model runs with prescribed CO2\r concentrations.33 Land and ocean CO2 uptake since 1850 is calculated from the net biome productivity on land, corrected for CO2 losses due to land-use change by \r [...]"


id: 435312db893c3e1d70f046590139ecb6
created_at: 2023-04-19 13:22:33
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"Panel (c) Global ocean surface pH (a measure of acidity) based on CMIP6 model simulations. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0.\r Panel (d) Global mean sea level change in metres, relative to 1900. The historical changes are observed (from tide gauges before 1992 and altimeters \r afterwards), and the future changes are assessed consistently with observational constraints based on emulation of CMIP, ice-sheet, and glacier models. Likely\r ranges are shown for SSP1-2.6 and SSP3-7.0. Only likely ranges are assessed for sea level changes due to difficulties in estimating the distribution of deeply \r uncertain processes. The dashed curve indicates the potential impact of these deeply uncertain processes. It shows the 83rd percentile of SSP5-8.5 projections that \r include low-likelihood, high-impact ice-sheet processes that cannot be ruled out; because of low confidence in projections of these processes, this curve does not \r [...]"


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created_at: 2023-04-19 13:22:33
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content:
"[...] constitute part of a likely range. Changes relative to 1900 are calculated by adding 0.158 m (observed global mean sea level rise from 1900 to 1995-2014) to \r simulated and observed changes relative to 1995-2014."


id: 999600f4a5dc8b5c005eb30c6be3d0e6
created_at: 2023-04-19 13:22:33
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content:
"Top panel: Historical data (thin black line) shows observed global surface temperature increase in degC since 1850-1900 as a function of historical cumulative carbon \r dioxide (CO2) emissions in GtCO2 from 1850 to 2019. The grey range with its central line shows a corresponding estimate of the historical human-caused surface \r warming (see Figure SPM.2). Coloured areas show the assessed very likely range of global surface temperature projections, and thick coloured central lines show the \r median estimate as a function of cumulative CO2 emissions from 2020 until year 2050 for the set of illustrative scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and \r SSP5-8.5; see Figure SPM.4). Projections use the cumulative CO2 emissions of each respective scenario, and the projected global warming includes the contribution \r from all anthropogenic forcers. The relationship is illustrated over the domain of cumulative CO2 emissions for which there is high confidence that the transient climate \r [...]"


id: a195606944b6ccdd7e436fc1dfe77119
created_at: 2023-04-19 13:22:33
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"[...] response to cumulative CO2 emissions (TCRE) remains constant, and for the time period from 1850 to 2050 over which global CO2 emissions remain net positive under \r all illustrative scenarios, as there is limited evidence supporting the quantitative application of TCRE to estimate temperature evolution under net negative CO2 emissions.\r Bottom panel: Historical and projected cumulative CO2 emissions in GtCO2 for the respective scenarios.\r {Section 5.5, Figure 5.31, Figure TS.18}"


id: f37999c685e2ddac9f82d6772d41e2e0
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"Krishna Achuta Rao (India), Bhupesh Adhikary (Nepal), Richard P. Allan (United Kingdom), \r Kyle Armour (United States of America), Govindasamy Bala (India/United States of America), \r Rondrotiana Barimalala (South Africa/Madagascar), Sophie Berger (France/Belgium), \r Josep G. Canadell (Australia), Christophe Cassou (France), Annalisa Cherchi (Italy), William Collins \r (United Kingdom), William D. Collins (United States of America), Sarah L. Connors (France/United \r Kingdom), Susanna Corti (Italy), Faye Cruz (Philippines), Frank J. Dentener (EU/The Netherlands), \r Claudine Dereczynski (Brazil), Alejandro Di Luca (Australia, Canada/Argentina), Aida Diongue \r Niang (Senegal), Francisco J. Doblas-Reyes (Spain), Alessandro Dosio (Italy), Herve Douville (France), \r Francois Engelbrecht (South Africa), Veronika Eyring (Germany), Erich Fischer (Switzerland), Piers \r Forster (United Kingdom), Baylor Fox-Kemper (United States of America), Jan  S. Fuglestvedt \r [...]"


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"[...] (Norway), John C. Fyfe (Canada), Nathan P. Gillett (Canada), Leah Goldfarb (France/United States \r of America), Irina Gorodetskaya (Portugal/Russian Federation, Belgium), Jose Manuel Gutierrez \r (Spain), Rafiq Hamdi (Belgium), Ed Hawkins (United Kingdom), Helene T. Hewitt (United Kingdom), \r Pandora Hope (Australia), AKM Saiful Islam (Bangladesh), Christopher Jones (United Kingdom), \r Darrell S.  Kaufman (United States of America), Robert E.  Kopp (United States of America), \r Yu  Kosaka (Japan), James Kossin (United States of America), Svitlana  Krakovska (Ukraine), \r June-Yi Lee (Republic of Korea), Jian Li (China), Thorsten Mauritsen (Sweden, Denmark), Thomas \r K. Maycock (United States of America), Malte Meinshausen (Australia/Germany), Seung-Ki Min \r (Republic of Korea), Pedro M. S. Monteiro (South Africa), Thanh Ngo-Duc (Vietnam), Friederike \r Otto (United Kingdom/Germany), Izidine Pinto (South Africa/Mozambique), Anna Pirani (Italy), \r [...]"


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"[...] Krishnan Raghavan (India), Roshanka Ranasinghe (The Netherlands/Sri Lanka, Australia), Alex \r C. Ruane (United States of America), Lucas Ruiz (Argentina), Jean-Baptiste Sallee (France), Bjorn \r H. Samset (Norway), Shubha Sathyendranath (UK/Canada, United Kingdom, Overseas Citizen of \r India), Sonia I. Seneviratne (Switzerland), Anna A. Sorensson (Argentina), Sophie Szopa (France), \r Izuru Takayabu (Japan), Anne-Marie Treguier (France), Bart van den Hurk (The Netherlands), "


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"Gudfinna Adalgeirsdottir (Iceland), Lincoln M. Alves (Brazil), Terje Berntsen (Norway), \r Sara M. Blichner (Norway), Lisa Bock (Germany), Gregory G. Garner (United States of America), \r Joelle Gergis (Australia), Sergey K. Gulev (Russian Federation), Mathias Hauser (Switzerland), \r Flavio Lehner (United States of America/Switzerland), Chao Li (China), Marianne T. Lund \r (Norway), Daniel J. Lunt (United Kingdom), Sebastian Milinski (Germany), Gemma Teresa \r Narisma (Philippines), Zebedee R. J. Nicholls (Australia), Dirk Notz (Germany), Sophie Nowicki \r (United States of America/France, United States of America), Bette Otto-Bliesner (United States \r of America), Brodie Pearson (United States of America/United Kingdom), Adam S. Phillips \r (United States of America), James Renwick (New Zealand), Stephane Senesi (France), Lucas Silva \r (Portugal/Switzerland), Aimee B. A. Slangen (The Netherlands), Thomas F. Stocker (Switzerland), \r [...]"


id: 56b907e93f4c4365bdc72434edccff92
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 12508
content:
"[...] Claudia Tebaldi (United States of America), Laurent Terray (France), Sabin Thazhe Purayil (India), \r Andrew Turner (United Kingdom), Steven Turnock (United Kingdom), Carolina Vera (Argentina), \r Cunde Xiao (China), Panmao Zhai (China)"


id: 8518a3dfa6a6bc3e2dc417bf86181905
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 20560
content:
"Arias, P.A., N. Bellouin, E. Coppola, R.G. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, G.-K. Plattner, J. Rogelj, \r M. Rojas, J. Sillmann, T. Storelvmo, P.W. Thorne, B. Trewin, K. Achuta Rao, B. Adhikary, R.P. Allan, K. Armour, G. Bala, \r R. Barimalala, S. Berger, J.G. Canadell, C. Cassou, A. Cherchi, W. Collins, W.D. Collins, S.L. Connors, S. Corti, F. Cruz, \r F.J. Dentener, C. Dereczynski, A. Di Luca, A. Diongue Niang, F.J. Doblas-Reyes, A. Dosio, H. Douville, F. Engelbrecht, \r V.  Eyring, E. Fischer, P. Forster, B. Fox-Kemper, J.S. Fuglestvedt, J.C. Fyfe, N.P. Gillett, L. Goldfarb, I. Gorodetskaya, \r J.M. Gutierrez, R. Hamdi, E. Hawkins, H.T. Hewitt, P. Hope, A.S. Islam, C. Jones, D.S. Kaufman, R.E. Kopp, Y. Kosaka, \r J.  Kossin, S.  Krakovska, J.-Y. Lee, J. Li, T. Mauritsen, T.K. Maycock, M. Meinshausen, S.-K. Min, P.M.S. Monteiro, \r T.  Ngo-Duc, F.  Otto, I. Pinto, A. Pirani, K. Raghavan, R. Ranasinghe, A.C. Ruane, L. Ruiz, J.-B. Sallee, B.H. Samset, \r [...]"


id: 179eb6175292f2155ffa9ae46ddee155
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1362
content:
"[...] S. Sathyendranath, S.I. Seneviratne, A.A. Sorensson, S. Szopa, I. Takayabu, A.-M. Treguier, B. van den Hurk, R. Vautard, \r K. von Schuckmann, S. Zaehle, X. Zhang, and K. Zickfeld, 2021: Technical Summary. In Climate Change 2021: The \r Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental \r Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Pean, S. Berger, N. Caud, Y. Chen, \r L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekci, R. Yu, \r and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 33-144. \r doi:10.1017/9781009157896.002."


id: 86e2e125f97efa19fee5d15668dec714
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index: climate_gpt_v2
vector_id: 20896
content:
"The Report has been peer-reviewed by the scientific community \r and governments (Annex X provides the Expert Reviewer list). The \r substantive introduction provided by Chapter 1 is followed by a first \r set of chapters dedicated to large-scale climate knowledge (Chapters \r 2-4), which encompasses observations and paleoclimate evidence, \r causes of observed changes, and projections; these are complemented \r by Chapter 11 for large-scale changes in extremes. The second set of \r chapters (Chapters 5-9) is orientated around the understanding of \r key climate system components and processes, including the global \r cycles of carbon, energy and water; short-lived climate forcers and their \r link to air quality; and the ocean, cryosphere and sea level change. \r The last set of chapters (Chapters 10-12 and the Atlas) is dedicated to \r the assessment and distillation of regional climate information from \r multiple lines of evidence at sub-continental to local scales (including \r [...]"


id: fd3c77e907124ddd9ffc40a33af7eeda
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index: climate_gpt_v2
vector_id: 41902
content:
"[...] urban climate), with a focus on recent and projected regional changes \r in mean climate, extremes, and climatic impact-drivers. The new online "


id: 76b301ee18ce1034d39c6a3575042c7f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18098
content:
"This Report assesses new scientific evidence relevant \r for a world whose climate system is rapidly changing, \r overwhelmingly due to human influence. The five IPCC \r assessment cycles since 1990 have comprehensively and \r consistently laid out the rapidly accumulating evidence \r of a changing climate system, with the Fourth Assessment \r Report in 2007 being the first to conclude that warming \r of the climate system is unequivocal. Sustained changes \r have been documented in all major elements of the climate \r system: the atmosphere, land, cryosphere, biosphere and \r ocean (Section TS.2). Multiple lines of evidence indicate \r the recent large-scale climatic changes are unprecedented \r in a multi-millennial context and that they represent \r a  millennial-scale commitment for the slow-responding \r elements of the climate system, resulting in continued \r worldwide loss of ice, increase in ocean heat content, sea \r level rise and deep ocean acidification (Box TS.2; Section \r [...]"


id: 56a432c070b7965fbccb61a9cd845de1
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 12499
content:
"[...] TS.2). {1.2.1, 1.3, Box 1.2, 2.2, 2.3, Figure 2.34, 5.1, 5.3, 9.2, \r 9.4-9.6, Appendix 1.A}"


id: f8047ca2e293bb98f63e18ffd652f060
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 41005
content:
"Paleoclimate evidence is integrated within multiple lines of evidence across the WGI Report to more fully understand \r the climate system. Paleo evidence extends instrument-based observations of climate variables and climate drivers \r back in time, providing the long-term context needed to gauge the extent to which recent and potential future \r changes are unusual (Section TS.2, Figure TS.1). Pre-industrial climate states complement evidence from climate model \r projections by providing real-world examples of climate characteristics for past global warming levels, with empirical \r evidence for how the slow-responding components of the climate system operate over centuries to millennia - the \r time scale for committed climate change (Core Concepts Box, Box TS.4, Box TS.9). Information about the state of \r the climate system during well-described paleoclimate reference periods helps narrow the uncertainty range in the \r [...]"


id: e37896c3cecdfc98205b22d54052df16
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37316
content:
"[...] overall assessment of Earth's sensitivity to climate forcing (Section TS.3.2.1). {Cross-Chapter Box 2.1, FAQ 1.3, FAQ 2.1}"


id: 2a6c168c7e88185d38f7664f832912e1
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 4689
content:
"Sea level and ice sheets. Although past and future global warming differ in their forcings, evidence from paleoclimate \r records and modelling show that ice-sheet mass and global mean sea level (GMSL) responded dynamically over multiple millennia \r (high confidence). This evidence helps to constrain estimates of the committed GMSL response to global warming (Box TS.4). For \r example, under a past global warming levels of around [2.5degC to 4degC] relative to 1850-1900, like during the mid-Pliocene Warm \r Period, sea level was [5 to 25 m] higher than 1900 (medium confidence); under past global warming levels of [10degC to 18degC], like \r during the Early Eocene, the planet was essentially ice free (high confidence). Constraints from these past warm periods, combined \r with physical understanding, glaciology and modelling, indicate a committed long-term GMSL rise over 10,000 years, reaching about \r [...]"


id: 1a854557eafa42bd05c9545a2e983470
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1867
content:
"[...] 8 to 13 m for sustained peak global warming of 2degC and up to 28 to 37 m for 5degC, which exceeds the AR5 estimate. {2.3.3.3, 9.4.1.4, \r 9.4.2.6, 9.6.2, 9.6.3.5}"


id: 7b77a983a4c55a604f4d6416d2aadf18
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18927
content:
"Ocean. Since AR5, better integration of paleo-oceanographic data with modelling along with higher-resolution analyses of \r transient changes have improved understanding of long-term ocean processes. Low-latitude sea surface temperatures at the Last \r Glacial Maximum cooled more than previously inferred, resolving some inconsistencies noted in AR5. This paleo context supports \r the assessment that ongoing increase in ocean heat content (OHC) represents a long-term commitment (see Core Concepts Box), \r essentially irreversible on human time scales (high confidence). Estimates of past global OHC variations generally track those of \r sea surface temperatures around Antarctica, underscoring the importance of Southern Ocean processes in regulating deep-ocean \r temperatures. Paleoclimate data, along with other evidence of glacial-interglacial changes, show that Antarctic Circumpolar flow \r [...]"


id: 477b8311a82ab7cbb46eab1d0909b28a
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 9793
content:
"[...] strengthened and that ventilation of Antarctic Bottom Water accelerated during warming intervals, facilitating release of CO2 stored in \r the deep ocean to the atmosphere. Paleo evidence suggests significant reduction of deep-ocean ventilation associated with meltwater \r input during times of peak warmth. {2.3.1.1, 2.3.3.1, 9.2.2, 9.2.3.2}"


id: d29dc2a97ae31b993da33e2b97bb9585
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 34403
content:
"satellite measurement techniques are now long enough to be \r relevant for climate assessments. For example, globally distributed, \r high-vertical-resolution profiles of temperature and humidity in the \r upper troposphere and stratosphere can be obtained from the early \r 2000s using global navigation satellite systems, leading to updated \r estimates of recent atmospheric warming. Improved measurements \r of ocean heat content, warming of the land surface, ice-sheet mass \r loss and sea level changes allow a better closure of the global \r energy and sea level budgets relative to AR5. For surface and \r balloon-based networks, apparent regional data reductions result \r from a combination of data policy issues, data curation/provision \r challenges, and real cessation of observations, and are to an extent \r counter-balanced by improvements elsewhere. Limited observational \r records of extreme events and spatial data gaps currently limit the \r [...]"


id: 1da3b75daa8a48e9069a9c7126a43b64
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 2400
content:
"[...] assessment of some observed regional climate change. {1.5.1, 2.3.2, \r 7.2.2, Box 7.2, Cross-Chapter Box 9.1, 9.6.1, 10.2.2, 10.6, 11.2, 12.4}"


id: c62be5408cab42fd9d8f3062d0e4b3b3
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32174
content:
"Reanalyses combine observations and models (e.g., a numerical \r weather prediction model) using data assimilation techniques to \r provide a spatially complete, dynamically consistent estimate of \r multiple variables describing the evolving climate state. Since AR5, \r new reanalyses have been developed for the atmosphere and the \r ocean with various combinations of increased resolution, extended \r records, more consistent data assimilation and larger availability \r of uncertainty estimates. Limitations remain, for example, in how \r reanalyses represent global-scale changes to the water cycle. Regional \r reanalyses use high-resolution, limited-area models constrained by \r regional observations and with boundary conditions from global \r reanalyses. There is high confidence that regional reanalyses better \r represent the frequencies of extremes and variability in precipitation, \r surface air temperature and surface wind than global reanalyses \r [...]"


id: acc538eee0f14aca7f3866c8de1eba17
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 27637
content:
"[...] and provide estimates that are more consistent with independent \r observations than dynamical downscaling approaches. {1.5.2, \r 10.2.1.2, Annex I}"


id: c0a2e759c64bf0547f5b140f9abbaa34
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31191
content:
"Climate model simulations coordinated and collected as part of the \r World Climate Research Programme's Coupled Model Intercomparison \r Project Phase 6 (CMIP6), complemented by a range of results from \r the previous phase (CMIP5), constitute a key line of evidence \r supporting this Report. The latest generation of CMIP6 models have \r an improved representation of physical processes relative to previous \r generations, and a wider range of Earth system models now represent \r biogeochemical cycles. Higher-resolution models that better capture \r smaller-scale processes are also increasingly becoming available \r for climate change research (Figure TS.2, Panels a and b). Results \r from coordinated regional climate modelling initiatives, such as the \r Coordinated Regional Climate Downscaling Experiment (CORDEX) \r complement and add value to the CMIP global models, particularly in \r complex topography zones, coastal areas and small islands, as well \r [...]"


id: fd7be23973915e66a222aaf6dbc702fd
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 41951
content:
"[...] as for extremes. {1.5.3, 1.5.4, 2.8.2, FAQ 3.3, 6.2.2, 6.4, 6.4.5, 8.5.1, \r 10.3.3, Atlas.1.4}"


id: 55079ffd7dab709197a3b4f7a189df8d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 12230
content:
"This report assesses results from climate models \r participating in the Coupled Model Intercomparison Project \r Phase 6 (CMIP6) of the World Climate Research Programme. \r These models include new and better representation of \r physical, chemical and biological processes, as well as \r higher resolution, compared to climate models considered \r in previous IPCC Assessment Reports. This has improved \r the simulation of the recent mean state of most large-scale \r indicators of climate change and many other aspects across \r the climate system. Some differences from observations \r remain, for example in regional precipitation patterns. \r Projections of the increase in global surface temperature, \r the pattern of warming, and global mean sea level rise \r from previous IPCC Assessment Reports and other studies \r are broadly consistent with subsequent observations, \r especially when accounting for the difference in radiative \r forcing scenarios used for making projections and the \r [...]"


id: 296b7ddace3417c3ad35243312a5aa3e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 4506
content:
"Some CMIP6 models demonstrate an improvement in how clouds \r are represented. CMIP5 models commonly displayed a negative \r shortwave cloud radiative effect that was too weak in the present \r climate. These errors have been reduced, especially over the \r Southern Ocean, due to a more realistic simulation of supercooled \r liquid droplets with sufficient numbers and an associated increase \r in the cloud optical depth. Because a negative cloud optical depth \r feedback in response to surface warming results from 'brightening' \r of clouds via active phase change from ice to liquid cloud particles \r (increasing their shortwave cloud radiative effect), the extratropical \r cloud shortwave feedback in CMIP6 models tends to be less negative, \r leading to a better agreement with observational estimates (medium \r confidence). CMIP6 models generally represent more processes \r that drive aerosol-cloud interactions than the previous generation \r [...]"


id: 1bd81c6fb3e89ef999d3115801b3201e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 2086
content:
"[...] of climate models, but there is only medium confidence that those \r enhancements improve their fitness-for-purpose of simulating \r radiative forcing of aerosol-cloud interactions. {6.4, 7.4.2, FAQ 7.2}"


id: cc699d036877a41895aab15784745e09
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 33280
content:
"CMIP6 models are able to reproduce most aspects of the spatial \r structure and variance of the El Nino-Southern Oscillation (ENSO) \r and Indian Ocean Basin and Dipole modes of variability (medium \r confidence). However, despite a slight improvement in CMIP6, some \r underlying processes are still poorly represented. Models reproduce \r observed spatial features and variance of the Southern Annular \r Mode (SAM) and Northern Annular Mode (NAM) very well (high \r confidence). The summertime SAM trend is well captured, with \r CMIP6 models outperforming CMIP5 models (medium confidence). \r By contrast, the cause of the NAM trend towards its positive phase \r is not well understood. In the Tropical Atlantic basin, which contains \r the Atlantic Zonal and Meridional modes, major biases in modelled \r mean state and variability remain. Model performance is limited in \r reproducing sea surface temperature anomalies for decadal modes \r of variability, despite improvements from CMIP5 to CMIP6 (medium \r [...]"


id: c695fd454cf9b5839ef0eab06aba5461
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32241
content:
"Two important quantities used to estimate how the climate system \r responds to changes in greenhouse gas (GHG) concentrations are the \r equilibrium climate sensitivity (ECS) and transient climate response \r (TCR16). The CMIP6 ensemble has broader ranges of ECS and TCR \r values than CMIP5 (see Section TS.3.2 for the assessed range). These \r higher sensitivity values can, in some models, be traced to changes \r in extratropical cloud feedbacks (medium confidence). To combine \r evidence from CMIP6 models and independent assessments of ECS \r and TCR, various emulators are used throughout the report. Emulators \r are a broad class of simple climate models or statistical methods \r that reproduce the behaviour of complex ESMs to represent key \r characteristics of the climate system, such as global surface temperature \r and sea level projections. The main application of emulators in AR6 \r is to extrapolate insights from ESMs and observational constraints to \r [...]"


id: 4a5b0c93ab139f24fef1c66d4adda76a
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content:
"[...] produce projections from a larger set of emissions scenarios, which \r is achieved due to their computational efficiency. These emulated \r projections are also used for scenario classification in WGIII. {Box 4.1, \r 4.3.4, 7.4.2, 7.5.6, Cross-Chapter Box 7.1, FAQ 7.2}"


id: 38f7b28570c39b047ba74eb8afba9093
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content_type: text
index: climate_gpt_v2
vector_id: 7227
content:
"Observational datasets have been extended and improved since \r AR5, providing stronger evidence that the climate is changing and \r allowing better estimates of natural climate variability on decadal \r time scales. There is very high confidence that the slower rate of global \r surface temperature change observed over 1998-2012 compared to \r 1951-2012 was temporary, and was, with high confidence, induced \r by internal variability (particularly Pacific Decadal Variability) and \r variations in solar irradiance and volcanic forcing that partly offset the \r anthropogenic warming over this period. Global ocean heat content \r continued to increase throughout this period, indicating continuous \r warming of the entire climate system (very high confidence). Hot \r extremes also continued to increase during this period over land \r (high confidence). Even in a continually warming climate, periods \r of reduced and increased trends in global surface temperature at \r [...]"


id: 1e1abf42ef9aac2daf9452c7cb2a935e
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vector_id: 2495
content:
"[...] decadal time scales will continue to occur in the 21st century (very \r high confidence). {Cross-Chapter Box 3.1, 3.3.1, 3.5.1, 4.6.2, 11.3.2}"


id: a47276db4a194d3d0a039a6949f8ade4
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 26142
content:
"properties, resulting in warming of the atmosphere, ocean \r and land components of the climate system. Other human \r activities influencing climate include the emission of \r aerosols and other short-lived climate forcers, and land-use \r change such as urbanization. Progress in our understanding \r of human influence is gained from longer observational \r datasets, improved paleoclimate information, a stronger \r warming signal since AR5, and improvements in climate \r models, physical understanding and attribution techniques \r (see Core Concepts Box). Since AR5, the attribution to \r human influence has become possible across a wider range \r of climate variables and climatic impact-drivers (CIDs, \r see Core Concepts Box). New techniques and analyses \r drawing on several lines of evidence have provided greater \r confidence in attributing changes in regional weather and \r climate extremes to human influence (high confidence). \r {1.3, 1.5.1, Appendix 1.A, 3.1-3.8, 5.2, 6.4.2, 7.3.5, 7.4.4, \r [...]"


id: 32900dac19d42703ce0503ab868ad4e4
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6154
content:
"Regional climate changes can be moderated or amplified by regional \r forcing from land-use and land-cover changes or from aerosol \r concentrations and other short-lived climate forcers (SLCFs). For \r example, the difference in observed warming trends between cities \r and their surroundings can partly be attributed to urbanization \r (very high confidence). While established attribution techniques \r provide confidence in our assessment of human influence on \r large-scale climate changes (as described in Section TS.2), new \r techniques developed since AR5, including attribution of individual \r events, have provided greater confidence in attributing changes in \r climate extremes to climate change (Box TS.10). Multiple attribution \r approaches support the contribution of human influence to several \r regional multi-decadal mean precipitation changes (high confidence). \r Understanding about past and future changes in weather and climate \r [...]"


id: be03b79f4a555a2ac36f457cda76016d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 30694
content:
"[...] extremes has increased due to better observation-based datasets, \r physical understanding of processes, an increasing proportion "


id: f2cf48ec5dc7f38e8f362343865e8eb5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 40116
content:
"SSP1-1.9 represents the low end of future emissions pathways, \r leading to warming below 1.5degC in 2100 and limited temperature \r overshoot of 1.5degC over the course of the 21st century (see \r Figure TS.6). At the opposite end of the range, SSP5-8.5 represents \r the very high warming end of future emissions pathways from the \r literature. SSP3-7.0 has overall lower GHG emissions than SSP5-8.5 \r but, for example, CO2 emissions still almost double by 2100 compared \r to today's levels. SSP2-4.5 and SSP1-2.6 represent scenarios with \r stronger climate change mitigation and thus lower GHG emissions. \r SSP1-2.6 was designed to limit warming to below 2degC. Infographic \r TS.1 presents a narrative depiction of SSP-related climate futures. \r No likelihood is attached to the scenarios assessed in this Report, \r and the feasibility of specific scenarios in relation to current trends \r is best informed by the WGIII contribution to AR6. In the scenario \r [...]"


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"[...] literature, the plausibility of some scenarios with high CO2 emissions, \r such as RCP8.5 or SSP5-8.5, has been debated in light of recent \r developments in the energy sector. However, climate projections from \r these scenarios can still be valuable because the concentration levels \r reached in RCP8.5 or SSP5-8.5 and corresponding simulated climate \r futures cannot be ruled out. That is because of uncertainty in carbon\u0002cycle feedbacks which, in nominally lower emissions trajectories, can \r result in projected concentrations that are higher than the central \r concentration levels typically used to drive model projections. {1.6.1; \r Cross-Chapter Box 1.4; 4.2.2, 5.4; SROCC; Chapter 3 in WGIII}"


id: 28e30154ca078a09c55ba45eecfbfe1a
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
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content:
"Scenarios in AR6 cover a broader range of emissions futures than \r considered in AR5, including high CO2 emissions scenarios without \r climate change mitigation as well as a low CO2 emissions scenario \r reaching net zero CO2 emissions (see Core Concepts Box) around mid\u0002century. In this Report, a core set of five illustrative scenarios is used \r to explore climate change over the 21st century and beyond (Section \r TS.2). They are labelled SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and \r SSP5-8.517 and span a wide range of radiative forcing levels in 2100. \r They start in 2015 and include scenarios with high and very high \r GHG emissions and CO2 emissions that roughly double from current \r levels by 2100 and 2050, respectively (SSP3-7.0 and SSP5-8.5); \r scenarios with intermediate GHG emissions and CO2 emissions \r remaining around current levels until the middle of the century \r (SSP2-4.5); and scenarios with very low and low GHG emissions and \r [...]"


id: 27669a2531dc993021de841c9dd38559
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"[...] CO2 emissions declining to net zero around or after 2050, followed by \r varying levels of net negative CO2 emissions (SSP1-1.9 and SSP1-2.6). \r These SSP scenarios offer unprecedented detail of input data for ESM \r simulations and allow for a more comprehensive assessment of \r climate drivers and responses, in particular because some aspects, \r such as the temporal evolution of pollutants, emissions or changes in \r land use and land cover, span a broader range in the SSP scenarios \r than in the RCPs used in AR5. Modelling studies utilizing the RCPs \r complement the assessment based on SSP scenarios, for example, "


id: ef0428050231bcbcadd090fc9b0746b7
created_at: 2023-04-19 13:22:33
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"The socio-economic narratives underlying SSP-based scenarios \r differ in their assumed level of air pollution control. Together with \r variations in climate change mitigation stringency, this difference \r strongly affects anthropogenic emissions trajectories of SLCFs, \r some of which are also air pollutants. SSP1 and SSP5 assume strong \r pollution control, projecting a decline of global emissions of ozone \r precursors (except methane; CH4) and of aerosols and most of \r their precursors in the mid- to long term. The reductions due to air \r pollution controls are further strengthened in scenarios that assume \r a marked decarbonization, such as SSP1-1.9 or SSP1-2.6. SSP2-4.5 \r is a medium pollution-control scenario with air pollutant emissions \r following current trends, and SSP3-7.0 is a weak pollution-control \r scenario with strong increases in emissions of air pollutants over the \r 21st century. Methane emissions in SSP-based scenarios vary with \r [...]"


id: 1742dc99c01688b8d72dc71d97742e54
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content:
"[...] the overall climate change mitigation stringency, declining rapidly \r in SSP1-1.9 and SSP1-2.6 but declining only after 2070 in SSP5-8.5. \r SSP trajectories span a wider range of air pollutant emissions than \r considered in the RCP scenarios (see Figure TS.4), reflecting the \r potential for large regional differences in their assumed pollution "


id: d81d7ee03b76f03bde2cf4d9772bf23c
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35323
content:
"Quantifying geographical response patterns of climate \r change at various global warming levels (GWLs), such as \r 1.5degC or 2degC above the 1850-1900 period, is useful for \r characterizing changes in mean climate, extremes and \r climatic impact-drivers. Global warming levels are used \r in this Report as a dimension of integration independent \r of the timing when the warming level is reached and of \r the emissions scenario that led to the warming. For many \r climate variables the response pattern for a given GWL is \r consistent across different scenarios. However, this is not \r the case for slowly responding processes, such as ice-sheet \r and glacier mass loss, deep ocean warming, and the related \r sea level rise. The response of these variables depends on \r the time it takes to reach the GWL, differs if the warming is \r reached in a transient warming state or after a temporary \r overshoot of the warming level, and will continue to evolve, \r [...]"


id: d2b494a9a875f10554b555830fbccb0d
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"[...] over centuries to millennia, even after global warming \r has stabilized. Different GWLs correspond closely to \r specific cumulative CO2 emissions due to their near-linear \r relationship with global surface temperature. This Report \r uses 1.0degC, 1.5degC, 2.0degC, 3.0degC and 4.0degC above 1850-1900 \r conditions as a primary set of GWLs. {1.6.2, 4.2.4, 4.6.1, 5.5, \r Cross-Chapter Box 11.1, Cross-chapter Box 12.1}"


id: 8b728fa9c023cb990da87e419081c0dc
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index: climate_gpt_v2
vector_id: 21694
content:
"Since the RCPs are also labelled by the level of radiative forcing \r they reach in 2100, they can in principle be related to the core set \r of AR6 scenarios (Figure TS.4). However, the RCPs and SSP-based \r scenarios are not directly comparable. First, the gas-to-gas \r compositions differ; for example, the SSP5-8.5 scenario has higher \r CO2 but lower CH4 concentrations compared to RCP8.5. Second, the \r projected 21st-century trajectories may differ, even if they result \r in the same radiative forcing by 2100. Third, the overall effective \r radiative forcing (see Core Concepts Box) may differ, and tends \r to be higher for the SSPs compared to RCPs that share the same \r nominal stratospheric-temperature-adjusted radiative forcing label. \r Comparing the differences between CMIP5 and CMIP6 projections \r (Cross-Section Box TS.1) that were driven by RCPs and SSP-based \r scenarios, respectively, indicates that about half of the difference in \r [...]"


id: fc3e1fde2ec0c88ae078308c06d7a8de
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content:
"[...] simulated warming arises because of higher climate sensitivity being \r more prevalent in CMIP6 model versions; the remainder arises from \r higher ERF in nominally corresponding scenarios (e.g., RCP8.5 and \r SSP5-8.5; medium confidence) (see Section TS.1.2.2). In SSP1-2.6 and \r SSP2-4.5, changes in ERF also explain about half of the changes in the \r range of warming (medium confidence). For SSP5-8.5, higher climate \r sensitivity is the primary reason behind the upper end of the CMIP6-\r projected warming being higher than for RCP8.5 in CMIP5 (medium \r confidence). Note that AR6 uses multiple lines of evidence beyond \r CMIP6 results to assess global surface temperature under various \r scenarios (see Cross-Section Box TS.1 for the detailed assessment). \r {1.6, 4.2.2, 4.6.2.2, Cross-Chapter Box 7.1}"


id: 3e53eff77a7b3f2a4b56abf10e1599c0
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 8140
content:
"Earth system models can be driven by anthropogenic CO2\r emissions ('emissions-driven' runs), in which case atmospheric \r CO2 concentration is a projected variable; or by prescribed time\u0002varying atmospheric concentrations ('concentration-driven' runs). In \r emissions-driven runs, changes in climate feed back on the carbon \r cycle and interactively modify the projected CO2 concentration \r in each ESM, thus adding the uncertainty in the carbon cycle \r response to climate change to the projections. Concentration\u0002driven simulations are based on a central estimate of carbon cycle \r feedbacks, while emissions-driven simulations help quantify the role \r of feedback uncertainty. The differences in the few ESMs for which \r both emissions and concentration-driven runs were available for the \r same scenario are small and do not affect the assessment of global \r surface temperature projections discussed in Cross-Section Box TS.1 \r [...]"


id: d7e04d780b7c052ec8111ff0fb6609e0
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35290
content:
"[...] and Section TS.2 (high confidence). By the end of the 21st century, \r emissions-driven simulations are on average around 0.1degC cooler \r than concentration-driven runs, reflecting the generally lower CO2\r concentrations simulated by the emissions-driven ESMs, and have a \r spread about 0.1degC greater, reflecting the range of simulated CO2\r concentrations. However, these carbon cycle-climate feedbacks do \r affect the transient climate response to cumulative CO2 emissions \r (TCRE18), and their quantification is crucial for the assessment of \r remaining carbon budgets consistent with global warming levels \r simulated by ESMs (see Section TS.3). {1.6.1, Cross-Chapter Box 1.4, \r 4.2, 4.3.1, 5.4.5, Cross-Chapter Box 7.1}"


id: 1db35dfc4a1d27330f9536d42dd860de
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 2410
content:
"resulting increase in global surface temperature (Section TS.3.2). This \r implies that continued CO2 emissions will cause further warming \r and associated changes in all components of the climate system. For \r declining cumulative CO2 emissions (i.e., if negative net emissions \r are achieved), the relationship is less strong for some components, \r such as the hydrological cycle. The WGI report uses cumulative CO2\r emissions to compare climate response across scenarios and provides \r a link to the emissions pathways assessment in WGIII. The advantage \r of using cumulative CO2 emissions is that it is an inherent emissions \r scenario characteristic rather than an outcome of the scenario-based \r projections, where uncertainties in the cause-effect chain from \r emissions to temperature change are important (Figure TS.4), for \r example, the uncertainty in ERF and TCR. Cumulative CO2 emissions \r can also provide a link to the assessments of mitigation options. \r [...]"


id: 9ce31521be4f2c14ec463554c409a31a
created_at: 2023-04-19 13:22:33
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vector_id: 24837
content:
"[...] Cumulative CO2 emissions do not carry information about non-CO2\r emissions, although these can be included with specific emissions \r metrics to estimate CO2-equivalent emissions. (Section TS.3.3) {1.3.2, \r 1.6, 4.6.2, 5.5, 7.6}"


id: 408664a5bea0dbb7efc00c9d8309354f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 8542
content:
"Multiple lines of evidence derived from observations, model simulations \r and other approaches can be used to construct climate information \r on a regional scale as described in detail in Sections TS.4.1.1 and \r TS.4.1.2. Depending on the phenomena and specific context, these \r sources and methodologies include theoretical understanding of the \r relevant processes, drivers and feedbacks of climate at regional scale; \r trends in observed data from multiple datasets; and the attribution \r of these trends to specific drivers. Furthermore, simulations from \r different model types (including global and regional climate models, \r emulators, statistical downscaling methods, etc.) and experiments \r (e.g., CMIP, CORDEX, and large ensembles of single-model simulations \r with different initial conditions), attribution methodologies and other \r relevant local knowledge (e.g., indigenous knowledge) are utilized \r (see Box TS.11). {1.5.3, 1.5.4, Cross-Chapter Box 7.1, 10.2-10.6, 11.2, \r [...]"


id: c7e51147d5f6058dfc6d7cfcc71e4e6c
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content:
"This box synthesizes the outcomes of the assessment of past, current and future global surface temperature. Global mean surface \r temperature (GMST) and global surface air temperature (GSAT) are the two primary metrics of global surface temperature used to \r estimate global warming in IPCC reports. GMST merges sea surface temperature (SST) over the ocean and 2 m air temperature over \r land and sea ice areas and is used in most paleo, historical and present-day observational estimates. The GSAT metric is 2 m air \r temperature over all surfaces and is the diagnostic generally used from climate models. Changes in GMST and GSAT over time differ \r by at most 10% in either direction (high confidence), but conflicting lines of evidence from models and direct observations, combined \r with limitations in theoretical understanding, lead to low confidence in the sign of any difference in long-term trend. Therefore, \r [...]"


id: 338de478018217b0a0edc16783bb3bce
created_at: 2023-04-19 13:22:33
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content:
"[...] long-term changes in GMST/GSAT are presently assessed to be identical, with expanded uncertainty in GSAT estimates. Hence the term \r global surface temperature is used in reference to both quantities in the text of the TS and SPM. {Cross-Chapter Box 2.3}"


id: 486ec79a0f85ed69601a355b94d30902
created_at: 2023-04-19 13:22:33
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vector_id: 9953
content:
"Global surface temperature has increased by 0.99 [0.84 to 1.10] degC from 1850-1900 to the first two decades of the \r 21st century (2001-2020) and by 1.09 [0.95 to 1.20] degC from 1850-1900 to 2011-2020. Temperatures as high as \r during the most recent decade (2011-2020) exceed the warmest centennial-scale range reconstructed for the present \r interglacial, around 6500 years ago [0.2degC to 1degC] (medium confidence). The next most recent warm period was \r about 125,000 years ago during the last interglacial when the multi-centennial temperature range [0.5degC to 1.5degC] \r encompasses the 2011-2020 values (medium confidence). The likely range of human-induced change in global surface \r temperature in 2010-2019 relative to 1850-1900 is 0.8degC to 1.3degC, with a central estimate of 1.07degC, encompassing \r the best estimate of observed warming for that period, which is 1.06degC with a very likely range of [0.88degC to 1.21degC], \r [...]"


id: fd5a386685a1b08def52fc093473b98e
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vector_id: 41930
content:
"[...] while the likely range of the change attributable to natural forcing is only -0.1degC to +0.1degC. "


id: 15420ce88b7a1a6d58477f4dc8b19157
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 957
content:
"Compared to 1850-1900, average global surface temperature over the period 2081-2100 is very likely to be higher by \r [1.0degC to 1.8degC] in the low CO2 emissions scenario SSP1-1.9 and by [3.3degC to 5.7degC] in the high CO2 emissions scenario \r SSP5-8.5. In all scenarios assessed here except SSP5-8.5, the central estimate of 20-year averaged global surface \r warming crossing the 1.5degC level lies in the early 2030s, which is in the early part of the likely range (2030-2052) \r assessed in SR1.5. It is more likely than not that under SSP1-1.9, global surface temperature relative to 1850-1900 will \r remain below 1.6degC throughout the 21st century, implying a potential temporary overshoot of 1.5degC global warming \r of no more than 0.1degC. Global surface temperature in any individual year could exceed 1.5degC relative to 1850-1900 \r by 2030 with a likelihood between 40% and 60% across the scenarios considered here (medium confidence). A 2degC \r [...]"


id: 474945ecb2115376122eebdd4282a24a
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 9746
content:
"[...] increase in global surface temperature relative to 1850-1900 will be crossed under SSP5-8.5 but is extremely unlikely \r to be crossed under SSP1-1.9. Periods of reduced and increased global surface temperature trends at decadal time \r scales will continue to occur in the 21st century (very high confidence). The effect of strong mitigation on 20-year \r global surface temperature trends would be likely to emerge during the near term (2021-2040), assuming no major \r volcanic eruptions occur. (Figure TS.8, Cross-Section Box TS.1, Figure 1) {2.3, 3.3, 4.3, 4.4, 4.5, 4.6, 7.3}"


id: 98c2c5fca8d50111060e74648c755e50
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content:
"Global surface temperature has evolved over geological time (Figure TS.1, Box TS.2). Beginning approximately 6500 years ago, global \r surface temperature generally decreased, culminating in the coldest multi-century interval of the post-glacial period (since roughly \r 7000 years ago), which occurred between around 1450 and 1850 (high confidence). Over the last 50 years, global surface temperature \r has increased at an observed rate unprecedented in at least the last two thousand years (high confidence). Temperatures as high as \r during the most recent decade (2011-2020) exceed the warmest centennial-scale range reconstructed for the present interglacial, \r around 6500 years ago [0.2degC to 1degC] (medium confidence). The next most recent warm period was about 125,000 years ago during \r the Last Interglacial when the multi-centennial temperature range [0.5degC to 1.5degC] encompasses the 2011-2020 values (medium \r [...]"


id: a3a36400c5501f15ca6006861da9084
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vector_id: 25992
content:
"[...] confidence) (Cross-Section Box TS.1, Figure 1). During the mid-Pliocene Warm Period, around 3.3-3.0 million years ago, global surface \r temperature was 2.5degC to 4degC warmer (medium confidence). {2.3.1, Cross-Chapter Box 2.1 and 2.4}"


id: ab7ad02ba4ca511b45eac8c86aedcc
created_at: 2023-04-19 13:22:33
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vector_id: 27400
content:
"The likely range of human-induced change in global surface temperature in 2010-2019 relative to 1850-1900 is 0.8degC to 1.3degC, \r with a central estimate of 1.07degC (Figure Cross-Section Box TS.1, Figure 1), encompassing the best estimate of observed warming \r for that period, which is 1.06degC with a very likely range of [0.88degC to 1.21degC], while the likely range of the change attributable \r to natural forcing is only -0.1degC to +0.1degC. This assessment is consistent with an estimate of the human-induced global surface \r temperature rise based on assessed ranges of perturbations to the top of the atmosphere (effective radiative forcing) and with metrics \r of feedbacks of the climate response (equilibrium climate sensitivity and the transient climate response). Over the same period, well\u0002mixed greenhouse gas forcing likely warmed global surface temperature by 1.0degC to 2.0degC, while aerosols and other anthropogenic \r [...]"


id: 6a5232782a66926fb58c8836ae3ba371
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content:
"[...] forcings likely cooled global surface temperature by 0.0degC to 0.8degC. {2.3.1, 3.3.1, 7.3.5, Cross-Chapter Box 7.1}"


id: 138f8dee87ccd40414495d00f9bd2cef
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 655
content:
"The observed slower increase in global surface temperature (relative to preceding and following periods) in the 1998-2012 period, \r sometimes referred to as 'the hiatus', was temporary (very high confidence). The increase in global surface temperature during the \r 1998-2012 period is also greater in the data sets used in the AR6 assessment than in those available at the time of AR5. Using these \r updated observational data sets and a like-for-like consistent comparison of simulated and observed global surface temperature, all \r observed estimates of the 1998-2012 trend lie within the very likely range of CMIP6 trends. Furthermore, the heating of the climate \r system continued during this period, as reflected in the continued warming of the global ocean (very high confidence) and in the \r continued rise of hot extremes over land (medium confidence). Since 2012, global surface temperature has risen strongly, with the \r [...]"


id: 7ae7b2d1ebcf9688b970d8b3c57da769
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vector_id: 18822
content:
"[...] past five years (2016-2020) being the hottest five-year period between 1850 and 2020 (high confidence). {2.3.1, 3.3.1, 3.5.1, Cross\u0002Chapter Box 3.1}"


id: 2ef3d084816ee7f34031ee5a4d481b25
created_at: 2023-04-19 13:22:33
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vector_id: 5535
content:
"Cross-Section Box TS.1, Figure 1 (continued): The intent of this figure is to show global surface temperature observed changes from the Holocene to now, \r and projected changes. (a) Global surface temperature over the Holocene divided into three time scales: (i) 12,000 to 1000 years ago (10,000 BCE to 1000 CE) \r in 100-year time steps, (ii) 1000 to 1900 CE, 10-year smooth, and (iii) 1900 to 2020 CE (mean of four datasets in panel c). Bold lines show the median of the \r multi-method reconstruction, with 5% and 95% percentiles of the ensemble members (thin lines). Vertical bars are 5-95th percentile ranges of estimated global \r surface temperature for the Last Interglacial and mid-Holocene (medium confidence) (Section 2.3.1.1). All temperatures are relative to 1850-1900. (b) Spatially \r resolved trends (degC per decade) for (upper map) HadCRUTv5 over 1981-2020, and (lower map, total change) multi-model mean projected changes from 1995-2014 \r [...]"


id: 7b90f03ad0749ec86d093b2e6385b191
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content:
"[...] to 2081-2100 in the SST3-7.0 scenario. Observed trends have been calculated where data are present in both the first and last decade and for at least 70% of all \r years within the period using ordinary least squares. Significance is assessed with autoregressive AR(1) model correction and denoted by stippling. Hatched areas \r in the lower map show areas of conflicting model evidence on significance of changes. (c) Temperature from instrumental data for 1850-2020, including annually \r resolved averages for the four global surface temperature datasets assessed in Section 2.3.1.1.3 (see text for references). The grey shading shows the uncertainty \r associated with the HadCRUTv5 estimate. All temperatures are relative to the 1850-1900 reference period. (d) Recent past and 2015-2050 evolution of annual mean \r global surface temperature change relative to 1850-1900, from HadCRUTv5 (black), Coupled Model Intercomparison Project Phase 6 (CMIP6) historical simulations \r [...]"


id: e41839cbe866a6c87c4aae6a977af1bb
created_at: 2023-04-19 13:22:33
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content:
"[...] (up to 2014, in grey, ensemble mean solid, 5% and 95% percentiles dashed, individual models thin), and CMIP6 projections under scenario SSP2-4.5, from four \r models that have an equilibrium climate sensitivity near the assessed central value (thick yellow). Solid thin coloured lines show the assessed central estimate of \r 20-year change in global surface temperature for 2015-2050 under three scenarios, and dashed thin coloured lines the corresponding 5% and 95% quantiles. (e)\r Assessed projected change in 20-year running mean global surface temperature for five scenarios (central estimate solid, very likely range shaded for SSP1-2.6 and \r SSP3-7.0), relative to 1995-2014 (left y-axis) and 1850-1900 (right y-axis). The y-axis on the right-hand side is shifted upward by 0.85degC, the central estimate of the \r observed warming for 1995-2014, relative to 1850-1900. The right y-axis in (e) is the same as the y-axis in (d). {2.3, 4.3, 4.4}"


id: 8b9d47fa4cc3a651f315065ba0ea07ad
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content:
"During the near term (2021-2040), a 1.5degC increase in global surface temperature, relative to 1850-1900, is very likely to occur \r in scenario SSP5-8.5, likely to occur in scenarios SSP2-4.5 and SSP3-7.0, and more likely than not to occur in scenarios SSP1-1.9 and \r SSP1-2.6. The time of crossing a warming level is defined here as the midpoint of the first 20-year period during which the average \r global surface temperature exceeds the level. In all scenarios assessed here except SSP5-8.5, the central estimate of crossing the 1.5degC \r level lies in the early 2030s. This is in the early part of the likely range (2030-2052) assessed in SR1.5, which assumed continuation of \r the then-current warming rate; this rate has been confirmed in the AR6. Roughly half of this difference arises from a larger historical \r warming diagnosed in AR6. The other half arises because for central estimates of climate sensitivity, most scenarios show stronger \r [...]"


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content:
"[...] warming over the near term than was estimated as 'current' in SR1.5 (medium confidence). When considering scenarios similar to SSP1-\r 1.9 instead of linear extrapolation, the SR1.5 estimate of when 1.5degC global warming is crossed is close to the central estimate reported \r here. (Cross-Section Box TS.1, Table 1) {2.3.1, Cross-Chapter Box 2.3, 3.3.1, 4.3.4, Box 4.1}"


id: fac4a467a1e7deaa985b30d885b1e880
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 41495
content:
"Table TS.2 | Summary table on observed changes in extremes, their attribution since 1950 (except where stated otherwise), and projected changes at \r +1.5degC, +2degC and +4degC of global warming, on global and continental scales. An increase in warm/hot extremes refers to warmer and/or more frequent hot days and \r nights and warm spells/heatwaves, over most land areas. A decrease in cold extremes refers to warmer and/or fewer cold days and nights and cold spells/cold waves, over most \r land areas. Drought events are relative to a predominant fraction of land area. For tropical cyclones, observed changes and attribution refer to Categories 3-5, while projected \r changes refer to Categories 4-5. Tables 11.1 and 11.2 are more detailed versions of this table, containing, in particular, information on regional scales. In general, higher \r [...]"


id: b735c11637b438663fc38f3fa11cd9c9
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 29445
content:
"[...] warming levels also imply stronger projected changes for indicators where the confidence level does not depend on the warming level and the table does not explicitly quantify \r the global sensitivity. See also Box TS.10. {9.6, Box 9.2, 11.3, 11.7}"


id: 32423ca1b7a2ef2f3909e136e6fe39e5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6096
content:
"There is high confidence that tropospheric ozone has been increasing \r from 1750 in response to anthropogenic changes in ozone precursor \r emissions (nitrogen oxides, carbon monoxide, non-methane volatile \r organic compounds, and methane), but with medium confidence in \r the magnitude of this change, due to limited observational evidence \r and knowledge gaps. Since the mid-20th century, tropospheric \r ozone surface concentrations have increased by 30-70% across the \r Northern Hemisphere (medium confidence); since the mid-1990s, \r free tropospheric ozone has increased by 2-7% per decade in most \r northern mid-latitude regions and 2-12% per decade in sampled \r tropical regions. Future changes in surface ozone concentrations will \r be primarily driven by changes in precursor emissions rather than \r climate change (high confidence). Stratospheric ozone has declined \r between 60degS-60degN by 2.2% from 1964-1980 to 2014-2017 \r (high confidence), with the largest declines during 1980-1995. \r [...]"


id: f97b73c86c0fdc2b2c2632f32b9835b7
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 41257
content:
"[...] The strongest loss of stratospheric ozone continues to occur in \r austral spring over Antarctica (ozone hole), with emergent signs of \r recovery after 2000. The 1750-2019 ERF for total (stratospheric and \r tropospheric) ozone is 0.47 [0.24 to 0.71] W m-2, which is dominated \r by tropospheric ozone changes. {2.2.5, 6.3.2, 7.3.2, 7.3.5}"


id: bbbb59496400fdc192483cc0a6acc318
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 30257
content:
"Tropospheric aerosols mainly act to cool the climate system, \r directly by reflecting solar radiation, and indirectly by enhancing \r cloud reflectance. Ice cores show increases in aerosols across the \r Northern Hemisphere mid-latitudes since 1700 and reductions \r since the late 20th century (high confidence). Aerosol optical depth \r (AOD), derived from satellite- and ground-based radiometers, \r has decreased since 2000 over the mid-latitude continents of \r both hemispheres, but increased over South Asia and East Africa \r (high confidence). Trends in AOD are more pronounced from sub\u0002micrometre aerosols for which the anthropogenic contribution is \r particularly large. Global carbonaceous aerosol budgets and trends \r remain poorly characterized due to limited observations, but black \r carbon (BC), a warming aerosol component, is declining in several \r regions of the Northern Hemisphere (low confidence). Total aerosol \r ERF in 2019, relative to 1750, is -1.1 [-1.7 to -0.4] W m-2 (medium \r [...]"


id: 65c1d9a5e5be6daafd0106e96a7d893d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 15165
content:
"It is likely that the proportion of major (Category 3-5) tropical \r cyclones (TCs) and the frequency of rapid TC intensification events \r have increased over the past four decades. The average location \r of peak TC wind-intensity has very likely migrated poleward in \r the western North Pacific Ocean since the 1940s, and TC forward \r translation speed has likely slowed over the contiguous USA since \r 1900. It is likely that the poleward migration of TCs in the western \r North Pacific and the global increase in TC intensity rates cannot be \r explained entirely by natural variability. There is high confidence\r that average peak TC wind speeds and the proportion of Category \r 4-5 TCs will increase with warming and that peak winds of the \r most intense TCs will increase. There is medium confidence that the \r average location where TCs reach their maximum wind-intensity will \r migrate poleward in the western North Pacific Ocean, while the total \r [...]"


id: 58839955e7d30c051bbcadd5d9814eab
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 12816
content:
"[...] global frequency of TC formation will decrease or remain unchanged \r with increasing global warming. {11.7.1}"


id: c86c31870f67005de4801066018a0e77
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32569
content:
"Since the 1970s, near-surface average winds have likely weakened \r over land. Over the ocean, near-surface average winds likely\r strengthened over 1980-2000, but divergent estimates lead to \r low confidence thereafter. Extratropical storm tracks have likely\r shifted poleward since the 1980s. There is low confidence in \r projected poleward shifts of the Northern Hemisphere mid-latitude \r jet and storm tracks due to large internal variability and structural \r uncertainty in model simulations. There is medium confidence in \r a projected decrease in the frequency of atmospheric blocking over \r Greenland and the North Pacific in boreal winter in 2081-2100 under \r the SSP3-7.0 and SSP5-8.5 scenarios. There is high confidence that \r Southern Hemisphere storm tracks and associated precipitation have \r migrated polewards over recent decades, especially in the austral \r summer and autumn, associated with a trend towards more positive \r [...]"


id: dbe1640649c8602ff56f2ab5a024ba7e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35970
content:
"[...] phases of the Southern Annular Mode (SAM) (Section TS.4.2.2) and \r the strengthening and southward shift of the Southern Hemisphere \r extratropical jet in austral summer. In the long term (2081-2100), "


id: d9e78656a239e4ce5a59ad63a4b2a15d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35636
content:
"There is low confidence in observed recent changes in the total \r number of extratropical cyclones over both hemispheres. There is also \r low confidence in past-century trends in the number and intensity of \r the strongest extratropical cyclones over the Northern Hemisphere \r due to the large interannual-to-decadal variability and temporal and \r spatial heterogeneities in the volume and type of assimilated data \r in atmospheric reanalyses, particularly before the satellite era. Over \r the Southern Hemisphere, it is likely that the number of extratropical \r cyclones with low central pressures (<980 hPa) has increased since \r 1979. The frequency of intense extratropical cyclones is projected to \r decrease (medium confidence). Projected changes in the intensity \r depend on the resolution of climate models (medium confidence). \r There is medium confidence that wind speeds associated with \r extratropical cyclones will change following changes in the storm \r [...]"


id: c84e0f7910b53d5c5da5bad06abf907b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32546
content:
"Future global warming exceeding the assessed very likely range cannot be ruled out and is potentially associated \r with the highest risks for society and ecosystems. Such low-likelihood, high-warming storylines tend to exhibit \r substantially greater changes in the intensity of regional drying and wetting than the multi-model mean. Even at \r levels of warming within the very likely range, global and regional low-likelihood outcomes might occur, such as large \r precipitation changes, additional sea level rise associated with collapsing ice sheets (see Box TS.4), or abrupt ocean \r circulation changes. While there is medium confidence that the Atlantic Meridional Overturning Circulation (AMOC) \r will not experience an abrupt collapse before 2100, if it were to occur, it would very likely cause abrupt shifts in \r regional weather patterns and water cycle. The probability of these low-likelihood outcomes increases with higher \r [...]"


id: a9a6df402b0ce689fe64bde6b1f43f56
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 27065
content:
"[...] global warming levels. If the real-world climate sensitivity lies at the high end of the assessed range, then global \r and regional changes substantially outside the very likely range projections occur for a given emissions scenario. \r With increasing global warming, some very rare extremes and some compound events (multivariate or concurrent \r extremes) with low likelihood in past and current climate will become more frequent, and there is a higher chance \r that events unprecedented in the observational record occur (high confidence). Finally, low-likelihood, high-impact \r outcomes may also arise from a series of very large volcanic eruptions that could substantially alter the 21st century \r climate trajectory compared to SSP-based Earth system model (ESM) projections. {Cross-Chapter Box 4.1, 4.3, 4.4, 4.8, \r 7.3, 7.4, 7.5, 8.6, 9.2, 9.6, Box 9.4, Box 11.2, Cross-Chapter Box 12.1}"


id: d7b5f83d2c4a846576ffe7c4931f44dd
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35259
content:
"Uncertainty in the true values of equilibrium climate sensitivity (ECS) and transient climate response (TCR) dominate uncertainty \r in projections of future warming under moderate to strong emissions scenarios (Section TS.3.2). A real-world ECS higher than the \r assessed very likely range (2degC-5degC) would require a strong historical aerosol cooling and/or a trend towards stronger warming from \r positive feedbacks linked to changes in SST patterns (pattern effects), combined with a strong positive cloud feedback and substantial \r biases in paleoclimate reconstructions - each of which is assessed as either unlikely or very unlikely, but not ruled out. Since CMIP6 \r contains several ESMs that exceed the upper bound of the assessed very likely range in future surface warming, these models can \r be used to develop low-likelihood, high warming storylines to explore risks and vulnerabilities, even in the absence of a quantitative \r [...]"


id: 7b47526904fc53202bd5e33e2b68d532
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18891
content:
"CMIP6 models with surface warming outside, or close to, the upper bound of the very likely range exhibit patterns of large widespread \r temperature and precipitation changes that differ substantially from the multi-model mean in all scenarios. For SSP5-8.5, the \r high-warming models exhibit widespread warming of more than 6degC over most extratropical land regions and parts of the Amazon. \r In the Arctic, annual mean temperatures increase by more than 10degC relative to present-day, corresponding to about 30% more than \r the best estimate of warming. Even for SSP1-2.6, high-warming models show on average 2degC-3degC warming relative to present-day \r conditions over much of Eurasia and North America (about 40% more than the best estimate of warming) and more than 4degC warming \r relative to the present over the Arctic in 2081-2100 (Box TS.3, Figure 1). Such a high global warming storyline would imply that the \r [...]"


id: 6811c8a25a60296b91331aa3256eab75
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 15576
content:
"[...] remaining carbon budget consistent with a 2degC warming is smaller than the assessed very likely range. Put another way, even if \r a carbon budget that likely limits warming to 2degC is met, a low-likelihood, high-warming storyline would result in warming of 2.5degC \r or more. {4.8}"


id: 54b1de580076450d037eb79c8f3808c5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 12175
content:
"CMIP6 models with global warming close to the upper bound of the assessed very likely warming range tend to exhibit greater \r changes in the intensity of regional drying and wetting than the multi-model mean. Furthermore, these model projections show \r a larger area of drying and tend to show a larger fraction of strong precipitation increases than the multi-model mean. However, \r regional precipitation changes arise from both thermodynamic and dynamic processes so that the most pronounced global warming \r levels are not necessarily associated with the strongest precipitation response. Abrupt human-caused changes to the water cycle \r cannot be ruled out. Positive land surface feedbacks, involving vegetation and dust, can contribute to abrupt changes in aridity, \r but there is only low confidence that such changes will occur during the 21st century. Continued Amazon deforestation, combined \r [...]"


id: 80db39574b277c270ccd81c8a8636682
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 19804
content:
"[...] with a warming climate, raises the probability that this ecosystem will cross a tipping point into a dry state during the 21st century \r (low confidence). (See also Box TS.9). {4.8, 8.6.2}"


id: e94f4e2b5de47b2baea8f73db8587651
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 38404
content:
"Observations, models and paleo-evidence indicate that \r recently observed changes in the ocean are unprecedented \r for centuries to millennia (high confidence). Over the past \r four to six decades, it is virtually certain that the global \r ocean has warmed, with human influence extremely \r likely the main driver since the 1970s, making climate \r change irreversible over centuries to millennia (medium \r confidence). It is virtually certain that upper ocean salinity \r contrasts have increased since the 1950s and extremely \r likely that human influence has contributed. It is virtually \r certain that upper ocean stratification has increased since \r 1970 and that sea water pH has declined globally over the \r last 40 years, with human influence being the main driver \r of the observed surface open ocean acidification (virtually \r certain). A long-term increase in surface open ocean pH \r occurred over the past 50 million years (high confidence), \r [...]"


id: 93ec8e969317c4cad5f95b3e4054eb6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 23229
content:
"[...] and surface ocean pH as low as recent times is uncommon \r in the last 2 million years (medium confidence). There is \r high confidence that marine heatwaves have become more \r frequent in the 20th century, and most of those since 2006 \r have been attributed to anthropogenic warming (very \r likely). There is high confidence that oxygen levels have \r dropped in many regions since the mid 20th century and \r that the geographic range of many marine organisms has \r changed over the last two decades. "


id: 351b1667c7b4a381c0fcf10c7f07157b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6585
content:
"It is virtually certain that the global ocean has warmed since at least \r 1971, representing about 90% of the increase in the global energy \r inventory (Section TS.3.1). The ocean is currently warming faster than \r at any other time since at least the last deglacial transition (medium \r confidence), with warming extending to depths well below 2000 m \r (very high confidence). It is extremely likely that human influence \r was the main driver of this recent ocean warming. Ocean warming \r will continue over the 21st century (virtually certain), and will likely\r continue until at least to 2300 even for low CO2 emissions scenarios. \r Ocean warming is irreversible over centuries to millennia (medium \r confidence), but the magnitude of warming is scenario-dependent from \r about the mid-21st century (medium confidence). The warming will \r not be globally uniform, with heat primarily stored in Southern Ocean \r water-masses and weaker warming in the subpolar North Atlantic (high \r [...]"


id: 7c4c97a32029f5726e4cca7868d3d8c
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 19076
content:
"[...] confidence). Limitations in the understanding of feedback mechanisms \r limit our confidence in future ocean warming close to Antarctica and \r how this will affect sea ice and ice shelves. {2.3.3, 3.5.1, 4.7.2, 7.2.2, \r 9.2.2, 9.2.3, 9.2.4, 9.3.2, 9.6.1, Cross-Chapter Box 9.1}"


id: 154162b529ed3598d952b67c91e39a74
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 956
content:
"It is virtually certain that surface pH has declined globally over the \r last 40 years and that the main driver is uptake of anthropogenic \r CO2. Ocean acidification and associated reductions in the saturation \r state of calcium carbonate - a constituent of skeletons or shells of \r a variety of marine organisms - is expected to increase in the 21st \r century under all emissions scenarios (high confidence). A long-term \r increase in surface open ocean pH occurred over the past 50 million \r years (high confidence), and surface ocean pH as low as recent \r times is uncommon in the last 2 million years (medium confidence). \r There is very high confidence that present-day surface pH values \r are unprecedented for at least 26,000 years and current rates of pH \r change are unprecedented since at least that time. Over the past 2-3 \r decades, a pH decline in the ocean interior has been observed in all \r ocean basins (high confidence) (Figure TS.11d). {2.3.3, 2.3.4, 3.6.2, \r [...]"


id: b5652b6605436c13a76425f455b28926
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 29145
content:
"Current Arctic sea ice coverage levels (both annual and late summer) \r are at their lowest since at least 1850 (high confidence), and for \r late summer for the past 1000 years (medium confidence). Since the \r late 1970s, Arctic sea ice area and thickness have decreased in both \r summer and winter, with sea ice becoming younger, thinner and more \r dynamic (very high confidence). It is very likely that anthropogenic \r forcing, mainly due to greenhouse gas increases, was the main driver \r of this loss, although new evidence suggests that anthropogenic \r aerosol forcing has offset part of the greenhouse gas-induced losses \r since the 1950s (medium confidence). The annual Arctic sea ice area \r minimum will likely fall below 1 million km2 at least once before \r 2050 under all assessed SSP scenarios. This practically sea ice-free \r state will become the norm for late summer by the end of the 21st \r century in high CO2 emissions scenarios (high confidence). Arctic \r [...]"


id: 4c44573a63ee49e24834c954896df446
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 10682
content:
"[...] summer sea ice varies approximately linearly with global surface \r temperature, implying that there is no tipping point and observed/\r projected losses are potentially reversible (high confidence). {2.3.2, \r 3.4.1, 4.3.2, 9.3.1, 12.4.9}"


id: 6d52ae8e38004651cd1f9a789ba5f8c6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 16512
content:
"It is likely that the Antarctic Ice Sheet has lost 2670 +- 530 Gt, \r contributing 7.4 +- 1.5 mm to GMSL rise over 1992-2020. The total \r Antarctic ice mass losses were dominated by the West Antarctic Ice \r Sheet, with combined West Antarctic and Peninsula annual loss rates \r increasing since about 2000 (very high confidence). Furthermore, it \r is very likely that parts of the East Antarctic Ice Sheet have lost mass \r since 1979. Since the 1970s, snowfall has likely increased over the \r western Antarctic Peninsula and eastern West Antarctica, with large \r spatial and interannual variability over the rest of Antarctica. Mass \r losses from West Antarctic outlet glaciers, mainly induced by ice shelf \r basal melt (high confidence), outpace mass gain from increased \r snow accumulation on the continent (very high confidence). \r However, there is only limited evidence, with medium agreement, \r of anthropogenic forcing of the observed Antarctic mass loss since \r [...]"


id: 240f798671304102efae1902f526b15e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 3524
content:
"[...] 1992 (with low confidence in process attribution). Increasing mass \r loss from ice shelves and inland discharge will likely continue to \r outpace increasing snowfall over the 21st century (Figure TS.11f). \r Deep uncertainty persists with respect to the possible evolution of \r the Antarctic Ice Sheet along high-end mass-loss storylines within \r the 21st century and beyond, primarily related to the abrupt and \r widespread onset of marine ice sheet instability and marine ice cliff \r instability. (See also Boxes TS.3 and TS.4). {2.3.2, 3.4.3, 9.4.2, 9.6.3, \r Box 9.4, Atlas.11.1}"


id: 25a6a70208f43f69951b601984181620
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 3809
content:
"The Greenland Ice Sheet was smaller than at present during the \r Last Interglacial period (roughly 125,000 years ago) and the mid\u0002Holocene (roughly 6,000 years ago) (high confidence). After reaching \r a recent maximum ice mass at some point between 1450 and 1850, \r the ice sheet retreated overall, with some decades likely close to \r equilibrium (i.e., mass loss approximately equalling mass gained). It \r is virtually certain that the Greenland Ice Sheet has lost mass since \r the 1990s, with human influence a contributing factor (medium \r confidence). There is high confidence that annual mass changes have \r been consistently negative since the early 2000s. Over the period \r 1992-2020, Greenland likely lost 4890 +- 460 Gt of ice, contributing \r 13.5 +- 1.3 mm to GMSL rise. There is high confidence that Greenland \r ice mass losses are increasingly dominated by surface melting and \r runoff, with large interannual variability arising from changes in \r [...]"


id: a71ed0b5b7babdd323b32675915cf0cf
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 26618
content:
"[...] surface mass balance. Projections of future Greenland ice-mass loss \r (Box TS.4, Table 1; Figure TS.11e) are dominated by increased surface \r melt under all emissions scenarios (high confidence). Potential \r irreversible long-term loss of the Greenland Ice Sheet, and of parts "


id: c983b01a98ed1db52c056d78db36096e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32778
content:
"Global mean sea level (GMSL) increased by 0.20 [0.15 to 0.25] m over the period 1901 to 2018, with a rate of rise \r that has accelerated since the 1960s to 3.7 [3.2 to 4.2] mm yr -1 for the period 2006-2018 (high confidence). Human \r activities were very likely the main driver of observed GMSL rise since 1971, and new observational evidence leads \r to an assessed sea level rise over the period 1901 to 2018 that is consistent with the sum of individual components \r contributing to sea level rise, including expansion due to ocean warming and melting of glaciers and ice sheets (high \r confidence). It is virtually certain that GMSL will continue to rise over the 21st century in response to continued \r warming of the climate system (Box TS.4, Figure 1). Sea level responds to greenhouse gas (GHG) emissions more \r slowly than global surface temperature, leading to weaker scenario dependence over the 21st century than for global \r [...]"


id: b7a33449e6d0696f7800198b2cf6dc9d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 29521
content:
"[...] surface temperature (high confidence). This slow response also leads to long-term committed sea level rise, associated \r with ongoing ocean heat uptake and the slow adjustment of the ice sheets, that will continue over the centuries and \r millennia following cessation of emissions (high confidence) (Box TS.9). By 2100, GMSL is projected to rise by 0.28-\r 0.55 m (likely range) under SSP1-1.9 and 0.63-1.01 m (likely range) under SSP5-8.5 relative to the 1995-2014 average \r (medium confidence). Under the higher CO2 emissions scenarios, there is deep uncertainty in sea level projections for \r 2100 and beyond associated with the ice-sheet responses to warming. In a low-likelihood, high-impact storyline and a \r high CO2 emissions scenario, ice-sheet processes characterized by deep uncertainty could drive GMSL rise up to about \r 5 m by 2150. Given the long-term commitment, uncertainty in the timing of reaching different GMSL rise levels is an \r [...]"


id: 283a682fd8b17494d88b7d6830440d45
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 4276
content:
"[...] important consideration for adaptation planning. {2.3, 3.4, 3.5, 9.6, Box 9.4, Cross-Chapter Box 9.1, Table 9.5}"


id: 835272df7347d5fc8b65c454b66e0a7b
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 20237
content:
"Beyond 2100, GMSL will continue to rise for centuries to millennia due to continuing deep ocean heat uptake and mass loss from \r ice sheets, and will remain elevated for thousands of years (high confidence). By 2150, considering only those processes in whose \r projections we have at least medium confidence and assuming no acceleration in ice-mass flux after 2100, GMSL is projected to rise \r between 0.6 m (0.4-0.9 m, likely range, SSP1-1.9) and 1.3 m (1.0-1.9 m, likely range) (SSP5-8.5), relative to the period 1995-2014 \r based on the SSP scenario extensions. Under high CO2 emissions, processes in which there is low confidence, such as MICI, could drive \r GMSL rise up to about 5 m by 2150 (Box TS.4, Figure 1a). By 2300, GMSL will rise 0.3-3.1 m under low CO2 emissions (SSP1-2.6) (low \r confidence). Under high CO2 emissions (SSP5-8.5), projected GMSL rise is between 1.7 and 6.8 m by 2300 in the absence of MICI and \r [...]"


id: ab4360b28407438f9d045fae0dd938f7
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 27358
content:
"[...] by up to 16 m considering MICI (low confidence). Over 2000 years, there is medium agreement and limited evidence that committed \r GMSL rise is projected to be about 2-3 m with 1.5degC peak warming, 2-6 m with 2degC of peak warming, 4-10 m with 3degC of peak \r warming, 12-16 m with 4degC of peak warming, and 19-22 m with 5degC of peak warming. {9.6.3}"


id: 15bdab741aa4d58de67af67e4122b80d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1042
content:
"Based on multiple lines of evidence using interhemispheric gradients of CO2 concentrations, isotopes, and inventory data, it is \r unequivocal that the growth in CO2 in the atmosphere since 1750 (see Section TS.2.2) is due to the direct emissions from human \r activities. The combustion of fossil fuels and land-use change for the period 1750-2019 resulted in the release of 700 +- 75 PgC (likely\r range, 1 PgC = 1015 g of carbon) to the atmosphere, of which about 41% +- 11% remains in the atmosphere today (high confidence). \r Of the total anthropogenic CO2 emissions, the combustion of fossil fuels was responsible for about 64% +- 15%, growing to an 86% +- \r 14% contribution over the past 10 years. The remainder resulted from land-use change. During the last decade (2010-2019), average \r annual anthropogenic CO2 emissions reached the highest levels in human history at 10.9 +- 0.9 PgC yr -1 (high confidence). Of these \r [...]"


id: db6dbea9dffde823751f09b65fbfd741
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35880
content:
"[...] emissions, 46% accumulated in the atmosphere (5.1 +- 0.02 PgC yr -1), 23% (2.5 +- 0.6 PgC yr-1) was taken up by the ocean and 31% \r (3.4 +- 0.9 PgC yr-1) was removed by terrestrial ecosystems (high confidence). {5.2.1, 5.2.2, 5.2.3}"


id: c2cee4e4a95ac0422bd5c39f58b8f8e7
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31549
content:
"In AR6, ESM projections are assessed with CO2 concentrations by 2100 from about 400 ppm (SSP1-1.9) to above 1100 ppm (SSP5-8.5). \r Most simulations are performed with prescribed atmospheric CO2 concentrations, which already account for a central estimate of \r climate-carbon feedback effects. Carbon dioxide emissions-driven simulations account for uncertainty in these feedbacks, but do \r not significantly change the projected global surface temperature changes (high confidence). Although land and ocean sinks absorb \r more CO2 under high emissions than low emissions scenarios, the fraction of emissions removed from the atmosphere decreases \r (high confidence). This means that the more CO2 that is emitted, the less efficient the ocean and land sinks become (high confidence), \r an effect which compensates for the logarithmic relationship between CO2 and its radiative forcing, which means that for each unit \r [...]"


id: be05003b0a598fbb78143e0ddac6ab73
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 30697
content:
"[...] increase in additional atmospheric CO2 the effect on global temperature decreases. (Box TS.5, Figure 1f,g). {4.3.1, 5.4.5, 5.5.1.2}"


id: ba22d5639a8076f473102d7cbc15bc2
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 29972
content:
"Ocean and land sinks show similar responses for a given scenario, but the land sink has a much higher interannual variability \r and wider model spread. Under SSP3-7.0 and SSP5-8.5, the initial growth of both sinks in response to increasing atmospheric \r concentrations of CO2 is subsequently limited by emerging carbon-climate feedbacks (high confidence) (Box TS.5, Figure  1f). \r Projections show that the ocean and land sinks will stop growing from the second part of the 21st century under all emissions \r scenarios, but with different drivers for different emissions scenarios. Under SSP3-7.0 and SSP5-8.5, the weakening growth rate \r of the ocean CO2 sink in the second half of the century is primarily linked to the strengthening positive feedback from reduced \r carbonate buffering capacity, ocean warming and altered ocean circulation (e.g., AMOC changes). In contrast, for SSP1-1.9, SSP1-2.6 \r [...]"


id: 53cce1915f89edd48c882a8f061533ed
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 12012
content:
"[...] and SSP2-4.5, the weakening growth rate of the ocean carbon sink is a response to the stabilizing or declining atmospheric \r CO2 concentrations. Under SSP1-1.9, models project that combined land and ocean sinks will turn into a weak source by 2100 \r (medium confidence). Under high CO2 emissions scenarios, it is very likely that the land carbon sink will grow more slowly due to \r warming and drying from the mid-21st century, but it is very unlikely that it will switch from being a sink to a source before 2100. "


id: 796cc0192793539e51f97023e4c6bdfd
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18560
content:
"Box TS.5, Figure 1 (continued): The intent of this figure is to show the response of the carbon cycle to carbon dioxide (CO2) emissions and climate and its \r role in determining future CO2 levels through projected changes to sinks and sink fractions. The figure shows changes in carbon storage in response to elevated \r CO2 (a, b) and the response to climate warming (c, d). Maps show spatial patterns of changes in carbon uptake during simulations with 1% per year increase in CO2\r (Section 5.4.5.5), and zonal mean plots show distribution of carbon changes is dominated by the land (green lines) in the tropics and Northern Hemisphere and ocean \r (blue lines) in the Southern Hemisphere. Hatching indicates regions where fewer than 80% of models agree on the sign of response. (e) Future CO2 projections: \r projected CO2 concentrations in the Shared Socio-economic Pathway (SSP) scenarios in response to anthropogenic emissions, results from coupled Earth system \r [...]"


id: 4812d6b8f3100281e736b13865ab775f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 9899
content:
"[...] models for SSP5-8.5 and from the MAGICC7 emulator for other scenarios (Section 4.3.1). (f) Future carbon fluxes: projected combined land and ocean fluxes (positive \r downward) up to 2100 for the SSP scenarios, and extended to 2300 for available scenarios, 5-95% uncertainty plumes shown for SSP1-2.6 and SSP3-7.0 (Sections \r 4.3.2.4, 5.4.5.4 and 5.4.10). The numbers near the top show the number of model simulations used. (g) Sink fraction: the fraction of cumulative emissions of CO2\r removed by land and ocean sinks. The sink fraction is smaller under conditions of higher emissions. {Figure 4.3; 5.4.5; Figures 5.25, 5.27 and 5.30}"


id: 8ea260f6ca379583f9ac4a6809a51382
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 22280
content:
"Hemisphere extratropics since the mid-20th century (high \r confidence), are consistent with large-scale warming. At the \r same time an increase in the amplitude of the seasonal cycle of \r atmospheric CO2 poleward of 45degN since the early 1960s (high \r confidence) and a global-scale increase in vegetation greenness \r of the terrestrial surface since the early 1980s (high confidence) \r have been observed. Increasing atmospheric CO2, warming at high \r latitudes, and land management interventions have contributed \r to the observed greening trend, but there is low confidence in \r their relative roles. There is medium confidence that increased \r plant growth associated with CO2 fertilization is the main driver \r of the observed increase in amplitude of the seasonal cycle of \r atmospheric CO2 in the Northern Hemisphere. Reactive nitrogen, \r ozone and aerosols affect terrestrial vegetation and carbon cycle \r through deposition and effects on large-scale radiation (high \r [...]"


id: 6a06766fce3c704d29f0f5452a17e23b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 15922
content:
"[...] confidence), but the magnitude of these effects on the land carbon \r sink, ecosystem productivity and indirect CO2 forcing remains \r uncertain. {2.3.4, 3.6.1, 5.2.1, 6.4.5, 12.3.7, 12.4}"


id: 637c947fc32ed9223e1276cefd1c1109
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 14796
content:
"Over the last century, there has been a poleward and upslope shift \r in the distribution of many land species (very high confidence) \r as well as increases in species turnover within many ecosystems \r (high confidence). There is high confidence that the geographical \r distribution of climate zones has shifted in many parts of the \r world in the last half century. The SRCCL concluded that continued \r warming will exacerbate desertification processes (medium \r confidence) and that ecosystems will become increasingly exposed \r to climates beyond those that they are currently adapted to (high \r confidence). There is medium confidence that climate change will \r increase disturbance by, for example, fire and tree mortality, across \r several ecosystems. Increases are projected in drought, aridity and \r fire weather in some regions (Section TS.4.3; high confidence). \r There is low confidence in the magnitude of these changes, but \r [...]"


id: 871d87234cb15b91270a0d2111d90794
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 20934
content:
"[...] the probability of crossing uncertain regional thresholds (e.g., fires, \r forest dieback) increases with further warming (high confidence). \r The response of biogeochemical cycles to the anthropogenic \r perturbation can be abrupt at regional scales, and irreversible on \r decadal to century time scales (high confidence). {2.3.4, 5.4.3, \r 5.4.9, 11.6, 11.8, 12.5, SRCCL 2.2, SRCCL 2.5, SR1.5 3.4}"


id: e4857744ca7a379ad55bbcbb39d361f6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37491
content:
"There is high confidence that the global water cycle has intensified since at least 1980 expressed by, for example, increased atmospheric \r moisture fluxes and amplified precipitation minus evaporation patterns. Global land precipitation has likely increased since 1950, \r with a faster increase since the 1980s (medium confidence), and a likely human contribution to patterns of change, particularly for \r increases in high-latitude precipitation over the Northern Hemisphere. Increases in global mean precipitation are determined by a \r robust response to global surface temperature (very likely 2-3% per degC) that is partly offset by fast atmospheric adjustments to \r atmospheric heating by greenhouse gases (GHGs) and aerosols (Section TS.3.2.2). The overall effect of anthropogenic aerosols is \r to reduce global precipitation through surface radiative cooling effects (high confidence). Over much of the 20th century, opposing \r [...]"


id: b73391506c80a007fc1aff3e58fd487e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 29443
content:
"[...] effects of GHGs and aerosols on precipitation have been observed for some regional monsoons (high confidence) (Box TS.13). Global \r annual precipitation over land is projected to increase on average by 2.4% (-0.2% to +4.7% likely range) under SSP1-1.9, 4.6% (1.5% \r to 8.3% likely range) under SSP2-4.5, and 8.3% (0.9% to 12.9% likely range) under SSP5-8.5 by 2081-2100 relative to 1995-2014 \r (Box TS.6, Figure 1). Inter-model differences and internal variability contribute to a substantial range in projections of large-scale and \r regional water cycle changes (high confidence). The occurrence of volcanic eruptions can alter the water cycle for several years (high \r confidence). Projected patterns of precipitation change exhibit substantial regional differences and seasonal contrast as global surface \r temperature increases over the 21st century (Box TS.6, Figure 1). {2.3.1, 3.3.2, 3.3.3, 3.5.2, 4.3.1, 4.4.1, 4.5.1, 4.6.1, Cross-Chapter \r [...]"


id: 9278d11ee2736d4e767f7c48ee8310f0
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 22991
content:
"Global total column water vapour content has very likely increased since the 1980s, and it is likely that human influence has contributed \r to tropical upper tropospheric moistening. Near-surface specific humidity has increased over the ocean (likely) and land (very likely) \r since at least the 1970s, with a detectable human influence (medium confidence). Human influence has been detected in amplified \r surface salinity and precipitation minus evaporation (P-E) patterns over the ocean (high confidence). It is virtually certain that \r evaporation will increase over the ocean and very likely that evapotranspiration will increase over land, with regional variations under \r future surface warming (Box TS.6, Figure 1). There is high confidence that projected increases in precipitation amount and intensity will \r be associated with increased runoff in northern high latitudes (Box TS.6, Figure 1). In response to cryosphere changes (Section TS.2.5), \r [...]"


id: 82545c56d971f680b81ce2dab928d68c
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 20056
content:
"[...] there have been changes in streamflow seasonality, including an earlier occurrence of peak streamflow in high-latitude and mountain \r catchments (high confidence). Projected runoff (Box TS.6, Figure 1c) is typically decreased by contributions from small glaciers because \r of glacier mass loss, while runoff from larger glaciers will generally increase with increasing global warming levels until their mass \r becomes depleted (high confidence). {2.3.1, 3.3.2, 3.3.3, 3.5.2, 8.2.3, 8.4.1, 11.5}"


id: 232d686d5c9a53f330774e9e20aec647
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 3391
content:
"Warming over land drives an increase in atmospheric evaporative demand and in the severity of drought events (high confidence). Greater \r warming over land than over the ocean alters atmospheric circulation patterns and reduces continental near-surface relative humidity, \r which contributes to regional drying (high confidence). A very likely decrease in relative humidity has occurred over much of the global \r land area since 2000. Projected increases in evapotranspiration due to growing atmospheric water demand will decrease soil moisture \r over the Mediterranean region, south-western North America, South Africa, South-Western South America and south-western Australia \r (high confidence) (Box TS.6, Figure 1). Some tropical regions are also projected to experience enhanced aridity, including the Amazon \r basin and Central America (high confidence). The total land area subject to increasing drought frequency and severity will expand (high \r [...]"


id: 3b566f67379936b34fa0303c6e8388b2
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 7627
content:
"[...] confidence), and in the Mediterranean, South-Western South America, and Western North America, future aridification will far exceed the \r magnitude of change seen in the last millennium (high confidence). {4.5.1, 8.2.2, 8.2.3, 8.4.1, Box 8.2, 11.6, 11.9}"


id: c72778b46b4ba944637eb0b22e2a6c75
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32358
content:
"Water cycle variability and related extremes are projected to increase faster than mean changes in most regions of the world \r and under all emissions scenarios (high confidence). A warmer climate increases moisture transport into weather systems, which \r intensifies wet seasons and events (high confidence). The magnitudes of projected precipitation increases and related extreme \r events depend on model resolution and the representation of convective processes (high confidence). Increases in near-surface \r atmospheric moisture capacity of about 7% per 1oC of warming lead to a similar response in the intensification of heavy precipitation \r from sub-daily up to seasonal time scales, increasing the severity of flood hazards (high confidence). The average and maximum \r rain-rates associated with tropical and extratropical cyclones, atmospheric rivers and severe convective storms will therefore also \r [...]"


id: 2d9ab0f5502977f2d50b8a125c4de0d4
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 5318
content:
"[...] increase with future warming (high confidence). For some regions, there is medium confidence that peak tropical cyclone rain\u0002rates will increase by more than 7% per 1degC of warming due to increased low-level moisture convergence caused by increases \r in wind intensity. In the tropics year-round and in the summer season elsewhere, interannual variability of precipitation and \r runoff over land is projected to increase at a faster rate than changes in seasonal mean precipitation (Figure TS.12e,f) (medium \r confidence). Sub-seasonal precipitation variability is also projected to increase, with fewer rainy days but increased daily mean \r precipitation intensity over many land regions (high confidence). {4.5.3, 8.2.3, 8.4.1, 8.4.2, 8.5.1, 8.5.2, 11.4, 11.5, 11.7, 11.9}"


id: ee58cc4aa8787370195a7e8393be1adc
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 39305
content:
"Box TS.6, Figure 1 | Projected water cycle changes. The intent of this figure is to give a geographical overview of changes in multiple components of the global \r water cycle using an intermediate emissions scenario. Important key message: without drastic reductions in greenhouse gas emissions, human-induced global warming \r will be associated with widespread changes in all components of the water cycle. Long-term (2081-2100) projected annual mean changes (%) relative to present-day \r (1995-2014) in the SSP2-4.5 emissions scenario for (a) precipitation, (b) surface evapotranspiration, (c) total runoff and (d) surface soil moisture. Numbers in top \r right of each panel indicate indicate the number of Coupled Model Intercomparison Project Phase 6 (CMIP6) models used for estimating the ensemble mean. For other \r scenarios, please refer to relevant figures in Chapter 8. Uncertainty is represented using the simple approach: No overlay indicates regions with high model agreement, \r [...]"


id: 1b09b63e9242869ca5d60bb34f6c3a49
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1955
content:
"[...] where >=80% of models agree on sign of change; diagonal lines indicate regions with low model agreement, where <80% of models agree on sign of change. For \r more information on the simple approach, please refer to the Cross-Chapter Box Atlas.1. {8.4.1; Figures 8.14, 8.17, 8.18, and 8.19}"


id: 3b238384ede93b5675737b5b75676754
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 7590
content:
"The best estimate ERF of 2.72 W m-2 has increased by 0.43 \r W m-2 relative to that given in AR5 (for 1750-2014) due \r to an increase in the greenhouse gas ERF that is partly \r compensated by a more negative aerosol ERF compared \r to AR5. The greenhouse gas ERF has been revised due to \r changes in atmospheric concentrations and updates to \r forcing efficiencies, while the revision to aerosol ERF is due \r to increased understanding of aerosol-cloud interactions \r and is supported by improved agreement between \r different lines of evidence. Improved quantifications \r of ERF, the climate system radiative response, and the \r observed energy increase in the Earth system for the \r period 1971-2018 demonstrate improved closure of the \r global energy budget (i.e., the extent to which the sum \r of the integrated forcing and the integrated radiative \r response equals the energy gain of the Earth system) \r compared to AR5 (high confidence). (See FAQ 7.1). {7.2.2, \r [...]"


id: 64d4abcb7407304df8f9542395e0f703
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 15012
content:
"Aerosols contributed an ERF of -1.3 [-2.0 to -0.6] W m-2 over the \r period 1750 to 2014 (medium confidence). The ERF due to aerosol-\r cloud interactions (ERFaci) contributes most to the magnitude of \r the total aerosol ERF (high confidence) and is assessed to be -1.0 \r [-1.7 to -0.3] W m-2 (medium confidence), with the remainder due \r to aerosol-radiation interactions (ERFari), assessed to be -0.3 [-0.6 \r to 0.0] W m-2 (medium confidence). There has been an increase in \r the estimated magnitude - but a reduction in the uncertainty - of \r the total aerosol ERF relative to AR5, supported by a combination \r of increased process-understanding and progress in modelling and \r observational analyses (Figure TS.15c). Effective radiative forcing \r estimates from these separate lines of evidence are now consistent \r with each other, in contrast to AR5, and support the assessment that \r it is virtually certain that the total aerosol ERF is negative. Compared \r [...]"


id: 439aaaef2d30e41b37cc673e8b758098
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 9117
content:
"[...] to AR5, the assessed magnitude of ERFaci has increased, while that \r of ERFari has decreased. {7.3.3, 7.3.5}"


id: e599f0cc36de67fce9eb851600f682dc
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37704
content:
"On average, CMIP6 models have higher mean ECS and TCR values \r than the CMIP5 generation of models and also have higher mean \r values and wider spreads than the assessed best estimates and very \r likely ranges within this Report. These higher mean ECS and TCR \r values can be traced to a positive net cloud feedback that is larger in \r CMIP6 by about 20%. The broader ECS and TCR ranges from CMIP6 \r also lead the models to project a range of future warming that \r is wider than the assessed future warming range, which is based \r on multiple lines of evidence (Cross-Section Box TS.1). However, \r some of the high-sensitivity CMIP6 models (Section TS.1.2.2) are \r less consistent with observed recent changes in global warming \r and with paleoclimate proxy records than models with ECS within \r the very likely range. Similarly, some of the low-sensitivity models \r are less consistent with the paleoclimate data. The CMIP6 models \r [...]"


id: e27ce9beeb8fbf2a583e9eadf25eaac7
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37144
content:
"[...] with the highest ECS and TCRs values provide insights into low\u0002likelihood, high-impact futures, which cannot be excluded based on \r currently available evidence (Cross-Section Box TS.1). {4.3.1, 4.3.4, \r 7.4.2, 7.5.6}"


id: 3ce1d4d2df3545b6799e64117d304159
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 7896
content:
"Earth system feedbacks can be categorized into three broad groups: \r physical feedbacks, biogeophysical and biogeochemical feedbacks, \r and feedbacks associated with ice sheets. In previous assessments, \r the ECS has been associated with a distinct set of physical feedbacks \r (Planck response, water vapour, lapse rate, surface albedo, and cloud \r feedbacks). In this assessment, a more general definition of ECS is \r adopted whereby all biogeophysical and biogeochemical feedbacks \r that do not affect the atmospheric concentration of CO2 are included. \r These include changes in natural CH4 emissions, natural aerosol \r emissions, N2O, ozone, and vegetation, which all act on time scales of \r years to decades and are therefore relevant for temperature change \r over the 21st century. Because the total biogeophysical and non-CO2\r biogeochemical feedback is assessed to have a central value that is \r near zero (low confidence), including it does not affect the assessed \r [...]"


id: 12cc239e2774c385ee90873af4617e60
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 513
content:
"[...] ECS but does contribute to the net feedback uncertainty. The \r biogeochemical feedbacks that affect the atmospheric concentration \r of CO2 are not included because ECS is defined as the response to \r a sustained doubling of CO2. Moreover, the long-term feedbacks \r associated with ice sheets are not included in the ECS owing to their \r long time scales of adjustment. {5.4, 6.4, 7.4, 7.5, Box 7.1}"


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vector_id: 3420
content:
"The combined effect of all known radiative feedbacks (physical, \r biogeophysical, and non-CO2 biogeochemical) is to amplify the \r base climate response (in the absence of feedbacks), also known \r as the Planck temperature response20 (virtually certain). Combining \r these feedbacks with the Planck response, the net climate feedback \r parameter is assessed to be -1.16 [-1.81 to -0.51] W  m-2 degC-1, \r which is slightly less negative than that inferred from the overall ECS \r assessment. The combined water vapour and lapse rate feedback \r makes the largest single contribution to global warming, whereas \r the cloud feedback remains the largest contribution to overall \r uncertainty. Due to the state-dependence of feedbacks, as evidenced \r from paleoclimate observations and from models, the net feedback \r parameter will increase (become less negative) as global temperature \r increases. Furthermore, on long time scales the ice-sheet feedback \r [...]"


id: 8111748c77374ffeee348730dbee4ee5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 19844
content:
"[...] parameter is very likely positive, promoting additional warming on \r millennial time scales as ice sheets come into equilibrium with the \r forcing. (high confidence) {7.4.2, 7.4.3, Figure 7.14, Table 7.10}"


id: a9ffb4563fffff448bc675006ec98116
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 27132
content:
"The net effect of changes in clouds in response to global warming is \r to amplify human-induced warming, that is, the net cloud feedback \r is positive (high confidence). Compared to AR5, major advances \r in the understanding of cloud processes have increased the level \r of confidence and decreased the uncertainty range in the cloud \r feedback by about 50% (Figure TS.17a). An assessment of the low\u0002altitude cloud feedback over the subtropical ocean, which was \r previously the major source of uncertainty in the net cloud feedback, \r is improved owing to a combined use of climate model simulations, \r satellite observations, and explicit simulations of clouds, altogether \r leading to strong evidence that this type of cloud amplifies global \r warming. The net cloud feedback is assessed to be +0.42 [-0.10 \r to 0.94] W m-2 degC-1. A net negative cloud feedback is very unlikely. \r The CMIP5 and CMIP6 ranges of cloud feedback are similar to this \r [...]"


id: c0d01ad9339b63a26f5c795aed60d6d9
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31218
content:
"[...] assessed range, with CMIP6 having a slightly more positive median \r cloud feedback (high confidence). The surface albedo feedback and \r combined water vapour-lapse rate feedback are positive (Figure \r TS.17a), with high confidence in the estimated value of each based \r on multiple lines of evidence, including observations, models and \r theory (Box TS.6). {7.4.2, Figure 7.14, Table 7.10}"


id: db1043a1894731192fcc0d27697ddb5e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35817
content:
"Figure TS.17 | An overview of physical and biogeochemical feedbacks in the climate system. The intent of this figure is to summarize assessed estimates of physical, \r biogeophysical and biogeochemical feedbacks on global temperature based on Chapters 5, 6 and 7. (a) Synthesis of physical, biogeophysical and non-carbon dioxide (CO2) \r biogeochemical feedbacks that are included in the definition of equilibrium climate sensitivity (ECS) assessed in this Technical Summary. These feedbacks have been assessed \r using multiple lines of evidence including observations, models and theory. The net feedback is the sum of the Planck response, water vapour and lapse rate, surface albedo, \r cloud, and biogeophysical and non-CO2 biogeochemical feedbacks. Bars denote the mean feedback values, and uncertainties represent very likely ranges; (b) Estimated values of \r [...]"


id: 74935ccfc2eddc52691b448443bd038
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 17745
content:
"[...] individual biogeophysical and non-CO2 biogeochemical feedbacks. The atmospheric methane (CH4) lifetime and other non-CO2 biogeochemical feedbacks have been calculated \r using global Earth system model simulations from AerChemMIP, while the CH4 and nitrous oxide (N2O) source responses to climate have been assessed for the year 2100 using \r a range of modelling approaches using simplified radiative forcing equations. The estimates represent the mean and 5-95% range. The level of confidence in these estimates \r is low owing to the large model spread. (c) Carbon-cycle feedbacks as simulated by models participating in the C4MIP of the Coupled Model Intercomparison Project Phase 6 \r (CMIP6). An independent estimate of the additional positive carbon-cycle climate feedbacks from permafrost thaw, which is not considered in most C4MIP models, is added. \r [...]"


id: 8985a3ef1ff18dd3f5d0f605e0c43293
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 21371
content:
"[...] The estimates represent the mean and 5-95% range. Note that these feedbacks act through modifying the atmospheric concentration of CO2 and thus are not included in the \r definition of ECS, which assumes a doubling of CO2, but are included in the definition and assessed range of the transient climate response to cumulative CO2 emissions (TCRE). \r {5.4.7, 5.4.8, Box 5.1, Figure 5.29, 6.4.5, Table 6.9, 7.4.2, Table 7.10}"


id: 16ec43476b363b95d595ca57d1198d6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1256
content:
"Thawing terrestrial permafrost will lead to carbon release (high \r confidence), but there is low confidence in the timing, magnitude \r and the relative roles of CO2 versus CH4 as feedback processes. An \r ensemble of models projects CO2 release from permafrost to be \r 3-41 PgC per 1oC of global warming by 2100, leading to warming \r strong enough that it must be included in estimates of the remaining \r carbon budget but weaker than the warming from fossil fuel burning. \r However, the incomplete representation of important processes, \r such as abrupt thaw, combined with weak observational constraints, \r only allow low confidence in both the magnitude of these estimates \r and in how linearly proportional this feedback is to the amount of \r global warming. There is emerging evidence that permafrost thaw \r and thermokarst give rise to increased CH4 and N2O emissions, which \r leads to the combined radiative forcing from permafrost thaw being \r [...]"


id: c27edcd73ef565bd3a22834f04223975
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31505
content:
"[...] larger than from CO2 emissions only. However, the quantitative \r understanding of these additional feedbacks is low, particularly for \r N2O. These feedbacks, as well as potential additional carbon losses \r due to climate-induced fire feedback are not routinely included in \r Earth system models. {Box 5.1, 5.4.3, 5.4.7, 5.4.8}"


id: 9857bccdb2ac892e47c5714d81efed0f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 24012
content:
"Limiting further climate change would require substantial and \r sustained reductions of GHG emissions. Without net zero CO2\r emissions, and a decrease in the net non-CO2 forcing (or sufficient \r net negative CO2 emissions to offset any further warming from \r net non-CO2 forcing), the climate system will continue to warm. \r There is high confidence that mitigation requirements for limiting \r warming to specific levels over this century can be estimated using \r a carbon budget that relates cumulative CO2 emissions to global \r mean temperature increase (Figure TS.18, Table TS.3). For the period \r 1850-2019, a total of 2390 +- 240 GtCO2 of anthropogenic CO2 has \r been emitted. Remaining carbon budgets (starting from 1  January \r 2020) for limiting warming to 1.5degC, 1.7degC and 2.0degC are estimated \r at 500 GtCO2, 850 GtCO2 and 1350 GtCO2, respectively, based on \r the 50th percentile of TCRE. For the 67th percentile, the respective \r [...]"


id: 870f10ee27a2336005845ad4c3dfbe71
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 20923
content:
"[...] values are 400 GtCO2, 700 GtCO2 and 1150 GtCO2. The remaining \r carbon budget estimates for different temperature limits assume \r that non-CO2 emissions are mitigated consistent with the median \r reductions found in scenarios in the literature as assessed in SR1.5, "


id: e96c1212afad26284bd372c7fccb1e80
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 38424
content:
"Methodological improvements and new evidence result in updated \r remaining carbon budget estimates. The assessment in AR6 applies \r the same methodological improvements as in SR1.5, which uses \r a recent observed baseline for historic temperature change and \r cumulative emissions. Changes compared to SR1.5 are therefore \r small: the assessment of new evidence results in updated median \r remaining carbon budget estimates for limiting warming to 1.5degC \r and 2degC being the same and about 60 GtCO2 smaller, respectively, \r after accounting for emissions since SR1.5. Meanwhile, remaining \r carbon budgets for limiting warming to 1.5degC would be about \r 300-350 GtCO2 larger if evidence and methods available at the \r time of AR5 would be used. If a specific remaining carbon budget \r is exceeded, this results in a lower probability of keeping warming \r below a specified temperature level and higher irreversible global \r warming over decades to centuries, or alternatively a need for net \r [...]"


id: 139ba02300a2cd80cf40aa2ea1da51dd
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 664
content:
"[...] negative CO2 emissions or further reductions in non-CO2 greenhouse \r gases after net zero CO2 is achieved to return warming to lower levels \r in the long term. {5.5.2, 5.6, Box 5.2}"


id: 178eb7b08ba9e495ecc087d72551addd
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1352
content:
"Carbon dioxide removal (CDR) refers to anthropogenic activities \r that deliberately remove CO2 from the atmosphere and durably \r store it in geological, terrestrial or ocean reservoirs, or in products. \r Carbon dioxide is removed from the atmosphere by enhancing \r biological or geochemical carbon sinks or by direct capture of CO2\r from air. Emissions pathways that limit global warming to 1.5degC or \r 2degC typically assume the use of CDR approaches in combination \r with GHG emissions reductions. CDR approaches could be used to \r compensate for residual emissions from sectors that are difficult or \r costly to decarbonize. CDR could also be implemented at a large scale \r to generate global net negative CO2 emissions (i.e., anthropogenic \r CO2 removals exceeding anthropogenic emissions), which could \r compensate for earlier emissions as a way to meet long-term climate \r stabilization goals after a temperature overshoot. This Report assesses \r [...]"


id: dc1d4cf827a90f2832d2c161f4007887
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 36002
content:
"[...] the effects of CDR on the carbon cycle and climate. Co-benefits and \r trade-offs for biodiversity, water and food production are briefly \r discussed for completeness, but a comprehensive assessment of the \r ecological and socio-economic dimensions of CDR options is left to \r the WGII and WGIII reports. {4.6.3, 5.6}"


id: c98889eb9fb7c172b1a31e4d2baf9e5f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 32782
content:
"CDR methods have the potential to sequester CO2 from the \r atmosphere (high confidence). In the same way part of current \r anthropogenic net CO2 emissions are taken up by land and ocean \r carbon stores, net CO2 removal will be partially counteracted by CO2\r release from these stores, such that the amount of CO2 sequestered \r by CDR will not result in an equivalent drop in atmospheric CO2 (very\r high confidence). The fraction of CO2 removed from the atmosphere \r that is not replaced by CO2 released from carbon stores - a measure \r of CDR effectiveness - decreases slightly with increasing amounts of \r removal (medium confidence) and decreases strongly if CDR is applied \r at lower atmospheric CO2 concentrations (medium confidence). The \r reduction in global surface temperature is approximately linearly \r related to cumulative CO2 removal (high confidence). Because of this \r near-linear relationship, the amount of cooling per unit CO2 removed \r [...]"


id: 7a13ca1e65ee316c9a7909f500b75054
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18676
content:
"[...] is approximately independent of the rate and amount of removal \r (medium confidence). {4.6.3, 5.6.2.1, Figure 5.32, Figure 5.34}"


id: cfb9f88ac8c95499fb97261fed25cc10
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 33905
content:
"Carbon dioxide removal methods have a range of side effects that \r can either weaken or strengthen the carbon sequestration and \r cooling potential of these methods and affect the achievement \r of sustainable development goals (high confidence). Biophysical \r and biogeochemical side-effects of CDR methods are associated \r with changes in surface albedo, the water cycle, emissions of CH4\r and N2O, ocean acidification and marine ecosystem productivity \r (high confidence). These side-effects and associated Earth system \r feedbacks can decrease carbon uptake and/or change local and \r regional climate and in turn limit the CO2 sequestration and cooling \r potential of specific CDR methods (medium confidence). Deployment \r of CDR, particularly on land, can also affect water quality and quantity, \r food production and biodiversity (high confidence). These effects are \r often highly dependent on local context, management regime, prior \r [...]"


id: fdea9105fcb38eeea42bbfe4efbb8de8
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 42040
content:
"[...] land use, and scale (high confidence). The largest co-benefits are \r obtained with methods that seek to restore natural ecosystems or \r improve soil carbon sequestration (medium confidence). The climate \r and biogeochemical effects of terminating CDR are expected to be \r small for most CDR methods (medium confidence). {4.6.3, 5.6.2.2, \r Figure 5.36, 8.4.3, 8.6.3}"


id: ab5ea400ce7bcd581f6870320914c3a
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 27385
content:
"Simulations with ESMs indicate that under scenarios where CO2\r emissions gradually decline, reach net zero and become net negative \r during the 21st century (e.g., SSP1-2.6), land and ocean carbon sinks \r begin to weaken in response to declining atmospheric CO2\r concentrations, and the land sink eventually turns into a source \r (Figure TS.19). This sink-to-source transition occurs decades to a few \r centuries after CO2 emissions become net negative. The ocean \r remains a sink of CO2 for centuries after emissions become net \r negative. Under scenarios with large net negative CO2 emissions \r (e.g., SSP5-3.4-OS) and rapidly declining CO2 concentrations, the land \r source is larger than for SSP1-2.6 and the ocean also switches to a \r source. While the general response is robust across models, there is \r low confidence in the timing of the sink-to-source transition and the \r magnitude of the CO2 source in scenarios with net negative CO2\r [...]"


id: 1c93e8e75cbd44a52947e5b49840e4d4
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 2208
content:
"[...] emissions. Carbon dioxide removal could reverse some aspects \r climate change if CO2 emissions become net negative, but some \r changes would continue in their current direction for decades to \r millennia. For instance, sea level rise due to ocean thermal expansion \r would not reverse for several centuries to millennia (high confidence) \r (Box TS.4). {4.6.3, 5.4.10, 5.6.2.1, Figure 5.30, Figure 5.33}"


id: 21b524c68138b872c2df69dba629ea0e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 3143
content:
"Emissions metrics are needed to aggregate baskets of gases to \r determine net zero GHG emissions. Generally, achieving net zero CO2\r emissions and declining non-CO2 radiative forcing would halt human\u0002induced warming. Reaching net zero GHG emissions quantified by \r GWP-100 typically leads to declining temperatures after net zero \r GHGs emissions are achieved if the basket includes short-lived gases, \r such as CH4. Net zero GHG emissions defined by CGTP or GWP* \r imply net zero CO2 and other long-lived GHG emissions and constant \r (CGTP) or gradually declining (GWP*) emissions of short-lived gases. \r The warming evolution resulting from net zero GHG emissions \r defined in this way corresponds approximately to reaching net zero \r CO2 emissions, and would thus not lead to declining temperatures \r after net zero GHG emissions are achieved but to an approximate \r temperature stabilization (high confidence). The choice of emissions \r [...]"


id: f21da395f6ad5288ec31f4b78f3955fd
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 39987
content:
"[...] metric hence affects the quantification of net zero GHG emissions, \r and therefore the resulting temperature outcome of reaching and \r sustaining net zero GHG emissions levels (high confidence). {7.6.1.4, \r 7.6.2, 7.6.3}"


id: 237ef94f48532e0359888447bd075ed6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 3443
content:
"The relative climate effects of different forcing agents are typically \r quantified using emissions metrics that compare the effects of \r an idealised pulse of 1 kg of some climate forcing agent against \r a reference climate forcing agent, almost always CO2. The two most \r prominent pulse emissions metrics are the global warming potential \r (GWP) and global temperature change potential (GTP) (see Glossary). \r The climate responses to CO2 emissions by convention include the \r effects of warming on the carbon cycle, so for consistency these also \r need to be determined for non-CO2 emissions. The methodology \r for doing this has been placed on a more robust scientific footing \r compared to AR5 (high confidence). Methane from fossil fuel sources \r has slightly higher emissions metric values than those from biogenic \r sources since it leads to additional fossil CO2 in the atmosphere \r (high confidence). Updates to the chemical adjustments for CH4 and \r [...]"


id: 33022303942dca0ff0e5465764df6985
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6238
content:
"[...] N2O emissions (Section TS.3.1) and revisions in their lifetimes result \r in emissions metrics for GWP and GTP that are slightly lower than \r in AR5 (medium confidence). Emissions metrics for the entire suite \r of GHGs assessed in the AR6 have been calculated for various time \r horizons. {7.6.1, Table 7.15, Table 7.SM.7}"


id: af52f086e6ae25dd814d4d61fa7e821b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 28079
content:
"The global surface temperature response following a climate change \r mitigation measure that affects emissions of both short- and long\u0002lived climate forcers depends on their lifetimes, their ERFs, how \r fast and for how long the emissions are reduced, and the thermal \r inertia in the climate system. Mitigation, relying on emissions \r reductions and implemented through new legislation or technology \r standards, implies that emissions reductions occur year after year. \r Global temperature response to a year's worth of current emissions \r from different sectors informs about the mitigation potential (Figure \r TS.20). Over 10- to 20-year time scales, the influence of SLCFs is \r at least as large as that of CO2, with sectors producing the largest \r warming being fossil fuel production and distribution, agriculture, \r and waste management. Because the effects of the SLCFs decay \r rapidly over the first few decades after emission, the net long-term \r [...]"


id: cdd83f656edd793c71b3701e587f578e
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 33542
content:
"[...] temperature effect from a single year's worth of current emissions is \r predominantly determined by CO2. Fossil fuel combustion for energy, \r industry and land transportation are the largest contributing sectors \r on a 100-year time scale (high confidence). Current emissions of CO2, \r N2O and SLCFs from East Asia and North America are the largest \r regional contributors to additional net future warming on both \r short (medium confidence) and long time scales (10 and 100 years, \r respectively) (high confidence). {6.6.1, 6.6.2, Figure 6.16}"


id: 9d72c0a23deb3e76493608b0d602875b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 24935
content:
"In the next two decades, it is very likely that SLCF emissions changes will cause a warming relative to 2019, across the WGI core set of \r SSPs (see Section TS.1.3.1), in addition to the warming from long-lived GHGs. The net effect of SLCF and HFC changes in global surface \r temperature across the SSPs is a likely warming of 0.06degC-0.35degC in 2040 relative to 2019. This near-term global mean warming \r linked to SLCFs is quite similar in magnitude across the SSPs due to competing effects of warming (CH4, ozone) and cooling (aerosols) \r forcers (Box TS.7, Figure 1). There is greater diversity in the end-of-century response among the scenarios. SLCF changes in scenarios \r with no climate change mitigation (SSP3-7.0 and SSP5-8.5) will cause a warming in the likely range of 0.4degC-0.9degC in 2100 relative to \r 2019 due to increases in CH4, tropospheric ozone and HFC levels. For the stringent climate change and pollution mitigation scenarios \r [...]"


id: d66d5d3f6a2a41843312c4a9f85f6b1b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 35029
content:
"[...] (SSP1-1.9 and SSP1-2.6), the cooling from reductions in CH4, ozone and HFCs partially balances the warming from reduced aerosols, \r primarily sulphate, and the overall SLCF effect is a likely increase in global surface temperature of 0.0degC-0.3degC in 2100, relative to \r 2019. With intermediate climate change and air pollution mitigations, SLCFs in SSP2-4.5 add a likely warming of 0.2degC-0.5degC to global \r surface temperature change in 2100, with the largest warming resulting from reductions in aerosols. {4.4.4, 6.7.3}"


id: a45e17353ddd7825499722ccbaadb159
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 26122
content:
"Since AR5, further modelling work has been conducted on aerosol-based solar radiation modification (SRM) options \r such as stratospheric aerosol injection, marine cloud brightening, and cirrus cloud thinning21 and their climate and \r biogeochemical effects. These investigations have consistently shown that SRM could offset some of the effects of \r increasing greenhouse gases on global and regional climate, including the carbon and water cycles (high confidence). \r However, there would be substantial residual or overcompensating climate change at the regional scales and seasonal \r time scales (high confidence), and large uncertainties associated with aerosol-cloud-radiation interactions persist. \r The cooling caused by SRM would increase the global land and ocean CO2 sinks (medium confidence), but this \r would not stop CO2 from increasing in the atmosphere or affect the resulting ocean acidification under continued \r [...]"


id: bfc116ac46a8bf80aaa8b33acf649d50
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31016
content:
"[...] anthropogenic emissions (high confidence). It is likely that abrupt water cycle changes will occur if SRM techniques \r are implemented rapidly. A sudden and sustained termination of SRM in a high CO2 emissions scenario would cause \r rapid climate change (high confidence). However, a gradual phase-out of SRM combined with emissions reduction and \r carbon dioxide removal (CDR) would avoid these termination effects (medium confidence). {4.6.3, 5.6.3. 6.4.6, 8.6.3}."


id: c1254bd3dd0c29e33bf2d834928bfb7b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 31281
content:
"Some climate system components are slow to respond, such as the deep ocean overturning circulation and the ice sheets. It is likely that \r under stabilization of global warming at 1.5degC, 2.0degC or 3.0degC relative to 1850-1900, the AMOC will continue to weaken for several \r decades by about 15%, 20% and 30% of its strength and then recover to pre-decline values over several centuries (medium confidence). \r At sustained warming levels between 2degC and 3degC, there is limited evidence that the Greenland and West Antarctic ice sheets will be lost \r almost completely and irreversibly over multiple millennia; both the probability of their complete loss and the rate of mass loss increases \r with higher surface temperatures (high confidence). At sustained warming levels between 3degC and 5degC, near-complete loss of the \r Greenland Ice Sheet and complete loss of the West Antarctic Ice Sheet is projected to occur irreversibly over multiple millennia (medium \r [...]"


id: cad99fc1a2a47034024695588c654524
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 33029
content:
"[...] confidence); with substantial parts or all of Wilkes Subglacial Basin in East Antarctica lost over multiple millennia (low confidence). Early\u0002warning signals of accelerated sea level rise from Antarctica could possibly be observed within the next few decades. For other hazards \r (e.g., ice-sheet behaviour, glacier mass loss and global mean sea level change, coastal floods, coastal erosion, air pollution, and ocean \r acidification) the time and/or scenario dimensions remain critical, and a simple and robust relationship with global warming level cannot \r be established (high confidence). {4.3.2, 4.7.2, 5.4.3, 5.4.5, 5.4.8, 8.6, 9.2, 9.4, Box 9.3, Cross-Chapter Box 12.1}"


id: c2b9c3d0aa134808173857d6a0771413
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 31542
content:
"For global climate indicators, evidence for abrupt change is limited. For global warming up to 2degC above 1850-1900 levels, paleoclimate \r records do not indicate abrupt changes in the carbon cycle (low confidence). Despite the wide range of model responses, uncertainty \r in atmospheric CO2 by 2100 is dominated by future anthropogenic emissions rather than uncertainties related to carbon-climate \r feedbacks (high confidence). There is no evidence of abrupt change in climate projections of global temperature for the next century: \r there is a near-linear relationship between cumulative CO2 emissions and maximum global mean surface air temperature increase \r caused by CO2 over the course of this century for global warming levels up to at least 2degC relative to 1850-1900. The increase in global \r ocean heat content (Section TS.2.4) will likely continue until at least 2300 even for low emissions scenarios, and global mean sea level \r [...]"


id: 4f979eaa071b158d7dc6665cb7339a15
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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"[...] will continue to rise for centuries to millennia following cessation of emissions (Box TS.4) due to continuing deep ocean heat uptake \r and mass loss of the Greenland and Antarctic ice sheets (high confidence). {2.2.3; Cross-Chapter Box 2.1; 5.1.1; 5.4; Cross-Chapter \r Box 5.1; Figures 5.3, 5.4, 5.25, and 5.26; 9.2.2; 9.2.4}"


id: a0f42d2bbf6594fa7aea29db93f80ed1
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"confidence). It is very unlikely that gas clathrates (mostly methane) in deeper terrestrial permafrost and subsea clathrates will lead to a \r detectable departure from the emissions trajectory during this century. Possible abrupt changes and tipping points in biogeochemical \r cycles lead to additional uncertainty in 21st century atmospheric GHG concentrations, but future anthropogenic emissions remain the \r dominant uncertainty (high confidence). There is potential for abrupt water cycle changes in some high emissions scenarios, but there \r is no overall consistency regarding the magnitude and timing of such changes. Positive land surface feedbacks, including vegetation, \r dust, and snow, can contribute to abrupt changes in aridity, but there is only low confidence that such changes will occur during \r the 21st century. Continued Amazon deforestation, combined with a warming climate, raises the probability that this ecosystem will \r [...]"


id: f43d3e8457358271c61d2448623cf9d7
created_at: 2023-04-19 13:22:33
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content:
"[...] cross a tipping point into a dry state during the 21st century (low confidence). (Section TS.3.2.2) {5.4.3, 5.4.5, 5.4.8, 5.4.9, 8.6.2, 8.6.3, \r Cross-Chapter Box 12.1}"


id: 7726c320ceb74466322dd9ee4e222688
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 18162
content:
"Climate change information at regional scale is generated using a range \r of data sources and methodologies (Section TS.1.4). Understanding \r of observed regional climate change and variability is based on the \r availability and analysis of multiple observational datasets that are \r suitable for evaluating the phenomena of interest (e.g., extreme \r events), including accounting for observational uncertainty (Section \r TS.1.2.1). These datasets are combined with climate model simulations \r of observed changes and events to attribute causes of those changes \r and events to large- and regional-scale anthropogenic and natural \r drivers and to assess the performance of the models. Future simulations \r with many climate models (multi-model ensembles) are then used to \r generate and quantify ranges of projected regional climate responses \r (Section TS.4.2). Discarding models that fundamentally misrepresent \r relevant processes improves the credibility of regional climate \r [...]"


id: 1bc784175859f2f15e56eb5a28b105f6
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 2073
content:
"[...] information generated from these ensembles (high confidence). \r However, multi-model mean and ensemble spread are not a full \r measure of the range of projection uncertainty and are not sufficient \r to characterize low-likelihood, high-impact changes (Box TS.3) or \r situations where different models simulate substantially different \r or even opposite changes (high confidence). Large single-model \r ensembles are now available and provide a more comprehensive \r spectrum of possible changes associated with internal variability (high \r confidence) (Section TS.1.2.3). {1.5.1, 1.5.4, 10.2, 10.3.3, 10.3.4, 10.4.1, \r 10.6.2, 11.2, Box 11.2, Cross-Chapter Box 11.1, 12.4, Atlas.1.4.1}"


id: 8d8f139b18a1ef93c2174c81bd80524c
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"The regional extremes and events that have been studied are geographically uneven (Section TS.4.1). A few events, for example, \r extreme rainfall events in the United Kingdom, heatwaves in Australia, or Hurricane Harvey that hit Texas in 2017, have been heavily \r studied. Many highly impactful extreme weather events have not been studied in the event attribution framework, particularly in \r the developing world where studies are generally lacking. This is due to various reasons, including lack of observational data, lack of \r reliable climate models, and lack of scientific capacity. While the events that have been studied are not representative of all extreme \r events that have occurred, and results from these studies may also be subject to selection bias, the large number of event attribution \r studies provide evidence that changes in the properties of these local and individual events are in line with expected consequences \r [...]"


id: a6eb761fe5b9c86086c9926b81d1ec4f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 26576
content:
"[...] of human influence on the climate and can be attributed to external drivers. {Cross-Working Group Box: Attribution, 11.1.4, 11.2.2}"


id: ab84003d47723c36f76413bbe8db8fdd
created_at: 2023-04-19 13:22:33
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content:
"Box TS.10, Figure 1 (continued): The IPCC AR6 WGI inhabited regions are displayed as hexagons of identical sizes in their approximate geographical location (see \r legend for regional acronyms). All assessments are made for each region as a whole and for the 1950s to the present. Assessments made on different time scales or \r more local spatial scales might differ from what is shown in the figure. The colours in each panel represent the four outcomes of the assessment on observed changes. \r Striped hexagons (white and light-grey) are used where there is low agreement in the type of change for the region as a whole, and grey hexagons are used when \r there is limited data and/or literature that prevents an assessment of the region as a whole. Other colours indicate at least medium confidence in the observed change. \r The confidence level for the human influence on these observed changes is based on assessing trend detection and attribution and event attribution literature, \r [...]"


id: 97203ccab88eb845705e8954129bb909
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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vector_id: 23781
content:
"[...] and it is indicated by the number of dots: three dots for high confidence, two dots for medium confidence and one dot for low confidence (single, filled dot: limited \r agreement; single, empty dot: limited evidence)."


id: ad96a7e00a60c4ecc3fc8c268aa1d9db
created_at: 2023-04-19 13:22:33
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vector_id: 27782
content:
"Panel (b) For heavy precipitation, the evidence is mostly drawn from changes in indices based on one-day or five-day precipitation amounts using global and \r regional studies. Green hexagons indicate regions where there is at least medium confidence in an observed increase in heavy precipitation. \r Panel (c) Agricultural and ecological droughts are assessed based on observed and simulated changes in total column soil moisture, complemented by evidence \r on changes in surface soil moisture, water balance (precipitation minus evapotranspiration) and indices driven by precipitation and atmospheric evaporative demand. \r Yellow hexagons indicate regions where there is at least medium confidence in an observed increase in this type of drought and green hexagons indicate regions \r where there is at least medium confidence in an observed decrease in agricultural and ecological drought.\r [...]"


id: 321718d1921104b62e65b598e61aa4d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 6070
content:
"[...] For all regions, Table TS.5 shows a broader range of observed changes besides the ones shown in this figure. Note that Southern South America (SSA) is the only \r region that does not display observed changes in the metrics shown in this figure, but is affected by observed increases in mean temperature, decreases in frost and \r increases in marine heatwaves."


id: e3158e06dd817861412c4349a4c45f9f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37248
content:
"Since AR5, physical climate storyline approaches have emerged as \r a complementary instrument to provide a different perspective, or \r additional climate information, to facilitate communication of the \r information or provide a more flexible consideration of risk. Storylines \r that condition climatic events and processes on a set of plausible \r but distinct large-scale climatic changes enable the exploration of \r uncertainties in regional climate projections. For example, they can \r explicitly address low-likelihood, high-impact outcomes, which would \r be less emphasized in a probabilistic approach, and can be embedded \r in a user's risk landscape, taking account of socio-economic factors \r as well as physical climate changes. Storylines can also be used to \r communicate climate information by narrative elements describing \r and contextualizing the main climatological features and the relevant \r consequences in the user context and, as such, can be used as part \r [...]"


id: 32eeab7d23a4bfb03683e7662ca4d7ea
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6226
content:
"[...] of a climate information distillation process. {1.4.4., Box 10.2, 11.2, \r Box 11.2, Cross-Chapter Box 12.2}"


id: 15bc731adbd08590f5f9603a3f5349b9
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 1040
content:
"The distillation process can vary substantially, as it needs to consider \r multiple lines of evidence on all physically plausible outcomes \r (especially when they are contrasting) relevant to a specific decision \r required in response to a changing climate. Confidence in the \r distilled regional climate information is enhanced when there is \r agreement across multiple lines of evidence, so the outcome can \r be limited if these are inconsistent or contradictory. For example, in \r the Mediterranean region the agreement between different lines of \r evidence, such as observations, projections by regional and global \r models, and understanding of the underlying mechanisms, provides \r high confidence in summer warming that exceeds the global average \r (see Box TS.12). In a less clear-cut case for Cape Town, South Africa, \r despite consistency among global model future projections, there \r is medium confidence in a projected future drier climate due to the \r [...]"


id: 42eeebb7d54f55a03f79af89168bf097
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"A significant innovation in the AR6 WGI Report is the Atlas. Part of its remit is to provide region-by-region assessment on changes in \r mean climate and to link with other WGI chapters to generate climate change information for the regions. An important component \r is the new online interactive tool, the Interactive Atlas, with flexible spatial and temporal analyses of much of the observed, simulated \r past and projected future climate change data underpinning the WGI assessment. This includes the ability to generate global maps \r and a number of regionally aggregated products (time series, scatter plots, tables, etc.) for a range of observations and ensemble \r climate change projections of variables (such as changes in the climatic impact-drivers summarized in Table TS.5) from the Coupled \r Model Intercomparison Project Phases 5 and 6 (CMIP5, CMIP6) and the Coordinated Regional Climate Downscaling Experiment \r [...]"


id: bec0af36eb9035b65a0005272014513e
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"[...] (CORDEX). The data can be displayed and summarized under a range of SSP-RCP scenarios and future time slices and also for different \r global warming levels, relative to several different baseline periods. The maps and various statistics can be generated for annual mean \r trends and changes or for any user-specified season. A new set of WGI reference regions is used for the regional summary statistics \r and applied widely throughout the report (with the regions, along with aggregated datasets and the code to generate these, available \r at the ATLAS GitHub: https://github.com/IPCC-WG1/Atlas)."


id: b7fd70bb1ae3a3fe95b51a50cef098d9
created_at: 2023-04-19 13:22:33
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"Box TS.12, Figure 1 (continued): The intent of this figure is to provide an example of using different lines of evidence to assess the confidence in or likelihood \r of a projected change in regional climate and which of these lines of evidence are available to view and explore in the Interactive Atlas. (a) Mechanisms and \r feedbacks involved in enhanced Mediterranean summer warming. (b) Locations of observing stations from different datasets. (c) Distribution of 1960-2014 summer \r temperature trends (degC per decade) for observations (black crosses), CMIP5 (blue circles), CMIP6 (red circles), HighResMIP (orange circles), CORDEX EUR-44 (light \r blue circles), CORDEX EUR-11 (green circles), and selected single model initial-condition large ensembles (SMILEs; grey boxplots, MIROC6, CSIRO-Mk3-6-0, MPI-ESM \r and d4PDF). (d) Time series of area averaged (25degN-50degN, 10degW-40degE) land point summer temperature anomalies (degC, baseline period is 1995-2014): the boxplot \r [...]"


id: 90862111727edbc0bd539b1a5fe04bee
created_at: 2023-04-19 13:22:33
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"[...] shows long term (2081-2100) temperature changes of different CMIP6 scenarios in respect to the baseline period. (e) Projected Mediterranean summer warming \r in comparison to global annual mean warming of CMIP5 (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) and CMIP6 (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) ensemble \r means (lines) and spread (shading). {Figure 10.20, Figure 10.21, Figure Atlas.8}"


id: 7720083293c28aa9a6504ad4786b5bc2
created_at: 2023-04-19 13:22:33
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content:
"Since the late 19th century, major MoVs (Table TS.4) show \r no sustained trends, exhibiting fluctuations in frequency and \r magnitude at multi-decadal time scales, except for the Southern \r Annular Mode (SAM), which has become systematically more \r positive (high confidence) (Table TS.4). It is very likely that human \r influence has contributed to this trend from the 1970s to the \r 1990s, and to the associated strengthening and southward shift \r of the Southern Hemispheric extratropical jet in austral summer. \r The influence of stratospheric ozone forcing on the SAM trend has \r been reduced since the early 2000s compared to earlier decades, \r contributing to the weakening of its positive trend observed over \r 2000-2019 (medium confidence). By contrast, the cause of the \r Northern Annular Mode (NAM) trend toward its positive phase \r since the 1960s and associated northward shifts of Northern \r Hemispheric extratropical jet and storm track in boreal winter \r [...]"


id: 18816f6fe43287c2909a8dbfcd7d8ac5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"[...] is not well understood. The evaluation of model performance on \r simulating MoVs is assessed in Section TS.1.2.2. {2.3.3, 2.4, 3.3.3, \r 3.7.1, 3.7.2}"


id: 50f50af0d3e1c25a8f604633aff5fa00
created_at: 2023-04-19 13:22:33
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vector_id: 11526
content:
"In the near term, the forced change in SAM in austral summer is likely\r to be weaker than observed during the late 20th century under all \r five SSPs assessed. This is because of the opposing influence in the \r near to mid-term from stratospheric ozone recovery and increases in \r other greenhouse gases on the Southern Hemisphere summertime \r mid-latitude circulation (high confidence). In the near term, forced \r changes in the SAM in austral summer are therefore likely to be \r smaller than changes due to natural internal variability. In the long \r term (2081-2100) under the SSP5-8.5 scenario, the SAM index is \r likely to increase in all seasons relative to 1995-2014. The CMIP6 \r multi-model ensemble projects a long-term (2081-2100) increase \r in the boreal wintertime NAM index under SSP3-7.0 and SSP5-8.5, \r but regional associated changes may deviate from a simple shift \r in the mid-latitude circulation due to a modified teleconnection \r [...]"


id: ffbfe5941d51ba34ecc0b17ded0e54b
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 42386
content:
"[...] resulting from interaction with a modified mean background state. \r {4.3.3, 4.4.3, 4.5.1, 4.5.3, 8.4.2}"


id: 88e8e81b15c46ae78d1d35989235461f
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 21253
content:
"Human influence has not affected the principal tropical modes of \r interannual climate variability (Table TS.4) and their associated \r regional teleconnections beyond the range of internal variability \r (high confidence). It is virtually certain that the El Nino-Southern \r Oscillation (ENSO) will remain the dominant mode of interannual \r variability in a warmer world. There is no consensus from models for \r a systematic change in amplitude of ENSO sea surface temperature \r (SST) variability over the 21st century in any of the SSP scenarios \r assessed (medium confidence). However, it is very likely that \r rainfall variability related to ENSO will be enhanced significantly \r by the latter half of the 21st century in the SSP2-4.5, SSP3-7.0 \r and SSP5-8.5 scenarios, regardless of the amplitude changes in \r SST variability related to the mode. It is very likely that rainfall \r variability related to changes in the strength and spatial extent of \r [...]"


id: e286e27b3bcc6dd9976ed925b841a1a2
created_at: 2023-04-19 13:22:33
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content_type: text
index: climate_gpt_v2
vector_id: 37153
content:
"[...] ENSO teleconnections will lead to significant changes at regional \r scale. {3.7.3, 3.7.4, 3.7.5, 4.3.3, 4.5.3, 8.4.2, 10.3.3}"


id: e757cf2b03ce9cd7c258507c8adba7d3
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 37993
content:
"Table TS.4 | Summary of the assessments on modes of variability (MoVs) and associated teleconnections. (a) Assessments on observed changes since the start \r of instrumental records, Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6) model performance, human influence on the observed changes, and \r near-term (2021-2040) and mid- to long-term (2041-2100) changes. Curves schematically illustrate the assessed overall changes, with the horizontal axis indicating time, \r and are not intended to precisely represent the time evolution. (b) Fraction of surface air temperature (SAT) and precipitation (pr) variance explained at interannual time scale \r by each MoV for each AR6 region (numbers in each cell; in percent). Values correspond to the average of significant explained variance fractions based on HadCRUT, GISTEMP, \r [...]"


id: 41270afa383727f3f497d8b091e3babc
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content:
"[...] BerkeleyEarth and CRU-TS (for SAT) and GPCC and CRU-TS (for precipitation). Significance is tested based on F-statistics at the 95% level confidence, and a slash indicates that \r the value is not significant in more than half of the available data sets. The colour scale corresponds to the sign and values of the explained variance as shown at the bottom. The \r corresponding anomaly maps are shown in Annex IV. DJF: December-January-February. MAM: March-April-May. JJA: June-July-August. SON: September-October-November. \r In (b), Northern Annular Mode (NAM) and El Nino-Southern Oscillation (ENSO) teleconnections are evaluated for 1959-2019, Southern Annular Mode (SAM) for 1979-2019, \r Indian Ocean Basin (IOB), Indian Ocean Dipole (IOD), Atlantic Zonal Mode (AZM) and Atlantic Meridional Mode (AMM) for 1958-2019, and Pacific Decadal Variability (PDV) \r [...]"


id: a2e7ed900ee09c0e9ba51302145070e1
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content:
"[...] and Atlantic Multi-decadal Variability (AMV) for 1900-2019. All data are linearly detrended prior to computation. (Section TS.1.2.2) {2.4, 3.7, 4.3.3, 4.4.3, 4.5.3, Table Atlas.1, \r Annex IV}"


id: 4ccf50592da687f655cb9a5235ee6d5d
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content_type: text
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vector_id: 10782
content:
"which are relevant for the region. In fact, local changes over SES \r in terms of moisture convergence, ascending motion and storm\u0002track locations depend on these climate phenomena, and they are \r overall responsible for the observed precipitation trends. Projections \r suggest continuing positive trends in rainfall over SES in the near\u0002term in response to GHG emissions scenarios. Multi-model mean and \r ensemble spread are not sufficient to characterize situations where \r different models simulate substantially different or even opposite \r changes (high confidence). In such cases, physical climate storylines \r addressing possible outcomes for climate phenomena shown to \r play a role in the variability of the region of interest can aid the \r interpretation of projection uncertainties. In addition, single-model \r initial-condition large ensembles of many realizations of internal \r variability are required to separate internal variability from forced \r [...]"


id: 4a95b0071521e89c8399aaec3b0975a7
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 10360
content:
"[...] changes (high confidence) and to partition the different sources of \r uncertainties as a function of future assessed periods. {10.3.4, 10.4.2, \r Figure 10.12a}"


id: e1b3541602e3b0ce465d096df45929d8
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 36977
content:
"Projections of regional monsoons during the 21st century indicate contrasting (region-dependent) and uncertain precipitation and \r circulation changes. The annual contrast between the wettest and driest month of the year is likely to increase by 3-5% per degree \r Celsius in most monsoon regions in terms of precipitation, precipitation minus evaporation, and runoff (medium confidence). For the \r North American monsoon, projections indicate a decrease in precipitation, whereas increased monsoon rainfall is projected over South \r and South East Asia and over East Asia (medium confidence) (Box TS.13, Figure 1). West African monsoon precipitation is projected \r to increase over the central Sahel and decrease over the far western Sahel (medium confidence). There is low confidence in projected \r precipitation changes in the South American and Australian-Maritime Continent regional monsoons (for both magnitude and sign) \r [...]"


id: 43153160749a8d9481d6959e87153240
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 9005
content:
"[...] (Box TS.13, Figure 1). There is medium confidence that the monsoon season will be delayed in the Sahel and high confidence that it \r will be delayed in North and South America. {8.2.2, 8.4.2.4, Box 8.2}"


id: 496400c8a592a2d6d33b2c3a70828b96
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 10133
content:
"the amplitude in the projected direction of change in CIDs at a given \r time horizon depends on climate change mitigation efforts over the \r 21st century. It is evident from Table TS.5 that many heat, cold, snow \r and ice, coastal, and oceanic CID changes are projected with high \r confidence in most regions starting from a global warming level \r (GWL) of 2degC, indicating worldwide challenges. Changes in many \r other regional CIDs have higher confidence later in the 21st century \r or at higher GWLs (high confidence), and another small subset are \r projected with high confidence for the 1.5degC GWL. This section \r focuses on the 2degC GWL and mid-century time period because the \r signal emerges from natural variability for a wider range of CIDs \r at this higher warming level. Figure TS.22 shows the geographical \r location of regions belonging to one of five groups characterized \r by a specific combination of changing CIDs. The Regional Synthesis \r [...]"


id: 99787d037718885d45daa15bc75199f4
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 24229
content:
"[...] component of the Interactive Atlas provides comprehensive synthesis \r information about changes in all of the individual CIDs across all of \r the AR6 WGI reference regions. {10.5, Cross-Chapter Box 10.3, 11.1, \r 11.9, Box 11.1, 12.1, 12.2, 12.4, 12.5}"


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"Figure TS.22 (continued): Panel (a) shows the geographical location of regions belonging to one of five groups characterized by a specific combination of changing climatic \r impact-drivers (CIDs). The five groups are represented by the five different colours, and the CID combinations associated with each group are represented in the corresponding \r 'fingerprint' and text below the map. Each fingerprint comprises a set of CIDs projected to change with high confidence in every region in the group and a second set of CIDs, \r one or more of which are projected to change in each region with high or medium confidence. The CID combinations follow a progression from those becoming hotter and drier \r (group 1) to those becoming hotter and wetter (group 5). In between (groups 2-4), the CIDs that change include some becoming drier and some wetter and always include \r [...]"


id: 51710b4d0f52802bbca22069f7c8691
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"[...] a set of CIDs which are getting hotter. Tropical cyclones and severe wind CID changes are represented on the map with black dots in the regions affected. Regions affected \r by coastal CID changes are described by text on the map. The five groups are chosen to provide a reasonable level of detail for each region while not overwhelming the map \r with a full summary of all aspects of the assessment, which is available in Table TS.5 and can be visualized in the Regional Synthesis component of the Interactive Atlas. The \r CID changes summarized in the figure represent high and medium confidence changes for the mid-21st century, considering scenarios SSP2-4.5, RCP4.5, SRES A1B, or above \r (SSP3-7.0, SSP5-8.5, RCP6.0, RCP8.5, SRES A2), which approximately encompasses global warming levels of 2.0degC to 2.4degC."


id: 649113b0ac9da2934475b0c167141347
created_at: 2023-04-19 13:22:33
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content_type: text
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content:
"The bar chart in panel (b) shows the numbers of regions where each CID is increasing or decreasing with medium or high confidence for all land regions and ocean regions \r listed in Table TS.5. The colours represent the direction of change and the level of confidence in the change: purple indicates an increase while brown indicates a decrease; darker \r and lighter shades refer to high and medium confidence, respectively. Lighter background colours represent the maximum number of regions for which each CID is broadly \r relevant. Sub-panel (i) shows the 30 CIDs relevant to the land and coastal regions while sub-panel (ii) shows the 5 CIDs relevant to the open ocean regions. Marine heatwaves \r and ocean acidity are assessed for coastal ocean regions in panel (i) and for open ocean regions in panel (ii). Changes refer to a 20- to 30-year period centred around 2050 \r [...]"


id: 868770797ae2384f87acce52014ad7f4
created_at: 2023-04-19 13:22:33
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content:
"[...] and/or consistent with 2degC global warming compared to a similar period within 1960-2014, except for hydrological drought and agricultural and ecological drought, which \r is compared to 1850-1900. Definitions of the regions are provided in Atlas.1, the Interactive Atlas (https://interactive-atlas.ipcc.ch/) and Chapter 12. (Table TS.5, Figure TS.24) \r {11.9, 12.2, 12.4, Atlas.1}"


id: d38323164f97f6852d0bfcc42d34dd48
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 34551
content:
"Heat and cold: Changes in temperature-related CIDs such as mean \r temperatures, growing season length, and extreme heat and frost have \r already occurred (high confidence), and many of these changes have \r been attributed to human activities (medium confidence). Over all \r land regions with sufficient data (i.e., all except Antarctica), observed \r changes in temperature have already clearly emerged outside the \r range of internal variability, relative to 1850-1900 (Figure TS.23). In \r tropical regions, recent past temperature distributions have already \r shifted to a range different to that of the early 20th century (high \r confidence) (Section TS.1.2.4). Most land areas have very likely\r warmed by at least 0.1degC per decade since 1960, and faster in recent \r decades. On regional-to-continental scales, trends of increased \r frequency of hot extremes and decreased frequency of cold extremes \r are generally consistent with the global-scale trends in mean \r [...]"


id: 6a68cd603b0862fae7eee692463dd18c
created_at: 2023-04-19 13:22:33
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vector_id: 16000
content:
"[...] temperature (high confidence). In a few regions, trends are difficult \r to assess due to limited data availability. {2.3.1.1, 11.3, 11.9, 12.4, \r Atlas.3.1}"


id: 696c706948faef688728f07e67eb8b4d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 15818
content:
"Wet and dry: Compared to the global scale, precipitation internal \r variability is stronger at the regional scale while uncertainties in \r observations, models and external forcing are all larger. However, \r GHG forcing has driven increased contrasts in precipitation amounts \r between wet and dry seasons and weather regimes over tropical land \r areas (medium confidence), with a detectable precipitation increase \r in the northern high latitudes (high confidence) (Box TS.6). The \r frequency and intensity of heavy precipitation events have increased \r over a majority of land regions with good observational coverage \r (high confidence). A majority of land areas have experienced \r decreases in available water in dry seasons due to human-induced \r climate change associated with changes in evapotranspiration \r (medium confidence). Global hydrological models project a larger \r fraction of land areas to be affected by an increase rather than by \r [...]"


id: 5a0f3bda708aa07b928d5969ef031db2
created_at: 2023-04-19 13:22:33
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vector_id: 13090
content:
"[...] a decrease in river floods (medium confidence). Extreme precipitation \r and pluvial flooding will increase in many regions around the world \r on almost all continents (high confidence), but regional changes \r in river floods are more uncertain than changes in pluvial floods \r because complex hydrological processes, including land cover and \r human water management, are involved. {8.2.2.1, 8.3.1, Box  8.2, \r 10.4.1, 11.5, 11.6, 11.9, 12.4, 12.5.1, Atlas.3.1}"


id: d8b821fc56876afb6354dd4d530c55ae
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index: climate_gpt_v2
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content:
"Snow and ice: Many aspects of the cryosphere either have seen \r significant changes in the recent past or will see them during the \r 21st century (high confidence). Glaciers will continue to shrink \r and permafrost to thaw in all regions where they are present (high \r confidence). Also, it is virtually certain that snow cover will experience \r a decline over most land regions during the 21st century, in terms \r of water equivalent, extent and annual duration. There is high \r confidence that the global warming-induced earlier onset of spring \r snowmelt and increased melting of glaciers have already contributed \r to seasonal changes in streamflow in high-latitude and low-elevation \r mountain catchments. Nevertheless, it is very likely that some high\u0002latitude regions will experience an increase in winter snow water \r equivalent due to the effect of increased snowfall prevailing over \r warming-induced increased snowmelt. (Section TS.2.5) {8.2.2.1, \r [...]"


id: 670b544768ced4fdb9281ebf5bd03a8c
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content:
"Other variables and concurrent CID changes: It is virtually certain\r that atmospheric CO2 and oceanic pH will increase in all climate \r scenarios, until net zero CO2 emissions are achieved (Section TS.2.2). \r In nearly all regions, there is low confidence in changes in hail, ice \r storms, severe storms, dust storms, heavy snowfall, and avalanches, \r although this does not indicate that these CIDs will not be affected \r by climate change. For such CIDs, observations are often short\u0002term or lack homogeneity, and models often do not have sufficient \r resolution or accurate parametrizations to adequately simulate them \r over climate change time scales. The probability of compound events \r has increased in the past due to human-induced climate change and \r will likely continue to increase with further global warming, including \r for concurrent heatwaves and droughts, compound flooding, and the \r possibility of connected sectors experiencing multiple regional extreme \r [...]"


id: 5d9cc38c5d6a9f7f4bc866f4a2e2ee38
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content:
"[...] events at the same time (for example, in multiple breadbaskets) (high \r confidence). {5.3.4.2, 11.8, Box 11.3, Box 11.4, 12.4}"


id: c34ef4701f1fb377352a6b3c0b10bf6b
created_at: 2023-04-19 13:22:33
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content_type: text
index: climate_gpt_v2
vector_id: 31632
content:
"Wet and dry: Mean precipitation changes have been observed \r over Africa, but the historical trends are not spatially coherent (high \r confidence). North Eastern Africa, East Southern Africa and Central \r Africa have experienced a decline in rainfall since about 1980 and \r parts of West Africa an increase (high confidence). Increases in the \r frequency and/or the intensity of heavy rainfall have been observed in \r East and West Southern Africa, and the eastern Mediterranean region \r (medium confidence). Increasing trends in river flood occurrence can \r be identified beyond 1980 in East and West Southern Africa (medium \r confidence) and Western Africa (high confidence). However, Northern \r Africa and West Southern Africa are likely to have a reduction in \r precipitation. Over West Africa, rainfall is projected to decrease \r in the western Sahel subregion and increase along the Guinea Coast \r subregion (medium confidence). Rainfall is projected to increase over \r [...]"


id: bc9701304a4b2247e273adcc2df0d9b8
created_at: 2023-04-19 13:22:33
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vector_id: 30427
content:
"[...] Eastern Africa (medium confidence). {8.3.1.6, 11.4, 11.9, 12.4.1.2, \r Atlas.4.2, Atlas.4.4, Atlas.4.5}"


id: 9006fd7ede084d2797e7954f7ba605a1
created_at: 2023-04-19 13:22:33
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content_type: text
index: climate_gpt_v2
vector_id: 22544
content:
"With 2degC global warming, and as early as the mid-21st \r century, a wide range of CIDs, particularly related to the \r water cycle and storms, are expected to show simultaneous \r region-specific changes relative to the recent past with high\r or medium confidence. In a number of regions (Southern \r Africa, the Mediterranean, North Central America, Western \r North America, the Amazon regions, South-Western South \r America, and Australia), increases in one or more of drought, \r aridity and fire weather (high confidence) will affect a wide \r range of sectors, including agriculture, forestry, health and \r ecosystems. In another group of regions (North-Western, \r Central and Eastern North America, Arctic regions, North\u0002Western South America, Northern, Western and Central \r and Eastern Europe, Siberia, Central, South and East Asia, \r Southern Australia and New Zealand), decreases in snow \r and/or ice or increases in pluvial/river flooding (high \r [...]"


id: 4ee9da3c923aacbbe8c7438faf53869c
created_at: 2023-04-19 13:22:33
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vector_id: 11166
content:
"[...] confidence) will affect sectors such as winter tourism, \r energy production, river transportation and infrastructure. \r {11.9, 12.3, 12.4, 12.5, Table 12.2}"


id: 3011a66d653b564841a3c94d01a7ea18
created_at: 2023-04-19 13:22:33
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content_type: text
index: climate_gpt_v2
vector_id: 5722
content:
"Additional regional changes in Central and South America, \r besides those features described in Section TS.4.3.1, include \r increases in mean and extreme precipitation in South\u0002Eastern South America since the 1960s (high confidence) \r (Section TS.4.2.3). Decreasing trends in mean precipitation \r and increasing trends in agricultural and ecological drought \r are observed over North-Eastern South America (medium \r confidence). The intensity and frequency of extreme \r precipitation and pluvial floods is projected to increase \r over South-Eastern South America, Southern South America, \r Northern South America, South American Monsoon and \r North-Eastern South America (medium confidence) for a 2degC \r GWL and above. Increases of agricultural and ecological \r drought are projected in South America Monsoon and \r Southern South America, and fire weather is projected to \r increase over several regions (Northern South America, the \r South American Monsoon, North-Eastern South America \r [...]"


id: d132a2dbda5bc9f0a2ef5e46c201f247
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content:
"[...] and South-Western South America) (high confidence). {8.3, \r 8.4, 11.3, 11.4, 11.9, Table 11.13, Table 11.14, Table 11.15, \r 12.4.4.2, Atlas.7.1, Atlas.7.2}"


id: 41b7fa04a4f0da488a4e5d6c105535bc
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
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content:
"Additional regional changes in Europe, besides those features \r described in Section TS.4.3.1, include observed increases \r in pluvial flooding in Northern Europe and hydrological \r and agricultural/ecological droughts in the Mediterranean \r (high confidence), which have been attributed to human \r influence with high and medium confidence, respectively. \r Increased mean precipitation amounts at high latitudes \r in boreal winter and reduced summer precipitation in \r southern Europe are projected starting from a 2degC GWL \r (high confidence). Aridity, agricultural and hydrological \r droughts and fire weather conditions will increase in \r the Mediterranean region starting from 2degC GWL (high \r confidence). Pluvial flooding will increase everywhere \r with high confidence except for medium confidence in the \r Mediterranean; in Western and Central Europe this also \r applies to river flooding starting from a 2degC GWL (high \r confidence). Most periglacial processes in Northern Europe \r [...]"


id: ef8b2a7335db79f5c36e41b1dc24900c
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content:
"[...] are projected to disappear by the end of the 21st century, \r even for a low warming scenario (medium confidence). {8.3, \r 11.3, 11.9, 12.4.5, 12.5.2, Atlas.8.2, Atlas.8.4}"


id: 993e739b89a77c67e4da35c7c475d167
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vector_id: 24177
content:
"Hui-Wen Lai (Sweden), Tania Villasenor (Chile), Rondrotiana Barimalala (South Africa/\r Madagascar), Rosario Carmona (Chile), Peter M. Cox (United Kingdom), Wolfgang Cramer (France/\r Germany), Francisco J. Doblas-Reyes (Spain), Hans Dolman (The Netherlands), Alessandro Dosio \r (Italy), Veronika Eyring (Germany), Gregory M. Flato (Canada), Piers Forster (United Kingdom), \r David Frame (New Zealand), Katja Frieler (Germany), Jan S. Fuglestvedt (Norway), John C. Fyfe \r (Canada), Mathias Garschagen (Germany), Joelle Gergis (Australia), Nathan P. Gillett (Canada), \r Michael  Grose (Australia), Eric Guilyardi (France), Celine Guivarch (France), Susan Hassol \r (United  States of America), Zeke Hausfather (United States of America), Hans Hersbach \r (United Kingdom/The Netherlands), Helene T. Hewitt (United Kingdom), Mark Howden (Australia), \r Christian Huggel (Switzerland), Margot Hurlbert (Canada), Christopher Jones (United Kingdom), \r [...]"


id: f88c749dcdfec22b18eb6eb3f1f34a92
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"[...] Richard G. Jones (United Kingdom), Darrell S. Kaufman (United States of America), Robert E. Kopp \r (United States of America), Anthony Leiserowitz (United States of America), Robert J. Lempert \r (United States of America), Jared Lewis (Australia/New Zealand), Hong Liao (China), \r Nikki  Lovenduski (United  States of America), Marianne  T.  Lund (Norway), Katharine  Mach \r (United States of America), Douglas Maraun (Austria/Germany), Jochem Marotzke (Germany), \r Jan Minx (Germany), Zebedee  R.J.  Nicholls (Australia), Brian  C.  O'Neill (United  States \r of America), M. Giselle Ogaz (Chile), Friederike Otto (United Kingdom/Germany), Wendy Parker \r (United  Kingdom), Camille  Parmesan (France, United Kingdom/United States of America), \r Warren Pearce (United Kingdom), Roque Pedace (Argentina), Andy Reisinger (New Zealand), \r James  Renwick (New  Zealand), Keywan  Riahi (Austria), Paul  Ritchie (United Kingdom), \r [...]"


id: c9b61f7a350718599ad4c8bacb4cfd88
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content:
"[...] Joeri  Rogelj (United Kingdom/Belgium), Rodolfo  Sapiains (Chile), Yusuke Satoh (Japan), \r Sonia I. Seneviratne (Switzerland), Theodore G. Shepherd (United Kingdom/Canada), Jana Sillmann \r (Norway/Germany), Lucas Silva (Portugal/Switzerland), Aimee B.A. Slangen (The Netherlands), "


id: 999eb65532174b96590fdfbf2ac122da
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content:
"Understanding of the fundamental features of the climate \r system is robust and well established. Scientists in the 19th century \r identified the major natural factors influencing the climate system. \r They also hypothesized the potential for anthropogenic climate \r change due to carbon dioxide (CO2) emitted by fossil fuel combustion. \r The principal natural drivers of climate change, including changes in \r incoming solar radiation, volcanic activity, orbital cycles, and changes \r in global biogeochemical cycles, have been studied systematically \r since the early 20th  century. Other major anthropogenic drivers, \r such as atmospheric aerosols (fine solid particles or liquid droplets), \r land-use change and non-CO2 greenhouse gases, were identified \r by the 1970s. Since systematic scientific assessments began in the \r 1970s, the influence of human activity on the warming of the climate \r system has evolved from theory to established fact. Past projections \r [...]"


id: 5489383489aa39745c5e94e03ef378e1
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"[...] of global surface temperature and the pattern of warming are \r broadly consistent with subsequent observations (limited evidence,\r high agreement), especially when accounting for the difference in \r radiative forcing scenarios used for making projections and the \r radiative forcings that actually occurred. {1.3.1-1.3.6}"


id: e76f59c2e7f459bb74b6fa9274596f17
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content:
"The WGI contribution to the IPCC Sixth Assessment Report (AR6) \r assesses new scientific evidence relevant for a world whose \r climate system is rapidly changing, overwhelmingly due to \r human influence. The five IPCC assessment cycles since 1990 have \r comprehensively and consistently laid out the rapidly accumulating \r evidence of a changing climate system, with the Fourth Assessment \r Report (AR4, 2007) being the first to conclude that warming of \r the climate system is unequivocal. Sustained changes have been \r documented in all major elements of the climate system, including \r the atmosphere, land, cryosphere, biosphere and ocean. Multiple \r lines of evidence indicate the unprecedented nature of recent large\u0002scale climatic changes in the context of all human history, and that \r these changes represent a millennial-scale commitment for the slow\u0002responding elements of the climate system, resulting in continued \r worldwide loss of ice, increase in ocean heat content, sea level rise \r [...]"


id: 704e0f96ea11f25f46f058937fb946a7
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updated_at: 2023-04-19 13:22:33
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"Since the IPCC Fifth Assessment Report (AR5), the international \r policy context of IPCC reports has changed. The UN Framework \r Convention on Climate Change (UNFCCC, 1992) has the overarching \r objective of preventing 'dangerous anthropogenic interference \r with the climate system'. Responding to that objective, the Paris \r Agreement (2015) established the long-term goals of 'holding the \r increase in global average temperature to well below 2degC above pre\u0002industrial levels and pursuing efforts to limit the temperature increase \r to 1.5degC above pre-industrial levels' and of achieving 'a balance \r between anthropogenic emissions by sources and removals by sinks \r of greenhouse gases in the second half of this century'. Parties to \r the Agreement have submitted Nationally Determined Contributions \r (NDCs) indicating their planned mitigation and adaptation strategies. \r However, the NDCs submitted as of 2020 are insufficient to reduce \r [...]"


id: b430974e03ed85af82dbb573bcb4b827
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vector_id: 28935
content:
"[...] greenhouse gas emissions enough to be consistent with trajectories \r limiting global warming to well below 2degC above pre-industrial levels \r (high confidence). {1.1, 1.2}"


id: 861c92e0672a4eb697e35eeb6c3932e0
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updated_at: 2023-04-19 13:22:33
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vector_id: 20743
content:
"The latest generation of complex climate models has an \r improved representation of physical processes, and a  wider \r range of Earth system models now represent biogeochemical \r cycles. Since AR5, higher-resolution models that better capture \r smaller-scale processes and extreme events have become \r available. Key model intercomparisons supporting this Assessment \r include the Coupled Model Intercomparison Project Phase 6 (CMIP6) \r and the Coordinated Regional Climate Downscaling Experiment \r (CORDEX), for global and regional models respectively. Results \r using CMIP Phase 5  (CMIP5) simulations are also assessed. Since \r AR5, large ensemble simulations, where individual models perform \r multiple simulations with the same climate forcings, are increasingly \r used to inform understanding of the relative roles of internal \r variability and forced change in the climate system, especially \r on regional scales. The  broader availability of ensemble model \r [...]"


id: 9b0acec445cc2c3bb1737c696f6eb877
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"[...] simulations has contributed to better estimations of uncertainty \r in projections of future change (high confidence). A  broad set of \r simplified climate models is assessed and used as emulators to \r transfer climate information across research communities, such as for \r evaluating impacts or mitigation pathways consistent with certain \r levels of future warming. {1.4.2, 1.5.3, 1.5.4, Cross-Chapter Box 7.1}"


id: fe66957b86e304cd80cdab7f4b0b6d10
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content:
"Assessments of future climate change are integrated within \r and across the three IPCC Working Groups through the use of \r three core components: scenarios, global warming levels, and \r the relationship between cumulative CO2 emissions and global \r warming. Scenarios have a long history in the IPCC as a method for \r systematically examining possible futures. A new set of illustrative \r scenarios that cover the range of possible future developments of \r anthropogenic drivers of climate change found in the literature, \r derived from the Shared Socio-economic Pathways (SSPs), is used \r to synthesize knowledge across the physical sciences and impact, \r adaptation and mitigation research. The core set of SSP scenarios \r used in the WGI report, SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and \r SSP5-8.5, cover a broad range of emissions pathways, including new \r low-emissions pathways. They start in 2015 and include scenarios \r with high and very high greenhouse gas (GHG) emissions (SSP3-7.0 \r [...]"


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content:
"[...] and SSP5-8.5) and CO2 emissions that roughly double from current \r levels by 2100 and 2050, respectively; scenarios with intermediate "


id: a8141fe4d02b9175e9cc23b9365bd268
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updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 26784
content:
"GHG emissions (SSP2-4.5) and CO2 emissions remaining around \r current levels until the middle of the century; and scenarios with very \r low and low GHG emissions and CO2 emissions declining to net zero \r around or after 2050, followed by varying levels of net negative CO2\r emissions (SSP1-1.9, SSP1-2.6). Emissions vary between scenarios \r depending on socio-economic assumptions, levels of climate change \r mitigation and, for aerosols and non-methane ozone precursors, \r air pollution controls. Alternative assumptions may result in similar \r emissions and climate responses, but the socio-economic assumptions \r and the feasibility or likelihood of individual scenarios are not part of \r this assessment, which focuses on the climate response to possible, \r prescribed emissions futures. Levels of global surface temperature \r change (global warming levels), which are closely related to a range \r of hazards and regional climate impacts, also serve as reference \r [...]"


id: 4ecd3e833f8f2348bfbe45344c74731a
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content:
"[...] points within and across IPCC Working Groups. Cumulative carbon \r emissions, which have a  nearly linear relationship to increases \r in global surface temperature, are also used. {1.6.1-1.6.4, \r Cross-Chapter Box 1.5, Cross-Chapter Box 11.1}"


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"Regional Information (Chapters  10, 11, 12 and Atlas). New \r knowledge on climate change at regional scales is reflected in this \r report with four chapters covering regional information. Chapter 10 \r provides a framework for assessment of regional climate information, \r including methods, physical processes, an assessment of observed \r changes at regional scales, and the performance of regional models. \r Chapter 11 addresses extreme weather and climate events, including \r temperature, precipitation, flooding, droughts and compound events. \r Chapter 12 provides a comprehensive, region-specific assessment of \r changing climatic conditions that may be hazardous or favourable \r (hence influencing climate risk) for various sectors to be assessed \r in WGII. Lastly, the Atlas assesses and synthesizes regional climate \r information from the whole report, focussing on the assessments of \r mean changes in different regions and on model assessments for \r [...]"


id: 935e10e8ad01def3983b6a438c69c9b5
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content:
"[...] the regions. It also introduces the online Interactive Atlas, a novel \r compendium of global and regional climate change observations and \r projections. It includes a visualization tool, which combines various \r warming levels and scenarios on multiple scales of space and time."


id: 9e93877e9d3f5be2c250b6cf455c09a2
created_at: 2023-04-19 13:22:33
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content:
"The chapter comprises seven sections (Figure 1.3). Section 1.2 describes \r the present state of Earth's climate, in the context of reconstructed \r and observed long-term changes and variations caused by natural \r and anthropogenic factors. It also provides context for the present \r Assessment by describing recent changes in international climate \r change governance and fundamental scientific values. The evolution \r of knowledge about climate change and the development of earlier \r IPCC assessments are presented in Section 1.3. Approaches, methods \r and key concepts of this Assessment are introduced in Section 1.4. \r New developments in observing networks, reanalyses, modelling \r capabilities and techniques since AR5 are discussed in Section 1.5. The \r three main 'dimensions of integration' across Working Groups in AR6, \r that is, emissions scenarios, global warming levels and cumulative \r carbon emissions, are described in Section 1.6. The Chapter closes \r [...]"


id: c8c1124a673c0d9d0af5f6b67b17b511
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
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content:
"The physical climate system comprises all processes that combine to \r form weather and climate. The early chapters of this report broadly \r organize their assessments according to overarching realms: the \r atmosphere, the biosphere, the cryosphere (surface areas covered \r by frozen water, such as glaciers and ice sheets), and the ocean. \r Elsewhere in the report, and in previous IPCC assessments, the land is \r also used as an integrating realm that includes parts of the biosphere \r and the cryosphere. These overarching realms have been studied \r and measured in increasing detail by scientists, institutions and \r the general public since the 18th  century, throughout the era of \r instrumental observation (Section 1.3). Today, observations include \r those taken by numerous land surface stations, ocean surface \r measurements from ships and buoys, underwater instrumentation, \r satellite and surface-based remote sensing, and in situ atmospheric \r [...]"


id: 61ff33b1324aa4b00f9ad4bdfc725972
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"[...] measurements from aeroplanes and balloons. These instrumental \r observations are combined with paleoclimate reconstructions and \r historical documentations to produce a  highly detailed picture \r of the past and present state of the whole climate system, and to \r allow assessments about rates of change across the different realms \r (Chapter 2 and Section 1.5)."


id: e1453e07e4efcaa980749262bd1c8157
created_at: 2023-04-19 13:22:33
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content:
"Figure  1.5 (continued): (a) Measurements of CO2 in air enclosed in Antarctic ice cores (Luthi et al., 2008; Bereiter et al., 2015 [a compilation]; uncertainty \r +-1.3 ppm; see Sections 2.2.3 and 5.1.2 for an assessment) and direct air measurements (Tans and Keeling, 2020; uncertainty +-0.12 ppm). Projected CO2 concentrations \r for five Shared Socio-economic Pathways (SSP) scenarios are indicated by dots on the right-hand side of each panel (grey background; (Meinshausen et al., 2020; SSPs are \r described in Section 1.6). (b) Reconstruction of GMST from marine paleoclimate proxies (light-grey line: Snyder (2016); dark grey line: Hansen et al. (2013); see Section 2.3.1 \r for an assessment). Observed and reconstructed temperature changes since 1850 are the AR6 assessed mean (referenced to 1850-1900; Box TS.3; 2.3.1.1); dots/whiskers \r [...]"


id: 3bba61845bd2e15c971ae2b011f19b45
created_at: 2023-04-19 13:22:33
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"[...] on the right-hand panels (grey background) indicate the projected mean and ranges of warming derived from Coupled Model Intercomparison Project Phase 6 (CMIP6) SSP\u0002based (2081-2100) and Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC7; 2300) simulations (Tables 4.5 and 4.9). (c) Sea level changes \r reconstructed from a  stack of oxygen isotope measurements on seven ocean sediment cores (Spratt and Lisiecki, 2016; see Chapter  2, Section  2.3.3.3 and Chapter  9, \r Section 9.6.2 for an assessment). The sea level record from 1850-1900 is from Kopp et al. (2016), while the 20th century record is an updated ensemble estimate of GMSL \r change (Palmer et al., 2021; Sections 2.3.3.3 and 9.6.1.1). Dots/whiskers on the right-hand panels of the figure (grey background) indicate the projected median and ranges \r [...]"


id: 74abd6688c18cbac9c3072829bf2f203
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"[...] derived from SSP-based simulations (2081-2100: Table 9.9; 2300: Section 9.6.3.5). Best estimates (dots) and uncertainties (whiskers), as assessed in Chapter 2, are included \r in the left and middle panels for each of the three indicators and selected paleo-reference periods used in this report (CO2: Table 2.1; GMST: Section 2.3.1.1 and Cross-Chapter \r Box 2.3, Table 1; GMSL: Sections 2.3.3.3 and 9.6.2. See also Cross-Chapter Box 2.1). Selected paleo-reference periods: LIG - Last Interglacial; LGM - Last Glacial Maximum; \r MH - mid-Holocene (Cross-Chapter Box 2.1, Table 1). The non-labelled best estimate in panel (c) corresponds to the sea level high-stand during Marine Isotope Stage 11, about \r 410 ka (410,000 years ago; Section 9.6.2). Further details on data sources and processing are available in the chapter data table (Table 1.SM.1)."


id: 12263065dc4d4607821fa2cbe35b9501
created_at: 2023-04-19 13:22:33
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content:
"This establishes an essential long-term context for the climate change \r of the past 150 years and the projected changes in the 21st century \r and beyond (Chapter  3; IPCC, 2013a; Masson-Delmotte et al., 2013). \r Figure 1.5 shows reconstructions of three key indicators of climate change \r over the past 800,000 years (800 kyr)2 - atmospheric CO2 concentrations, \r global mean surface temperature (GMST) and global mean sea level \r (GMSL) - comprising at least eight complete glacial-interglacial cycles \r (EPICA Community Members, 2004; Jouzel et al., 2007), which are largely \r driven by oscillations in the Earth's orbit and consequent feedbacks \r on multi-millennial time scales (Berger, 1978; Laskar et al., 1993). The \r dominant cycles  - recurring approximately every 100 kyr  - can be \r found imprinted in the natural variations of these three key indicators. \r Before industrialisation, atmospheric CO2 concentrations varied between \r [...]"


id: 1a999fd0f2384704ecf927dd3f1ceba5
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 1882
content:
"[...] 174 ppm and 300 ppm, as measured directly in air trapped in ice at \r Dome Concordia, Antarctica (Bereiter et al., 2015; Nehrbass-Ahles et al., \r 2020). Relative to 1850-1900 CE, the reconstructed GMST changed in \r the range of -6degC to +1degC across these glacial-interglacial cycles (see \r Chapter 2, Section 2.3.1 for an assessment of different paleo-reference \r periods). GMSL varied between about -130 m during the coldest glacial \r maxima and +5 to +25 m  during the warmest interglacial periods \r (Chapter 2; Spratt and Lisiecki, 2016). They represent the amplitudes of \r natural, global-scale climate variations over the last 800 kyr prior to the \r influence of human activity. Further climate information from a variety of \r paleoclimatic archives is assessed in Chapters 2, 5, 7 and 9."


id: b6610fa0957637a036d1c512d1648d5c
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 29302
content:
"The rate, scale and magnitude of anthropogenic changes in the \r climate system since the mid-20th century suggested the definition \r of a new geological epoch: the Anthropocene (Crutzen and Stoermer, \r 2000; Steffen et al., 2007), referring to an era in which human \r activity is altering major components of the Earth system and leaving \r measurable imprints that will remain in the permanent geological \r record (Figure  1.5; IPCC, 2018). These alterations include not only \r climate change itself, but also chemical and biological changes in \r the Earth system such as rapid ocean acidification due to uptake \r of anthropogenic CO2, massive destruction of tropical forests, \r a  worldwide loss of biodiversity and the sixth mass extinction of \r species (Hoegh-Guldberg and Bruno, 2010; Ceballos et al., 2017; \r IPBES, 2019). According to the key messages of the last global \r assessment of the Intergovernmental Science-Policy Platform on \r [...]"


id: fad62008678a0840df0e07af3cf3e347
created_at: 2023-04-19 13:22:33
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content:
"[...] Biodiversity and Ecosystem Services (IPBES, 2019), climate change is \r a 'direct driver that is increasingly exacerbating the impact of other \r drivers on nature and human well-being', and 'the adverse impacts \r of climate change on biodiversity are projected to increase with \r increasing warming.'"


id: e57931fbcda80ffb23b944d8874aa7a6
created_at: 2023-04-19 13:22:33
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content:
"Numerous studies of the NDCs submitted since adoption of the PA \r in 2015 (Fawcett et al., 2015; UNFCCC, 2015, 2016; Lomborg, 2016; \r Rogelj et al., 2016, 2017; Benveniste et al., 2018; Gutschow et al., \r 2018; UNEP, 2019) conclude that they are insufficient to meet the \r Paris temperature goal. In the present IPCC Sixth Assessment Cycle, \r a  Special Report on Global Warming of 1.5degC (SR1.5, IPCC, 2018) \r found, with high agreement, that current NDCs 'are not in line with \r pathways that limit warming to 1.5degC by the end of the century.' The \r PA includes a ratcheting mechanism designed to increase the ambition \r of voluntary national pledges over time. Under this mechanism, NDCs \r will be communicated or updated every five years. Each successive \r NDC will represent a 'progression beyond' the 'then current' NDC and \r reflect the 'highest possible ambition' (Article 4). These updates will \r be informed by a five-yearly periodic review including the Structured \r [...]"


id: 3c5de539ab8508e025984bb560cdb4b3
created_at: 2023-04-19 13:22:33
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vector_id: 7811
content:
"The SED of the first periodic review (2013-2015) provided an \r important opportunity for face-to-face dialogue between decision \r makers and experts on review themes, based on 'the best available \r scientific knowledge, including the assessment reports of the IPCC.' \r That SED was instrumental in informing the long-term global goal of \r the PA and in providing the scientific argument for the consideration \r of limiting warming to 1.5degC warming (UNFCCC, 2015; Fischlin, \r 2017). The SED of the second periodic review, initiated in the second \r half of 2020, focuses on, among other things, 'enhancing Parties' \r understanding of the long-term global goal and the scenarios \r towards achieving it in the light of the ultimate objective of the \r Convention'. The second SED provides a  formal venue for the \r scientific and the policy communities to discuss the requirements \r and benchmarks to achieve the 'long-term temperature goal' (LTTG) \r [...]"


id: 6ff15c3a409accba04873ae8b360c540
created_at: 2023-04-19 13:22:33
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vector_id: 16949
content:
"[...] of 1.5degC and well below 2degC global warming. The discussions also \r concern the associated timing of net zero emissions targets and the \r different interpretations of the PA LTTG, including the possibility \r of overshooting the 1.5deg C warming level before returning to it by \r means of negative emissions (e.g.,  Section  1.6; Schleussner and \r Fyson, 2020). The second periodic review is planned to continue until \r November 2022 and its focus includes the review of the progress \r made since the first review, while minimising 'possible overlaps' and \r profiting from 'synergies with the global stocktake'."


id: ecfd88406c17709692731b9f76b21143
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 39065
content:
"The global stocktake under the Paris Agreement (PA) evaluates the collective progress of countries' actions towards \r attaining the Agreement's purpose and long-term goals every five years. The first global stocktake is due in 2023, and then \r every five years thereafter, unless otherwise decided by the Conference of the Parties. The purpose and long-term goals of the PA \r are captured inter alia in Article 2: to 'strengthen the global response to the threat of climate change, in the context of sustainable \r development and efforts to eradicate poverty, including by': mitigation3 specifically, 'holding the increase in the global average \r temperature to well below 2degC above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5degC above \r pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change'; adaptation, that is, \r [...]"


id: b3365edf710c2168ff05ff52d7a3f35b
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"[...] 'increasing the ability to adapt to the adverse impacts of climate change and foster climate resilience and low greenhouse gas (GHG) \r emissions development, in a manner that does not threaten food production'; and means of implementation and support, that is, \r 'making finance flows consistent with a pathway towards low GHG emissions and climate-resilient development.'"


id: e284b566c456f781e8ff094702de9f78
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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vector_id: 37150
content:
"Many interactions among environmental problems and development \r are addressed in the United Nations 2030 Agenda for Sustainable \r Development and its Sustainable Development Goals. The 2030 \r Agenda, supported by the finance-oriented Addis Ababa Action \r Agenda (UN DESA, 2015), calls on nations to 'take the bold and \r transformative steps which are urgently needed to shift the world \r onto a sustainable and resilient path.' The 2030 Agenda recognizes \r that 'climate change is one of the greatest challenges of our time and \r its adverse impacts undermine the ability of all countries to achieve \r sustainable development.' SDG 13 deals explicitly with climate \r change, establishing several targets for adaptation, awareness\u0002raising and finance. Climate and climate change are also highly \r relevant to most other SDGs, and UNFCCC is acknowledged as the \r main forum to negotiate the global response to climate change. \r For example, both long-lived GHGs (through mitigation decisions), \r [...]"


id: 39ff788eac197623967f6d0397ae8641
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 7417
content:
"[...] and SLCFs (through air quality), are relevant to SDG 11 (sustainable \r cities and communities). Chapter  6  assesses the effects of SLCFs \r on climate and the implications of changing climate for air quality, \r including opportunities for mitigation relevant to the SDGs (Box 6.2). \r Also, the UN Conference on Housing and Sustainable Development \r established a New Urban Agenda (United Nations, 2017) envisaging \r cities as part of the solutions for sustainable development, climate \r change adaptation and mitigation."


id: 27b1ab0efd05b3df7e0a4e13384add1d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 4167
content:
"Addressing climate change alongside other environmental problems, \r while simultaneously supporting sustainable socio-economic \r development, requires a  holistic approach. Since AR5, there is \r increasing attention on the need for coordination among previously \r independent international agendas, and a  recognition that climate \r change, disaster risk, economic development, biodiversity conservation \r and human well-being are tightly interconnected. The  current \r COVID-19 pandemic provides an example of the need for such \r interconnection, with its widespread impacts on economy, society and \r environment (e.g., Shan et al., 2021). Cross-Chapter Box 6.1 assesses \r the consequences of the COVID-19 lockdowns for emissions of GHGs \r and SLCFs, and related implications for the climate. Another example \r of the interconnected nature of these issues is the close link between \r SLCF emissions, climate change and air quality concerns (Chapter 6). \r [...]"


id: f14f1b17b3e4e096fde84e772ec4e3a1
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content:
"[...] Emissions of halocarbons have previously been successfully regulated \r under the Montreal Protocol and its Kigali Amendment. This has \r been achieved in an effort to reduce ozone depletion that has also \r modulated other anthropogenic climate influence (Estrada et al., \r 2013; Wu et al., 2013). In the process, emissions of some SLCFs were \r jointly regulated to reduce environmental and health impacts from air \r pollution (e.g., Gothenburg Protocol; Reis et al., 2012). Considering the \r recognized importance of SLCFs in climate change processes, the IPCC \r decided in May 2019 to approve that the IPCC Task Force on National \r Greenhouse Gas Inventories produces an IPCC Methodology Report on \r SLCFs to develop guidance for national SLCF inventories."


id: d45fcc7c28e2c2df9272a4eca659ee9a
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index: climate_gpt_v2
vector_id: 34685
content:
"Political cultures also give rise to variation in how climate science \r knowledge is interpreted, used and challenged (Leiserowitz, 2006; \r Oreskes and Conway, 2010; Brulle et al., 2012; Dunlap and Jacques, \r 2013; Mahony, 2014, 2015; Brulle, 2019). A  meta-analysis of \r 87  studies carried out between 1998 and 2016 (62 USA national, \r 16 non-USA national, 9 cross-national) found that political orientation \r and political party identification were the second most important \r predictors of views on climate change after environmental values \r (McCright et al. 2016). Ruiz et al. (2020) systematically reviewed \r 34 studies of non-US nations or clusters of nations and 30 studies \r of the USA alone. They found that in the non-US studies, 'changed \r weather' and 'socio-altruistic values' were the most important \r drivers of public attitudes. For the USA case, by contrast, political \r affiliation and the influence of corporations were most important. \r [...]"


id: 62325acbcd6b06b9808076ccbf9bf48
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"[...] Widely varying media treatment of climate issues also affects public \r responses (Section 1.2.3.4). In summary, environmental and socio\u0002altruistic values are the most significant influences on public opinion \r about climate change globally, while political views, political party \r affiliation, and corporate influence also had strong effects, especially \r in the USA (high confidence)."


id: 2ffb475014636a61ef99d5afabebbcca
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content:
"If the author team concludes that there is sufficient evidence and agreement, the level of confidence can be evaluated. In this \r step, assessments of evidence and agreement are combined into a single metric (steps 3-5). The assessed level of confidence is \r expressed using five qualifiers: very low, low, medium, high, and very high. Step 4 depicts how summary statements for evidence and \r agreement relate to confidence levels. For a given evidence and agreement statement, different confidence levels can be assigned \r depending on the context, but increasing levels of evidence and degrees of agreement correlate with increasing confidence. When \r confidence in a finding is assessed to be low, this does not necessarily mean that confidence in its opposite is high, and vice versa. \r Similarly, low confidence does not imply distrust in the finding; instead, it means that the statement is the best conclusion based on \r [...]"


id: 7ed245ba1fa1094b725673085dcf4cc7
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index: climate_gpt_v2
vector_id: 19466
content:
"[...] currently available knowledge. Further research and methodological progress may change the level of confidence in any finding in \r future assessments."


id: d19bf2c84418422e3d9266c23389bab1
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 34227
content:
"Budescu et al. (2014) surveyed 25 samples in 24 countries (a total \r of 10,792 individual responses), finding that even when shown IPCC \r uncertainty guidance, lay readers systematically misunderstood \r IPCC likelihood statements. When presented with a 'high likelihood' \r statement, they understood it as indicating a lower likelihood than \r intended by the IPCC authors. Conversely, they interpreted 'low \r likelihood' statements as indicating a  higher likelihood than \r intended. In another study, British lay readers interpreted uncertainty \r language somewhat differently from IPCC guidance, but Chinese \r lay people reading the same uncertainty language translated into \r Chinese differed much more in their interpretations (Harris et al., \r 2013). Further, even though it is objectively more probable that wide \r uncertainty intervals will encompass true values, wide intervals were \r interpreted by lay people as implying subjective uncertainty or lack \r [...]"


id: 6f344df9f106c8663d058921eca745d
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
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content:
"[...] of knowledge on the part of scientists (Lohre et al., 2019). Mach \r et al. (2017) investigated the advances and challenges in approaches \r to expert judgment in AR5. Their analysis showed that the shared \r framework increased the overall comparability of assessment \r conclusions across all Working Groups and topics related to climate \r change, from the physical science basis to resulting impacts, risks, and \r options for response. Nevertheless, many challenges in developing \r and communicating assessment conclusions persist, especially for \r findings drawn from multiple disciplines and Working Groups, for \r subjective aspects of judgements, and for findings with substantial \r uncertainties (Adler and Hirsch Hadorn, 2014). In summary, the \r calibrated language cannot entirely prevent misunderstandings, \r including a tendency to systematically underestimate the probability \r of the IPCC's higher-likelihood conclusions and overestimate the \r [...]"


id: aa9b8dc50bd2812d94f8f03966616bc1
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 27237
content:
"[...] probability of the lower-likelihood ones (high confidence). However, \r a  consistent and systematic approach across Working Groups to \r communicate the assessment outcomes is an important characteristic \r of the IPCC."


id: 6f7a4a60fef3ec974ede3b61943c3426
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 16877
content:
"As noted above, values  - fundamental attitudes about what \r is important, good, and right  - play critical roles in all human \r endeavours, including climate science. In AR5, Chapters 3 and 4 of \r the WGIII Assessment addressed the role of cultural, social and ethical \r values in climate change mitigation and sustainable development \r (Fleurbaey et al., 2014; Kolstad et al., 2014). These values include \r widely accepted concepts of human rights, enshrined in international \r law, that are relevant to climate impacts and policy objectives (Hall \r and Weiss, 2012; Peel and Osofsky, 2018; Setzer and Vanhala, 2019). \r Specific values  - human life, subsistence, stability, and equitable \r distribution of the costs and benefits of climate impacts and policies - \r are explicit in the texts of the UNFCCC and the PA (Breakey et al., \r 2016; Dooley and Parihar, 2016). Here we address the role of values \r in how scientific knowledge is created, verified and communicated. \r [...]"


id: 8897cc95aa39d33487cd8ecaadd422ac
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 21195
content:
"[...] Chapters 10, 12 and Cross-Chapter Box 12.2 address how the specific \r values and contexts of users can be addressed in the co-production \r of climate information."


id: 534a86ea01a9049b32ca123106b07960
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 11927
content:
"The epistemic (knowledge-related) values of science include \r explanatory power, predictive accuracy, falsifiability, replicability, \r and justification of claims by explicit reasoning (Popper, 1959; \r Kuhn, 1977). These are supported by key institutional values, \r including openness, 'organized scepticism', and objectivity or \r 'disinterestedness' (Merton, 1973), operationalized as well-defined \r methods, documented evidence, publication, peer review, and \r systems for institutional review of research ethics (COSEPUP, 2009; \r Elliott, 2017). In recent decades, open data, open code and scientific \r cyber-infrastructure (notably the Earth System Grid Federation, \r a partnership of climate modelling centers dedicated to supporting \r climate research by providing secure, web-based, distributed access \r to climate model data) have facilitated scrutiny from a larger range \r of participants, and FAIR data stewardship principles  - making \r [...]"


id: 7175eac3f55ad329e60672f23f0f177
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 17213
content:
"[...] data Findable, Accessible, Interoperable and Reusable (FAIR)  - are \r being mainstreamed in many fields (Wilkinson et al., 2016). Climate \r science norms and practices embodying these scientific values and \r principles include the publication of data and model code, multiple \r groups independently analysing the same problems and data, model \r intercomparison projects (MIPs), explicit evaluations of uncertainty, \r and comprehensive assessments by national academies of science \r and the IPCC."


id: e7f1c6f48f85551aa09affedbf4ee88d
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"The framework for communicating uncertainties does not allow \r for indicating cases where 'deep uncertainty' is identified in the \r assessment (Adler and Hirsch Hadorn, 2014). The definition of deep \r uncertainty in IPCC assessments has been described in the context \r of SROCC (IPCC, 2019b; Box 5 in Abram et al., 2019): a situation of \r deep uncertainty exists when experts or stakeholders do not know \r or cannot agree on: (i) appropriate conceptual models that describe \r relationships among key driving forces in a system; (ii) the probability \r distributions used to represent uncertainty about key variables and \r parameters; and/or (iii) how to weigh and value desirable alternative \r outcomes (Cross-Chapter Box  1.2 and Annex VII: Glossary; Abram \r et al., 2019). Since AR5, 'storylines' or 'narratives' approaches have \r been used to address issues related to deep uncertainty, for example \r low-likelihood events that would have high impact if they occurred, \r [...]"


id: f252feb940f8c4e5b71d2e2fce496e2b
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"Responding to national and regional policymakers' needs for \r tailored information relevant to risk assessment and adaptation, \r AR6 emphasizes assessment of regional information more than \r earlier reports. Here the phrase 'regional climate information' refers \r to predefined reference sets of land and ocean regions; various \r typological domains (such as mountains or monsoons); temporal \r frames including baseline periods as well as near term (2021-2040), \r medium term (2041-2060) and long term (2081-2100); and global \r warming levels (Chapters 10 and 12, Sections 1.4.1 and 1.4.5, and \r Atlas). Regional climate change information is constructed from \r multiple lines of evidence including observations, paleoclimate \r proxies, reanalyses, attribution of changes and climate model \r projections from both global and regional climate models \r (Sections 1.5.3 and 10.2-10.4). The constructed regional information \r needs to take account of user context and values for risk assessment, \r [...]"


id: 38dd12ea8561825fcb7d2fb66c9ed02e
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"Social values are implicit in many choices made during the \r construction, assessment and communication of climate science \r information (Heymann et al., 2017; Skelton et al., 2017). Some \r climate science questions are prioritized for investigation, or given \r a specific framing or context, because of their relevance to climate \r policy and governance. One example is the question of how the \r effects of a 1.5degC global warming would differ from those of a 2degC \r warming, an assessment specifically requested by Parties to the PA. \r The SR1.5 (2018) explicitly addressed this issue 'within the context of \r sustainable development; considerations of ethics, equity and human \r rights; and the problem of poverty' (Chapters 1 and 5; see also Hoegh\u0002Guldberg et al., 2019) following the outcome of the approval of the \r outline of the Special Report by the IPCC during its 44th Session \r (Bangkok, Thailand, 17-20 October 2016). Likewise, particular metrics \r [...]"


id: 4c836417f1ae514c6f96bc92d9c7bfd4
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"[...] are sometimes prioritized in climate model improvement efforts \r because of their practical relevance for specific economic sectors or \r stakeholders. Examples include reliable simulation of precipitation in \r a specific region, or attribution of particular extreme weather events \r to inform rebuilding and future policy (Chapters 8 and 11; Intemann, \r 2015; Otto et al., 2018; James et al., 2019). Sectors or groups whose \r interests do not influence research and modelling priorities may thus \r receive less information in support of their climate-related decisions \r (Parker and Winsberg, 2018)."


id: fe59f32aa2e48201766495ee8181fb05
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"As detailed in Chapter 10, scientific climate information often requires \r 'tailoring' to meet the requirements of specific decision-making \r contexts. In a study of the UK Climate Projections 2009 (UKCP09) \r project, researchers concluded that climate scientists struggled to \r grasp and respond to users' information needs because they lacked \r experience interacting with users, institutions and scientific idioms \r outside the climate science domain (Porter and Dessai, 2017). \r Economic theory predicts the value of 'polycentric' approaches \r to climate change informed by specific global, regional and local \r knowledge and experience (Ostrom, 1996, 2012). This is confirmed \r by numerous case studies of extended, iterative dialogue among \r scientists, policymakers, resource managers and other stakeholders \r to produce mutually understandable, usable, task-related information \r and knowledge, policymaking and resource management around the \r [...]"


id: 77f8a82cab429b0a5068d7bce7c22d6b
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"[...] world (Lemos and Morehouse, 2005; Lemos et al., 2012, 2014, 2018; \r see Vaughan and Dessai, 2014 for a critical view). The SR1.5 (2018) \r assessed that 'education, information, and community approaches, \r including those that are informed by indigenous knowledge and \r local knowledge, can accelerate the wide-scale behaviour changes \r consistent with adapting to and limiting global warming to 1.5degC. \r These approaches are more effective when combined with other \r policies and tailored to the motivations, capabilities and resources \r of specific actors and contexts (high confidence).' These extended \r dialogic co-production and education processes have thus been \r demonstrated to improve the quality of both scientific information \r and governance (high confidence) (Section  10.5 and Cross \r Chapter Box 12.2)."


id: 317f114c52c3e1a0457adbe890bb661e
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"Recent work also recognizes that choices made throughout the \r research process can affect the relative likelihood of false alarms \r (overestimating the probability and/or magnitude of hazards) or \r missed warnings (underestimating the probability and/or magnitude \r of hazards), known respectively as Type I and Type II errors. Researchers \r may choose different methods depending on which type of error they \r view as most important to avoid, a  choice that may reflect social \r values (Douglas, 2009; Knutti, 2018; Lloyd and Oreskes, 2018). This \r reflects a fundamental trade-off between the values of reliability and \r informativeness. When uncertainty is large, researchers may choose to \r report a wide range as very likely, even though it is less informative \r about potential consequences. By contrast, high-likelihood statements \r about a  narrower range may be more informative, yet also prove \r less reliable if new evidence later emerges that widens the range. \r [...]"


id: c1b7d2949199dcc83b732a92d370d4a7
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"[...] Furthermore, the difference between narrower and wider uncertainty \r intervals has been shown to be confusing to lay readers, who often \r interpret wider intervals as less certain (Lohre et al., 2019)."


id: d2eb5b4e9ec2b628a3e4b4bd956999f1
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"Since AR5, social media platforms have dramatically altered the mass\u0002media landscape, bringing about a shift from uni-directional transfer \r of information and ideas to more fluid, multi-directional flows \r (Pearce et al., 2019). A survey covering 18 Latin American countries \r (StatKnows-CR2, 2019) found that the main sources of information \r about climate change mentioned were the Internet (52% of mentions), \r followed by social media (18%). There are well-known challenges \r with social media, such as misleading or false presentations of \r scientific findings, incivility that diminishes the quality of discussion \r around climate change topics, and 'filter bubbles' that restrict \r interactions to those with broadly similar views (Anderson and \r Huntington, 2017). However, at certain moments (such as at the \r release of the AR5 WGI report), Twitter studies have found that more \r mixed, highly-connected groups existed, within which members \r [...]"


id: 20e3c18c91b115fc81e03af2cce754a1
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"[...] were less polarized (Pearce et al., 2014; Williams et al., 2015). Thus, \r social media platforms may in some circumstances support dialogic \r or co-production approaches to climate communication. Because the \r contents of IPCC reports speak not only to policymakers, but also to \r the broader public, the character and effects of media coverage are \r important considerations across Working Groups."


id: dd1461669b91f9912c2ee469d49010b8
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content:
"Climate services focus on users with specific needs for climate \r information, but most people learn about climate science findings \r from media coverage. Since AR5, research has expanded on how \r mass media report climate change and how their audiences respond \r (Dewulf, 2013; Jaspal and Nerlich, 2014; Jaspal et al., 2014). \r For  example, in five European Union (EU) countries, television \r coverage of AR5 used 'disaster' and 'opportunity' as its principal \r themes, but virtually ignored the 'risk' framing introduced by \r AR5 WGII (Painter, 2015) and now extended by the AR6 (Cross\u0002Chapter Box 1.3). Other studies show that people react differently \r to climate change news when it is framed as a  catastrophe (Hine \r et al., 2016), as associated with local identities (Sapiains et al., \r 2016), or as a social justice issue (Howell, 2013). Similarly, audience \r segmentation studies show that responses to climate change vary \r [...]"


id: 5dfb85e9ba8458d2275b1b82828b3c0f
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"[...] between groups of people with different, although not necessarily \r opposing, views on this phenomenon (e.g.,  Maibach et al., 2011; \r Sherley et al., 2014; Detenber et al., 2016). In Brazil, two studies \r have shown the influence of mass media on the high level of public \r climate change concern in that country (Rodas and Di Giulio, 2017; \r Dayrell, 2019). In the USA, analyses of television network news show \r that climate change receives minimal attention, is most often framed \r in a political context, and largely fails to link extreme weather events \r to climate change using appropriate probability framing (Hassol \r et al., 2016). However, recent evidence suggests that Climate Matters \r (an Internet resource to help US television weather forecasters link \r weather to climate change trends) may have had a positive effect \r on public understanding of climate change (Myers et al., 2020). \r Also, some media outlets have recently adopted and promoted \r [...]"


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"[...] terms and phrases stronger than the more neutral 'climate change' \r and 'global warming', including 'climate crisis', 'global heating', \r and 'climate emergency' (Zeldin-O'Neill, 2019). Google searches on \r those terms, and on 'climate action', increased 20-fold in 2019, when "


id: 72b2fb025fc2c1745449ed5ef97b32a3
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content:
"Data at altitude came initially from scattered mountain summits, \r balloons and kites, but the upper troposphere and stratosphere \r were not systematically observed until radiosonde (weather balloon) \r networks emerged in the 1940s and 1950s. These provide the \r longest continuous quasi-global record of the atmosphere's vertical \r dimension (Stickler et al., 2010). New methods for spatial and temporal \r homogenisation (intercalibration and quality control) of radiosonde \r records were introduced in the 2000s (Sherwood et al., 2008, 2015; \r Haimberger et al., 2012). Since 1978, Microwave Sounding Units \r (MSU) mounted on Earth-orbiting satellites have provided a second \r high-altitude data source, measuring temperature, humidity, ozone, \r and liquid water throughout the atmosphere. Over time, these satellite \r data have required numerous adjustments to account for such factors \r as orbital precession and decay (Edwards, 2010). Despite repeated \r [...]"


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"[...] adjustments, however, marked differences remain in the temperature \r trends from surface, radiosonde, and satellite observations; between \r the results from three research groups that analyse satellite data \r (University of Alabama in Huntsville (UAH), Remote Sensing Systems \r (RSS), and NOAA); and between modelled and satellite-derived \r tropospheric warming trends (Thorne et al., 2011; Santer et al., 2017). \r These differences are the subject of ongoing research (Maycock \r et al., 2018). In the 2000s, Atmospheric Infrared Sounder (AIRS) and \r radio occultation (GNSS-RO) measurements provided new ways to \r measure temperature at altitude, complementing data from the MSU. \r GNSS-RO is a new independent, absolutely calibrated source, using \r the refraction of radio-frequency signals from the Global Navigation \r Satellite System (GNSS) to measure temperature, pressure and water \r vapour (Section 2.3.1.2.1; Foelsche et al., 2008; Anthes, 2011)."


id: 63c20f8b330b0f9173d3e3b50fd0bfa9
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"National and colonial weather services built networks of surface \r stations in the 19th  century. By the mid-19th  century, semi\u0002standardized naval weather logs recorded winds, currents, \r precipitation, air pressure, and temperature at sea, initiating the \r longest continuous quasi-global instrumental record (Maury, 1849, \r 1855, 1860). Because the ocean covers over 70% of global surface \r area and constantly exchanges energy with the atmosphere, both air \r and sea surface temperatures (SST) recorded in these naval logs are \r crucial variables in climate studies. Dove (1853) mapped seasonal \r isotherms over most of the globe. By 1900, a patchy weather data\u0002sharing system reached all continents except Antarctica. Regular \r compilation of climatological data for the world began in 1905 with \r the Reseau Mondial (Air Ministry - Meteorological Office, 1921), and \r similar compilations  - the World Weather Records (Clayton, 1927) \r [...]"


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"[...] and Monthly Climatic Data for the World (est. 1948)  - have been \r published continuously since their founding."


id: a5e8370e4d755d7b1b686ffc40551192
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"Land and ocean surface temperature data have been repeatedly \r evaluated, refined and extended (Section 1.5.1). As computer power \r increased and older data were recovered from handwritten records, \r the number of surface station records used in published global land \r temperature time series grew. A  pioneering study for 1880-1935 \r used fewer than 150 stations (Callendar, 1938). A benchmark study \r of 1880-2005 incorporated 4300 stations (Brohan et al., 2006). \r A  study of the 1753-2011 period included previously unused \r station data, for a  total of 36,000 stations (Rohde et al., 2013); \r recent versions of this dataset comprise over 40,000 land stations \r (Rohde and Hausfather, 2020). Several centres, including the National \r Oceanic and Atmospheric Administration (NOAA), Hadley, and Japan \r Meteorological Agency (JMA), produce SST datasets independently \r calculated from instrumental records. In the 2000s, adjustments \r [...]"


id: e52f118404db39fcace57a9f8f4e629d
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"[...] for bias due to different measurement methods (buckets, engine \r intake thermometers, moored and drifting buoys) resulted in major \r improvements of SST data (Thompson et al., 2008), and these \r improvements continue (Huang et al., 2017; Kennedy et al., 2019). \r SST  and land-based data are incorporated into global surface \r temperature datasets calculated independently by multiple research \r groups, including NOAA, NASA, Berkeley Earth, Hadley-CRU, JMA, and \r China Meteorological Administration (CMA). Each group aggregates \r the raw measurement data, applies various adjustments for non\u0002climatic biases such as urban heat-island effects, and addresses \r unevenness in geospatial and temporal sampling with various \r techniques (see Section 2.3.1.1.3 and Table 2.4 for references). Other \r research groups provide alternative interpolations of these datasets \r using different methods (e.g., Cowtan and Way, 2014; Kadow et al., \r [...]"


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"[...] 2020). Using the then available global surface temperature datasets, \r AR5 WGI assessed that the GMST increased by 0.85degC from 1880 \r to 2012 and found that each of the three decades following 1980 \r was successively warmer at the Earth's surface than any preceding \r decade since 1850 (IPCC, 2013b). Marine air temperatures, especially \r those measured during nighttime, are increasingly also used to \r examine variability and long-term trends (e.g., Rayner et al., 2006; \r Kent et al., 2013; Cornes et al., 2020; Junod and Christy, 2020). \r Cross-Chapter Box 2.3 discusses updates to the global temperature \r datasets, provides revised estimates for the observed changes and \r considers whether marine air temperatures are changing at the \r same rate as SSTs."


id: af161252e129b3c136a46622f4455c6b
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"reaching full equilibrium with the atmosphere only after hundreds \r to thousands of years (Yang and Zhu, 2011). The earliest subsurface \r measurements in the open ocean date to the 1770s (Abraham et al., \r 2013). From 1872-76, the research ship HMS Challenger measured \r global ocean temperature profiles at depths up to 1700 m along its \r cruise track. By 1900, research ships were deploying instruments \r such as Nansen bottles and mechanical bathythermographs \r (MBTs) to develop profiles of the upper 150 m in areas of interest \r to navies and commercial shipping (Abraham et al., 2013). Starting \r in 1967, eXpendable BathyThermographs (XBTs) were deployed by \r scientific and commercial ships along repeated transects to measure \r temperature to 700 m  (Goni et al., 2019). Ocean data collection \r expanded in the 1980s with the Tropical Ocean Global Experiment \r (TOGA; Gould, 2003). Marine surface observations for the globe, \r assembled in the mid-1980s in the International Comprehensive \r [...]"


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"[...] Ocean-Atmosphere Data Set (ICOADS; Woodruff et al., 1987, 2005), \r were extended to 1662-2014 using newly recovered marine records \r and metadata (Woodruff et al., 1998; Freeman et al., 2017). The Argo \r submersible float network, developed in the early 2000s, provided "


id: c446820ad4cb16e2210265509a3b71e2
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"With the gradual acceptance of evidence for geological 'deep time' in \r the 19th century came investigation of fossils, geological strata, and \r other evidence pointing to large shifts in the Earth's climate, from ice \r ages to much warmer periods, across thousands to billions of years. \r This awareness set off a search for the causes of climatic changes. \r The long-term perspective provided by paleoclimate studies is essential \r to understanding the causes and consequences of natural variations \r in climate, as well as crucial context for recent anthropogenic climatic \r change. The reconstruction of climate variability and change over \r recent millennia began in the 1800s (Bruckner, 1890; Stehr and von \r Storch, 2000; Coen, 2018, 2020). In brief, paleoclimatology reveals \r the key role of CO2 and other greenhouse gases in past climatic \r variability and change, the magnitude of recent climate change in \r comparison to past glacial-interglacial cycles, and the unusualness \r [...]"


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"[...] of recent climate change (Section 1.2.1.2 and Cross-Chapter Box 2.1; \r Tierney et al., 2020a). FAQ 1.3 provides a plain-language summary of \r its importance."


id: 6fe5c096dbb7e9524d05803f6ce5ff98
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"Water expands as it warms. This thermal expansion, along with glacier \r mass loss, were the dominant contributors to GMSL rise during the \r 20th century (high confidence) according to AR5 (IPCC, 2013b). Sea \r level can be measured by averaging across tide gauges, some of which \r date to the 18th century. However, translating tide gauge readings \r into GMSL is challenging, since their spatial distribution is limited to \r continental coasts and islands, and their readings are relative to local \r coastal conditions that may shift vertically over time. Satellite radar \r altimetry, introduced operationally in the 1990s, complements the \r tide gauge record with geocentric measurements of GMSL at much \r greater spatial coverage (Katsaros and Brown, 1991; Fu et al., 1994). \r The AR5 WGI assessed that GMSL rose by 0.19 [0.17 to 0.21] m over \r the period 1901-2010, and that the rate of sea level rise increased \r from 2.0 [1.7 to 2.3] mm yr-1 in 1971-2010 to 3.2 [2.8 to 3.6] mm yr-1\r [...]"


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"[...] from 1993-2010. Warming of the ocean very likely contributed 0.8 \r [0.5 to 1.1] mm yr-1 of sea level change during 1971-2010, with the \r majority of that contribution coming from the upper 700 m (IPCC, \r 2013b). Chapter 2 (Section 2.3.3.3) assesses current understanding \r of the extent and rate of sea level rise, past and present."


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"Satellite remote sensing also revolutionized studies of the cryosphere \r (Sections  2.3.2 and 9.3-9.5), particularly near the poles, where \r conditions make surface observations very difficult. Satellite mapping \r and measurement of snow cover began in 1966, with land and \r sea ice observations following in the mid-1970s. Yet prior to the \r Third Assessment Report, researchers lacked sufficient data to tell \r whether the Greenland and Antarctic ice sheets were shrinking or \r growing. Through a combination of satellite and airborne altimetry \r and gravity measurements, and improved knowledge of surface \r mass balance and perimeter fluxes, a  consistent signal of ice loss \r for both ice sheets was established by the time of AR5 (Shepherd \r et al., 2012). After 2000, satellite radar interferometry revealed rapid \r changes in surface velocity at ice-sheet margins, often linked to \r reduction or loss of ice shelves (Scambos et al., 2004; Rignot and \r [...]"


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"[...] Kanagaratnam, 2006). Whereas sea ice area and concentration have \r been continuously monitored since 1979 via microwave imagery, \r datasets for ice thickness emerged later from upward sonar profiling \r by submarines (Rothrock et al., 1999) and radar altimetry of sea ice \r freeboards (Laxon et al., 2003). A  recent reconstruction of Arctic \r sea ice extent back to 1850 found no historical precedent for the \r Arctic sea ice minima of the 21st century (Walsh et al., 2017). Glacier \r length has been monitored for decades to centuries; internationally \r coordinated activities now compile worldwide glacier length and \r mass balance observations (World Glacier Monitoring Service, Zemp \r et al., 2015), global glacier outlines (Randolph Glacier Inventory, \r Pfeffer et al., 2014), and ice thickness data for about 1100 glaciers "


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"On longer time scales, tiny air bubbles trapped in polar ice sheets \r provide direct evidence of past atmospheric composition, including \r CO2 levels (Petit et al., 1999), and the 18O isotope in frozen precipitation \r serves as a  proxy marker for temperature (Dansgaard, 1954). \r Sulphate deposits in glacier ice and as ash layers within sediment \r record major volcanic eruptions, providing another mechanism for \r dating. The first paleoclimate reconstructions used an almost 100-kyr \r ice core taken at Camp Century, Greenland (Dansgaard et al., 1969; \r Langway Jr, 2008). Subsequent cores from Antarctica extended this \r climatic record to 800 kyr (EPICA Community Members, 2004; Jouzel, \r 2013). Comparisons of air contained in these ice samples against \r measurements from the recent past enabled AR5 WGI to assess that \r atmospheric concentrations of CO2, methane (CH4), and nitrous oxide \r (N2O) had all increased to levels unprecedented in at least the last \r [...]"


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"The natural and anthropogenic factors responsible for climate \r change are known today as radiative 'drivers' or 'forcers'. The net \r change in the energy budget at the top of the atmosphere, resulting \r from a  change in one or more such drivers, is termed 'radiative \r forcing' (RF; Glossary) and measured in watts per square metre (W \r m-2). The total radiative forcing over a given time interval (often since \r 1750) represents the sum of positive drivers (inducing warming) and \r negative ones (inducing cooling). Past IPCC reports have assessed \r scientific knowledge of these drivers, quantified their range for the \r period since 1750, and presented the current understanding of how \r they interact in the climate system. Like all previous IPCC reports, AR5 \r assessed that total radiative forcing has been positive at least since \r 1850-1900, leading to an uptake of energy by the climate system, \r and that the largest single contribution to total radiative forcing is \r [...]"


id: 304ef302e962eedcfeeb14608da7b582
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content:
"[...] the rising atmospheric concentration of CO2 since 1750 (Chapter 7, \r and Cross-Chapter Box 1.2; IPCC, 2013a)."


id: 2abcff9cfeceebd9cb5066802cef84ab
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content:
"others indirect (e.g., cloud droplet nucleation); specific effects may \r cause either positive or negative radiative forcing. Major volcanic \r eruptions inject SO2 (a negative driver) into the stratosphere, creating \r aerosols that can cool the planet for years at a time by reflecting some \r incoming solar radiation. The history and climatic effects of volcanic \r activity have been traced through historical records, geological \r traces, and observations of major eruptions by aircraft, satellites and \r other instruments (Dorries, 2006). The negative RF of major volcanic \r eruptions was considered in the First Assessment Report (FAR; IPCC, \r 1990a). In subsequent assessments, the negative RF of smaller \r eruptions has also been considered (e.g., Cross-Chapter Box 4.1 in \r Chapter 4 of this Report; Section 2.4.3 in IPCC, 1996). Dust and other \r natural aerosols have been studied since the 1880s (e.g.,  Aitken, \r 1889; Angstrom, 1929, 1964; Twomey, 1959), particularly in relation \r [...]"


id: e1fa8e3d8133b0a560926ed8a962cbb8
created_at: 2023-04-19 13:22:33
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content:
"[...] to their role in cloud nucleation, an aerosol indirect effect whose \r RF may be either positive or negative depending on such factors \r as cloud altitude, depth and albedo (Stevens and Feingold, 2009; \r Boucher et al., 2013)."


id: d2f343fdeae5b5ec6d87af5fc8e860a
created_at: 2023-04-19 13:22:33
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content:
"Radioactive fallout from atmospheric nuclear weapons testing \r (1940s-1950s) and urban smog (1950s-1960s) first provoked \r widespread attention to anthropogenic aerosols and ozone in the \r troposphere (Edwards, 2012). Theory, measurement and modelling \r of these substances developed steadily from the 1950s (Hidy, 2019). \r However, the radiative effects of anthropogenic aerosols did not \r receive sustained study until around 1970 (Bryson and Wendland, \r 1970; Rasool and Schneider, 1971), when their potential as cooling \r agents was recognized (Peterson et al., 2008). The US Climatic \r Impact Assessment Program (CIAP) found that proposed fleets of \r supersonic aircraft, flying in the stratosphere, might cause substantial \r aerosol cooling and depletion of the ozone layer, stimulating efforts \r to understand and model stratospheric circulation, atmospheric \r chemistry, and aerosol radiative effects (Mormino et al., 1975; Toon \r [...]"


id: 6cdeebeb40a5a522d8cf396adaf886a0
created_at: 2023-04-19 13:22:33
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content:
"[...] and Pollack, 1976). Since the 1980s, aerosols have increasingly been \r integrated into comprehensive modelling studies of transient climate \r evolution and anthropogenic influences, through treatment of volcanic \r forcing, links to global dimming and cloud brightening, and their \r influence on cloud nucleation and other properties (e.g., thickness, \r lifetime and extent), and precipitation (e.g.,  Hansen et al., 1981; \r Charlson et al., 1987, 1992; Albrecht, 1989; Twomey, 1991)."


id: 5b9223059755577e9ad8c7773924c48c
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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content:
"Anthropogenic drivers of climatic change were hypothesized as early as \r the 17th century, with a primary focus on forest clearing and agriculture \r (Grove, 1995; Fleming, 1998). In the 1890s, Arrhenius was first to \r calculate the effects of increased or decreased CO2 concentrations on \r planetary temperature, and Hogbom estimated that worldwide coal \r combustion of about 500 Mt yr-1 had already completely offset the \r natural absorption of CO2 silicate rock weathering (Hogbom, 1894; \r Arrhenius, 1896; Berner, 1995; Crawford, 1997). As coal consumption \r reached 900 Mt yr-1 only a  decade later, Arrhenius wrote that \r anthropogenic CO2 from fossil fuel combustion might eventually \r warm the planet (Arrhenius, 1908). In 1938, analysing records from \r 147  stations around the globe, Callendar calculated atmospheric \r warming over land at 0.3degC-0.4degC from 1880-1935 and attributed \r about half of this warming to anthropogenic CO2 (Figure 1.8; Callendar, \r [...]"


id: ab68b468d59e36422dc032b01a733107
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
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content:
"The FAR (1990) focused attention on human emissions of CO2, CH4, \r tropospheric O3, chlorofluorocarbons (CFCs), and N2O. Of these, at \r that time only the emissions of CO2 and CFCs were well measured, \r with methane sources known only 'semi-quantitatively' (IPCC, \r 1990a). The FAR assessed that some other trace gases, especially \r CFCs, have global warming potentials hundreds to thousands of \r times greater than CO2 and CH4, but are emitted in much smaller \r amounts. As a  result, CO2 remains by far the most important \r positive anthropogenic driver, with CH4 next most significant \r (Section 1.6.3); anthropogenic methane stems from such sources as \r fossil fuel extraction, natural gas pipeline leakage, agriculture and \r landfills. In 2001, increased greenhouse forcing attributable to CO2, \r CH4, O3, CFC-11 and CFC-12 was detected by comparing satellite \r measurements of outgoing longwave radiation measurements taken \r [...]"


id: ba893a667efd05fde7d2dcb2deea0a59
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index: climate_gpt_v2
vector_id: 30031
content:
"[...] in 1970 and in 1997 (Harries et al., 2001). AR5 assessed that the 40% \r increase in atmospheric CO2 contributed most to positive RF since \r 1750. Together, changes in atmospheric concentrations of CO2, CH4, \r N2O and halocarbons from 1750-2011 were assessed to contribute \r a positive RF of 2.83 [2.26 to 3.40] W m-2 (IPCC, 2013b)."


id: 35363fb69aa40dd854fd79c80dee46a0
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
content_type: text
index: climate_gpt_v2
vector_id: 6610
content:
"Studies of radiocarbon (14C) in the 1950s established that increasing \r atmospheric CO2 concentrations were due to fossil fuel combustion. \r Since all the 14C once contained in fossil fuels long ago decayed \r into non-radioactive 12C, the CO2 produced by their combustion \r reduces the overall concentration of atmospheric 14C (Suess, 1955). \r Related work demonstrated that while the ocean was absorbing \r around 30% of anthropogenic CO2, these emissions were also \r accumulating in the atmosphere and biosphere (Section 1.3.1 and \r Chapter  5, Section  5.2.1.5). Further work later established that \r atmospheric oxygen levels were decreasing in inverse relation to the \r anthropogenic CO2 increase, because combustion of carbon consumes \r oxygen to produce CO2 (Chapters 2 and 6; Keeling and Shertz, 1992; \r IPCC, 2013a). Revelle and Suess (1957) famously described fossil fuel \r emissions as a 'large scale geophysical experiment', in which 'within \r [...]"


id: 8722bc3eda0f9e30841818108ecb4e63
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 20938
content:
"[...] a  few centuries we are returning to the atmosphere and ocean \r the concentrated organic carbon stored in sedimentary rocks over \r hundreds of millions of years.' The 1960s saw increasing attention \r to other radiatively active gases, especially ozone (O3; Manabe and \r Moller, 1961; Plass, 1961). Methane and nitrous oxide (N2O) were \r not considered systematically until the 1970s, when anthropogenic \r increases in those gases were first noted (Wang et al., 1976). In the \r 1970s and 1980s, scientists established that synthetic halocarbons "


id: a5692220283c7c08cc7d4412d786c757
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 26334
content:
"Since controlled experiments at planetary scale are impossible, \r climate simulations provide one important way to explore the \r differential effects and interactions of variables such as solar \r irradiance, aerosols and GHGs. To assess their quality, models or \r components of models may be compared with observations. For this \r reason, they can be used to attribute observed climatic effects to \r different natural and human drivers (Hegerl et al., 2011). As early \r as Arrhenius (1896), simple mathematical models were used to \r calculate the effects of doubling atmospheric carbon dioxide over pre\u0002industrial concentrations (approximately 550 ppm vs approximately \r 275 ppm respectively). In the early 20th century Bjerknes formulated \r the Navier-Stokes equations of fluid dynamics for motion of the \r atmosphere (Bjerknes, 1906; Bjerknes et al., 1910), and Richardson \r (1922) developed a system for numerical weather prediction based \r [...]"


id: 1330000dd9c0d7ec2159699d871b0cd6
created_at: 2023-04-19 13:22:33
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vector_id: 587
content:
"[...] on these equations. When electronic computers became available \r in the late 1940s, the methods of Bjerknes and Richardson were \r successfully applied to weather forecasting (Charney et al., 1950; \r Nebeker, 1995; Harper, 2008)."


id: 14f63fc7fdf30ecde1236196863239ab
created_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 907
content:
"In the 1990s, AOGCMs were state of the art. By the 2010s, Earth \r system models (ESMs, also known as coupled carbon-cycle climate \r models) incorporated land surface, vegetation, the carbon cycle, \r and other elements of the climate system. Since the 1990s, some \r major modelling centres have deployed 'unified' models for \r both weather prediction and climate modelling, with the goal \r of a  seamless modelling approach that uses the same dynamics, \r physics and parameterisations at multiple scales of time and space \r (Section  10.1.2; Cullen, 1993; Brown et al., 2012; NRC, 2012; \r WMO, 2015). Because weather forecast models make short-term \r predictions that can be frequently verified, and improved models are \r introduced and tested iteratively on cycles as short as 18 months, this \r approach allows major portions of the climate model to be evaluated \r as a  weather model and more frequently improved. However, all \r climate models exhibit biases of different degrees and types, and \r [...]"


id: 2e36b27e1713d9fc83f07b08b8215337
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 5403
content:
"[...] the practice of 'tuning' parameter values in models to make their \r outputs match variables such as historical warming trajectories has \r generated concern throughout their history (Section 1.5.3.2; Randall \r and Wielicki, 1997; Edwards, 2010; Hourdin et al., 2017). Overall, \r AR5 WGI assessed that climate models had improved since previous \r reports (IPCC, 2013b)."


id: c3cc6a658f57bc659cdb2c62ca58daa
created_at: 2023-04-19 13:22:33
updated_at: 2023-04-19 13:22:33
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index: climate_gpt_v2
vector_id: 31721
content:
"modelling community developed increasingly sophisticated model \r intercomparison projects (MIPs; Gates et al., 1999; Covey et al., \r 2003). MIPs prescribe standardized experiment designs, time periods, \r output variables or observational reference data to facilitate direct \r comparison of model results. This aids in diagnosing the reasons for \r biases and other differences among models, and furthers process \r understanding (Section  1.5). Both the CMIP3 and CMIP5 model \r intercomparison projects included experiments testing the ability \r of models to reproduce 20th-century global surface temperature \r trends both with and without anthropogenic forcings. Although some \r individual model runs failed to achieve this (Hourdin et al., 2017), the \r mean trends of multi-model ensembles did so successfully (Meehl \r et al., 2007a; Taylor et al., 2012). When only natural forcings were \r included (creating the equivalent of a 'control Earth' without human \r [...]"


id: c85e47d89a4c0e5e23cd2d8cf0c4a118
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index: climate_gpt_v2
vector_id: 32557
content:
"[...] influence), similar multi-model ensembles could not reproduce the \r observed post-1970 warming at either global or regional scales \r (Edwards, 2010; Jones et al., 2013). The GCMs and ESMs compared \r in CMIP6 (used in this Report) offer more explicit documentation and \r evaluation of tuning procedures (Section 1.5; Schmidt et al., 2017; \r Burrows et al., 2018; Mauritsen and Roeckner, 2020)."


