# document

id: b2debcda9875c8158ae302026dfe36a9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28706
content:
"Storm tracks and mid-latitude westerly jets are dynamically related \r\naspects of mid-latitude circulation. The AR5 assessed that a poleward \r\nshift of the SH westerlies and storm track is likely by the end of the \r\n21st  century under RCP8.5 (medium confidence). In contrast, low \r\nconfidence was assessed for the storm-track response in the NH."


id: 43db5d3733e64b8b1a68071d4e125ffc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9169
content:
"zonal winds by the end of the century are generally smaller than in the \r\nSH. In boreal winter, there is a weak poleward shift of the NH zonal\u0002mean westerly jet maximum in SSP3-7.0."


id: f1a78ebebbd1d70f0e2c5663beff8747
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39899
content:
"boreal summer, while the North Pacific jet weakens in this season \r\n(Simpson et al., 2014; Davini and D'Andrea, 2020; Harvey et al., 2020). \r\nThere is a poleward shift in the westerlies in both the North Pacific and \r\nNorth Atlantic in Autumn (Barnes and Polvani, 2013; Simpson et al., \r\n2014). However, the shift of the westerlies is more uncertain in the \r\nother seasons, particularly in the North Atlantic in winter (Simpson \r\net al., 2014; Zappa and Shepherd, 2017). Here, the circulation response \r\nis not well described as a simple shift, since the North Atlantic jet tends \r\nto be squeezed on both its equatorward and poleward flanks, together "


id: 284983fc4ef62bd0c0298e87888baa2a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4287
content:
"CMIP5 and CMIP6 models show a  strong seasonal and regional \r\ndependence in the response to climate change of NH westerlies (Barnes \r\nand Polvani, 2013; Grise and Polvani, 2014b; Simpson et al., 2014; Zappa \r\net al., 2015; Harvey et al., 2020; Oudar et al., 2020). CMIP5 projections \r\nindicate a  poleward shift of the westerlies in the North Atlantic in "


id: c8d0ddff09bdc1e71659a7a620f3e472
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32656
content:
"Figure 4.26 | Long-term change of zonal-mean, zonal wind. Displayed are multi-model mean changes in (left) boreal winter (December-January-February, DJF) and \r\n(right) austral winter (June-July-August, JJA) zonal mean, zonal wind (m s-1) in 2081-2100 for (top) SSP1-2.6 and (bottom) SSP3-7.0 relative to 1995-2014. The 1995-2014 \r\nclimatology is shown in contours with spacing 10 m s-1. Diagonal lines indicate regions where less than 80% of the models agree on the sign of the change and no overlay \r\nwhere at least 80% of the models agree on the sign of the change. Further details on data sources and processing are available in the chapter data table (Table 4.SM.1)."


id: 8d0681e864cb31e7aaaf1b9adad84d60
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21999
content:
"The storyline approach is grounded in the identification of a set of \r\nphysical predictors of atmospheric circulation change, such as those \r\ndescribed above (Harvey et al., 2014; Manzini et al., 2014; Shepherd \r\net al., 2018), which act together to determine a specific outcome in \r\nthe projected atmospheric circulation change. The consequences \r\nof multi-model spread in the physical predictors of atmospheric \r\ncirculation change can be investigated, conditioned on a  specified \r\nlevel of global warming (see also Section 1.4.4.2 and Box 10.2; Zappa \r\nand Shepherd, 2017; Zappa, 2019; Mindlin et al., 2020)."


id: 96728d817d1e3e849bd240d504d67d7d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 23672
content:
"As stated in AR5, the number of extratropical cyclones (ETC) \r\ncomposing the storm tracks is projected to weakly decline in future \r\nprojections, but by no more than a few percent change. The reduction \r\nis mostly located on the equatorward flank of the storm tracks, which \r\nis associated with the Hadley cell expansion and a poleward shift in \r\nthe mean genesis latitude of ETCs (Tamarin-Brodsky and Kaspi, 2017). \r\nFurthermore, the poleward propagation of individual ETCs is expected \r\nto increase with warming (Graff and LaCasce, 2014; Tamarin-Brodsky \r\nand Kaspi, 2017), thus contributing to a  poleward shift in the \r\nmid-latitude transient-eddy kinetic energy. The increased poleward \r\npropagation results from the strengthening of the upper tropospheric \r\njet and increased cyclone-associated precipitation (Tamarin-Brodsky \r\nand Kaspi, 2017), which are robust aspects of climate change."


id: 6c6b4e269bf191637ec4860ba8f62b58
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 16367
content:
"In the NH boreal winter, CMIP6 models show a  northward shift \r\nof the ETC density in the North Pacific, a  tripolar pattern in the \r\nNorth Atlantic, and a  weakening of the Mediterranean storm \r\ntrack (Figure  4.27a). CMIP6 models show overall low agreement\r\non changes in ETC density in the North Atlantic in boreal winter \r\n(Figure 4.27a). A poleward shift of the storm track is evident in the \r\nSH (Figure 4.27b), particularly in the Indian and Pacific Ocean sectors. \r\nCMIP6 models still feature long-standing biases in the representation \r\nof storm tracks; for example, the winter storm track into Europe is \r\ntoo zonal, though different measures of storm track activity indicate \r\nsome improvements compared to the previous generations of models \r\n(Harvey et al., 2020; Priestley et al., 2020)."


id: feaf704ba399d4f2d3dc4b4cb91845fc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 42193
content:
"weather conditions, from heat waves in summer to cold spells in \r\nwinter (see Section 11.7.2 for a detailed discussion of these features \r\nand Section 3.3.3.3 for the assessment of blocking biases in models \r\nsimulations). The AR5 assessed with medium confidence that the \r\nfrequency of blocking would not increase under enhanced GHG \r\nconcentrations, while changes in blocking intensity and persistence \r\nremained uncertain."


id: 3b5b9d7f3fe0f9973ad35124d00a04fd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7631
content:
"heating to cyclone intensification (Li et al., 2014; Pfahl et al., 2015; \r\nWillison et al., 2015; Michaelis et al., 2017). In conclusion, there is \r\nonly medium confidence in the projected decrease in the frequency \r\nof intense NH ETCs."


id: 2bfbf7d34127f826691da9aa78fced0b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4990
content:
"In contrast to the Northern Hemisphere, the Southern Hemisphere \r\nshows an increase in the frequency of intense ETCs in CMIP5 models \r\n(Chang, 2017), and there is high confidence that wind speeds \r\nassociated with ETCs are expected to intensify in the SH storm \r\ntrack for high emissions scenarios. These changes in intensity are \r\naccompanied by an overall southward shift of the SH winter storm \r\ntrack (Figure 4.27b) due to the poleward shift in the upper-level jet \r\nand the increase in the meridional SST gradient linked to the slower \r\nwarming of the Southern Ocean (Grieger et al., 2014)."


id: 32f274c950ef492c34e345389e22911f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6228
content:
"Regardless of dynamical intensity changes, there is high confidence \r\nthat the number of ETCs associated with extreme precipitation \r\nis projected to increase with warming, due to the increased \r\nmoisture-loading capacity of the atmosphere (Section 8.4.2; Yettella \r\nand Kay, 2017; Hawcroft et al., 2018). "


id: d99edfd4d6bb22acd769dfdefacb29d9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35586
content:
"Blocking is associated with a class of quasi-stationary, high-pressure \r\nweather systems in the middle and high latitudes that disrupt the \r\nprevailing westerly flow. These events can persist for extended \r\nperiods, such as a week or longer, and can cause long-lived extreme "


id: abccf4c76f4d9d7e65298a5575260281
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27469
content:
"To better understand the uncertainty in future blocking activity, \r\na process-oriented approach has been proposed that aims to link \r\nblocking responses to different features of the global warming \r\npattern. Upper-level tropical warming might be the key factor \r\nleading to a  reduced blocking, because of the strengthening \r\nof zonal winds (Kennedy et  al., 2016). The more controversial \r\ninfluence of near-surface Arctic warming might lead to an increased \r\nblocking frequency (Mori et  al., 2014; Francis and Vavrus, 2015) \r\n(see Chapter 10, Box 10.1)."


id: ea42e9311742aaa3b10213c5bd0c4417
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38571
content:
"The model-simulated, long-term trend of ocean acidification is assessed \r\nin Section 4.3.2.5 and Chapter 5 (Section 5.3.4.1). It is virtually certain \r\nthat surface ocean acidification will continue in response to the rise \r\nin atmospheric CO2, and continued penetration of anthropogenic \r\nCO2 from the surface to the deep ocean will acidify the ocean interior \r\n(Figure 4.29). By the end of this century, under SSP3-7.0, a pH reduction \r\nof about 0.3 is found at a few hundred metres depth of the global \r\nocean, with stronger acidification in the interior North Atlantic and the \r\nmid- to high-latitude Southern Ocean. At a depth of about 1 km, a pH \r\nreduction of about 0.1 is found."


id: 790c97832ea157291f0661f20eff1b7f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18485
content:
"Figure 4.28 shows a clear decrease in blocking activity over Greenland \r\nand North Pacific for SSP7.0 and SSP8.5. Models with the largest \r\ndecrease in blocking frequency in boreal winter are those showing \r\nthe smallest frequency bias during the historical period (Davini \r\nand D'Andrea, 2020). In conclusion, there is medium confidence \r\nthat the frequency of atmospheric blocking events over Greenland \r\nand the North Pacific will decrease in boreal winter in the SSP3-7.0 \r\nand SSP5-8.5 scenarios."


id: be81f2575ab9c46b139fa25a999a1cf9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30779
content:
"Projections of long-term ocean thermal properties are assessed \r\ncomprehensively in Chapter 9 (Sections 9.2.1.1 and 9.2.2.1) and are \r\nnot covered here to avoid unnecessary overlap."


id: 484f6984324dbd6feb6946f88d451b29
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9937
content:
"more positive by the end of the century except in boreal summer (JJA) \r\nwhen there is no change in the NAM in these simulations. In boreal \r\nwinter (DJF) under SSP5-8.5, the central estimate is an increase in \r\nthe NAM by almost 3 hPa in the long-term compared to 1995-2014. \r\nThis can be compared to a multi-model mean interannual standard \r\ndeviation in the winter NAM index of 3.4 hPa during the period \r\n1850-1900. We conclude with high confidence that in the mid- to \r\nlong-term, the boreal wintertime surface NAM is more positive under \r\nSSP3-7.0 and SSP5-8.5, while under SSP1-1.9 and SSP1-2.6, the NAM \r\ndoes not show any robust change."


id: cae57a463593fdbc7b6af99f5ec79ade
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33034
content:
"In most seasons, the SAM becomes more positive by the end of \r\nthe century relative to 1995-2014 under SSP2-4.5, SSP3-7.0, and \r\nSSP5-8.5 (Figure 4.30b). Conversely, under SSP1-1.9 and SSP1-2.6, \r\nin most seasons the SAM index does not show a  robust change \r\ncompared to 1995-2014 except in austral summer when it becomes \r\nsignificantly more negative. The greatest change in the SAM occurs \r\nin austral winter, where CMIP6 models show an ensemble-mean \r\nincrease in the SAM index of almost 5 hPa in SSP5-8.5. This can be \r\ncompared to a  multi-model mean interannual standard deviation \r\nin the austral winter SAM index of 4.0 hPa during 1850-1900. In \r\nconclusion, there is high confidence that in high emissions scenarios \r\n(SSP3-7.0 and SSP5-8.5) the SAM becomes more positive in all \r\nseasons, while in the lowest scenario (SSP1-1.9) there is a  robust \r\ndecrease in austral summer."


id: 6d34dd8001a7c5b63a7e559bb523d3a9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
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content:
"The AR5 assessed from CMIP5 simulations that the future boreal \r\nwintertime NAM is very likely to exhibit natural variability and \r\nforced trends of similar magnitude to that observed in the historical \r\nperiod and is likely to become slightly more positive in the future. \r\nConsiderable uncertainty is related to physical mechanisms to explain \r\nthe observed and projected changes in the NAM, but NAM trends are \r\nclearly closely connected to projected shifts in the mid-latitude jets \r\nand storm tracks."


id: 2ebcae090d7c68c4c8ba44e3916dc736
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5500
content:
"NAM projections from climate models analysed since AR5 reveal \r\nbroadly similar results to the late 21st century. CMIP6 models show \r\na  positive ensemble-mean trend in most seasons and the higher \r\nemissions scenarios that is comparable to between-model or between\u0002realization variability (Figure  4.30a). The NAM generally becomes "


id: 1aed8a67f72684d3d333e9313ef0b080
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 1930
content:
"simulate linear ENSO stability realistically exhibit a  decrease in \r\nENSO amplitude by the second half of the 21st century. However, an \r\nincrease of ENSO SST variability has been projected when considering \r\nbiases in ENSO pattern simulation by different models (Zheng et al., \r\n2016; Cai et al., 2018a). This highlights the importance of constraining \r\ntropical Pacific mean state changes in order to enhance confidence in \r\nthe projected response of ENSO."


id: 46e5412fa1f8d4b46cc720fa57a90198
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9675
content:
"The AR5 assessed that it is very likely that the El Nino-Southern \r\nOscillation (ENSO) will remain the dominant mode of interannual \r\nvariability in the future. Moreover, due to increased moisture \r\navailability, the associated precipitation variability on regional scales \r\nwas assessed to likely intensify. An eastward shift in the patterns of \r\ntemperature and precipitation variations in the North Pacific and North \r\nAmerica related to El Nino and La Nina teleconnections was projected \r\nwith medium confidence. The stability of teleconnections to other \r\nregional implications including those in Central and South America, \r\nthe Caribbean, parts of Africa, most of Asia, Australia and most Pacific \r\nIslands were assessed to be uncertain (Christensen et al., 2013)."


id: eb15baec8b15a8668d5f6fae6e5f459c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38715
content:
"There is also no robust consensus on changes in ENSO diversity. \r\nSeveral studies suggest that an increase in Eastern Pacific (EP)-ENSO \r\nevents tends to be projected particularly in the models with an \r\nEl Nino-like warming (Zheng et al., 2016; Cai et al., 2018a; Fredriksen \r\net al., 2020). However, Freund et al. (2020) suggested that models \r\nwith a  El Nino-like mean warming show a  tendency toward more \r\nCentral Pacific (CP) events but fewer EP events compared to models \r\nwith an La Nina-like warming in both CMIP5 and CMIP6 models."


id: d138318a61041da9da51c23448ceb04c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34160
content:
"Even though there is low agreement in simulated changes in ENSO \r\nSST variability, the majority of models project an increase in \r\namplitude of ENSO rainfall variability attributable to the increase \r\nin mean SST and moisture in CMIP5 (Power et al., 2013; Watanabe \r\net  al., 2014; Huang and Xie, 2015) and CMIP6 (Yun et  al., 2021). \r\nIt is likely that extreme El Nino events, accompanied by the eastern \r\nequatorial Pacific rainfall exceeding the 5 mm day-1 rainfall threshold, \r\nwill increase in intensity (Cai et al., 2014a, 2017). However, it has \r\nalso been suggested that historical model biases over the equatorial \r\nPacific cold tongue in CMIP5 may lead to the greater precipitation \r\nmean change and amplification of extreme ENSO-associated rainfall \r\nin CMIP5 (Stevenson et al., 2021)."


id: 236cd805b330bfeec28cd5005ffb0be4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3431
content:
"There is limited intermodel agreement on future changes in ENSO \r\nteleconnections largely depending on changes in the mean state and \r\nchanges in ENSO properties (Yeh et al., 2018). Many CMIP5 and CMIP6 \r\nmodels project that the centres of the extratropical teleconnection over \r\nNorth Pacific and North America will shift eastward in association with \r\nan eastward shift in tropical convective anomalies (Yeh et al., 2018; \r\nFredriksen et al., 2020). There is an indication that tropical cyclones "


id: fe31090452395f03a549e7d8491de15f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 42087
content:
"will become more frequent during future El Nino events (and less \r\nfrequent during future La Nina events) by the end of the 21st century \r\n(Chand et  al., 2017), thus contributing to the projected increase in \r\nENSO-associated hydro-climate impacts."


id: 415b9b1c608ac8887c0cb9013f650439
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8685
content:
"The AR5 assessed that there is low confidence in projected changes \r\nof the Tropical Atlantic Variability (TAV) because of the general failure \r\nof climate models to simulate main aspects of this variability such \r\nas the northward displaced ITCZ. The models that best represent the \r\nAtlantic meridional mode (AMM) show a weakening for future climate \r\nconditions. However, model biases in representation of Altantic Ninos \r\nstrongly limit an assessment of future changes."


id: f7df06b5c1b93dd6c72879b8fefb244c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40985
content:
"While CMIP6 models show no robust change in ENSO SST amplitude \r\nin the mid- and long-term period across all four SSPs, a  robust \r\nincrease in ENSO rainfall amplitude is found particularly in SSP2-4.5, \r\nSSP3-7.0, and SSP5-8.5 (Figure 4.10). The changes in ENSO rainfall \r\namplitude in the long-term future (2081-2100) relative to the recent \r\npast (1995-2014) are statistically significant at the 95% confidence."


id: 3e851a49a5942e7dbc94886bb9875983
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8188
content:
"Long-term changes in TAVs and associated teleconnections are \r\nexpected as a result of global warming, but large uncertainties exist \r\ndue to the models' systematic underestimation of the connection \r\nbetween PDV and Indo-Pacific SST variations (Lubbecke et al., 2018; \r\nCai et al., 2019). Observational analyses show large discrepancies in \r\nSST and trade wind strength (Servain et al., 2014; Mohino and Losada, \r\n2015). Single-model sensitivity experiments show that Atlantic Nino \r\ncharacteristics at the end of 21st  century remain consistent with \r\nthose of the 20th century, though changes in the climatological SSTs \r\ncan lead to changes in the associated teleconnections (Mohino and \r\nLosada, 2015)."


id: ddeb7a630bc87a1ddb776bbfe4b0ca75
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36304
content:
"To conclude, the forced change in ENSO SST variability is highly \r\nuncertain in CMIP5 and CMIP6 models (medium confidence). However, \r\nit is very likely that ENSO-related rainfall variability will increase \r\nsignificantly regardless of ENSO amplitude changes in the mid- and \r\nlong-term future. It is likely that the pattern of ENSO teleconnection \r\nover the North Pacific and North America will shift eastward."


id: a76f2a9cbdefde090c67a775a95d002f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26670
content:
"The weakening of the AMOC expected from global warming \r\n(see  Section  4.3.2.3) has been suggested to have an influence on \r\nthe mean background state of tropical-Atlantic surface conditions, \r\nthereby enhancing equatorial Atlantic variability and resulting in \r\na stronger tropical Atlantic-ENSO teleconnection (see Section 3.7.5 \r\nfor a detailed discussion; Svendsen et al., 2014). A recent multi-model \r\nstudy, based on CMIP5, concluded that the TAV-Pacific teleconnection \r\nwill weaken under global warming due to the increased thermal \r\nstability of the atmosphere (F. Jia et al., 2019). However, there is still \r\na clear lack of model studies, and hence no robust evidence on the \r\nlong-term evolution of TAV and associated teleconnections."


id: 4d17f5d17dd15616b3e792027201caf1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10834
content:
"The AR5 assessed that there is low confidence in projections of \r\nfuture changes in Pacific decadal variability (PDV) due to the inability \r\nof CMIP5 models to represent the connection between PDV and \r\nIndo-Pacific SST variations. Because the PDV appears to encompass \r\nthe combined effects of different dynamical processes operating \r\nat different time scales, representation of PDV in climate models \r\nremains a challenge (Section 3.7.6) and its long-term evolution under \r\nclimate change uncertain."


id: 9c6bcd180dcda3608ec1c33a82c0fda2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24771
content:
"However, it was also found that the frequency of extreme positive \r\nIOD events, which exhibit the largest climate impacts, might increase \r\nby a  factor of about three under the CMIP5 RCP8.5 scenario \r\n(Cai et al., 2014b). Partially consistent with the above result, a more \r\nrecent study by Cai et al. (2021), based on CMIP5 RCP8.5 and CMIP6 \r\nSSP5-8.5 simulations, shows a  robust increased SST variability of \r\nlarge positive IOD events, but a  decreased variability of moderate \r\nIOD events. An approximate doubling of these extreme positive IOD \r\nevents was still found for global warming of 1.5degC warming above \r\npre-industrial levels, without a  projected decline thereafter (Cai \r\net al., 2018b). These results depend, however, on the realism of the \r\nprojected mean state change in the Indian Ocean (G. Li et al., 2016)."


id: be0e43cb26be6b24a0dee2c33fd67654
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 30705
content:
"In addition to uncertainty from the future evolution of the mechanisms \r\nthat determined the PDV, it is also unclear how the background state \r\nin the Pacific Ocean will change due to time-varying radiative forcing, \r\nand how this change will interact with variability at interannual and \r\nlow-frequency time scales (Fedorov et  al., 2020). Recent research \r\nsuggests that the PDV will have a  weaker amplitude and higher \r\nfrequency with global warming (Zhang and Delworth, 2016; Xu and \r\nHu, 2017; Geng et al., 2019). The former appears to be associated \r\nwith a decrease in SST variability and the meridional gradient over \r\nthe Kuroshio-Oyashio region, with a reduction in North Pacific wind \r\nstress and meandering of the subpolar/subtropical gyre interplay \r\n(Zhang and Delworth, 2016). The latter is hypothesized to rely on "


id: 69a284290371f490e6ff6f8d0bee8d96
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15850
content:
"To conclude, the forced change in IOD in mid- and long-term \r\nfuture remains uncertain due to limited lines of evidence and its \r\ndependence on model mean biases. However, there is low confidence\r\nthat the frequency of extreme positive IOD events will increase under \r\nthe high-emissions scenario of SSP5-8.5."


id: 3c6769f431dbc88e31701003be5f116f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7818
content:
"the enhanced ocean stratification and shallower mixed layers of \r\na  warmer climate, which would increase the phase speed of the \r\nwestward-propagating oceanic waves, hence shortening the decadal \r\nto inter-decadal component (Goodman and Marshall, 1999; Zhang \r\nand Delworth, 2016; Xu and Hu, 2017). The weakening of the PDV \r\nin a  warmer climate may reduce the internal variability of global \r\nmean surface temperature, to which PDV seems associated (Zhang \r\net al., 1997; Kosaka and Xie, 2016; Geng et al., 2019). Thus, a weaker \r\nand higher frequency PDV could reduce the contribution of internal \r\nvariability to the GSAT trend and eventually lead to a  reduced \r\nprobability of surface-warming hiatus events."


id: f2f18b341aa7e107d104fb5774f0dcd1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40132
content:
"This subsection provides an assessment of changes in climate \r\nat 1.5degC, 2degC, 3degC, and 4degC of global warming relative to the \r\nperiod 1850-1900 (Section  1.6.2), in particular a  discussion of \r\nthe regional patterns of change in temperature (Section  4.6.1.1), \r\nprecipitation (Section 4.6.1.2), and aspects of atmospheric circulation \r\n(Section  4.6.1.3). An assessment of changes in extreme weather \r\nevents as a function of different levels of global warming is provided \r\nin Chapter  11, while corresponding analyses of regional climate \r\nchange are provided in Chapter  12 and in the Atlas. This section \r\nbuilds upon assessments from AR5 (Bindoff et al., 2013; Christensen \r\net al., 2013; Collins et al., 2013; Hartmann et al., 2013) and SR1.5 \r\n(SR1.5; Hoegh-Guldberg et  al., 2018), as well as new literature \r\nrelated to projections of climate at 1.5degC, 2degC, and higher levels of \r\nglobal warming above pre-industrial levels."


id: 7ba7c30c5a9a42f4a2a4be7ca999bc37
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18966
content:
"In summary, based on CMIP5, there is medium confidence that \r\na weaker and higher frequency PDV is expected under global warming."


id: d14d2b55020f02e1beb3f352871c239b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34174
content:
"Based on paleoclimate reconstructions and model simulations, AR5 \r\nassessed that AMV is unlikely to change its behaviour in the future. \r\nHowever, AMV fluctuations over the coming decades are likely\r\nto influence regional climate, enhancing or offsetting some of the \r\neffects of global warming."


id: 45dcd6a4c7f8a69ef98391ecca16b7a6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9510
content:
"Recent proxy-derived reconstructions of AMV-related signals show \r\npersistent multi-decadal variability over the last three centuries \r\n(Kilbourne et al., 2014; Svendsen et al., 2014; Moore et al., 2017), \r\nup to the last millennium (Chylek et  al., 2011; Zhou et  al., 2016; \r\nJ. Wang et  al., 2017b) and beyond (Knudsen et  al., 2011). This \r\nimplies that in the past AMV properties were little affected by large \r\nclimatic excursions."


id: 3c84c13515b7f5122ca8d21f1ca9e18e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7839
content:
"In conclusion, on the basis of paleoclimate reconstructions and \r\nCMIP5 model simulations, there is low confidence that the AMV \r\nis not expected to change in the future."


id: 44f30f186571b23d41d38cfd81dc2c98
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9360
content:
"sections. These include overshoot versus stabilization scenarios and \r\nlimitations of pattern scaling for strong mitigation and stabilization \r\nscenarios (Tebaldi and Arblaster, 2014). At least for the case of annual \r\nmean temperature and precipitation, strong evidence exists that even \r\nfor strong mitigation and stabilization scenarios, patterns of change \r\nat lower levels of warming scale similarly to those reconstructed \r\nfrom transient simulations using either standard pattern-correlation \r\nor time-shift methodologies (Tebaldi and Knutti, 2018)."


id: 7d9cf64761d4622612516aa07440682
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19274
content:
"Pattern scaling performance based on scenario experiments is \r\ngenerally better for near-surface temperature than for precipitation \r\n(Ishizaki et  al., 2013). For precipitation, rapid adjustments due to \r\ndifferent forcing agents must be accounted for (Richardson et  al., \r\n2016). Possible non-linear responses to different forcing levels are \r\nalso important (Good et al., 2015, 2016). Pattern scaling does not \r\nwork as well at high forcing levels (Osborn et al., 2018). It is also \r\nimportant to distinguish the forced response from internal variability \r\nwhen comparing similar warming levels (Suarez-Gutierrez et  al., \r\n2018). The purpose of this section is not to repeat the analysis for \r\nall the variables considered in Sections 4.4 and 4.5, but rather to \r\nshow a selected number of key variables that are important from the \r\nperspective of understanding the response of the physical climate \r\nsystem to different levels of warming."


id: 21d7c5fab2682f977632d04fef197e7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3175
content:
"While global mean precipitation increases as GSAT rises with the \r\nvery likely range of 1-3% per 1degC (high confidence) (Sections 8.2.1 \r\nand 8.4.1), patterns of precipitation change do not scale as \r\nlinearly with GSAT increase. Nevertheless, common features of \r\nprecipitation change in the multi-model mean across scenarios \r\nstill exist for different levels of global warming (Figure  4.32). \r\nPrecipitation will very likely increase in the high latitudes and \r\nover tropical regions, and will likely increase in large parts of the \r\nmonsoon region, but are likely to decrease over the subtropical \r\nregions, including the Mediterranean, southern Africa, parts of \r\nAustralia and South America at all four levels of global warming. \r\nThe increases and decreases in precipitation will amplify at higher \r\nlevels of global warming (high confidence) (Figure 4.32). Changes \r\nin extreme precipitation events under different levels of global \r\nwarming are assessed in Chapter 11."


id: ef90a333fe146679d85833dba855f41e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39528
content:
"than over land (Figure 4.33). Precipitation variability in most climate \r\nmodels increases over the global land area in response to warming \r\n(Pendergrass et al., 2017)."


id: 8c96a20b9b7c3d8b9db908ba2a1afb3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21921
content:
"In summary, based on the assessment of CMIP6 models, there is high \r\nconfidence that global mean precipitation will increase with increase \r\nin global mean surface temperature. Precipitation will very likely\r\nincrease in the high latitudes and over tropical regions, likely increase \r\nin large parts of the monsoon region, but will likely decrease over \r\nthe subtropical regions. There is high confidence that increases and \r\ndecreases in precipitation will amplify over higher levels of global \r\nwarming. As warming increases, there is medium confidence that \r\na larger land area will experience statistically significant increases or \r\ndecreases in precipitation."


id: 2794cf4fdf221384ad8011a7e0fbfff7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4142
content:
"The AR5 reported that the application of pattern scaling to extract \r\ninformation on variables other than surface temperature and \r\nprecipitation was relatively unexplored. Since AR5, new studies \r\nhave examined the relationship between projections of mid-latitude \r\natmospheric circulation and GSAT both in terms of interpreting spread \r\nin responses across the CMIP5 multi-model ensemble (Grise and \r\nPolvani, 2014a, 2016) and to investigate variations in the circulation \r\nresponse as a  function of GSAT change over time within a  given \r\nforcing experiment (Grise and Polvani, 2017; Ceppi et al., 2018)."


id: ec90977e0b0fda5bc99dd1eb2b20826f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38977
content:
"At a  fixed time horizon, the CMIP5 multi-model spread in GSAT \r\nexplains only a small fraction of the spread in the shift of the Northern \r\nHemisphere mid-latitude circulation due to an abrupt quadrupling in \r\nCO2 (Grise and Polvani, 2016). The fraction of model spread explained \r\nby GSAT in the shift of the Southern Hemisphere circulation is larger, \r\nbut still fairly small (Grise and Polvani, 2014a, 2016). At a fixed time \r\nhorizon and for a  given emissions scenario, CMIP5 multi-model \r\nspread in storm track shifts, and the closely related mid-latitude jets, \r\ncan be better explained by multi-model spread in lower and upper \r\nlevel meridional temperature gradients than by GSAT (Harvey et al., \r\n2014; Grise and Polvani, 2016)."


id: 78e805a4454cc1a8ae9f2416caa82684
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18460
content:
"simulations. In particular, the differences of regional monsoon \r\nchanges among model setups are dominated by strategy choices \r\nsuch as transient versus quasi-equilibrium set-up, prescription of SST, \r\nand treatment of aerosols (Zhang and Zhou, 2021)."


id: faa4a183b4475a4e1fe7f5af84da41d3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41471
content:
"The global and land area fractions with significant precipitation \r\nchanges with global warming are shown in Figure 4.33. It is virtually \r\ncertain that average warming will be higher over land. As warming \r\nincreases, a larger global and land area will experience statistically \r\nsignificant increases or decreases in precipitation (medium confidence). \r\nThe increase of the area fraction with significant precipitation increase \r\nis larger over land than over the ocean, but the increase of the area \r\nfraction with significant precipitation decrease is larger over the ocean "


id: 921ad8b3e0e3b8803c123b0b9c304f16
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22919
content:
"of warming therefore confounds the effects of ozone recovery and \r\nGHG increases (Ceppi et al., 2018). Given these various limitations, \r\nwe do not apply epoch analysis to assess mid-latitude atmospheric \r\ncirculation changes and related annular modes of variability."


id: c894e2d6d13b3feb88a0bc3a791bb916
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32605
content:
"Many scenarios aiming at limiting warming by 2100 to 1.5degC involve \r\novershoot - ERF temporarily exceeds a certain level before peaking \r\nand declining again (Annex VII: Glossary). To quantify the implications \r\nof any such overshoot, this subsection assesses reversibility of \r\nclimate due to temporary overshoot of GSAT levels during the \r\n21st century, and implications for the use of carbon budgets. It also \r\nassesses differences in climate outcomes under different pathways, \r\nwith a focus on comparing the SSPs used in CMIP6 with the RCPs \r\nused in CMIP5."


id: 246c70b4e7a137782c1397d33412ff1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3601
content:
"4.6.2.2 Consistency Between Shared Socio-economic \r\nPathways and Representative Concentration Pathways"


id: 14cc5ab392086cc36d99e7ae8f6e20cc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 886
content:
"tipping points are not well understood, but the higher the warming \r\nlevel and the longer the duration of overshoot, the greater the risk of \r\nunexpected changes (Section 4.7.2). Non-reversal of the hydrological \r\ncycle has also been found in some studies with an increase in global \r\nprecipitation following CO2 decrease being attributed to a build-up of \r\nocean heat (Wu et al., 2010), and to a fast atmospheric adjustment to \r\nCO2 radiative forcing (Cao et al., 2011)."


id: 360dccc884067fd7e3eb2eb9e65cff19
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6758
content:
"As CMIP5 and CMIP6 employed different scenario sets (RCPs and SSPs, \r\nrespectively; see Section 1.6.1.1 and Cross-Chapter Box 1.4), we assess \r\nhow much of the differences in projections are due to the scenario \r\nchange and how much due to model changes. The CMIP6-simulated \r\nGSAT increases tend to be larger than in CMIP5, for nominally \r\ncomparable scenarios (Section 4.3.1; Tebaldi et al., 2021)."


id: bc977d602bf570db818322f6f1bf221d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30428
content:
"In summary, there is medium confidence that about half of the warming \r\nincrease in CMIP6 compared to CMIP5 is due to higher  climate \r\nsensitivity in CMIP6 models; the other half arises from higher ERF in \r\nnominally comparable scenarios (e.g., RCP8.5 and SSP5-8.5)."


id: df74898cdcf41dd10da4c65a2573ccd6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36562
content:
"Climate change can be also offset by solar radiation modification \r\n(SRM) measures that modify the Earth's radiation budget to reduce \r\nglobal warming (see Glossary). CDR and SRM approaches have been \r\ntogether referred to as 'geoengineering' or 'climate engineering' \r\nin the literature (The Royal Society, 2009; NRC, 2015a, b; Schafer \r\net  al., 2015). However, following SR1.5 (de Coninck et  al., 2018), \r\nthese terms are inconsistently used in the literature, so that CDR \r\nand SRM are explicitly differentiated here. SRM contrasts with \r\nclimate change mitigation because it introduces a  'mask' to the \r\nclimate  change  problem by altering the Earth's radiation budget, \r\nrather than attempting to address the root cause of the problem, \r\nwhich is the increase in GHGs in the atmosphere."


id: c585a2c35af0efce845b6247d7394292
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32055
content:
"Section 4.6.3.1 assesses the emergence of the climate response to \r\nmitigation, which is reflected by the difference between high- and \r\nlow-emissions scenarios. Section  4.6.3.2 then assesses the climate \r\nresponse to mitigation through CDR options, usually assumed \r\nagainst the background of some emissions scenario; note that the \r\nCDR options themselves are assessed in Chapter 5 (Section 5.6.2). \r\nSection 4.6.3.3 assesses the climate system response to SRM options. \r\nThe biogeochemical implications of CDR and SRM are assessed in \r\nChapter 5 (Sections 5.6.2 and 5.6.3, respectively). The importance of \r\nCDR for reaching net zero or negative CO2 emissions in mitigation \r\npathways is assessed in the AR6 WGIII report (Chapters 3, 4, 6, 7 \r\nand 12). The risks for and impacts on human and natural systems \r\ndue to SRM are assessed in the AR6 WGII report (Chapter 16), and \r\nthe international governance issues related to SRM and CDR are \r\nassessed in the AR6 WGIII report (Chapter 14)."


id: f60148e3433576c3eb8fdc7586306367
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40639
content:
"Reducing GHG emissions will eventually slow and limit the degree of \r\nclimate change relative to high-emissions scenarios such as SSP5-8.5 \r\n(very high confidence). Even when CO2 emissions are reduced, \r\nhowever, atmospheric CO2 concentrations continue to increase \r\nas long as emissions exceed removal by sinks (Millar et al., 2017). \r\nSurface warming would likewise initially continue under scenarios of \r\ndecreasing emissions, resulting in a substantial lag between a peak \r\nin CO2 emissions and peak warming (high confidence) (Ricke and \r\nCaldeira, 2014; Zickfeld and Herrington, 2015). The lag between \r\npeak emissions and warming depends on the emissions history \r\nprior to the peak and also on the rate of the subsequent emissions \r\nreductions (Matthews, 2010; Ricke and Caldeira, 2014; Zickfeld and \r\nHerrington, 2015)."


id: cf068595b5e98195d9c4584acde5a712
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33765
content:
"Most strong-mitigation scenarios assume - in addition to emissions \r\nreductions  - some form of carbon dioxide removal (CDR). \r\nAnthropogenic activities that remove CO2 from the atmosphere and \r\ndurably store it in geological, terrestrial, or ocean reservoirs, or in \r\nproducts (see Glossary). The SR1.5 (Rogelj et  al., 2018b) assessed \r\nthat all pathways that limit warming to 1.5degC by 2100 with no or \r\nlimited overshoot use CDR. In the SSP class of scenarios, SSP1-1.9 \r\nis characterized by a rapid decline of net CO2 emissions to zero by \r\n2050 and net negative CO2 emissions in the second half of this \r\ncentury (O'Neill et al., 2016; Rogelj et al., 2018a), implying the use of \r\nCDR. The term 'net CO2 emissions' refers to the difference between \r\nanthropogenic CO2 emissions and removal by CDR options, and 'net \r\nnegative CO2 emissions' imply a scenario where CO2 removal exceeds \r\nemissions (van Vuuren et  al., 2011, 2016). The terms 'negative "


id: 97a4c0a4b947e3dbc7428b40169813c3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23898
content:
"In addition to the lag between peak emissions and peak warming, \r\nthe climate response to reduced emissions would be overlain by \r\ninternal variability, which can amplify or attenuate the forced \r\nresponse. The resulting masking of differences between scenarios is \r\nillustrated in Figure 4.36 for GSAT trends over 2021-2040 (Maher \r\net al., 2020). The overall trends conform to expectations in that most \r\nsimulations show warming almost everywhere, especially under \r\nscenario RCP8.5 (Figure 4.36 bottom row). But any individual grid \r\npoint can in principle show no warming or even cooling, even under "


id: b075c380424fd4f1838377fe06326bf3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28281
content:
"RCP 8.5, over the near term (Figure 4.36, middle row). The magnitude \r\nof pointwise maximum and minimum temperature trends can be as \r\nlarge as 0.5degC per year (Figure 4.36, top and middle rows), exceeding \r\npossible trends in the global mean by one order of magnitude. While \r\nit is only a small fraction of the surface that simultaneously can show \r\ncooling, cooling at any given location is fully consistent with globally \r\naveraged surface warming over the near term (high confidence, since \r\nthe findings of Maher et al. (2020) are consistent across six different \r\nlarge initial-condition ensembles)."


id: afd647e8104b3d28026959d7211bfcbc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28172
content:
"possible to observe what the climate would have been without these \r\nmeasures, and any statement about emergence of the response to \r\nmitigation is contingent upon the assumed strength of mitigation in \r\nrelation to an assumed ('counterfactual') no-mitigation scenario. Still, \r\nthere is high agreement on the emergence of the climate response \r\nto mitigation across a number of independent studies using different \r\nmodels and different statistical approaches."


id: cfed4133ff0327e402823b63635e7e0e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33933
content:
"Among global quantities, emergence of the response to differing CO2\r\nemissions - representing differences between low- and high-emissions \r\nscenarios - is first expected to arise in global mean CO2 concentrations, \r\nabout 10 years after emissions pathways have started diverging (high \r\nconfidence) (Tebaldi and Friedlingstein, 2013; Peters et  al., 2017; \r\nSchwartzman and Keeling, 2020; Spring et al., 2020). In these studies, \r\nemergence is generally defined as the time at which the global mean "


id: 7c6f6a1a5c586a51b6d70500c9603b95
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19093
content:
"An important development since AR5 has been the quantification \r\nof when the climate response to mitigation can be expected to \r\nemerge from the background noise of internal variability (illustrated \r\nin Figure 4.36; see Section 1.4.2.2 and Glossary). A basic ambiguity \r\narises because once mitigation measures are in place, it is no longer "


id: eac3d2154f893ef0a026d81b943dcfe8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38661
content:
"Figure 4.36 | Masking of climate response to mitigation by internal variability in the near term. Near-term (2021-2040) pointwise maximum (top row) and \r\npointwise minimum (middle row) surface air temperature trends in the large initial-condition ensemble from MPI (left and centre columns), and CESM (right-hand \r\ncolumn) models in the RCP2.6 (left-hand column) and RCP8.5 scenarios (centre and right columns). The percentage of ensemble members with a warming trend in \r\nthe near term is shown in the bottom panels. Figure modified from Maher et al. (2020). Further details on data sources and processing are available in the chapter data table \r\n(Table 4.SM.1)."


id: f0595fdd920595445c8afacbb4a71794
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39667
content:
"concentration first differs between mitigation and non-mitigation \r\nscenarios by more than two standard deviations of internal variability, \r\nalthough there are some methodological differences."


id: 27533548b836534ac61331322bcfbcc6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4092
content:
"Attribution to emissions reductions, for the case of RCP2.6 relative \r\nto RCP4.5, is not substantially more likely for 2021-2035 trends \r\nin upper-2000 m OHC than for GSAT (Marotzke, 2019), although \r\nOHC change is thought to be less susceptible to internal variability. \r\nFurthermore, Marotzke (2019) found only around 10% likelihood \r\nof mitigation-benefit emergence during 2021-2035 for change \r\nin AMOC and September Arctic sea ice area. Tebaldi and Wehner \r\n(2018) showed that the differences in temperature extremes \r\nbetween RCP4.5 and RCP8.5 over all land areas become statistically \r\nsignificant by 2050. The seemingly contrasting result of Ciavarella \r\net  al. (2017) that mitigation benefits arise earlier for climate \r\nextremes poses no contradiction, because Ciavarella et  al. (2017) \r\ndid not look at emergence as defined here but at the extremes of \r\na distribution, which differ between scenarios already at a time when \r\nthe distributions are still largely overlapping."


id: aea7f179dc0fc08da696124d71ec9851
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27962
content:
"In summary, if strong mitigation is applied from 2020 onward as \r\nreflected in SSP1-1.9, its effect on 20-year trends in GSAT would \r\nlikely emerge during the near term, measured against an assumed \r\nnon-mitigation scenario such as SSP3-7.0 and SSP5-8.5. However, \r\nthe response of many other climate quantities to mitigation would \r\nbe largely masked by internal variability during the near term, \r\nespecially on the regional scale (high confidence). The mitigation \r\nbenefits for these quantities would emerge only later during the \r\n21st century (high confidence). During the near term, a small fraction \r\nof the surface can show cooling under all scenarios assessed here, \r\nso near-term cooling at any given location is fully consistent with \r\nglobally averaged surface warming (high confidence)."


id: b79d7d9e3e3be8c44fcd39b677affb2a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29516
content:
"CDR options include afforestation, soil carbon sequestration, bioenergy \r\nwith carbon capture and storage (BECCS), wet land restoration, ocean \r\nfertilization, ocean alkalinisation, enhanced terrestrial weathering \r\nand direct air capture and storage (see Section 5.6.2 and Table 5.9 for \r\na more complete discussion). Chapter 8 (Section 8.4.3) assesses the \r\nimplications of CDR for water cycle changes. The potential of different \r\nCDR options in terms of the amount of CO2 removed per year from the \r\natmosphere, costs, co-benefits and side effects of the CDR approaches \r\nare assessed in SR1.5 (de Coninck et al., 2018), the AR6 WGIII Report \r\n(see Chapters 7 and 12), and in several review papers (Fuss et  al., \r\n2018; Lawrence et al., 2018; Nemet et al., 2018). In the literature, CDR \r\noptions are also referred to as 'negative CO2 emissions technologies'."


id: 535e8599fde4b0692dda1a6ca6d32b6d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11941
content:
"Emergence of mitigation benefits has been studied much less \r\nfor quantities other than globally and annually averaged CO2\r\nconcentration and surface temperature. Boreal-winter temperatures \r\nare more challenging for emergence, due to larger variability in \r\nboreal winter and adding a  decade to the time of emergence, \r\nwhereas emergence times for boreal-summer averages are similar \r\nto the annual temperature averages (Tebaldi and Friedlingstein, \r\n2013). Emergence happens later at the regional scale, with a median \r\ntime of emergence of 30-45 years after emissions paths separate in \r\nRCP2.6 relative to RCP4.5 and RCP8.5; a stricter requirement of 95% \r\nconfidence level instead of median induces a delay of several decades, \r\nbringing time of emergence toward the end of the 21st century at \r\nregional scales (Tebaldi and Friedlingstein, 2013)."


id: f7a46a56a7566cef3fd54da26b58e12f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40943
content:
"Deployment of CDR will lead to a reduction in atmospheric CO2 levels \r\nonly if uptake by sinks exceeds net CO2 emissions. Hence, there could \r\nbe a  substantial delay between the initiation of CDR and net CO2\r\nemissions turning negative (van Vuuren et al., 2016), and the time to \r\nreach net negative CO2 emissions and the evolution of atmospheric \r\nCO2 and climate thereafter would depend on the combined pathways \r\nof anthropogenic CO2 emissions, CDR, and natural sinks. The cooling \r\n(or avoided warming) due to CDR would be proportional to the \r\ncumulative amount of CO2 removed from the atmosphere by CDR \r\n(Tokarska and Zickfeld, 2015; Zickfeld et al., 2016), as implied by the \r\nnear-linear relationship between cumulative carbon emissions and \r\nGSAT change (Section 5.5)."


id: 948032394c7e6f369034824c41c56670
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23334
content:
"CDR termination would depend on the amount CO2 removed by CDR \r\nprior to termination and the rate of background CO2 emissions at the \r\ntime of termination. See also Chapter 5, Table 5.9, which summarizes \r\nthe termination effects of individual CDR options."


id: adebb5f521d195cbbae538fac5715273
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27843
content:
"portfolio of SRM options (Table 4.7) for consistency with AR5 (Boucher \r\net al., 2013) and SR1.5 (de Coninck et al., 2018). Other approaches \r\nsuch as injection of sulphate aerosols into the Arctic troposphere \r\nand sea ice albedo enhancements for moderating regional warming \r\nhave also been suggested (MacCracken, 2016; Field et  al., 2018). \r\nAs noted in SR1.5 (de Coninck et al., 2018), SRM is only considered as \r\na potential supplement to deep mitigation, for example in overshoot \r\nscenarios (MacMartin et al., 2018)."


id: 5e11887c3faa59290cf0488aef077a79
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13845
content:
"In summary, there is high confidence that, due to the near-linear \r\nrelationship between cumulative carbon emissions and GSAT change, \r\ncooling or avoided warming due to a  CDR option would depend \r\non the cumulative amount of CO2 removed by that CDR option. \r\nThe climate system response to the deployment of CDR is expected \r\nto be delayed by years (e.g.,  in temperature, precipitation, sea ice \r\nextent) to centuries (e.g.,  sea level and AMOC) (high confidence). \r\nThe climate response to a  sudden and sustained CDR termination \r\nwould depend on the amount of CDR-induced cooling prior to \r\ntermination and the rate of background CO2 emissions at the time of \r\ntermination (high confidence)."


id: ec1a257a32e543917c2ba99acace4632
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38905
content:
"Most SRM approaches, including stratospheric aerosol injection (SAI), \r\nmarine cloud brightening (MCB), and surface albedo enhancements \r\n(Table 4.7), aim to cool the Earth by deflecting more solar radiation \r\nto space. Although cirrus cloud thinning (CCT) aims to cool the planet \r\nby increasing the longwave emission to space, it is included in the "


id: 2deb8be67b858285782c63603cc0dfa6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5358
content:
"To offset the same amount of CO2-induced GSAT increase, \r\ndifferent levels of ERF are required for different methods of SRM \r\n(Schmidt et al., 2012; Chiodo and Polvani, 2016; Modak et al., 2016; \r\nDuan et  al.,  2018; Russotto and Ackerman, 2018; Krishnamohan \r\net al., 2019; Zhao et al., 2021)."


id: 33d5f7b43091f398c97d08375348d685
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6360
content:
"The SR1.5 (de Coninck et  al., 2018) assessed SRM in terms of its \r\npotential to limit warming to below 1.5degC in temporary overshoot \r\nscenarios and the associated impacts. It concluded that SAI could \r\nlimit warming to below 1.5degC but that the climate response to SAI is \r\nuncertain and varies across climate models. Overall, the assessment \r\nconcluded that the combined uncertainties related to SRM approaches, \r\nincluding technological maturity, limited physical understanding of the \r\nresponse to SRM, potential impacts, and challenges of governance, \r\nconstrain potential deployment of SRM in the near future."


id: e0446211d09677f411adbe0068e8e26d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36706
content:
"As assessed in AR5 (Boucher et al., 2013), abruptly introducing SRM to \r\nfully offset global warming reduces temperature toward 1850-1900 \r\nvalues with an e-folding time of only about five years (Matthews and \r\nCaldeira, 2007). A more realistic approach would be a slow ramp-up \r\nof SRM to offset further warming (MacCracken, 2016; Tilmes et al., \r\n2016). Modelling studies have consistently shown that SRM has the \r\npotential to offset some effects of increasing GHGs on global and \r\nregional climate, including the melting of Arctic sea ice (Berdahl et al., \r\n2014; Moore et al., 2014) and mountain glaciers (Zhao et al., 2017), \r\nweakening of Atlantic meridional overturning circulation (AMOC; Cao \r\net al., 2016; Hong et al., 2017; Tilmes et al., 2020), changes in extremes \r\nof temperature and precipitation (Curry et al., 2014; Ji et al., 2018; \r\nMuthyala et  al., 2018), and changes in frequency and intensity of \r\ntropical cyclone (Moore et al., 2015; Jones et al., 2017)."


id: 2292147950b7ad3e6b918ff9f0e05dbd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3300
content:
"The AR5 assessed SRM modelling mainly based on idealized \r\nsimulations that used solar constant reductions. Since then, more \r\nin-depth investigations into specific SRM approaches have been \r\nconducted with more sophisticated treatment of aerosol-cloud-\r\nradiative interactions and stratospheric dynamics and chemistry \r\nunderlying SAI, MCB, and CCT. Another major development since AR5 \r\nis the investigation into whether multiple climate policy goals may be \r\nmet by optimally designed SRM strategies, including large-ensemble \r\nSAI simulations using multiple injection locations. There are large \r\nuncertainties in important SRM-related processes such as aerosol \r\nmicrophysics and aerosol-cloud-radiation interaction and hence the \r\nlevel of understanding is low."


id: 5f18e6da8a281c2c10ef606457ea72ae
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14033
content:
"As assessed in SR1.5 (de Coninck et al., 2018), most of the knowledge \r\nabout SRM is based on idealized model simulations and some \r\nnatural analogues. In addition to single-model studies, more results \r\nfrom the coordinated modelling work of Geoengineering Model \r\nIntercomparison Project (GeoMIP) have become available. GeoMIP \r\nwas initiated at the time of AR5 (Kravitz et al., 2011, 2013a) and is \r\nnow in its second phase under the framework of CMIP6 (GEOMIP6, \r\nKravitz et al., 2015). However, studies based on GeoMIP6 data are \r\ncurrently limited and hence the assessment on climate response to \r\nSRM here is derived mostly from GeoMIP literature together with \r\nstudies with single models."


id: c14f5fa1d2bbe272c7229c1a30611926
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31313
content:
"For the same amount of global mean cooling achieved, the pattern \r\nof climate response would depend on SRM characteristics (Niemeier \r\net al., 2013; Duan et al., 2018; Muri et al., 2018). This is illustrated \r\nin Figure 4.38 for temperature and precipitation change relative to \r\na  high-CO2 world for scenarios of CO2 reduction, solar irradiance \r\nreduction, SAI, and MCB. The pattern differences for different \r\nmethods are much larger for precipitation than for temperature. The \r\npattern of climate change resulting from SRM is also different from \r\nthat resulting from CO2 reduction (Figure 4.38). It is virtually certain\r\nthat SRM approaches would not be able to precisely offset the GHG\u0002induced anthropogenic climate change at global and regional scales."


id: c81fd51068bb9f72621f2def9919a35b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32524
content:
"Simple calculations and climate modelling studies show that about \r\n2% extra solar irradiance reflected away from Earth or a  one \r\npercentage point increase in planetary albedo (0.31 to 0.32) would \r\nsuffice to offset global mean warming from a doubling of the CO2 \r\nconcentration (The Royal Society, 2009; Kravitz et al., 2013a, 2021). "


id: e526bf8a401f8accaecf70c4efbcdca6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37616
content:
"Because of different sensitivity of precipitation change to CO2 and \r\nsolar forcings (Myhre et  al., 2017), if shortwave-based SRM is used "


id: ae9897bf3fb70a6685aa4915b07d5b4e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27950
content:
"to fully offset GHG-induced global mean warming, there would \r\nbe a  overcompensation of GHG-induced increase in global mean \r\nprecipitation (Kravitz et  al., 2013a; Tilmes et  al., 2013; Irvine et  al., \r\n2016). Further, regional SRM approaches such as aerosol injections \r\ninto the Arctic stratosphere are likely to remotely influence on tropical \r\nmonsoon precipitation by shifting the mean position of ITCZ (Nalam \r\net al., 2018). However, the shift could be avoided by simultaneously \r\ncooling the southern hemisphere (MacCracken et  al., 2013; Kravitz \r\net al., 2016; Nalam et al., 2018). The SRM response of precipitation \r\nminus evapotranspiration (P-E) is found to be smaller than that \r\nof precipitation because of reduction in both precipitation and \r\nevapotranspiration (Tilmes et al., 2013; Nalam et al., 2018; Irvine et al., \r\n2019). Thus, global mean soil moisture could be effectively maintained, \r\nthough with significant regional variability (Cheng et al., 2019)."


id: b0a5030f9d907a5f115406a4cff2c699
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28308
content:
"The Geoengineering Large Ensemble Project (GLENS) has investigated \r\nachieving multiple climate policy goals by adjusting the rate of \r\nstratospheric SO2 injection at four different latitudes. GSAT, the \r\ninter-hemispheric temperature difference, and the equator-to-pole \r\ntemperature gradient could be maintained simultaneously at the \r\nyear-2020 level under RCP 8.5 (Tilmes et al., 2018a). The possibility of \r\nusing SAI to simultaneously stabilize non-temperature metrics such \r\nas tropical precipitation and Arctic sea ice extent is also explored (Lee \r\net al., 2020). Furthermore, the potential of achieving multiple climate \r\npolicy goals by combining two SRM approaches is also examined \r\nin a few modelling studies, with low confidence in the outcome of \r\ncombining various approaches and the related climate response \r\n(Boucher et al., 2017; Cao et al., 2017)."


id: 886bf1ef369098368e47c58acd5d9370
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21161
content:
"The cooling potential of SAI using sulphate aerosols depends on \r\nmany factors (Visioni et al., 2017) including the amount of injection \r\n(Niemeier and Timmreck, 2015), aerosol microphysics (Krishnamohan \r\net al., 2020), the spatial and temporal pattern of injection (Tilmes et al., \r\n2017), response of stratospheric dynamics and chemistry (Richter \r\nJadwiga et al., 2018), and aerosol effect on cirrus clouds (Visioni et al., \r\n2018). A negative radiative forcing of a few W m-2 (ranging from one "


id: 53c7ec43c525a93917a11a1b46535582
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12009
content:
"the climate response to MCB is as uncertain. Results from global \r\nclimate models are subject to large uncertainty because of different \r\ntreatment of cloud microphysics and inadequate representation of \r\nsub-grid aerosol and cloud processes (Alterskjaer and Kristjansson, \r\n2013; Stuart et al., 2013; Connolly et al., 2014; Stjern et al., 2018). \r\nSea salt deposition over land (Muri et al., 2015) and the effect of sea \r\nsalt emission on atmospheric chemistry (Horowitz et al., 2020) are \r\nsome of the potential side effects of MCB."


id: 62ba52bead477b94b1b1f81f382e26c3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14663
content:
"Modelling studies suggest that MCB has the potential to achieve \r\na negative forcing of about 1 to 5 W m-2, depending on the deployment \r\narea and strategies of cloud seeding (Hill and Ming, 2012; Partanen \r\net al., 2012; Alterskjaer et al., 2013; Ahlm et al., 2017; Stjern et al., \r\n2018). Regional applications of MCB has also been suggested for \r\noffsetting severe impacts from tropical cyclones whose genesis is \r\nassociated with higher SST (MacCracken, 2016; Latham et al., 2014) \r\nand for protecting coral reefs from higher SST (Latham et al., 2013). \r\nHowever, such regional approaches also involve large uncertainties \r\nin the magnitude of the responses and consequences."


id: 611a045fc9f85908ce2bbabe8c020f3f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14375
content:
"Relative to the high-GHG climate and for the same amount of global \r\ncooling, CCT is simulated to cause an increase in global precipitation \r\ncompared to shortwave-based SRM options such as SAI and MCB \r\n(Duan et al., 2018; Muri et al., 2018) because of the opposing effects of \r\nCCT and increased CO2 on outgoing longwave radiation (Kristjansson \r\net  al., 2015; Jackson et  al., 2016). Combining SAI and CCT has \r\nsuggested that GHG-induced changes in global mean temperature \r\nand precipitation can be simultaneously offset (Cao et al., 2017), but \r\nthere is low confidence in the applicability of this result to the real \r\nworld owing to the large uncertainty in simulating aerosol forcing \r\nand the complex cirrus microphysical processes."


id: f00fc455ac6f383c6dbda9df7ac5fb11
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39614
content:
"Several modelling studies suggest that the direct scattering effect by \r\ninjected particles might also play an important role in the cooling effect \r\nof MCB, but the relative contribution of aerosol-cloud and aerosol-\r\ncloud-radiation effect is uncertain (Partanen et  al., 2012; Kravitz \r\net al., 2013b; Ahlm et al., 2017). Relative to the high-GHG climate, \r\nit is likely that MCB would increase precipitation over tropical land \r\ndue to the inhomogeneous forcing pattern of MCB over ocean and \r\nland (medium confidence) (Bala et al., 2011; Alterskjaer et al., 2013; \r\nNiemeier et al., 2013; Ahlm et al., 2017; Muri et al., 2018; Stjern et al., \r\n2018). Because of the high level of uncertainty associated with cloud \r\nmicrophysics and aerosol-cloud-radiation interaction (Section 7.3), "


id: 5c7ded96a955a0d268817f51e97f3c9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13532
content:
"Surface-based albedo modification could, in principle, achieve \r\na negative radiative forcing of a few W m-2 by enhancing the albedo \r\nof the ocean surface (Gabriel et  al., 2017; Kravitz et  al., 2018). \r\nHowever, the technology does not exist today to increase ocean \r\nalbedo at large scale. An increase in crop albedo or roof albedo in \r\nurban areas could help to reduce warming in densely populated and \r\nimportant agricultural regions, but the effect would be limited to \r\nlocal scales and ineffective at counteracting global warming (Crook \r\net al., 2015; Zhang et al., 2016). Large changes in desert albedo could \r\nin principle result in substantial global cooling, but would severely \r\nalter the hydrological cycle (Crook et al., 2015)."


id: 38d147998dfd0b20c311f1a698ba25e9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7199
content:
"In addition to above-mentioned SRM methods, a  number of local \r\nintervention methods have been proposed to limit the loss of \r\ncryosphere, such as applying reflective materials over sea ice (Field \r\net  al., 2018), pumping seawater on top of the ice surface (Desch \r\net  al., 2017; Zampieri and Goessling, 2019), depositing a  massive \r\namount of snow over ice sheets (Feldmann et al., 2019), and blocking \r\nwarm seawater from reaching glaciers (J.C. Moore et  al., 2018). \r\nThe  stabilization of ice sheets through local intervention methods \r\nwould reduce sea level commitment (Section 9.6.3.5). However, these \r\nmethods are subject to large uncertainty concerning their feasibility \r\nand effectiveness, and their effects would be largely localized."


id: c0ba51627fb7feba2abd99026b391884
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31206
content:
"Modelling studies have consistently shown that SRM has the potential \r\nto offset some effect of increasing GHGs on global and regional \r\nclimate (high confidence), but there would be substantial residual or \r\novercompensating climate change at the regional scale and seasonal \r\ntime scale (high confidence). Large uncertainties associated with \r\naerosol-cloud-radiation interactions persist in our understanding \r\nof climate response to aerosol-based SRM options. For the same \r\namount of global mean cooling, different SRM options would cause \r\ndifferent patterns of climate change (medium confidence). Modelling \r\nstudies suggest that it is conceptually possible to achieve multiple \r\nclimate policy goals by optimally designed SRM strategies."


id: 19bc9d37c231bbadf0550f433c279c90
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1726
content:
"The effect of SRM options on global temperature and precipitation \r\nresponse would be detectable after one or two decades, which is \r\nsimilar to the time scale for the detection of strong mitigation. There \r\nis high confidence that a sudden and sustained termination of a high \r\nlevel of SRM against a high-GHG background would cause a rapid \r\nincrease in temperature at a rate that far exceeds that projected for \r\nclimate change without SRM. However, a gradual phase-out of SRM \r\ncombined with mitigation and CDR would more likely than not avoid \r\nlarge rates of warming."


id: ffacf717e28abfe6d608318ebdb23fa3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 42375
content:
"This section assesses changes in climate beyond 2100. An advance \r\nsince AR5 is the availability of ESM results for scenarios beyond 2100 \r\nand for much longer stabilisation simulations compared with analysis \r\npredominantly based on Earth system models of intermediate \r\ncomplexity (EMICs) at the time of AR5 (e.g., Eby et al., 2013; Zickfeld \r\net al., 2013). Long-term commitment of sea level rise due to thermal \r\nexpansion and ice-sheet loss is assessed in Chapter 9 (Section 9.6.3.5 \r\nand Figure  9.30). Here we assess projections of GSAT, global "


id: cbe4bfdfafa1c686626f0f24bbb06aca
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 33196
content:
"precipitation, and Arctic sea ice. Uncertainties relating to potential \r\nlong-term changes in AMOC are treated in Section 9.2.3.1.\r\n* "


id: 62e301279f271b638e5442c6e27421e4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14695
content:
"On multi-century time scales it is common to explore changes that \r\nare due to long-term commitment. Here we differentiate between:"


id: 8185457596a5ed68dc92f942a4038716
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 19914
content:
"The zero emissions commitment (ZEC) is the climate change \r\ncommitment that would result, in terms of projected GSAT, from \r\nsetting carbon dioxide (CO2) emissions to zero. It is determined by both \r\ninertia in physical climate system components (ocean, cryosphere, \r\nland surface) and carbon cycle inertia (see Annex VII). In its widest \r\nsense it refers to emissions of all compounds including greenhouses \r\ngases, aerosols and their pre-cursors. A specific sub-category of zero \r\nemissions commitment is the zero CO2 emissions commitment, which \r\nrefers to the climate system response to a cessation of anthropogenic \r\nCO2 emissions excluding the impact of non-CO2 forcers. Assessment \r\nof remaining carbon budgets requires an assessment of zero CO2\r\nemissions commitment as well as of the transient climate response \r\nto cumulative carbon emissions (TCRE; Section 5.5.2)."


id: c8915643f93e34c0e529bd9ffeca0cbd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 32597
content:
"There is an offset of continued warming following cessation \r\nof emissions by continued CO2 removal by natural sinks (high \r\nconfidence) (e.g.,  Matthews and Caldeira, 2008; Solomon et  al., \r\n2009; Joos et  al., 2013; Ricke and Caldeira, 2014). Some models \r\ncontinue warming by up to 0.5degC after emissions cease at 2degC of \r\nwarming (Frolicher et al., 2014; Frolicher and Paynter, 2015; Williams \r\net al., 2017), while others simulate little to no additional warming \r\n(Nohara et  al., 2015). In SR1.5, the available evidence indicated \r\nthat past CO2 emissions do not commit to substantial further "


id: bd7e4511176110e58dffe04d4476856a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 30597
content:
"Table 4.8 | The 20-year average GSAT change 50 years after the cessation \r\nof emissions (ZEC50). Displayed are ZEC50 estimated from eleven ESMs (top) and \r\nnine EMICs (bottom)."


id: 2a2b1637b952348af4b785c479ec743f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 4629
content:
"(neither ECS nor TCR; MacDougall et al., 2020). It is therefore likely\r\nthat the absolute magnitude of ZEC50 is less than 0.3degC, but we \r\nassess low confidence in the sign of ZEC on 50-year time scales. This \r\nis small compared with natural variability in GSAT."


id: b05417982412cad8eb487be1464b765b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
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vector_id: 28259
content:
"warming (Allen et al., 2018). A ZEC close to zero was thus applied \r\nfor the computation of the remaining carbon budget (Rogelj et al., \r\n2018b). However, the  available literature consisted of simulations \r\nfrom a  small number of models using a  variety of experimental \r\ndesigns, with some simulations showing a  complex evolution of \r\ntemperature following cessation of emissions (e.g., Frolicher et al., \r\n2014; Frolicher and Paynter, 2015; Williams et al., 2017)."


id: 7d8683febdef7baf015a56152cd620bc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19254
content:
"Changes in climate at 2300 have impacts and commitments \r\nbeyond this timeframe (high confidence). Sea level rise may \r\nexceed 2 m on millennial time scales even when warming is \r\nlimited to 1.5degC-2degC, and tens of metres for higher warming levels \r\n(Table 9.10). Randerson et al. (2015) showed increasing importance \r\non carbon cycle feedbacks of slow ocean processes, Mahowald \r\net  al. (2017) showed the long-lasting legacy of land-use effects \r\nand J.K. Moore et al. (2018) show how changes in Southern Ocean \r\nwinds affect nutrients and marine productivity well beyond 2300. \r\nClark et al. (2016) show that physical and biogeochemical impacts \r\nof 21st century emissions have a potential committed legacy of at \r\nleast 10,000 years."


id: f9314f25d863116809429dcca75acf27
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41206
content:
"time scales. High latitude warming led to longer growing seasons \r\nand increased vegetation growth in the CESM1 model (Liptak \r\net al., 2017), and Burke et al. (2017) found that carbon release from \r\npermafrost areas susceptible to this warming may amplify future \r\nclimate change by up to 17% by 2300."


id: 2e462ace2649198aeb6d167855b39cd5
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5414
content:
"Too few CMIP6 models performed the extension simulations to allow \r\na  robust assessment of GSAT projection, and some of those which \r\ndid had higher than average climate sensitivity values. Therefore, we \r\nbase our assessment of GSAT projections (Table 4.9) on the MAGICC7 \r\nemulator calibrated against assessed GSAT to 2100 (Section  4.3.4, \r\nCross-Chapter Box 7.1). Because the emulator approach has not been \r\nevaluated in depth up to 2300 in the same way as it has up to 2100 \r\n(Cross-Chapter Box 7.1) we account for possible additional uncertainty \r\nby assessing the 5-95% range from MAGICC as likely instead of very \r\nlikely. It is therefore likely that GSAT will exceed 2degC above that of \r\nthe period 1850-1900 at the year 2300 in the extended SSP scenarios \r\nSSP2-4.5, SSP3-7.0 and SSP5-8.5  (Figure  4.40). For  SSP1-2.6 and "


id: 198ef6417e6f387b2a53b274208a6aa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1706
content:
"Table 4.9 | Change of global surface air temperature at 2300. Displayed are \r\nthe median and 5-95% range of GSAT change at 2300 relative to 1850-1900 for the \r\nsix scenarios used with MAGICC7."


id: 9d4a69d693826d866d3d4f487284aa9b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24907
content:
"CMIP5 extension simulations, minimum (September) Arctic sea ice \r\narea began to recover for most models under RCP2.6 out to 2300, \r\nwhile RCP4.5 and RCP8.5 extensions became ice-free in September \r\n(Hezel et al., 2014; Bathiany et al., 2016). They also found increasingly \r\nstrong winter responses under continued warming such that under \r\nthe RCP8.5 extension, the Arctic became ice-free nearly year-round \r\nby 2300. Consistent with the assessment in Section  9.3.1.1 that \r\nArctic sea ice area is correlated with GSAT, CMIP6 projections to 2300 \r\nshow partial sea ice recovery by 2300 in SSP1-2.6 in line with GSAT \r\n(Figure 4.40), with one model (MRI-ESM2-0) showing near complete \r\nrecovery to present-day values. SSP1-2.6 and SSP5-3.4-OS are not \r\ndistinguishable in behaviour of Arctic sea ice in these models after \r\n2100. SSP5-8.5 remains ice-free in September up to 2300."


id: 114ad0534d5e695387aaa038554d40e9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 238
content:
"SSP1-1.9, mean warming at 2300 is 1.5degC and 0.9degC respectively. \r\nGSAT differences between SSP5-3.4-overshoot and SSP1-2.6 peak \r\nduring the 21st century but decline to less than about 0.25degC after \r\n2150 (medium confidence)."


id: c0b9602cfed7ccd51753381b2efda946
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31205
content:
"To place the temperature projections for the end of the 23rd century \r\ninto the context of paleo temperatures, GSAT under SSP2-4.5 (likely\r\n2.3degC-4.6degC higher than over the period 1850-1900) has not been \r\nexperienced since the Mid Pliocene, about three million years ago. \r\nGSAT projected for the end of the 23rd  century under SSP5-8.5 \r\n(likely  6.6degC-14.1degC higher than over the period 1850-1900) \r\noverlaps with the range estimated for the Miocene Climatic Optimum \r\n(5degC-10degC higher) and Early Eocene Climatic Optimum (10degC-18degC \r\nhigher), about 15 and 50 million years ago, respectively (medium \r\nconfidence) (Chapter 2)."


id: 73dae7cd9a4af598d6deb39043a43cff
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17636
content:
"Abrupt and irreversible changes in the climate system are assessed \r\nacross multiple chapters in AR6. This section provides a cross-chapter \r\nsynthesis of these assessments as an update to Table  12.4 in AR5 \r\nand Table 6.1 in SROCC. Understanding of abrupt climate change and \r\nirreversibility has advanced considerably since AR5 with many of the \r\nprojected changes in proposed Tipping Elements having grown more \r\nconfident (Table 4.10). Many aspects of the physical climate changes \r\ninduced by GHG warming previously demonstrated to be reversible \r\nin a single model have been confirmed in multiple models (Boucher \r\net al., 2012; Tokarska and Zickfeld, 2015) with others such as sea level \r\nrise or terrestrial ecosystems confirmed to continue to respond on long \r\ntime scales (Clark et al., 2016; Zickfeld et al., 2017; Pugh et al., 2018)."


id: bd7c8687e0a2a00ed3287c0a0509ef4a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30596
content:
"Chapter  9 assesses with high confidence that on decadal and \r\nlonger time scales, Arctic summer sea ice area will remain highly \r\ncorrelated with global mean temperature until the summer sea ice \r\nhas vanished (Section  9.3.1.1). This means that Arctic sea ice will \r\ncontinue to decline in scenarios of continued warming but will begin \r\nto recover in scenarios where GSAT begins to decrease. Under the "


id: 2e53dd739648b14b82bd1279cd6eb82a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5425
content:
"The Carbon Dioxide Removal Model Intercomparison Project \r\n(CDR-MIP; Keller et  al., 2018) comprises a  set of 1% ramp-up, \r\nramp-down simulations aimed at establishing a  multi-model "


id: c652496d5bf997a298f3c5af55b610ab
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 32205
content:
"They found that some degree of irreversible loss of the West Antarctic \r\nIce Sheet (WAIS) may have already begun, that tropical forests are \r\nadversely affected by drought, and rapid development of aragonite \r\nundersaturation at high latitudes affecting calcifying organisms."


id: 8e8bf520b4dd7750ecebda50b5cbbeaa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22261
content:
"New since AR5 is the fundamental recognition in SRCCL and in \r\nthis Report (Chapter 5) that projected changes in forests strongly \r\ndepend on the human disturbance and that tropical forest dieback \r\nin the absence of disturbance is largely driven by the increased \r\npotential for drought, while that in boreal forests includes both \r\nthermal and hydrological factors (Drijfhout et al., 2015). For some \r\nproposed tipping elements, the role of seasonal change has become \r\nbetter understood. For example, the lack of a tipping point in the \r\nreduction of summer Arctic sea ice area (Stroeve and Notz, 2015) \r\nhas been further substantiated. The role of abrupt change at the "


id: a9cfb694a9fe7f8f6dea42c826367c17
created_at: 2023-04-19 13:21:35
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vector_id: 27098
content:
"Table 4.10 | Cross-chapter assessment updating AR5 and SROCC of components in the Earth system that have been proposed as susceptible to tipping \r\npoints/abrupt change, irreversibility, projected 21st century change, and overall change in assessment from previous IPCC reports. Also provided are \r\nconfidence levels and, in parentheses, the main section(s) of this Report in which proposed tipping elements are assessed."


id: f500d241468d0ecb01e5e8491e70ac3f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40470
content:
"However,  low-warming storylines are not specifically assessed in \r\nthis section to focus on storylines associated with highest risks. This \r\nsection further focuses on storylines of high and very high global \r\nwarming levels along with their manifestation in global patterns \r\nof temperature and precipitation changes. However, this does not \r\naccount for the largest potential changes at regional levels, which \r\nwould require taking into account storylines of regional changes \r\ndependent on changes in atmospheric circulation, land-atmosphere \r\ninteractions, and regional to local feedbacks."


id: 3ec18cf67fae5e904071ccaaca85e67
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"Previous IPCC assessments have primarily assessed the projected \r\nlikely range of changes (e.g., Collins et al., 2013; see also Box 1.1). \r\nThe focus on the likely range partly results from the design of model \r\nintercomparison projects that are not targeted to systematically \r\nassess the upper and lower bounds of projections, which in principle \r\nwould require a  systematic sampling of structural and parametric \r\nmodel uncertainties. The upper and lower bounds of model \r\nprojections may further be sensitive to the missing representation \r\nof processes and to deep uncertainties about aspects of the climate \r\nsystem (Section 1.2.3.1)."


id: 19eaecae94b662a7faa5349a6ac6925e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 1758
content:
"However, a  comprehensive risk assessment requires taking into \r\naccount high potential levels of warming whose likelihood is low, \r\nbut potential impacts on society and ecosystems are high (Xu and \r\nRamanathan, 2017; Sutton, 2018). Climate-related risks have been \r\nargued to increase with increasing levels of global warming even if \r\ntheir likelihood decreases (O'Neill et al., 2017). Thus, it has recently \r\nbeen argued that an assessment that is too narrowly focused on \r\nthe likely range potentially ignores the changes in the physical \r\nclimate system associated with the highest risks (Sutton, 2018; \r\nsee Section 1.4.4.1)."


id: 93ddec5bcdf5e166c712ff772d59ce0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 23223
content:
"Given that the CMIP experiments can be considered ensembles of \r\nopportunity that are not designed for probabilistic assessments, \r\nalternative approaches such as physically plausible high-impact \r\nscenarios (Sutton, 2018) or storylines have been suggested to \r\ninvestigate the tail of the distribution (Lenderink et al., 2014; Zappa \r\nand Shepherd, 2017; Kjellstrom et al., 2018; Shepherd et al., 2018; \r\nsee Section  1.4.4). Such storylines informed by a  combination of \r\nprocess understanding, model evidence, and paleo information can \r\nbe used for risk assessment and adaptation planning to test how \r\nwell adaptation strategies would cope if the impacts of climate \r\nchange were more severe than suggested by the likely model range \r\n(Section  1.4.4). Note that by definition the lower bound of the \r\nlikely model range (Box  4.1) is equally likely as the upper bound. "


id: a1461e50ffefbe8ce7542e37d3b119c1
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content:
"For the high-emissions scenarios SSP3-7.0 and SSP5-8.5, \r\na  high-warming storyline is associated with wide-spread warming \r\nthat exceeds the already high best-estimate warming by another \r\n35-50%. For SSP5-8.5, this corresponds to a warming of 1degC-3degC in \r\naddition to the best estimate over most land regions, which implies \r\nmore than 6degC relative to 1995-2014 over most extratropical land \r\nregions and Amazonia. Over large parts of the Arctic, annual mean \r\ntemperatures increase by more than 10degC relative to 1995-2014 \r\nin such a  high-warming storyline under SSP5-8.5. The two lines \r\nof evidence yield more consistent patterns for SSP5-8.5 than for \r\nSSP1-2.6, but there are substantial differences concerning whether \r\nthe strongest warming above the best estimate occurs over the \r\ntropics or extratropical land regions."


id: e26972ee01b56d479695a030e9f298f1
created_at: 2023-04-19 13:21:35
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content:
"High-warming storylines are very likely also associated with \r\nsubstantial changes in the hydrological cycle due to strong \r\nthermodynamic changes, which can be amplified or offset by \r\ndynamical changes (Emori and Brown, 2005; Seager et  al., 2014b; \r\nChavaillaz et al., 2016; Kroner et al., 2017; Chen et al., 2019). Here \r\nthe assessment of the hydrological cycle in high-warming storylines \r\nis limited to changes in annual mean precipitation, but changes in \r\nseasonal mean precipitation can be even stronger due to enhanced \r\nseasonality in many regions (Box 8.2)."


id: 41e842a388da8ad99213ae839ba92f4b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8788
content:
"The high-warming storyline shown in Figure  4.42b,c does not \r\ncorrespond to an upper or lower estimate of annual precipitation \r\nincrease and decrease over individual locations, which in many \r\nregions may differ in the sign of the response (Figure  4.42e,f) \r\ndue to differences in the model response and internal variability \r\n(Madsen et  al., 2017). Figure  4.42e,f illustrates upper and lower \r\nlocal estimates corresponding to the 5-95% model range of local \r\nuncertainties as opposed to the global-warming storylines. Note, \r\nhowever, that Figure  4.42e,f does not show a  physically plausible \r\nglobal precipitation response pattern, because information at the \r\ndifferent grid points is taken from different model simulations."


id: d595597c4538f32ca91e7ed2e3d549cd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 34886
content:
"Quantifying precipitation changes associated with high-warming \r\nstorylines is challenging since models show the largest changes \r\nin precipitation over different regions (Sections 4.5.1 and 4.6.1). \r\nIn some areas, models project opposing signals in different seasons \r\nor a  combination of decreasing mean and increasing extreme \r\nprecipitation (Kendon et  al., 2014; Ban et  al., 2015; Giorgi et  al., \r\n2016; Pendergrass et al., 2017). Models with the most pronounced \r\nGSAT warming are not necessarily associated with the strongest \r\nprecipitation response in all regions, in part due to projected \r\nchanges in atmospheric dynamics (Madsen et al., 2017; Zappa and \r\nShepherd, 2017; Li et al., 2018)."


id: f551cee58f71a697a715efa7284b1cb9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40530
content:
"Again, the manifestation of changes in the hydrological cycle for \r\na  high-warming storyline is not limited to precipitation, but would \r\nsubstantially affect other variables such as soil moisture, runoff, \r\natmospheric humidity, and evapotranspiration. The changes are also \r\nnot limited to annual mean precipitation but may be stronger or weaker \r\nfor individual seasons and for precipitation extremes and dry spells."


id: 2cb41d31c143d300ad02605007e2341b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5127
content:
"While this assessment is limited to temperature and precipitation, \r\nsuch a  high-warming storyline would manifest itself also in other \r\nclimate variables (Sanderson et  al., 2011) assessed in this chapter \r\nsuch as Arctic sea ice, atmospheric circulation changes, and sea \r\nlevel rise (Ramanathan and Feng, 2008; Xu and Ramanathan, 2017; \r\nSteffen et al., 2018)."


id: b999ee8b8ab7f454338648bc3d594671
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29861
content:
"In summary, while high-warming storylines - those associated with \r\nglobal warming levels above the upper bound of the assessed very \r\nlikely range  - are by definition extremely unlikely, they cannot be \r\nruled out. For SSP1-2.6, such a  high-warming storyline implies \r\nwarming well above rather than well below 2degC (high confidence). \r\nIrrespective of scenario, high-warming storylines imply changes \r\nin many aspects of the climate system that exceed the patterns \r\nassociated with the best estimate of GSAT changes by up to more \r\nthan 50% (high confidence)."


id: f5252db4c21196ffc17e1b1b8aec4db4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 40494
content:
"The authors are deeply grateful to the WGI Bureau and Technical \r\nSupport Unit for their support throughout the writing process. \r\nSpecial thanks go to Anna Pirani, Sarah Connors, Clotilde Pean, Robin \r\nMatthews and Elisabeth  Lonnoy for their organizational support. \r\nSpecial thanks go to Michael Sigmond, Sophie Berger, Paolo Davini, \r\nMelissa Gomis and Tom Maycock for their contributions to figures \r\nand FAQs. We acknowledge outstanding contributions from our two \r\nchapter scientists, Sebastian Milinski and Kyung-Sook Yun. We thank \r\nZiming Chen for contributing the analysis of CMIP6 models. Finally, \r\nwe would like to thank all reviewers for their constructive comments."


id: f9841faf1bc2f02e6e201395c77f3379
created_at: 2023-04-19 13:21:35
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vector_id: 41269
content:
"The parts of the climate system that have shown clear increasing or decreasing trends in recent decades will \r\ncontinue these trends for at least the next twenty years. Examples include changes in global surface temperature, \r\nArctic sea ice cover, and global average sea level. However, over a period as short as twenty years, these trends are \r\nsubstantially influenced by natural climate variability, which can either amplify or attenuate the trend expected \r\nfrom the further increase in greenhouse gas concentrations."


id: c9c139fc1cf9f81cff0aabc16964b20
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32825
content:
"Twenty years are a long time by human standards but a short time from a climate point of view. Emissions of \r\ngreenhouse gases will continue over the next twenty years, as assumed in all the scenarios considered in this \r\nReport, albeit with varying rates. These emissions will further increase concentrations of greenhouse gases in \r\nthe atmosphere (see FAQ 4.2), leading to continued trends in global surface warming and other parts of the \r\nclimate system, including Arctic sea ice and global average sea level (see FAQ 9.2). FAQ 4.1, Figure 1 shows that \r\nboth global surface temperature rise and the shrinking of sea ice in the Arctic will continue, with little difference \r\nbetween high- and low-emissions scenarios over the next 20 years (that is, between the red and blue lines)."


id: b70be72334352caf15ff30d194269248
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29413
content:
"Locally, the effect of natural variability would be much larger still. Simulations (not shown here) indicate that, \r\nlocally, a cooling trend over the next twenty years cannot be ruled out, even under the high-emissions scenario - \r\nat a small number of locations on Earth, but these might lie anywhere. Globally, though, temperatures would \r\nrise under all scenarios."


id: 64353bfa61861a2dd6b6282d21180071
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14918
content:
"In summary, while the direction of future change is clear for the two important climate quantities shown here - \r\nthe global surface temperature and the Arctic sea ice area in September - the magnitude of the change is much \r\nless clear because of natural variability."


id: 5292bd4ce7421dda146d6db885466011
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11810
content:
"Current climatic trends will continue in the next 2 decades \r\nbut their exact magnitude cannot be predicted, because of \r\nnatural variability."


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vector_id: 21353
content:
"The effects of substantial reductions in carbon dioxide emissions would not be apparent immediately, and \r\nthe time required to detect the effects would depend on the scale and pace of emissions reductions. Under the \r\nlower-emissions scenarios considered in this Report, the increase in atmospheric carbon dioxide concentrations \r\nwould slow visibly after about five to ten years, while the slowing down of global surface warming would be \r\ndetectable after about twenty to thirty years. The effects on regional precipitation trends would only become \r\napparent after several decades."


id: 1a5c35f9a4be0899cec0e35c14550d15
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1835
content:
"Reducing emissions of carbon dioxide (CO2) - the most important greenhouse gas emitted by human activities - \r\nwould slow down the rate of increase in atmospheric CO2 concentration. However, concentrations would only \r\nbegin to decrease when net emissions approach zero, that is, when most or all of the CO2 emitted into the \r\natmosphere each year is removed by natural and human processes (see FAQ 5.1 and FAQ 5.3). This delay between \r\na peak in emissions and a decrease in concentration is a manifestation of the very long lifetime of CO2 in the \r\natmosphere; part of the CO2 emitted by humans remains in the atmosphere for centuries to millennia."


id: d988d78602b75510864fd9034e99c1ea
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35571
content:
"Reducing the rate of increase in CO2 concentration would slow down global surface warming within a decade. \r\nBut this reduction in the rate of warming would initially be masked by natural climate variability and might \r\nnot be detected for a few decades (see FAQ 1.2, FAQ 3.2 and FAQ 4.1). Detecting whether surface warming has \r\nindeed slowed down would thus be difficult in the years right after emissions reductions begin."


id: dd5cfa94b3989010ae2082c417f113a1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36212
content:
"FAQ 4.2, Figure 1 shows that the atmospheric CO2 concentrations differ noticeably between the two scenarios \r\nabout five to ten years after the emissions have begun to diverge in year 2015. In contrast, the difference in \r\nglobal surface temperatures between the two scenarios does not become apparent until later - about two to \r\nthree decades after the emissions histories have begun to diverge in this example. This time would be longer if \r\nemissions were reduced more slowly than in the low-emissions scenario illustrated here and shorter in the case \r\nof stronger reductions. Detection would take longer for regional quantities and for precipitation changes, which \r\nvary more strongly from natural causes. For instance, even in the low-emissions scenario, the effect of reduced \r\nCO2 emissions would not become visible in regional precipitation until late in the 21st century."


id: 4cb48f0940cafbaabe4690caa0a57396
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10758
content:
"In summary, it is only after a few decades of reducing CO2 emissions that we would clearly see global temperatures \r\nstarting to stabilize. By contrast, short-term reductions in CO2 emissions, such as during the COVID-19 pandemic, \r\ndo not have detectable effects on either CO2 concentration or global temperature. Only sustained emissions \r\nreductions over decades would have a widespread effect across the climate system."


id: e56b25a071fb9564b7c5d0da74c30a8f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37668
content:
"Sustained reduction in carbon dioxide (CO2) emissions \r\nwould become apparent in atmospheric concentration \r\nafter 5-10 years and in the temperature after 20-30 years."


id: 8e39cc391614d17f6f3aef5aa26b9a50
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22214
content:
"As the planet warms, climate change does not unfold uniformly across the globe, but some patterns of regional \r\nchange show clear, direct and consistent relationships to increases in global surface temperature. The Arctic \r\nwarms more than other regions, land areas warm more than the ocean surface, and the Northern Hemisphere \r\nmore than the Southern Hemisphere. Precipitation increases over high latitudes, tropics and large parts of \r\nthe monsoon regions, but decreases over the subtropics. For cases like these, we can infer the direction and \r\nmagnitude of some regional changes - particularly temperature and precipitation changes - for any given level \r\nof global warming."


id: b6514be1e92bec9667955b867654331e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29292
content:
"The intensity of climate change will depend on the level of global warming. It is possible to identify certain \r\npatterns of regional climate change that occur consistently, but increase in amplitude, across increasing levels of \r\nglobal warming. Such robust spatial patterns of climate change are largely independent of the specific scenario \r\n(and pathway in time) that results in a given level of global warming. That is, as long as different scenarios result \r\nin the same global warming level, irrespective of the time when this level is attained in each scenario, we can \r\ninfer the patterns of regional change that would result from this warming. When patterns of changes are robust, \r\nregional consequences can be assessed for all levels of global warming, for all future time periods, and for all \r\nscenarios. Temperature and precipitation show such robust patterns of changes that are particularly striking."


id: cb89a552561e09a087ff44448fd72413
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33139
content:
"The high latitudes of the Northern Hemisphere are projected to warm the most, by two to four times the level \r\nof global warming - a phenomenon referred to as Arctic amplification (FAQ 4.3, Figure 1, left). Several processes \r\ncontribute to this high rate of warming, including increases in the absorption of solar radiation due to the loss \r\nof reflective sea ice and snow in a warmer world. In the Southern Hemisphere, Antarctica is projected to warm \r\nfaster than the mid-latitude Southern Ocean, but the Southern Hemisphere high latitudes are projected to \r\nwarm at a reduced amplitude compared to the level of global warming (FAQ 4.3, Figure 1, left). An important \r\nreason for the relatively slower warming of the Southern Hemisphere high latitudes is the upwelling of Antarctic \r\ndeep waters that drives a large surface heat uptake in the Southern Ocean."


id: 9fbccdb82e176b7d4691ab7a993955ba
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25307
content:
"The warming is generally stronger over land than over the ocean, and in the Northern Hemisphere compared to \r\nthe Southern Hemisphere, and with less warming over the central subpolar North Atlantic and the southernmost \r\nPacific. The differences are the result of several factors, including differences in how land and ocean areas \r\nabsorb and retain heat, the fact that there is more land area in the Northern Hemisphere than in the Southern \r\nHemisphere, and the influence of ocean circulation. In the Southern Hemisphere, robust patterns of relatively \r\nhigh warming are projected for subtropical South America, southern Africa, and Australia. The relatively strong \r\nwarming in subtropical southern Africa arises from strong interactions between soil moisture and temperature \r\nand from increased solar radiation as a consequence of enhanced subsidence."


id: 136b40d5ad5257de1d7285983497257d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 624
content:
"Precipitation changes are also proportional to the level of global warming (FAQ 4.3, Figure 1, right), although \r\nuncertainties are larger than for the temperature change. In the high latitudes of both the Southern and Northern \r\nHemispheres, increases in precipitation are expected as the planet continues to warm, with larger changes \r\nexpected at higher levels of global warming (FAQ 4.3, Figure 1, right). The same holds true for the projected \r\nprecipitation increases over the tropics and large parts of the monsoon regions. General drying is expected \r\nover the subtropical regions, particularly over the Mediterranean, southern Africa and parts of Australia, South \r\nAmerica, and south-west North America, as well as over the subtropical Atlantic and parts of the subtropical \r\nIndian and Pacific Oceans. Increases in precipitation over the tropics and decreases over the subtropics amplify \r\nwith higher levels of global warming."


id: bf9bb24c7b2162a7429227fe9a6d675d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30976
content:
"Some regions that are already dry and warm, such as southern Africa and the Mediterranean, are expected to \r\nbecome progressively drier and drastically warmer at higher levels of global warming."


id: edf8767537895f720063f9621299c2fe
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39239
content:
"In summary, climate change will not affect all the parts of the globe evenly. Rather, distinct regional patterns of \r\ntemperature and precipitation change can be identified, and these changes are projected to amplify as the level \r\nof global warming increases."


id: ac303a6f7dea1477efe923292d6e7bd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27541
content:
"FAQ 4.3, Figure 1 | Regional changes in temperature (left) and precipitation (right) are proportional to the level of global warming, \r\nirrespective of the scenario through which the level of global warming is reached. Surface warming and precipitation change are shown relative \r\nto the 1850-1900 climate, and for time periods over which the globally averaged surface warming is 1.5degC (top) and 3degC (bottom), respectively. Changes \r\npresented here are based on 31 CMIP6 models using the high-emissions scenario SSP3-7.0."


id: d2d43730cfe80870904748da9ffc1f8d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34442
content:
"Marcos H.  Costa (Brazil), Leticia Cotrim da Cunha (Brazil), Peter M.  Cox (United Kingdom), \r\nAlexey V. Eliseev (Russian Federation), Stephanie Henson (United Kingdom), Masao Ishii (Japan), \r\nSamuel Jaccard (Switzerland), Charles Koven (United States of America), Annalea Lohila (Finland), \r\nPrabir K.  Patra (Japan/India), Shilong Piao (China), Joeri Rogelj (United Kingdom/Belgium), \r\nStephen Syampungani (Zambia), Sonke Zaehle (Germany), Kirsten Zickfeld (Canada/Germany)"


id: e976fb8a1132d1e6883e2e65db4e182e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38429
content:
"Jean-Baptiste  Sallee  (France), Marielle Saunois (France), Edward  A.G.  Schuur (United States \r\nof America), Sonia I. Seneviratne (Switzerland), Ann Stavert (Australia), Parvadha Suntharalingam \r\n(United Kingdom/United States of America), Kaoru Tachiiri (Japan), Jens Terhaar (Switzerland/\r\nGermany), Rona Thompson (Norway, Luxembourg/New Zealand), Hanqin Tian (United States \r\nof America), Jocelyn Turnbull (New Zealand), Sergio M. Vicente-Serrano (Spain), Xuhui Wang \r\n(China), Rik Wanninkhof (United States of America), Philip Williamson (United Kingdom)"


id: b621f245d49531cb052d4d2590801328
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29262
content:
"Canadell, J.G., P.M.S. Monteiro, M.H. Costa, L. Cotrim da Cunha, P.M. Cox, A.V. Eliseev, S. Henson, M. Ishii, S. Jaccard, \r\nC. Koven, A. Lohila, P.K. Patra, S. Piao, J. Rogelj, S. Syampungani, S. Zaehle, and K. Zickfeld, 2021: Global Carbon and \r\nother Biogeochemical Cycles and Feedbacks. In Climate Change 2021: The Physical Science Basis. Contribution of \r\nWorking Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, \r\nV., P. Zhai, A. Pirani, S.L. Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, \r\nE. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekci, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, \r\nCambridge, United Kingdom and New York, NY, USA, pp. 673-816, doi:10.1017/9781009157896.007."


id: d0f7b8327992a4292cea8a0a016e6af8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34112
content:
"The CO2 emitted from human activities during the decade \r\nof 2010-2019 (decadal average 10.9 +-  0.9  PgC yr-1) was \r\ndistributed between three Earth system components: 46% \r\naccumulated in the atmosphere (5.1 +- 0.02 PgC yr-1), 23% was \r\ntaken up by the ocean (2.5 +- 0.6 PgC yr-1) and 31% was stored \r\nby vegetation in terrestrial ecosystems (3.4 +-  0.9  PgC yr-1) \r\n(high confidence). Of the total anthropogenic CO2 emissions, the \r\ncombustion of fossil fuels was responsible for 81-91%, with \r\nthe  remainder being the net CO2 flux from land-use change and \r\nland management (e.g., deforestation, degradation, regrowth after \r\nagricultural abandonment, and peat drainage). {5.2.1.2, 5.2.1.5; \r\nTable 5.1; Figures 5.5, 5.7, 5.12}"


id: 18b35a9e4063c3e3659154334a457c57
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1563
content:
"Over the past six decades, the average fraction \r\nof  anthropogenic CO2 emissions that has accumulated in \r\nthe atmosphere (referred to as the airborne fraction) has \r\nremained nearly constant at approximately 44%. The ocean and \r\nland sinks of CO2 have continued to grow over the past six decades \r\nin response to increasing anthropogenic CO2 emissions (high \r\nconfidence). Interannual and decadal variability of the regional and \r\nglobal ocean and land sinks indicate that these sinks are sensitive to \r\nclimate conditions and therefore to climate change (high confidence). \r\n{5.2.1.1, 5.2.1.2, 5.2.1.3, 5.2.1.4; Figures 5.7, 5.8, 5.10}"


id: 49d551fd8fc08263e9c4bb265865fa1d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10228
content:
"Recent observations show that ocean carbon processes are \r\nstarting to change in response to the growing ocean sink, \r\nand these changes are expected to contribute significantly to \r\nfuture weakening of the ocean sink under medium- to high\u0002emissions scenarios. However, the effects of these changes are not \r\nyet reflected in a weakening trend of the contemporary (1960-2019) \r\nocean sink (high confidence). {5.1.2, 5.2.1.3, 5.3.2.1; Figures  5.8, \r\n5.20; Cross-Chapter Box 5.3}"


id: c610561cfa35946c148369ef37685e6b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32157
content:
"Atmospheric concentration of CH4 grew at an average rate \r\nof 7.6 +- 2.7 ppb yr-1 for the last decade (2010-2019), with \r\na faster growth of 9.3 +- 2.4 ppb yr-1 over the last six years \r\n(2014-2019) (high confidence). The multi-decadal growth trend \r\nin atmospheric CH4 is dominated by anthropogenic activities (high \r\nconfidence), and the growth since 2007 is largely driven by emissions \r\nfrom both fossil fuels and agriculture (dominated by livestock) \r\n(medium confidence). The interannual variability is dominated by \r\nEl Nino-Southern Oscillation cycles, during which biomass burning \r\nand wetland emissions, as well as loss by reaction with tropospheric \r\nhydroxyl radical (OH) play an important role. {5.2.2; Figures  5.13, \r\n5.14; Table 5.2; Cross-Chapter Box 5.2}"


id: 7c9e6098720a8f617abc96418a29e2d5
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19123
content:
"It is unequivocal that the increase of CO2, CH4, and N2O in \r\nthe atmosphere over the industrial era is the result of human \r\nactivities (very high confidence). This assessment is based on \r\nmultiple lines of evidence including atmospheric gradients, isotopes, \r\nand inventory data. During the last measured decade, global average \r\nannual anthropogenic emissions of CO2, CH4, and N2O, reached the \r\nhighest levels in human history at 10.9 +- 0.9 petagrams of carbon \r\nper year (PgC yr-1, 2010-2019), 335-383 teragrams of methane per \r\nyear (TgCH4 yr-1, 2008-2017), and 4.2-11.4 teragrams of nitrogen \r\nper year (TgN yr-1, 2007-2016), respectively (high confidence). \r\n{5.2.1, 5.2.2, 5.2.3, 5.2.4; Figures 5.6, 5.13, 5.15}."


id: 1d647fd1ed555f131ec289bd7492747d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 2355
content:
"Atmospheric concentration of N2O grew at an average \r\nrate of 0.85 +-  0.03 ppb yr-1 between 1995 and 2019, with \r\na further increase to 0.95 +- 0.04 ppb yr-1 in the most recent \r\ndecade (2010-2019). This increase is dominated by anthropogenic \r\nemissions, which have increased by 30% between the 1980s and the \r\nmost recent observational decade (2007-2016) (high confidence). \r\nIncreased use of nitrogen fertilizer and manure contributed to about \r\ntwo-thirds of the increase during the 1980-2016 period, with the \r\nfossil fuels/industry, biomass burning, and wastewater accounting for \r\nmuch of the rest (high confidence). {5.2.3; Figures 5.15, 5.16, 5.17}"


id: 3516bcab82c62ee67c4c32075ba77c60
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6583
content:
"expected to increase land carbon accumulation in the high latitudes \r\n(not including permafrost) and also to lead to a counteracting loss of \r\nland carbon in the tropics (medium confidence, Figure 5.25). More \r\nthan half of the latest CMIP6 ESMs include nutrient limitations on \r\nthe  carbon cycle, but these models still project increasing tropical \r\nland carbon (medium confidence) and increasing global land carbon \r\n(high confidence) through the 21st century. {5.4.1, 5.4.3, 5.4.5; \r\nFigure 5.27; Cross-Chapter Box 5.1}"


id: 585082dc6dda14d828b78ade62cbe508
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12795
content:
"Future trajectories of the ocean CO2 sink are strongly \r\nemissions-scenario dependent (high confidence). Emissions \r\nscenarios SSP4-6.0 and SSP5-8.5 lead to warming of the surface ocean \r\nand large reductions of the buffering capacity, which will slow the \r\ngrowth of the ocean sink after 2050. Scenario SSP1-2.6 limits further \r\nreductions in buffering capacity and warming, and the ocean sink \r\nweakens in response to the declining rate of increasing atmospheric \r\nCO2. There is low confidence in how changes in the biological pump \r\nwill influence the magnitude and direction of the ocean carbon \r\nfeedback. {5.4.2, 5.4.4, Cross-Chapter Box 5.3}"


id: e064287482a1b5604f9ab3282ec459a1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36731
content:
"Ocean deoxygenation is projected to continue to increase with \r\nocean warming (high confidence). Earth system models (ESMs) \r\nproject a 32-71% greater subsurface (100-600 m) oxygen decline, \r\ndepending on the scenario, than reported in the Special Report on \r\nthe Ocean and Cryosphere (SROCC) for the period 2080-2099. This is \r\nattributed to the effect of larger surface warming in CMIP6 models, \r\nwhich increases ocean stratification and reduces ventilation (medium \r\nconfidence). There is low confidence in the projected reduction of \r\noceanic N2O emissions under high-emissions scenarios because \r\nof greater oxygen losses simulated in ESMs in CMIP6, uncertainties \r\nin the process of oceanic N2O emissions, and a  limited number of \r\nmodelling studies available. {5.3.3.2; 7.5}"


id: 9ffab32fd8085895792c14a92726ebff
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25362
content:
"Oceanic and terrestrial carbon sinks are projected to continue \r\nto grow with increasing atmospheric concentrations of CO2, \r\nbut the fraction of emissions taken up by land and ocean is \r\nexpected to decline as the CO2 concentration increases (high \r\nconfidence). ESMs suggest approximately equal global land and \r\nocean carbon uptake for each of the SSP scenarios. However, the range \r\nof model projections is much larger for the land carbon sink. Despite \r\nthe wide range of model responses, uncertainty in atmospheric CO2\r\nby 2100 is dominated by future anthropogenic emissions rather than \r\nuncertainties related to carbon-climate feedbacks (high confidence). \r\n{5.4.5; Figure 5.25, 5.26}"


id: 6d43bdbd234756ade833d419b8bc7215
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 16502
content:
"Thawing terrestrial permafrost will lead to carbon release \r\n(high confidence), but there is low confidence in the timing, \r\nmagnitude and the relative roles of CO2 versus CH4 as feedback \r\nprocesses. CO2 release from permafrost is projected to be 3-41 PgC \r\nper 1degC of global warming by 2100, based on an ensemble of models. \r\nHowever, the incomplete representation of important processes such \r\nas abrupt thaw, combined with weak observational constraints, \r\nonly allow low confidence in both the magnitude of these estimates \r\nand in how linearly proportional this feedback is to the amount of \r\nglobal warming. It is very unlikely that gas clathrates in terrestrial \r\nand subsea permafrost will lead to a detectable departure from the \r\nemissions trajectory during this century. {5.4.9; Box 5.1}"


id: fa360e8f01cfe9300df2fddc173d29df
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41390
content:
"Increases in atmospheric CO2 lead to increases in land carbon \r\nstorage through CO2 fertilization of photosynthesis and \r\nincreased water use efficiency (high confidence). However, \r\nthe overall change in land carbon also depends on land-use change \r\nand on the response of vegetation and soil to continued warming and \r\nchanges in the water cycle, including increased droughts in some \r\nregions that will diminish the sink capacity. Climate change alone is "


id: 84785987ab9d5015b4da22d10afa55ce
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20451
content:
"The net response of natural CH4 and N2O sources to future \r\nwarming will be increased emissions (medium confidence). \r\nKey processes include increased CH4 emissions from wetlands and \r\npermafrost thaw, as well as increased soil N2O emissions in a warmer \r\nclimate, while ocean N2O emissions are projected to decline at "


id: 75fd329943e6e48d47ebdfd16c044cb2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17983
content:
"centennial time scale. The magnitude of the responses of each \r\nindividual process and how linearly proportional these feedbacks \r\nare to the amount of global warming is known with low confidence \r\ndue to incomplete representation of important processes in models \r\ncombined with weak observational constraints. Models project that, \r\nover the 21st century, the combined feedback of 0.02-0.09 W m-2 degC-1\r\nis comparable to the effect of a  CO2 release of 5-18 petagrams \r\nof carbon equivalent per degC (PgCeq degC-1) (low confidence). {5.4.7, \r\n5.4.8; Figure 5.29}"


id: 36869d3a0d31e8af5718f82b9bf04245
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6824
content:
"improvements, resulting in larger, yet consistent estimates. {5.5.2, \r\n5.6; Figure 5.31; Table 5.8}"


id: 39269f5a9e06fe4314faf2416669883b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7263
content:
"The response of biogeochemical cycles to the anthropogenic \r\nperturbation can be abrupt at regional scales, and irreversible \r\non decadal to century time scales (high confidence). The \r\nprobability of crossing uncertain regional thresholds (e.g.,  high \r\nseverity fires, forest dieback) increases with climate change \r\n(high confidence). Possible abrupt changes and tipping points in \r\nbiogeochemical cycles lead to additional uncertainty in 21st century \r\nGHG concentrations, but these are very likely to be smaller than the \r\nuncertainty associated with future anthropogenic emissions (high \r\nconfidence). {5.4.9}"


id: 8f67e5ea1d4c9d44e91564e8e62a5777
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22443
content:
"Land- and ocean-based carbon dioxide removal (CDR) methods \r\nhave the potential to sequester CO2 from the atmosphere, \r\nbut the benefits of this removal would be partially offset by \r\nCO2 release from land and ocean carbon stores (very high \r\nconfidence). The fraction of CO2 removed that remains out of the \r\natmosphere, a measure of CDR effectiveness, decreases slightly with \r\nincreasing amount of removal (medium confidence) and decreases \r\nstrongly if CDR is applied at lower CO2 concentrations (medium \r\nconfidence). {5.6.2.1; Figures 5.32, 5.33, 5.34}"


id: 93eda91bb3f1ec1cb744d315c6b53449
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23230
content:
"The century-scale climate-carbon cycle response to a  CO2\r\nremoval from the atmosphere is not always equal and opposite \r\nto the response to a CO2 emission (medium confidence). For \r\nsimultaneously cumulative CO2 emissions and removals of greater \r\nthan or equal to 100 PgC, CO2 emissions are 4 +- 3% more effective \r\nat raising atmospheric CO2 than CO2 removals are at lowering \r\natmospheric CO2. The asymmetry originates from state-dependencies \r\nand non-linearities in carbon cycle processes and implies that an extra \r\namount of CDR is required to compensate for a positive emission of \r\na given magnitude to attain the same change in atmospheric CO2. \r\nThe net effect of this asymmetry on the global surface temperature \r\nis poorly constrained due to low agreement between models (low \r\nconfidence). {5.6.2.1; Figure 5.35}"


id: 810171edd8c0e156b23468204b9c9531
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19836
content:
"Mitigation requirements over this century for limiting \r\nmaximum warming to specific levels can be quantified using \r\na  carbon budget that relates cumulative CO2 emissions to \r\nglobal mean temperature increase (high confidence). For the \r\nperiod 1850-2019, a total of 655 +- 65 PgC (2390 +- 240 GtCO2, likely\r\nrange) of anthropogenic CO2 has been emitted. Remaining carbon \r\nbudgets (starting from 1 January 2020) for limiting warming to 1.5degC, \r\n1.7degC, and 2.0degC are 140 PgC (500 GtCO2), 230 PgC (850 GtCO2) and \r\n370  PgC (1350  GtCO2), respectively, based on the 50th percentile \r\nof TCRE. For the 67th percentile, the respective values are 110 PgC \r\n(400 GtCO2), 190 PgC (700 GtCO2) and 310 PgC (1150 GtCO2). These \r\nremaining carbon budgets may vary by an estimated +-  60  PgC \r\n(220 GtCO2) depending on how successfully future non-CO2 emissions \r\ncan be reduced. Since AR5 and the Special Report on Global Warming \r\nof 1.5degC (SR1.5), estimates have undergone methodological "


id: d01071ace7109c3bee5a2da865dc68d1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33959
content:
"Wide-ranging side effects of CDR methods have been \r\nidentified that can either weaken or strengthen the carbon \r\nsequestration and cooling potential of these methods and \r\naffect the achievement of sustainable development goals \r\n(high confidence). Biophysical and biogeochemical side effects \r\nof CDR methods are associated with changes in surface albedo, "


id: b79f66b1db47af1f25ac9aa0b36f8d35
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29518
content:
"Solar radiation modification (SRM) would increase the global \r\nland and ocean CO2 sinks (medium confidence) but would not \r\nstop CO2 from increasing in the atmosphere, thus exacerbating \r\nocean acidification under continued anthropogenic emissions \r\n(high confidence). SRM acts to cool the planet relative to \r\nunmitigated climate change, which would increase the land sink by \r\nreducing plant and soil respiration and slow the reduction of ocean \r\ncarbon uptake due to warming (medium confidence). SRM would not \r\ncounteract or stop ocean acidification (high confidence). The sudden \r\nand sustained termination of SRM would rapidly increase global \r\nwarming, with the return of positive and negative effects on the \r\ncarbon sinks (very high confidence). {4.6.3; 5.6.3}"


id: 248c6f83dbdc7c219e6cef933238508e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3623
content:
"2020). This emphasizes the central role of terrestrial and ocean CO2\r\nsinks in regulating its atmospheric concentration (Ballantyne et al., \r\n2012; W. Li et al., 2016; Le Quere et al., 2018a; Ciais et al., 2019; \r\nGruber et al., 2019b; Friedlingstein et al., 2020)."


id: f194f60b3ea4a3fc1044778000bc3ff
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39887
content:
"The physical and biogeochemical controls of greenhouse gases \r\n(GHGs) is a  central motivation for this chapter, which identifies \r\nbiogeochemical feedbacks that have led or could lead to a  future \r\nacceleration, slowdown or abrupt transitions in the rate of GHG \r\naccumulation in the atmosphere, and therefore of climate change. \r\nA  characterization of the trends and feedbacks lead to improved \r\nquantification for the remaining carbon budgets for climate \r\nstabilization, and the responses of the carbon cycle to atmospheric \r\ncarbon dioxide removal (CDR), which is embedded in many of the \r\nmitigation scenarios, to achieve the goals of the Paris Agreement."


id: a3427013a2f0a46dc5edd4b845f8e74c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25933
content:
"The chapter covers three dominant GHGs in the human perturbation \r\nof the Earth's radiation budget for which high-quality records exist: \r\nCO2, CH4 and N2O (Figure 5.1)."


id: dd9099d250da69fae8adf1cbf1cb5f3e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36245
content:
"Section 5.1 (this section) provides the time context on how unique \r\ncurrent and future scenarios of GHGs atmospheric concentrations \r\nand growth rates are in the Earth's history. It also introduces the \r\nmain processes involved in carbon-climate feedbacks, followed by \r\nan assessment of what can be learned from the paleo record towards \r\na  better understanding of contemporary and future GHGs-climate \r\ndynamics and their response to different mitigation trajectories."


id: b6f6e212af3e14220172fcd8805ada3b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29402
content:
"Section  5.2 covers the state of the carbon cycle and other \r\nbiogeochemical cycles, and global budgets of CO2, CH4 and N2O for the \r\nindustrial era (since 1750). The section emphasizes the last 60-year \r\nperiod for which high-resolution observations are available and the \r\nmost recent decade for comprehensive GHG budgets. Significant \r\nadvances have taken place since the IPCC Fifth Assessment Report \r\n(AR5), particularly in constraining the annual-to-decadal variability \r\nof the ocean and land carbon sources and sinks, and in revealing the \r\nsensitivity of carbon pools to current and future climate changes. There \r\nhas been an important increase in modelling capability of the three \r\nGHGs, for land and oceans, atmospheric and ocean observations, and "


id: 207f26fe1d267d80670a2b1502c3d8a3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 2938
content:
"remote sensing products that have enabled researchers to constrain \r\nthe causes of the observed trends and variability."


id: 3626ed276eec8157feb504462dadc026
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6776
content:
"Section 5.3 builds on the Special Report on the Ocean and Cryosphere \r\n(SROCC) covering the change in ocean acidification due to oceanic \r\nCO2 uptake across the paleo, historical periods and future projections \r\nusing Coupled Model Intercomparison Project Phase 6  (CMIP6), \r\nwith consequences for marine life (assessed in the Sixth Assessment \r\nReport Working Group II, AR6 WGII) and biogeochemical cycles. The \r\nsection also assesses changes in deoxygenation of the oceans due to \r\nwarming, increased stratification of the surface ocean, and slowing \r\nof the meridional overturning circulation."


id: c5a441e00a091426ea816a0bee333b57
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32077
content:
"Section  5.4 covers the future projections of biogeochemical cycles \r\nand their feedbacks to the climate system fully utilizing the database \r\nof the concentration-driven CMIP6. Since AR5, Earth system models \r\n(ESMs) have made progress towards including more complex carbon \r\ncycle and associated biogeochemical processes that enable exploring \r\na  range of possible future carbon-climate feedbacks and their \r\ninfluences on the climate system. The section addresses uncertainties \r\nand limits of our models to predict future dynamics for GHG emissions \r\ntrajectories, as well as new understanding on processes involved in \r\ncarbon-climate feedbacks and the possibility for rapid and abrupt \r\nchanges brought by non-linear dynamics."


id: e193c2ca65eeabaaad5f6e674988e021
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36956
content:
"Section  5.5 covers the development of the total and remaining \r\ncarbon budgets to climate stabilization targets and the associated \r\ntransient climate response to cumulative CO2 emissions. The section \r\nshows the progress made since AR5 (IPCC, 2013a) and the Special \r\nReport on Global Warming of 1.5degC (IPCC, 2018), particularly on \r\nkey components required to estimate the remaining carbon budget, \r\nincluding the transient response to cumulative emissions of CO2, the \r\nzero emissions commitment, the projected non-CO2 warming, and \r\nthe unrepresented Earth system feedbacks."


id: 5262d5ef87dfcff144d55bf42a7c1f07
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11773
content:
"Section  5.6 assesses the impacts of CDR and solar radiation \r\nmodification for the purpose of climate change mitigation on the \r\nglobal carbon cycle, building from the assessment in the IPCC Special \r\nReport on Climate Change and Land (SRCCL). It includes an overview \r\nof the major CDR options and potential collateral biogeochemical \r\neffects beyond the intended climate change mitigation strategies. \r\nThe potential capacity to deliver atmospheric reductions and the \r\nsocio-economic feasibility of such options are assessed in detail in \r\nAR6 working group III (WGIII)."


id: e06b151f7a91e9c3fd7a8d762d81315a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36733
content:
"Finally, Section 5.7 highlights the knowledge gaps as limits to the \r\nassessment. The assessment would have been strengthened had \r\nthose gaps not existed."


id: 3cfba93b09aa7cca50b0a8f12aae9ced
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7906
content:
"Positive and negative climate and carbon feedbacks involve: (i) fast \r\nprocesses on land and oceans at time scales from minutes to years, \r\nsuch as photosynthesis, soil respiration, net primary production, \r\nshallow ocean physics and air-sea fluxes; and (ii) slower processes \r\ntaking from decades to millennia, such as changing ocean buffering \r\ncapacity, ocean ventilation, vegetation dynamics, permafrost \r\nchanges, peat formation and decomposition (Figure 5.2; Ciais et al., \r\n2013; Forzieri et al., 2017; Williams et al., 2019). Depending on the \r\nparticular combination of driver process and response dynamics, \r\nthey behave as positive or negative feedbacks that amplify or "


id: 6344606368ab0163197aa78fe5a75bc6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14758
content:
"dampen the magnitude and rates of climate change, respectively \r\n(Cox et al., 2000; Friedlingstein et al., 2003, 2006; Hauck and Volker, \r\n2015; Williams et al., 2019); red and turquoise arrows in Figure 5.2 \r\nand Table 5.1)."


id: 5d273af4aa097bea26358a239e4ffd91
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13664
content:
"global warming, which is used as the basis to estimate the remaining \r\ncarbon budget (Section  5.5; MacDougall and Friedlingstein, \r\n2015; MacDougall, 2017; Bronselaer and Zanna, 2020; Jones and \r\nFriedlingstein, 2020). There is still low confidence on the relative \r\nroles and importance of the ocean and terrestrial carbon processes \r\non TCRE variability and uncertainty on centennial time scales \r\n(MacDougall, 2016; MacDougall et al., 2017; N.L.  Williams et al., \r\n2017; Katavouta et al., 2018, 2019; Jones and Friedlingstein, 2020) \r\n(Sections 5.5.1.1, 5.5.1.2)."


id: e4cd3fa887dcc25d48f28905a3d03469
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37536
content:
"Carbon cycle feedbacks co-exist with climate (heat and moisture) \r\nfeedbacks (Cross-Chapter Boxes 5.1 and 5.3), which together drive \r\ncontemporary (Section 5.2) and future (Section 5.4) carbon-climate \r\nfeedbacks (Williams et al., 2019). The excess heat generated by \r\nradiative forcing from increasing concentration of atmospheric \r\nCO2 and other GHGs is mostly taken up by the ocean (>90%) and \r\nthe residual balance partitioned between atmospheric, terrestrial \r\nand ice melting (Cross-Chapter Box 9.2; Frolicher et al., 2015). The \r\ncombined effect of these two large-scale negative feedbacks of CO2\r\nand heat are reflected in the TCRE (Section 5.5 and Cross-Chapter \r\nBox  5.3), which points to a  quasi-linear and quasi-emission-path \r\nindependent relationship between cumulative emissions of CO2 and "


id: e451156f7720e888d1c6b62864b66a17
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37467
content:
"The combined effects of climate and CO2 concentration feedbacks \r\non the global carbon cycle are projected by ESMs to modify both the \r\nprocesses and natural reservoirs of carbon on a regional and global \r\nscale that may result in positive feedbacks (red arrows in Figure 5.2), \r\nwhich could weaken the major terrestrial and ocean sinks and disrupt \r\nthe airborne fraction and TCRE under medium- to high-emissions \r\nscenarios (Section 5.4.5 and Figure 5.25)."


id: 16b0802332aeeb2223cf09fa75cf967a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1201
content:
"Paleoclimatic proxy records extend beyond the variability of recent \r\ndecadal climate oscillations and thus provide an independent \r\nperspective on feedbacks between climate and carbon cycle \r\ndynamics. According to reconstructions, these past changes were \r\nslower than the current anthropogenic ones, so they cannot provide \r\nan unequivocal comparison. Nonetheless, they can help appraise \r\nsensitivities and point towards potentially dominant mechanisms \r\nof change (Tierney et al., 2020) on (sub)centennial to (multi)\r\nmillennial time scales."


id: c9705407e0ab4333deb2a2e525bf77c3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32765
content:
"Quantifying past changes in the rate of CO2 accumulation in the \r\natmosphere based on reconstructions using marine sediment \r\nproxies is complex as age model uncertainties, assumptions and \r\nshortcomings underlying proxy applications and sedimentary \r\nprocesses conspire to alter and confound rate estimates (Ajayi et al., \r\n2020). Differential sediment mixing and bioturbation contribute \r\nto smooth and attenuate proxy records (Hupp and Kelly, 2020), \r\nthereby tending to underestimate maximum rates of change (Kemp \r\net al., 2015). Considering the extent to which uncertainties can affect \r\nsediment-based rate estimates, and notwithstanding recent effort \r\nin minimizing their inherent contribution, there is generally low to \r\nmedium confidence in quantifying rates of change on a time scale less \r\nthan a decade back thousands of years, and less than a millennium \r\nback millions of years in the past based on marine sediments."


id: 4e40c4086ed44de544da924a955c867d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11038
content:
"The AR5 (WGI, Chapter 5) concluded with medium confidence that \r\natmospheric CO2 concentrations reached 350-450  ppm during \r\nthe mid-Pliocene (3.3-3.0  million years ago (Ma)), and possibly \r\n1000  ppm during the Early Eocene (52-48  Ma). The AR5 (WGI, \r\nChapter 5) also concluded with very high confidence that the current \r\nrates of increases in CO2, CH4 and N2O atmospheric concentrations \r\nwere unprecedented with respect to the ice core record covering the \r\nlast deglacial transition (LDT, 18-11 ka) and with medium confidence\r\nthat the rate of change of the reconstructed GHG rise was also \r\nunprecedented compared to the lower resolution of the records of \r\nthe past 800 kyr."


id: dd24db9b83ab2a23f6c7ca130d0b695e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36171
content:
"In the past, atmospheric CO2 concentrations reached much higher \r\nlevels than present day (Cross-Chapter Box  2.1 and Figure  5.3). \r\nIn  particular, the Paleocene-Eocene thermal maximum (PETM), \r\n55.9-55.7 Ma (Figure 5.3), provides some level of comparison with \r\nthe current and projected anthropogenic increase in CO2 emissions \r\n(Chapter 2). Atmospheric CO2 concentrations increased from about \r\n900 to around 2000 ppm in 3-20 kyr as a result of geological carbon "


id: 3be46570218429ab03c796fba1efee81
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7731
content:
"ice cores represent the only climatic archive from which past GHG \r\nconcentrations can be directly measured. Major GHGs, CH4, N2O and \r\nCO2 generally co-vary on orbital time scales (Loulergue et al., 2008; \r\nLuthi et al., 2008; Schilt et al., 2010b; Chapter 2), with consistently \r\nhigher atmospheric concentrations during warm intervals of the past, \r\npointing to a  strong sensitivity to climate (Figure  5.4). Modelling \r\nwork suggests that the carbon cycle contributed to globalise \r\nand amplify changes in orbital forcing, which are pacing glacial-\r\ninterglacial climate oscillations (Ganopolski and Brovkin, 2017), \r\nwith ocean biogeochemistry and physics, terrestrial vegetation, \r\npeatland, permafrost and exchanges with the lithosphere including \r\nchemical weathering, volcanic activity, sediment burial and marine \r\ncalcium carbonate compensation all playing a role in modulating the \r\nconcentration of atmospheric GHGs."


id: 9f11e84b407cea7621967fae43a8e471
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25209
content:
"Since AR5, the number of ice core records and the temporal resolution \r\nof their data for the last 800 kyr have improved, in particular for the \r\nlast 60  kyr. Additionally, the advent of isotopic measurements on \r\nGHGs extracted from air trapped in ice, allows for more robust source \r\napportionments and inventory assessments. Therefore, the ensuing \r\ndiscussion focuses on these two specific aspects."


id: b8745f7ad3d006cdf79b0476f37d1d6d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29663
content:
"The last 50 Myr (50  million years) have been characterized by \r\na  gradual decline in atmospheric CO2 levels at a  rate of about \r\n16 ppm Myr-1 (Figure 5.3; Foster et al., 2017; Gutjahr et al., 2017). \r\nThe exact cause of this long-term change in CO2 remains uncertain, \r\nbut may be related to an imbalance between long-term sources of \r\nCO2 (volcanic outgassing) and long-term sinks (organic carbon burial \r\nand silicate weathering)."


id: c1f71a1ad4b637152bbc3c4afd269266
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31423
content:
"Major pre-industrial sources of CH4 comprise wetlands (including \r\nsubglacial environments) and biomass burning (Bock et al., 2010, \r\n2017; Lamarche-Gagnon et al., 2019; Kleinen et al., 2020). Pre\u0002industrial atmospheric N2O concentrations were regulated by \r\nmicrobial production in marine and terrestrial environments and \r\nby photochemical removal in the stratosphere (Schilt et al., 2014; \r\nBattaglia and Joos, 2018b; H.  Fischer et al., 2019). Pre-industrial \r\natmospheric CO2 concentrations were largely regulated by exchange \r\nwith exogenic terrestrial and ocean carbon reservoirs. The imbalance \r\nbetween geological sources and sinks in the ocean-atmosphere-land \r\nbiosphere system additionally plays an important role in modulating \r\nthe air-sea partitioning of the active carbon inventory on multi\u0002millennial time scales (Cartapanis et al., 2018)."


id: 23e0cc47e99cb619c5aaffc4d603b6a8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3500
content:
"The most recent time interval when atmospheric CO2 concentration \r\nwas as high as 1000  ppm (i.e.,  similar to the end of 21st century \r\nprojection for the high-end emissions scenario RCP8.5) was around \r\n33.5 Ma, prior to the Eocene-Oligocene transition (Y.G. Zhang et al., \r\n2013; Anagnostou et al., 2016). Atmospheric CO2 levels then reached \r\na critical threshold (1000-750 ppm; DeConto et al., 2008) to allow \r\nfor the development of permanent regional ice sheets on Antarctica, \r\nassociated with changes in Southern Ocean hydrography, which \r\nwould have increased deep ocean CO2 storage (Leutert et al., 2020)."


id: b5fb6cc0c7b7867c2650a9e8976e325e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29239
content:
"Model-based estimates indicate that wetland CH4 emissions were \r\nreduced by 24-40% during the Last Glacial Maximum (LGM) when \r\ncompared to pre-industrial, while CH4 emissions related to biomass \r\nburning (wildfires) decreased by 35-75% (Valdes et al., 2005; Hopcroft \r\net al., 2017; Kleinen et al., 2020). N2O emissions decreased by about \r\n30% during the LGM based on data-constrained model estimates \r\n(Schilt et al., 2014; H.  Fischer et al., 2019) owing to a  combination \r\nof a  weaker hydrological cycle and a  generally better ventilated \r\nintermediate depth ocean relative to present, reducing (de)nitrification \r\nprocesses (Galbraith et al., 2013; H. Fischer et al., 2019)."


id: 98da6f433788c830ff50194d8056384d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24111
content:
"The most recent interval characterized by atmospheric CO2 levels \r\nsimilar to modern (i.e.,  360-420  ppm) was the mid-Pliocene Warm \r\nPeriod (MPWP, 3.3-3.0 Ma; Martinez-Boti et al., 2015; de la Vega et al., \r\n2020) (Chapter 2). The relatively high atmospheric CO2 concentration \r\nduring the MPWP are related to vigorous ocean circulation and \r\na rather inefficient marine biological carbon pump (Burls et al., 2017), \r\nwhich would have reduced deep ocean carbon storage. After the \r\nMPWP, atmospheric CO2 concentrations declined gradually at a rate \r\nof 30 ppm Myr-1 (Figure 5.3; de la Vega et al., 2020), as an increase in \r\nocean stratification led to enhanced ocean carbon storage, allowing for \r\nmajor, sustained advances in Northern Hemisphere ice sheets, 2.7 Ma \r\n(Sigman et al., 2004; DeConto et al., 2008)."


id: 46f455f42753ba51b8c8de63da3a5c6d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9685
content:
"During past ice ages, generally colder and drier climate conditions \r\ncontributed to a  substantial decline of the land biosphere carbon \r\ninventory, in particular in boreal peatlands (-300  PgC; Treat et al., \r\n2019). Estimates assessing the glacial decrease in the global terrestrial \r\nbiosphere carbon stock vary between -300 and -600 PgC (Ciais et al., \r\n2012; Peterson et al., 2014; Menviel et al., 2017; Kleinen et al., 2020), \r\npossibly -850 PgC when accounting for ocean-sediment interactions \r\nand burial (Jeltsch-Thommes et al., 2019), a considerable contraction \r\nwhen compared to the modern land biosphere stock. The large range \r\nof estimates reflects a  yet limited understanding of how carbon "


id: f081cc4988ebe7e0c5ff6b8586c2d640
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39692
content:
"The Antarctic ice core record covering the past 800  kyr provides \r\nan important archive to explore the carbon-climate feedbacks \r\nprior to anthropogenic perturbations (Brovkin et al., 2016). Polar "


id: 1e13b426a8684227a28c523b287800e9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 2486
content:
"and N2O emissions were reduced under glacial climate conditions. \r\nMultiple lines of evidence indicate with high confidence that \r\nenhanced storage of remineralized CO2 in the ocean interior, owing \r\nto a combination of synergistic mechanisms, was sufficient to balance \r\nthe removal of carbon from the atmosphere and the terrestrial \r\nbiosphere reservoirs combined during the last ice age."


id: 91570f179b32ff6967021c53fe7c4006
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22773
content:
"Vegetation regrowth and increased precipitation in wetland \r\nregions associated with the mid-deglacial Northern Hemisphere \r\nwarming (referred to as the Bolling/Allerod (B/A) warm interval, \r\n14.7-12.7 ka), in particular in the (sub)tropics, accounts for large \r\nincreases in both CH4 and N2O emissions to the atmosphere \r\n(Baumgartner et al., 2014; Schilt et al., 2014; Bock et al., 2017; \r\nH. Fischer et al., 2019). Specifically, changes in CH4 sources were \r\nsteered by variations in vegetation productivity, source size area, \r\ntemperatures and precipitation as modulated by insolation, local \r\nsea level changes and monsoon intensity (Bock et al., 2017; \r\nKleinen et al., 2020). Changes in the CH4 atmospheric sink term \r\nprobably only played a secondary role in modulating atmospheric \r\nCH4 inventories across the LDT (Hopcroft et al., 2017; Kleinen et al., "


id: fab6809c09531fc1d87b802440ebdfae
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41487
content:
"2020) Geological emissions, related to the destabilization of fossil \r\n(radiocarbon-dead) CH4 sources buried in continental margins \r\nas a  result of sudden warming, appear small (Bock et al., 2017; \r\nPetrenko et al., 2017; Dyonisius et al., 2020). Stable isotope analysis \r\non N2O extracted from Antarctic and Greenland ice reveal that \r\nmarine and terrestrial emissions increased by 0.7 +-  0.3 and 1.7 \r\n+-  0.3 TgN, respectively, across the LDT (H.  Fischer et al., 2019). \r\nDuring abrupt Northern Hemisphere warmings, terrestrial emissions \r\nresponded rapidly to the northward displacement of the Intertropical \r\nConvergence Zone (ITCZ) associated with the resumption of the \r\nAtlantic meridional overturning circulation (AMOC; H. Fischer et al., \r\n2019). About 90% of these step increases occurred rapidly, possibly \r\nin less than 200 years (H. Fischer et al., 2019). In contrast, marine \r\nemissions increased more gradually, modulated by global ocean \r\ncirculation reorganization."


id: 908931a1f1464bea38bd73927b42f460
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22637
content:
"Atmospheric CO2 led reconstructed global average temperature by \r\nseveral centuries (Shakun et al., 2012), corroborating the importance \r\nof CO2 as an amplifier of orbitally driven warming. During the LDT, \r\nthe phasing between Antarctic air temperature and atmospheric \r\nGHG concentration changes was nearly synchronous, yet variable, \r\nowing to the complex nature of the mechanisms modulating the \r\nglobal carbon cycle (Chowdhry Beeman et al., 2019). Mean ocean \r\ntemperature reconstructions, based on noble gas extracted from \r\nAntarctic ice are closely correlated with Antarctic air temperature \r\nand pCO2 records, emphasizing the role the Southern Ocean is \r\nplaying in modulating global climate variability (Bereiter et al., \r\n2018; Baggenstos et al., 2019)."


id: 27cebbab4394110e82ed5e40bd830e8f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4194
content:
"Enhanced mid-ocean ridge magmatism and/or hydrothermal activity \r\nmodulated by sea level rise has recently been hypothesized to have \r\ncontributed to the deglacial CO2 rise (Crowley et al., 2015; Lund \r\net al., 2016; Huybers and Langmuir, 2017; Stott et al., 2019b). While \r\ngeological carbon release may have affected the ocean's radiocarbon \r\nbudget (Ronge et al., 2016; Rafter et al., 2019; Stott et al., 2019a), \r\nmodel results suggest that the potential contribution of geological \r\ncarbon sources to the atmosphere remained small (Roth and Joos, \r\n2012; Hasenclever et al., 2017)."


id: 3135095cac3f6cfd8cadaa2f8ded02cd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5909
content:
"Simulations of Earth models of intermediate complexity (EMIC) with \r\ncoupled glacial-interglacial climate and the carbon cycle were able to \r\nreproduce first-order changes in the atmospheric CO2 content for the \r\nfirst time in recent years (Ganopolski and Brovkin, 2017; Khatiwala \r\net al., 2019). The most important processes accounting for the full \r\ndeglacial CO2 amplitude in the models include solubility changes, \r\nchanges in oceanic circulation and marine carbonate chemistry. The \r\neffect of the terrestrial carbon cycle, variable volcanic outgassing \r\nand the temperature dependence on the oceanic remineralization \r\nlength scale contribute less than 15 ppm CO2 between the glacial \r\nand interglacial intervals of the cycles. However, details in the \r\nsimulated response of the marine carbon cycle and atmospheric CO2\r\nconcentrations to changes in ocean circulation depend to a  large \r\ndegree on model parametrization (Gottschalk et al., 2019)."


id: c6fcabd40800cc19951dcb96f5b75138
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32318
content:
"Independent paleoclimatic evidence suggests with high confidence\r\nthat marine and terrestrial CH4 and N2O emissions are highly sensitive \r\nto climate on (sub)centennial time scales. Limited, yet internally \r\nconsistent ice core measurements indicate with medium confidence\r\nthat pulsed geologic CH4 release from continental margins associated \r\nwith warming remained negligible across the LDT. Multiple lines of \r\nevidence suggest with high confidence that CO2 was released from the \r\nocean interior on centennial time scales during the LDT in response \r\nto, or associated with warming, contributing to the transition out of \r\nthe last glacial stage to the current interglacial period."


id: 3985bc15ffef9f201ec48d30240433c0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7332
content:
"Multiple lines of evidence inferred from marine sediment proxies \r\nindicate with low to medium confidence that the millennial rates of \r\nCO2 concentration change in the atmosphere during the last 56 Myr \r\nwere at least four to five times lower than during the last century \r\n(Figure  5.3). In spite of uncertainties in ice core reconstructions \r\nrelated to delayed enclosure of air bubbles, which tend to smooth \r\nthe records, there is high confidence that the rates of atmospheric \r\nCO2 and CH4 change during the last century were at least 10 and 5 "


id: 435439cb1655d3ed3a6b0b14b87f6daa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9060
content:
"times faster, respectively, than the maximum centennial growth rate \r\naverages of those gases during the last 800 kyr (Fig. 5.4).\r\n5.2 "


id: 21ab7f868302888120405518ee6ac736
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3135
content:
"This section assesses the trends and variability in atmospheric \r\naccumulation of the three main greenhouse gases (GHGs) -  CO2, \r\nCH4 and N2O - their ocean and terrestrial sources and sinks as well \r\nas their budgets during the Industrial Era (1750-2019). Emphasis is \r\nplaced on the more recent contemporary period (1959-2019) where \r\nunderstanding is increasingly better constrained by atmospheric, \r\nocean and land observations. The section also assesses our increased \r\nunderstanding of the anthropogenic forcing and processes driving \r\nthe trends, as well as how variability at the seasonal to decadal \r\nscales provide insights on the mechanism governing long-term \r\ntrends and emerging biogeochemical-climate feedbacks with their \r\nregional characteristics."


id: d382f7a571562595a66aac91c0c67ff7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34550
content:
"Fossil CO2 emissions have grown continuously since the beginning \r\nof the industrial era (Figure  5.5) with short intermissions due to \r\nglobal economic crises or social instability (Peters et al., 2012; \r\nFriedlingstein et al., 2020). In the most recent decade (2010-2019), \r\nfossil CO2 emissions reached an average 9.6 +-  0.5  PgC yr-1 and \r\nwere responsible for 86% of all anthropogenic CO2 emissions. In \r\n2019, fossil CO2 emissions were estimated to be 9.9 +- 0.5 PgC yr-1\r\nexcluding carbonation (Friedlingstein et al., 2020), the highest on \r\nrecord. These estimates exclude the cement carbonation sink of \r\naround 0.2 PgC yr-1. Fossil CO2 emissions grew at 0.9% yr-1 in the \r\n1990s, increasing to 3.0% yr-1 in the 2000s, and reduced to 1.2% \r\nfrom 2010 to 2019. The slower growth in fossil CO2 emissions in \r\nthe last decade is due to a  slowdown in growth from coal use. "


id: c06e2e9f15432cf15ae2f191c2606f92
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31154
content:
"occurring due to interannual variability or trends in environmental \r\nconditions (in particular, climate, CO2, and nutrient deposition) \r\n(Houghton, 2013)."


id: a454a5fc30f969a64551823dd1d6c52b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26115
content:
"The global net flux from land-use change and land management \r\nis composed of carbon fluxes from land-use conversions, land \r\nmanagement and changes therein (Pongratz et al., 2018) and is \r\nequivalent to the LULUCF fluxes from the agriculture, forestry and \r\nother land use (AFOLU) sector (Jia et al., 2019). It consists of gross \r\nemissions (loss of biomass and soil carbon in clearing or logging, \r\nharvested product decay, emissions from peat drainage and \r\nburning, degradation) and gross removals (CO2 uptake in natural \r\nvegetation regrowing after harvesting or agricultural abandonment, \r\nafforestation). The LULUCF flux relates to direct human interference \r\nwith terrestrial vegetation, as opposed to the natural carbon fluxes "


id: 66031fa74215b75bf39b4a47724bdeb0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15206
content:
"Land-use-related component fluxes can be verified by the growing \r\ndatabases of global satellite-based biomass observations in \r\ncombination with information on remotely sensed land cover change. "


id: 248a8c96d59136a06b7bd5b26727924f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3620
content:
"pre-industrial times (Erb et al., 2018; see also Section 5.1.2.3). Low \r\nconfidence is assigned to pre-industrial emissions estimates."


id: 2bd372edbc7827de3706c32c58f4a544
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4964
content:
"However, they differ from bookkeeping and modelling with Dynamic \r\nGlobal Vegetation Models (DGVMs) in excluding legacy emissions \r\nfrom pre-satellite-era land-use change and land management, and \r\nneglecting soil carbon changes, often focusing on gross deforestation, \r\nnot regrowth (Jia et al., 2019)."


id: 661774ba3a13fc2d8320ea74b7129b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15224
content:
"Since AR5, evidence emerged that the LULUCF flux might have been \r\nunderestimated as DGVMs include anthropogenic land cover change, \r\nbut often ignore land management practices not associated with \r\na change in land cover; land management is more widely captured \r\nby bookkeeping models through use of observation-based carbon \r\ndensities (Ciais et al., 2013; Pongratz et al., 2018). Sensitivity studies \r\nshow that practices such as wood and crop harvesting increase \r\nglobal net LULUCF emissions (Arneth et al., 2017) and explain about \r\nhalf of the cumulative loss in biomass (Erb et al., 2018)."


id: abfa2116b8eafa8a8d4dd7b8333601de
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27498
content:
"Gross emissions are on average two to three times larger than the net \r\nflux from LULUCF, increasing from an average of 3.5 +- 1.2 PgC yr-1 for \r\nthe decade of the 1960s to an average of 4.4 +- 1.6 PgC yr-1 during \r\n2010-2019 (Friedlingstein et al., 2020). Gross removals partly \r\nbalance these gross emissions to yield the net flux from LULUCF and \r\nincrease from -2.0 +- 0.7 PgC yr-1 for the 1960s to -2.9 +- 1.2 PgC yr-1\r\nduring 2010-2019. These large gross fluxes show the relevance of \r\nland management, such as harvesting or rotational agriculture, and \r\nthe large potential to reduce emissions by halting deforestation \r\nand degradation."


id: 5a7ff0beeec6a3a6fcfcc1fa0b765325
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13176
content:
"Over the past six decades, the fraction of anthropogenic CO2\r\nemissions that has accumulated in the atmosphere (referred to as \r\nairborne fraction) has remained near constant at approximately \r\n44% (Figure 5.7) (Ballantyne et al., 2012; Ciais et al., 2019; Gruber \r\net al., 2019b; Friedlingstein et al., 2020). This suggests that the land \r\nand ocean CO2 sinks have continued to grow at a  rate consistent \r\nwith the growth rate of anthropogenic CO2 emissions, albeit with \r\nlarge interannual and sub-decadal variability dominated by the land \r\nsinks (Figure 5.7)."


id: 6a0c49fe665e24e09c8e98fe6af87ff8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15930
content:
"Since AR5, an alternative observable diagnostic to the airborne \r\nfraction has been proposed to understand the trends in land and \r\nocean sinks in response to its driving atmospheric CO2 concentrations \r\n(Raupach et al., 2014; Bennedsen et al., 2019). It is the sink rate \r\nthat is defined as the combined ocean and land sink flux per unit of \r\natmospheric excess of CO2 above pre-industrial levels (Raupach et al., "


id: ef0ed202d40011f24f500c719133d108
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39428
content:
"(1960-2018), air-sea fluxes and storage of anthropogenic CO2 are \r\nlargely influenced by atmospheric CO2 concentrations, physical \r\nocean processes and physicochemical carbonate chemistry, which \r\ndetermines the unique properties of CO2 in seawater (Chapter 9 and \r\nCross-Chapter Box  5.3; Wanninkhof, 2014; DeVries et al., 2017; \r\nMcKinley et al., 2017, 2020, Gruber et al., 2019a, b; Hauck et al., \r\n2020). Here we assess three different approaches (Figures  5.8a,b \r\nand 5.9) that together provide high confidence that, during the \r\nhistorical period (1960-2018), the ocean carbon sink (Socean) and its \r\nassociated ocean carbon storage have grown in response to global \r\nanthropogenic CO2 emissions (Gruber et al., 2019a; Hauck et al., \r\n2020; McKinley et al., 2020)."


id: a3a37e4ce6db61f18db73371f2d0906c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25993
content:
"SROCC Section  5.2.2.3.2; Bates et al., 2014; Sutton et al., 2016; \r\nFassbender et al., 2017; Landschutzer et al., 2018; Jiang et al., 2019). \r\nA recent model-based study suggests that re-emergence of previously \r\nstored anthropogenic CO2 is changing the buffering capacity of the \r\nmixed layer and reducing the ocean sink for anthropogenic CO2\r\nduring the historical period (Rodgers et al., 2020). This trend is \r\nnot reflected in observations-based products (Figure  5.8a), so we \r\nattribute a low confidence."


id: ea3e4b1427ef4b0db85c381fb13cbcc0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38567
content:
"The second assessment approach makes use of six independent \r\nmethods to constrain the mean decadal ocean sink over the period \r\n1990-2019 (Figure  5.8b). This provides a  multi-decadal advance \r\non the 1990-1999 decadal constraint from (Denman et al., 2007) \r\nthat has been widely used as a model constraint for GOBMs used \r\nfor the global carbon budget (Hauck et al., 2020). The medium \r\nconfidence attributed by this assessment of the global multi-decadal \r\ntrend (Figure  5.8a) is further supported by the broad agreement \r\nin magnitude and trend of the decadal mean ocean CO2 uptake \r\nwith assessments that also include additional observations-based, \r\nindependent methods such as ocean CO2 inversion and atmospheric \r\nCO2 and O2/N2 measurements (Figure 5.8b; Supplementary Materials \r\nTables 5.SM.1 and 5.SM.2)."


id: 28bd5604947e47c021368cecb3dc08c3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4382
content:
"also be a factor amplifying the global decadal perturbation of the \r\n1990s (Gloege et al., 2021). Therefore, while there is high confidence\r\nin the 1990s hiatus of the global ocean sink for anthropogenic CO2, \r\nand that the Southern Ocean makes an observable contribution to \r\nit, there is still low confidence in the attribution for the processes \r\nbehind the 1990s hiatus (Section 5.2.1.3.2). Observed increases in \r\nthe amplitude of the seasonal cycle of ocean pCO2 and reductions in \r\nthe mean global buffering capacity provide high confidence that the \r\ngrowing CO2 sink is also beginning to drive observable large-scale \r\nchanges in ocean carbonate chemistry (Jiang et al., 2019). However, \r\nthere is medium confidence that these changes which, depending \r\non the emissions scenario, could drive future ocean feedbacks, are \r\nstill too small to emerge from the historical multi-decadal observed \r\ngrowth rate of Socean (Sections 5.1.2; 5.3.2 and 5.4.2, and Figure 5.8a; "


id: 98622fc762a1fa91fd860705c6f36092
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24018
content:
"interior support the medium confidence assessment that the ocean \r\nanthropogenic carbon storage rates continue to be determined by the \r\nocean sink (Socean) in response to growing CO2 emissions (Figure 5.9; \r\nMcKinley et al., 2020)."


id: 9a1fc177cc332c2795e768a69a2fba1b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24351
content:
"equatorial oceans' influence on global mean Fnet has a low correlation \r\nbecause, notwithstanding the coherence in interannual variability, it \r\ndoes not show the same global mean trend of strengthening sink \r\nin response to growing global emissions (Supplementary Materials \r\nFigure 5.SM.1d; Gregor et al., 2019). All regions, except the equatorial \r\nocean, contribute to varying extents to the multi-decadal trend of \r\ngrowth in the global ocean sink (Supplementary Materials Figure 5.\r\nSM.1). Data sparseness in the high latitudes and the relatively short \r\nlength of the observational records leads to low confidence in the \r\nattribution of the processes that link regional-global variability to \r\nclimate (Landschutzer et al., 2019; Gloege et al., 2021)."


id: 142fa79ccc38018c1db553f7ccde41ec
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 767
content:
"the Southern Ocean, the storage rate of the anthropogenic CO2 was \r\nrather lower after 2005 than before (Section 9.2.3.2; Tanhua et al., \r\n2017; Bindoff et al., 2019). These changes have been predominantly \r\nascribed to the impact of changes in the MOC on the transport of \r\nanthropogenic CO2 into the ocean interior due to regional climate \r\nvariability, in addition to the increase in the atmospheric CO2\r\nconcentration (Section 9.2.3.1; Wanninkhof et al., 2010; Perez et al., \r\n2013; DeVries et al., 2017, 2019; Gruber et al., 2019b; McKinley \r\net al., 2020). However, the low frequency of carbon observations \r\nin the interior of the vast ocean leads to medium confidence in the \r\nassessment of temporal variability in the rate of regional ocean CO2\r\nstorage and its controlling mechanisms."


id: c50271e6e5d0ce02d9d3e89a09901a45
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31969
content:
"enhanced vegetation photosynthesis over the past decades (medium \r\nto high confidence) (Figure 5.10), including increasing satellite-derived \r\nvegetation greenness (e.g., see Chapter 2; Mao et al., 2016; Zhu et al., \r\n2016; Jia et al., 2019) and satellite-derived photosynthesis indicators \r\n(e.g., Badgley et al., 2017; Zhang et al., 2018), change in atmospheric \r\nconcentration of carbonyl sulphide (Campbell et al., 2017), enhanced \r\nseasonal CO2 amplitude (Graven et al., 2013; Forkel et al., 2016), \r\nobservation-driven inference of increasing photosynthesis CO2\r\nuptake based mostly on enhanced water use efficiency (Cheng et al., \r\n2017), and DGVM simulated increase of photosynthesis CO2 uptake \r\n(Anav et al., 2015)."


id: b03a11f962741e1ec82511d2422c81bc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28243
content:
"Substantial progress has been made since AR5 on attributing change \r\nof the global net land CO2 sink. Increasing global net land CO2 sink \r\nsince the 1980s is mainly driven by the fertilization effect from rising \r\natmospheric CO2 concentrations (Schimel et al., 2015; Sitch et al., 2015; \r\nFernandez-Martinez et al., 2019; O'Sullivan et al., 2019; Tagesson \r\net al., 2020; Walker et al., 2021) (medium confidence). Increasing \r\nnitrogen deposition (de Vries et al., 2009; Devaraju et al., 2016; \r\nHuntzinger et al., 2017) or the synergy between increasing nitrogen \r\ndeposition and atmospheric CO2 concentration (O'Sullivan et al., \r\n2019) could have also contributed to the increasing global net land \r\nCO2 sink. The effects of climate change alone on the global net land \r\nCO2 sink is so divergent that even the signs (directions) of the effects \r\nare not the same across DGVMs (e.g., Huntzinger et al., 2017)."


id: 39bf507fd6d94769e33f743b1d892d9d
created_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 7372
content:
"In summary, multiple lines of observational and modelling evidence \r\nprovide high confidence in the finding that the ocean sink for \r\nanthropogenic CO2 has increased quasi-linearly over the past 60 years \r\nin response to growing global emissions of anthropogenic CO2, with \r\na  mean fraction of 23% of total emissions. The high confidence\r\nassessment is moderated to medium confidence due to a  number \r\nof ocean CO2 flux terms yet to be adequately constrained. Observed \r\nchanges in the variability of ocean pCO2 and observed reductions in \r\nthe mean global buffering capacity provide high confidence that the \r\ngrowing CO2 sink is also beginning to drive observable large-scale \r\nchanges in ocean carbonate chemistry. However, there is medium \r\nconfidence that these changes which, depending on the emissions \r\nscenario, could drive future ocean feedbacks, are still too small to \r\nemerge from the historical multi-decadal observed growth rate of Socean."


id: d01e2ce96b10e2714ce6c0a6090cdbfc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33972
content:
"Significant uncertainties remain for the land CO2 sink partition \r\nof processes due to challenges in reconciling multiple-scale \r\nevidence from experiments to the globe (Fatichi et al., 2019; Walker \r\net al., 2021), due to large spatial and inter-model differences in \r\ndiagnosing dominant driving factors affecting the net land CO2 sink "


id: 9a3ffe5767beb835233b5067de2e88c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24377
content:
"Carbon uptake by vegetation photosynthesis exerts a  first-order \r\ncontrol over the net land CO2 sink. Several lines of evidence show "


id: c39ee1f775c329288b17a88df539a94
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31689
content:
"Understanding the mechanisms driving interannual variability in \r\nthe carbon cycle has the potential to provide insights into whether \r\nand to what extent the carbon cycle can affect the climate (carbon-\r\nclimate feedback), with particular interests over the highly climate\u0002sensitive tropical carbon cycle (e.g.,  Cox et al., 2013; X.  Wang \r\net al., 2014; Fang et al., 2017; Jung et al., 2017; Humphrey et al., \r\n2018; Malhi et al., 2018; see Section 5.4). Consistent findings from \r\nstudies with atmospheric inversions, satellite observations and \r\nDGVMs (e.g.,  Malhi et al., 2018; Rodenbeck et al., 2018) lead to \r\nhigh confidence that the tropical net land CO2 sink is reduced under \r\nwarmer and drier conditions, particularly during El Nino events. \r\nInterannual variations in tropical land-atmosphere CO2 exchange \r\nare significantly correlated with anomalies of tropical temperature, \r\nwater availability and terrestrial water storage (X. Wang et al., 2014; "


id: 1e383c7eb6829b92a9bf6311b600babb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 2515
content:
"(Huntzinger et al., 2017; Fernandez-Martinez et al., 2019), and due \r\nto model deficiency in process representations (He et al., 2016). \r\nNitrogen dynamics, a major gap in DGVMs identified in AR5, have \r\nnow been incorporated in about half of the DGVMs contributing to \r\nthe carbon budget of the Global Carbon Project (GCP) (see Le Quere \r\net al. (2018a) for model characteristics) and a  growing number \r\nof ESMs (Arora et al., 2020). However, as the representations of "


id: 4b9a2937e09a9f80ceedfb8efc9fadcf
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10563
content:
"Jung et al., 2017; Humphrey et al., 2018; Piao et al., 2020), whose \r\nrelative contribution are difficult to separate due to covariations \r\nbetween these climatic factors. At continental scale, the dominant \r\nclimatic driver of interannual variations of tropical land-atmosphere "


id: 3b041cb0d9e9bedc9363fd197bd4f7ac
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7573
content:
"CO2 exchange was temperature variations (Figure 5.11; Piao et al., \r\n2020), which could partly result from the spatial compensation of \r\nthe water availability effects on land-atmospheric CO2 exchange \r\n(Jung et al., 2017)."


id: 75655e260c7efddbb1ec0048a24b7fff
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17883
content:
"Cross-Chapter Box 5.1 | Interactions Between the Carbon and Water Cycles, Particularly Under \r\nDrought Conditions"


id: 7296264ad3bce5f7abc0366c20705b65
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17403
content:
"Contributors: Josep G. Canadell (Australia), Philippe Ciais (France), Herve Douville (France), Sabine Fuss (Germany), Robert Jackson \r\n(United States of America), Annalea Lohila (Finland), Shilong Piao (China), Sonia I.  Seneviratne (Switzerland), Sergio M. Vicente\u0002Serrano (Spain), Sonke Zaehle (Germany)"


id: 42e84182450c56ffe134019efd133827
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8963
content:
"This box presents an assessment of interactions between the carbon and water cycles that influence the dynamics of the biosphere \r\nand its interaction with the climate system. It also highlights carbon-water trade-offs arising from the use of land-based climate \r\nchange mitigation options. Individual aspects of the interactions between the carbon and water cycles are addressed in separate \r\nchapters (Sections 5.2.1, 5.4.1, 8.2.3, 8.3.1, 8.4.1 and 11.6). The influence of wetlands and dams on methane emissions is assessed \r\nelsewhere (Sections 5.2.2, 5.4.7 and 8.3.1), as well as the consequences of permafrost thawing (Section 9.5.2 and Box 5.1) and/or \r\nincreased flooding (Sections 8.4.1, 11.5 and 12.4) on wetland extent in the northern high latitudes and wet tropics."


id: 81b1da830544b873eae39138dc08dcdb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19949
content:
"Increasing atmospheric CO2 concentration enhances leaf photosynthesis and drives a partial closure of leaf stomata, leading to higher \r\nwater-use efficiency (WUE) at the leaf canopy and ecosystem scales (Norby and Zak, 2011; De Kauwe et al., 2013; Fatichi et al., 2016; \r\nKnauer et al., 2017; Mastrotheodoros et al., 2017). Since AR5 (Box 6.3), a growing body of evidence from tree-ring and carbon isotopes \r\nfurther confirms an increase of plant water-use efficiency over decadal to centennial time scales, with some evidence for a stronger \r\nenhancement of photosynthesis compared to stomatal reductions (Frank et al., 2015; Guerrieri et al., 2019; Adams et al., 2020)."


id: 582532552917200d9561435c83bee4a3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12765
content:
"Leaf stomata closure can have large effects on land freshwater availability because of reduced plant transpiration, leading in some \r\nregions to higher soil moisture and runoff (Roderick et al., 2015; Milly and Dunne, 2016; Y. Yang et al., 2019). However, increased water \r\navailability is often not realized because other CO2 physiological effects that enhance ecosystem evapotranspiration might offset the \r\ngains. These effects include plant growth and leaf area expansion (Ainsworth and Long, 2005; Ukkola et al., 2016; McDermid et al., \r\n2021), lengthening of the vegetative growing season (Frank et al., 2015; Lian et al., 2021), and the effects of stomatal closure on \r\nnear-surface atmosphere that leads to increased air temperature and VPDs (Berg et al., 2016; Vogel et al., 2018; Zhou et al., 2019; \r\nGrossiord et al., 2020)."


id: f9e315fbd6926f2d48e22d25bea4e6cf
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41326
content:
"ESMs show no consensus about the net hydrological response to physiological CO2 effects. Some studies show water savings as \r\na consequence of the CO2 effects on leaf stomata closure (Swann et al., 2016; Lemordant et al., 2018), while other studies show \r\nthat increased leaf area offsets the gains from increased WUE (Mankin et al., 2019). However, these projections are subject to ESM \r\nuncertainties to quantify transpiration (Lian et al., 2021), among them the correct representations of plant hydraulic architecture such \r\nas changes in xylem anatomical properties and deep rooting (Nie et al., 2013; L. Liu et al., 2020)."


id: 65f59105db999ff1a8684eb9b65a397
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15198
content:
"In conclusion, it is very likely that elevated CO2 leads to increased WUE at the leaf level, concurrent with enhanced photosynthesis. \r\nIncreased CO2 concentrations alleviate the effects of water deficits on plant productivity (medium confidence) but there is low \r\nconfidence for its role under extreme drought conditions. There is low confidence that increased WUE by vegetation will substantially \r\nreduce global plant transpiration and diminish the frequency and severity of soil moisture and streamflow deficits associated with the \r\nradiative effect of higher CO2 concentrations."


id: d6088a4923b732394afd872ab179dbc6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34973
content:
"How does drought affect the terrestrial CO2 sink?\r\nWater availability controls the spatial distribution of photosynthesis - gross primary productivity (GPP) - over a larger part of the globe \r\n(Beer et al., 2010) and, at local scale, drought decreases GPP more than respiration (Schwalm et al., 2012) over most ecosystem types. \r\nThis makes water availability a major climatic driver of variability in net ecosystem exchange (Jung et al., 2017; Humphrey et al., 2018). "


id: cbb4f1ad77256b3011729bc2c9f4ea0b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33164
content:
"In addition to suppressing photosynthesis, field evidence suggests that droughts reduce the land CO2 sink, also through increasing \r\nforest mortality and promoting wildfire (Allen et al., 2015; Brando et al., 2019; Abram et al., 2021)."


id: cf0ce684a439bc1e4f97a967f2e37c1f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33776
content:
"At the global scale, interannual variability in the atmospheric CO2 growth rate and global-scale terrestrial water storage from satellite \r\nshow that a  lower global net land CO2 sink is associated with below-average terrestrial water storage (Humphrey et al., 2018). \r\nAtmospheric inversions based on surface and satellite column CO2 measurements show significant carbon release during drought \r\nevents in pan-tropic areas (Phillips et al., 2009; Gatti et al., 2014; J. Liu et al., 2017; Palmer et al., 2019). Regional extreme droughts in \r\nthe mid-latitudes also decrease GPP and land CO2 sink (Ciais et al., 2005; Wolf et al., 2016; W. Peters et al., 2020; Flach et al., 2021). \r\nDroughts are not compensated by equivalent wet anomalies because of the non-linear response of the terrestrial carbon uptake to \r\nsoil moisture (Green et al., 2019)."


id: b8e971a92ec384020d328962d6d77aaa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29739
content:
"In conclusion, there is high confidence that the global net land CO2 sink is reduced on interannual scale when regional-scale \r\nreductions in water availability associated with droughts occur, particularly in tropical regions. There is also high confidence that the \r\nglobal land sink will become less efficient due to soil moisture limitations and associated drought conditions in some regions for high\u0002emissions scenarios, specially under global warming above 4degC. However, there is low confidence on how these water cycle feedbacks \r\nwill play out in lower emissions scenarios (at 2degC global warming or lower) due to uncertainties in regional rainfall changes and the \r\nbalance between the CO2 fertilization effect, through WUE, and the radiative impacts of greenhouse gases."


id: c577329d598885934461bfe0fa519f11
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32051
content:
"Most of the water consumed in BECCS is used to grow the feedstock, with carbon capture and storage constituting a smaller portion \r\nacross all crops (Rosa et al., 2020), with an estimated evaporative loss of 260 km3 yr-1 for 3.3 GtC yr-1 (Smith et al., 2016). The \r\nsame authors also estimate water use for CDR through afforestation at 1040 km3 yr-1 for 3.3 GtC yr-1, including interception and \r\ntranspiration, adjusted for the original land cover's water use. "


id: 8b3d2b93d96ee73e57de5af7fc237b5f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21661
content:
"The impacts of different CDR options on the water cycle depend crucially on regional climate, prior land cover, and scale of deployment \r\n(Trabucco et al., 2008). Extensive irrigation for afforestation in drier areas will have larger downstream impacts than in wetter regions, \r\nwith the difference in water use between the afforested landscapes and its previous vegetation determining the level of potential \r\nimpacts on evapotranspiration and runoff (Jackson et al., 2005; Teuling et al., 2017). Afforestation and reforestation sometimes "


id: 31338ff309a0b5d62181bac2c750f9f3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5908
content:
"enhances precipitation through atmospheric feedbacks such as increased convection, at least in the tropics (Ellison et al., 2017) and \r\nthe increase in precipitation can, in some regions, even cancel out the increased evapotranspiration (Li et al., 2018). "


id: 52733f2d5431d0f808471be4b2af7028
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11790
content:
"In conclusion, extensive deployment of BECCS and afforestation/reforestation will require larger amounts of freshwater resources \r\nthan used by the previous vegetation, altering the water cycle at regional scales (high confidence). Consequences of high water \r\nconsumption on downstream uses, biodiversity, and regional climate depend on prior land cover, background climate conditions, \r\nand scale of deployment (high confidence). Therefore, a regional approach is required to determine the efficacy and sustainability \r\nof CDR projects."


id: e192bcd094aad0a6ed65bdec462d81d0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36955
content:
"from land use, land-use change, and forestry (ELULUCF), the growth rate \r\nof CO2 in the atmosphere (Gatm), and the ocean (Socean) and natural \r\nland (Sland) CO2 sinks. An imbalance term (BImb) is required to ensure \r\nmass balance of the source and sinks that have been independently \r\nestimated: EFOS +  ELULUCF =  Gatm +  Socean +  Sland. +  BImb. All estimates \r\nare reported with 1 standard deviation (+-1s, 1 sigma) representing \r\na likelihood of 68%."


id: 261b4526051071c296112def5e49e7b4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3876
content:
"The global CO2 budget (Figure  5.12) encompasses all natural \r\nand anthropogenic CO2 sources and sinks. Table  5.1 shows the \r\nperturbation of the global carbon mass balance between reservoirs \r\nsince the beginning of the industrial era, circa 1750."


id: f1d486c98a4558be6c28ea3ba1f960c7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39931
content:
"Since AR5 (Ciais et al., 2013), a number of improvements have led to the \r\nmore constrained carbon budget presented here. Some new additions \r\ninclude: (i) the use of independent estimates for the residual carbon \r\nsink on natural terrestrial ecosystems (Le Quere et al., 2018a); (ii) \r\nimprovements in the estimates of emissions from cement production \r\n(Andrew, 2019) and the sink associated with cement carbonation (Cao \r\net al., 2020); (iii) improved and new emissions estimates from forestry \r\nand other land use (Hansis et al., 2015; Gasser et al., 2020); (iv) the \r\nuse of ocean observation-based sink estimates and a  revised river \r\nflux partition between hemispheres (Friedlingstein et al., 2020); and \r\n(v) the expansion of constraints from atmospheric inversions, based on \r\nsurface networks and the use of satellite retrievals. "


id: edb6a106eae5029fd9a92ffa6bfde188
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39180
content:
"The budget, based on the annual assessment by the GCP \r\n(Friedlingstein et al., 2020), uses independent estimates of all major \r\nflux components: fossil fuel and carbonate emissions (EFOS), CO2 fluxes "


id: 457be6774e1235f37172db0120f86505
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9442
content:
"Table 5.1 | Global anthropogenic CO2 budget accumulated since the Industrial Revolution (onset in 1750) and averaged over the 1980s, 1990s, 2000s, \r\nand 2010s. By convention, a negative ocean or land to atmosphere CO2 flux is equivalent to a gain of carbon by these reservoirs. The table does not include natural exchanges \r\n(e.g., rivers, weathering) between reservoirs. Uncertainties represent the 68% confidence interval (Friedlingstein et al., 2020)."


id: c5ce3d70db48be9a1b2f31c788e5505c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32109
content:
"Resplandy et al., 2018) and corrected to account for 0.2 PgC buried \r\nin ocean floor sediments. These terms are included in Figure  5.12. \r\nInclusion of other smaller fluxes could further constrain the carbon \r\nbudget (Ito, 2019; Friedlingstein et al., 2020)."


id: 4635fc6c59d96cc6720de2aa5942fced
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9572
content:
"land-ocean aquatic continuum comprising freshwaters, estuaries, \r\nand coastal areas. Natural and anthropogenic transfers of carbon \r\nfrom soils to freshwater systems are significant (2.4-5.1 PgC yr-1) \r\n(Regnier et al., 2013; Drake et al., 2018). Some of the carbon is \r\nburied in freshwater bodies (0.15 PgC) (Mendonca et al., 2017), and \r\na  significant proportion returns to the atmosphere via outgassing \r\nfrom lakes, rivers and estuaries (Raymond et al., 2013; Regnier et al., \r\n2013; Lauerwald et al., 2015). The net export of carbon from the \r\nterrestrial domain to the open oceans is estimated to be 0.80 PgC yr-1\r\n(medium confidence), based on the average of (Jacobson et al., 2007; "


id: 2673d73e4e9ee7243cc5dc73e506be28
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3933
content:
"Methane is a  much more powerful greenhouse gas than CO2\r\n(Chapter 7) and participates in tropospheric chemistry (Chapter 6). "


id: 123d519b5e84349de1b10e2d4a6c66b0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 403
content:
"emissions from the oil and gas sectors declined by about 10 Tg yr-1\r\nthrough the 1990s, and atmospheric CH4 loss steadily increased \r\n(Dlugokencky et al., 2003; Simpson et al., 2012; Crippa et al., 2020; \r\nHoglund-Isaksson et al., 2020; Chandra et al., 2021). The methane \r\ngrowth rate began to increase again at 7 +- 3 ppb yr-1 during 2007-\r\n2016, the causes of which are highly debated since AR5 (Rigby et al., \r\n2008; Dlugokencky et al., 2011; Dalsoren et al., 2016; Nisbet et al., "


id: e5fb3f539dec545157edb84a93f29406
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37756
content:
"This section discusses both bottom-up and top-down estimates of \r\nemissions and sinks. Bottom-up estimates are based on empirical \r\nupscaling of point measurements, emissions inventories and \r\ndynamical model simulations, while top-down estimates refer to \r\nthose constrained by atmospheric measurements and chemistry\u0002transport models in inversion systems. Since AR5, a  larger suite \r\nof atmospheric inversions using both in situ and remote sensing \r\nmeasurement have led to better understanding of the regional \r\nCH4 sources (Cross-Chapter Box  5.2). New ice core measurements \r\nof 14C-CH4 are used for estimating the geological sources of CH4\r\n(Table 5.2). Compared to the SRCCL (IPCC, 2019a; Jia et al., 2019), \r\nwe provide a whole atmospheric sources-sinks budget consisting of \r\nall emissions and losses."


id: c1324d022a63386da00f3132970a25b2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31290
content:
"Emissions from rice cultivation decreased from about 45 Tg yr-1 in the \r\n1980s to about 29 Tg yr-1 in the decade 2000-2009, but increased \r\nagain slightly to 31 Tg yr-1 during 2008-2017, based on inventories \r\ndata. However, ecosystem models showed a gradual increase with \r\ntime due to climate change (limited evidence, low agreement) \r\n(Crippa et al., 2020; Hoglund-Isaksson et al., 2020; Ito, 2020)."


id: e03fdbb1b1a38475153f10269213fd0c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36703
content:
"Biomass burning and biofuel consumption (including natural and \r\nanthropogenic processes) caused at least 30 Tg yr-1 emissions during \r\n2008-2017 and constituted up to about 5% of global anthropogenic \r\nCH4 emissions. Methane emissions from open biomass burning \r\ndecreased during the past two decades mainly due to reduction \r\nof burning in savanna, grassland and shrubland (van der Werf \r\net al., 2017; Worden et al., 2017). There is recent evidence from the \r\ntropics that fire occurrence is non-linearly related to precipitation, \r\nimplying that severe droughts will increase CH4 emissions from fires, \r\nparticularly from the degraded peatlands (Field et al., 2016)."


id: 9891a91d583dc3682a004e5707d8ece2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24057
content:
"Table 5.2 | Global CH4 budget. Sources and sinks of CH4 for the two most recent decades for wich data is available, from bottom-up and top-down estimations (in Tg CH4 yr-1). \r\nThe data are updated from Saunois et al. (2020), for the bottom-up anthropogenic emissions (FAO, 2019; US EPA, 2019; Crippa et al., 2020; Hoglund-Isaksson et al., 2020), \r\ntop-down geological emissions (Schwietzke et al., 2016; Petrenko et al., 2017; Hmiel et al., 2020), and top-down sinks from seven selected inverse models. The means (min-max) \r\nwith outliers removed from the range and the means are given. Outliers defined as >75th percentile + 3 x the interquartile range or <25th percentile - 3 x the interquartile \r\nrange. The top-down budget imbalances are calculated for each model separately and averaged. Note also the round-off error for the sources and sinks, which sometimes leads \r\nto last digit mismatch in the sums. For detailed information on datasets, see further details on data table 5.SM.6."


id: c5365aeae02e723614dd6045b03bec0d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32001
content:
"All geological sources around the world, including the coastal oceans \r\nand fjords, are estimated to emit CH4 in the range of 35-76 Tg yr-1\r\n(Etiope et al., 2019). There is evidence that the ventilation of geological \r\nCH4 is likely to be smaller than 15 Tg yr-1 (Petrenko et al., 2017; Hmiel \r\net al., 2020). A lower geological CH4 ventilation will reduce the gap \r\nbetween bottom-up and top-down estimates (Table 5.2), but widen \r\nthe gap in the ratio of fossil fuel-derived sources to the biogenic \r\nsources for matching the D14C-CH4 observations."


id: 17923292849fa171dfcb591d176ee4be
created_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 1354
content:
"Trees in upland and wetland forests contribute to CH4 emissions by \r\nabiotic production in the canopy, by the methanogenesis taking place \r\nin the stem, and by conducting CH4 from soil into the atmosphere \r\n(Covey and Megonigal, 2019). There is emerging evidence of the \r\nimportant role of trees in transporting and conducting CH4 from \r\nsoils into the atmosphere, especially in tropics (Pangala et al., 2017), \r\nwhereas direct production of CH4 by vegetation only has a  minor \r\ncontribution (limited evidence, high agreement) (Bruhn et al., 2012; \r\nCovey and Megonigal, 2019). The contribution of trees in transporting \r\nCH4 may further widen the gap between the bottom-up and top-down \r\nestimates in the global budget, particularly needing a re-assessment \r\nof emissions in the tropics and in forested wetlands of temperate and \r\nboreal regions (Pangala et al., 2017; Jeffrey et al., 2019; Welch et al., \r\n2019; Sjogersten et al., 2020)."


id: 839236a5ec1456af782b5af91c9ec0aa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20288
content:
"Microbial methane uptake by soil comprises up to 5% (30 Tg yr-1) \r\nof the total CH4 sink in 2008-2017 (Table  5.2). There is evidence \r\nfrom experimental and modelling studies of increasing soil microbial \r\nuptake due to increasing temperature (Yu et al., 2017), although \r\nevidence also exists for decreasing CH4 consumption, possibly linked \r\nto precipitation changes (Ni and Groffman, 2018). The estimate of \r\nglobal methane loss by microbial oxidation in upland soils has been \r\nlowered marginally by 4 Tg yr-1, compared to 34 Tg yr-1 in AR5, for \r\nthe period 2000-2009. Termites, an infraorder of insects (Isoptera) \r\nfound in almost all land masses, emitted about 9 Tg yr-1 of CH4 in \r\n2000-2009. Increased emissions from insects and other anthropods \r\nare projected (Brune, 2018)."


id: 8877103c5b26b550f25b961e017ca87e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21171
content:
"the bottom-up estimates of their emissions (Thornton et al., 2016a). \r\nAlthough there is evidence that regional human activities and \r\nglobal warming both increase inland water CH4 emissions (Beaulieu \r\net al., 2019), the increase in the decadal emissions since AR5 (Ciais \r\net al., 2013) rather reflect improvements in the estimate (medium \r\nconfidence), due to updates in the datasets and new upscaling \r\napproaches (Saunois et al., 2020)."


id: fe1329eba2c9966bc55c2f1e3ddad4b0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 42067
content:
"Recent analysis using D14C-CH4 in ice samples suggest that CH4\r\nemissions from fossil fuel exploitation are responsible for 30% of \r\ntotal CH4 emissions (Lassey et al., 2007; Hmiel et al., 2020), which is \r\nlargely inconsistent with sectorial budgets where fossil fuel emissions \r\nadd up to 20% only (Ciais et al., 2013). However, recent model \r\nsimulations produce fairly consistent d13C-CH4 values and trends, as \r\nobserved in the atmospheric samples using 20% fossil fuel emissions \r\nfraction (Ghosh et al., 2015; Warwick et al., 2016; Fujita et al., 2020; \r\nStrode et al., 2020). Further research is needed to clarify the relative \r\nroles of CH4 emissions from fossil fuel exploitation and freshwater \r\ncomponents. A key challenge is to accommodate the higher estimated \r\nemissions from these two components without a major increase in \r\nthe sinks, in order to be consistent with the observed changes in the \r\ncarbon and hydrogen isotopes."


id: 39322a478d3953c198975167740399e0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7272
content:
"A summary of top-down and bottom-up estimates of CH4 emissions \r\nand sinks for the period 2008-2017 is presented in Figure 5.14 (details \r\nin Table 5.2 and the associated text for the emissions). In addition to \r\n483-682 Tg yr-1 loss of CH4 in the troposphere by reaction with OH, \r\n1-35 Tg yr-1 of CH4 loss is estimated to occur in the lower troposphere \r\ndue to Cl but are not included in the top-down models as shown in \r\nTable 5.2 (Hossaini et al., 2016; Gromov et al., 2018; X. Wang et al., \r\n2019). The decadal mean CH4 burden/imbalance increased at the rate \r\nof 30, 12, 7 and 21 Tg yr-1 in the 1980s (1980-1989), 1990s (1990-\r\n1999), 2000s (2000-2009) and the most recent decade (2008-2017), \r\nrespectively (virtually certain), as can be estimated from observed \r\natmospheric growth rate (Cross-Chapter Box 5.2, Figure 1)."


id: a5cf10a3731d825c20deca1a32be6272
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26395
content:
"Figure 5.14 | Global methane (CH4) budget (2008-2017). Values and data sources as in Table  5.2 (in TgCH4). The atmospheric stock is calculated from mean CH4\r\nconcentration, multiplying a factor of 2.75 +- 0.015 Tg ppb-1, which accounts for the uncertainties in global mean CH4 (Chandra et al., 2021). Further details on data sources and \r\nprocessing are available in the chapter data table (Table 5.SM.6)."


id: efbfcd6e4d8eb0d698c6b06a70b619a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39565
content:
"Contributors: Prabir K. Patra (Japan/India), Josep G. Canadell (Australia), Frank J. Dentener (European Union, The Netherlands), Xin \r\nLan (United States of America/China), Vaishali Naik (United States of America)"


id: 139e80d696f5e75fa9903248365f6c84
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 669
content:
"Cross-Chapter Box 5.2, Figure 1 shows the decadal CH4 budget derived from the Global Carbon Project (GCP)-CH4 synthesis for 1980s, \r\n1990s and 2000s (Kirschke et al., 2013), and for 2010-2017 (Saunois et al., 2020). The imbalance of the sources and sinks estimated \r\nby atmospheric inversions (dark blue bars) can be used to explain the changes in CH4 concentration increase rates between the \r\ndecades (Table 5.2)."


id: caf07716d63cfa3c42706932ebc3b426
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33044
content:
"Since AR5, many studies have discussed the role of different source categories in explaining the increase in CH4 growth rate since \r\n2007 and a coincident decrease of d13C-CH4 and dD-CH4 isotopes (Figure 5.13; Rice et al., 2016). Both 13C and D are enriched in "


id: dceb71630d6162886073d016279af4d3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36130
content:
"mass-weighted average source signatures for CH4 emissions from thermogenic sources (e.g., coal mining, oil and gas industry) and \r\npyrogenic (biomass burning) sources, and depleted in biogenic (e.g., wetlands, rice paddies, enteric fermentation, landfill and waste) \r\nsources. Proposed hypotheses for CH4 growth (2007-2017) are inconclusive and vary from a concurrent decrease in thermogenic and \r\nincrease in wetland and other biogenic emissions (Nisbet et al., 2016; Schwietzke et al., 2016), an increase in emissions from agriculture \r\nin the tropics (Schaefer et al., 2016), a concurrent reduction in pyrogenic emissions and an increase in thermogenic emissions (Worden \r\net al., 2017), or an emissions increase from biogenic sources and a slower increase in emissions from thermogenic sources compared \r\nto inventory emissions (Patra et al., 2016; Thompson et al., 2018; Jackson et al., 2020; Chandra et al., 2021)."


id: 6dae67baa4da2ce732f11f2b61078cf0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 16555
content:
"In natural ecosystems, nitrous oxide (N2O) is primarily produced as \r\na by-product during the remineralization of organic matter via the \r\nprimary processes of nitrification and denitrification (Butterbach\u0002Bahl et al., 2013; Voss et al., 2013). The net N2O production is highly \r\nsensitive to local environmental conditions such as temperature, \r\noxygen concentrations, pH and the concentrations of ammonium and \r\nnitrate, among others, causing strong variability of N2O emissions in \r\ntime and space, even at small scales. Changes in the atmospheric \r\nabundance of N2O result largely from the balance of the net N2O \r\nsources on land and ocean, and the photochemical destruction of \r\nN2O in the stratosphere."


id: 2d36053c8deea9994f049681b1851f6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5240
content:
"Since AR5 (WGI, Section  6.4.3), improved understanding of N2O \r\nsources allows for a  more comprehensive assessement of the \r\nglobal N2O budget (Table 5.3). This progress is based on extended \r\natmospheric observations (Francey et al., 2003; Elkins et al., 2018; \r\nPrinn et al., 2018), improved atmospheric N2O inversions (Saikawa \r\net al., 2014; Thompson et al., 2019), updated and expanded \r\ninventories of N2O sources (Winiwarter et al., 2018; Janssens\u0002Maenhout et al., 2019), as well as improved bottom-up estimate of \r\nfreshwater, ocean and terrestrial sources (Martinez-Rey et al., 2015; \r\nLandolfi et al., 2017; Buitenhuis et al., 2018; Lauerwald et al., 2019; \r\nMaavara et al., 2019; Tian et al., 2019)."


id: 60fd86fb4a3fe70f319003fc59d86b8b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14359
content:
"As assessed by SRCCL (IPCC, 2019a), combined firn, ice, air and \r\natmospheric measurements show that the 15N/14N isotope ratio \r\n(robust evidence, high agreement) and the predominant position of \r\nthe 15N atom in atmospheric N2O (limited evidence, low agreement) \r\nin N2O has changed since 1940 (Figure 5.15b, c) whereas they were \r\nrelatively constant in the pre-industrial period (Ishijima et al., 2007; \r\nPark et al., 2012; Prokopiou et al., 2017, 2018). The SRCCL concluded \r\nthat this change indicates a shift in the nitrogen-substrate available \r\nfor denitrification, and the relative contribution of nitrification to \r\nthe global N2O source (robust evidence, high agreement), which are \r\nassociated with increased fertilizer use in agriculture (Park et al., \r\n2012; Snider et al., 2015; Prokopiou et al., 2018)."


id: 7a4623415295515916dd92adfff4e778
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18708
content:
"The human perturbation of the natural nitrogen cycle through the \r\nuse of synthetic fertilizers and manure, as well as nitrogen deposition \r\nresulting from land-based agriculture and fossil fuel burning has \r\nbeen the largest driver of the increase in atmospheric N2O of 31.0 \r\n+-  0.5 ppb (10%) between 1980 and 2019 (robust evidence, high \r\nagreement) (Tian et al., 2020). The long atmospheric lifetime of N2O \r\nimplies that it will take more than a  century before atmospheric \r\nabundances stabilize after the stabilization of global emissions. \r\nThe rise of atmospheric N2O is of concern, not only because of its \r\ncontribution to the anthropogenic radiative forcing (Chapter 7) but \r\nalso because of the importance of N2O in stratospheric ozone loss \r\n(Ravishankara et al., 2009; Fleming et al., 2011; W. Wang et al., 2014)."


id: bd2a040b74b50344203260b52bd7cb05
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30533
content:
"Since AR5 (WGI, Section 6.4.3), the mean atmospheric lifetime of N2O \r\nhas been revised to 116 +- 9 years (Prather et al., 2015). The small \r\nnegative feedback of the N2O lifetime to increasing atmospheric \r\nN2O results in a slightly lower residence time (109 +- 10 years) of N2O "


id: 85b561d6455a56933ddad5028a060dad
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20669
content:
"perturbations compared with that assessed by AR5 (118-131 years) \r\n(Prather et al., 2015). The dominant N2O loss occurs through \r\nphotolysis and oxidation by O(1D) radicals in the stratosphere and \r\namounts to approximately 13.1 (12.4-13.6) TgN yr-1 (Minschwaner \r\net al., 1993; Prather et al., 2015; Tian et al., 2020)."


id: f3a76604727a0c63cca2acfa4e6d496c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40239
content:
"Biomass burning from crop residue burning, grassland, savannah and \r\nforest fires, as well as biomass burnt in household stoves, releases N2O \r\nduring the combustion of organic matter. Updated inventories since \r\nAR5 (WGI, Section 6.4.3) result in a lower range of the decadal mean \r\nemissions of 0.6 (0.5-0.8) TgN yr-1 (van der Werf et al., 2017; Tian \r\net al., 2020). The attribution of grassland, savannah or forest fires to \r\nnatural or anthropogenic origins is uncertain, preventing a separation \r\nof the biomass burning source into natural and anthropogenic."


id: cfb01aaa82e9cca89b8f854e9a6fb61a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33899
content:
"account for up to 50% of the global ocean source (Codispoti, 2010; \r\nArevalo-Martinez et al., 2015; Babbin et al., 2015). However, recent \r\nglobal-scale analyses estimate lower contributions (4-7%, Battaglia \r\nand Joos, 2018b; Buitenhuis et al., 2018). Further investigation \r\nis required to reconcile these estimates and provide improved \r\nconstraints on the N2O source from low-oxygen zones."


id: df6739cb9f4eb0c65ec58d37334f0b36
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36552
content:
"Since AR5 (WGI, Section  6.4.3), new estimates of the global ocean \r\nN2O source derived from ocean biogeochemistry models are 3.4 (2.5-\r\n4.3) TgN yr-1 for the period 2007-2016 (Figure 5.16; Manizza et al., \r\n2012; Suntharalingam et al., 2012; Martinez-Rey et al., 2015; Landolfi \r\net al., 2017; Buitenhuis et al., 2018; Tian et al., 2020). This is slightly \r\nlower than climatological estimates from empirically based methods \r\nand surface ocean data syntheses (Bianchi et al., 2012; S. Yang et al., \r\n2020). Nitrous oxide processes in coastal upwelling zones continue \r\nto be poorly represented in global estimates of marine N2O emissions \r\n(Kock et al., 2016), but may account for an additional 0.2-0.6 TgN yr-1\r\nof the global ocean source (Seitzinger et al., 2000; Nevison et al., 2004)."


id: 76e67ae962cbeb75d2d592e8f0c3da3b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18130
content:
"Atmospheric deposition of anthropogenic N on oceans can stimulate \r\nmarine productivity and influence ocean emissions of N2O.  New \r\nocean model analyses since AR5 (WGI, 6.4.3), suggest a  relatively \r\nmodest global potential impact of 0.01-0.32 TgN yr-1 (pre-industrial \r\nto present-day) equivalent to 0.5-3.3% of the global ocean N2O \r\nsource (Suntharalingam et al., 2012; Jickells et al., 2017; Landolfi \r\net al., 2017). However, larger proportionate impacts are predicted in \r\nnitrogen-limited coastal and inland waters downwind of continental \r\npollution outflow, such as the Northern Indian Ocean (Jickells et al., \r\n2017; Suntharalingam et al., 2019)."


id: f5cb07078329e11dd494977bac101914
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40602
content:
"In the oxic ocean (>97% of ocean volume), nitrification is believed \r\nto be the primary N2O source (Freing et al., 2012). In sub-oxic ocean \r\nzones (Section  5.3), where denitrification prevails, higher N2O \r\nyields and turnover rates make these regions potentially significant \r\nsources of N2O (Arevalo-Martinez et al., 2015; Babbin et al., 2015; \r\nJi et al., 2015). The relative proportion of ocean N2O from oxygen\u0002minimum zones is highly uncertain (Zamora et al., 2012). Estimates \r\nderived from in situ sampling, particularly in the eastern tropical \r\nPacific, suggest significant fluxes from these regions, and potentially "


id: a0a25f676858b8998d599eeb4966faab
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25470
content:
"Inland waters and estuaries are generally sources of N2O as \r\na  result of nitrification and denitrification of dissolved inorganic \r\nnitrogen, however, they can serve as N2O sinks in specific conditions \r\n(Webb et al., 2019). Since AR5 (WGI, 6.4.3), improved emissions \r\nfactors, including their spatio-temporal scaling, and consideration \r\nof transport within the aquatic system allows for better constraint "


id: 2b7e60fca779c3fa4e8631c907e0ef61
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4907
content:
"of these emissions (Murray et al., 2015; Hu et al., 2016; Lauerwald \r\net al., 2019; Maavara et al., 2019; Kortelainen et al., 2020; Yao et al., \r\n2020). Despite uncertainties because of the side effects of canals and \r\nreservoirs on nutrient cycling, these advances permit attribution of \r\na fraction of inland water N2O emissions to anthropogenic sources \r\n(Tian et al., 2020), which contributes to the increased anthropogenic \r\nshare of the global N2O source in this report compared to AR5 (Ciais \r\net al., 2013). As an indirect consequence of agricultural nitrogen use \r\nand waste-water treatment, the anthropogenic emissions from inland \r\nwaters have increased by about a quarter (0.1 TgN yr-1) between the \r\n1980s and 2007-2016 (Tian et al., 2020)."


id: 3b69a97aa53d99ad7efd2c33edaaa507
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7642
content:
"show that global warming has led to increased soil N2O emissions \r\nof 0.8 (0.3-1.3) TgN yr-1 since approximately pre-industrial times, of \r\nwhich about half occurred since the 1980s (limited evidence, high \r\nagreement) (Tian et al., 2019, 2020)."


id: 9f69102d2384438e6e563331802f6380
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25267
content:
"The SRCCL assessed that deforestation and other forms of land-use \r\nchange significantly alter terrestrial N2O emissions through emission \r\npulses following conversions, generally resulting in long-term \r\nreduced emissions in unfertilized ecosystems (medium evidence, \r\nhigh agreement). This conclusion is supported by a  recent study \r\ndemonstrating that the deforestation-pulse effect is offset by the \r\neffect of reduced area of mature tropical forests (Tian et al., 2020)."


id: f6b0d2a062c5c5d29214cbda4786602b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40775
content:
"Uncertainties remain in process-based models with respect to their \r\nability to capture the complicated responses of terrestrial N2O \r\nemissions to rain pulses, freeze-thaw cycles and the net consequences \r\nof elevated levels of CO2 accurately (Tian et al., 2019). Emerging \r\nliterature suggests that permafrost thaw may contribute significantly \r\nto arctic N2O emissions (Voigt et al., 2020), but these processes are \r\nnot yet adequately represented in models and upscaling to large\u0002scale remains a significant challenge."


id: ef76a88905bf54bb429a49a6f62aaacf
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39505
content:
"The synthesis of bottom-up estimates of N2O sources (Sections 5.2.3.2-\r\n5.2.3.4 and Figure  5.17) yields a  global source of 17.0 (12.2 to \r\n23.5) TgN yr-1 for the years 2007-2016 (Table  5.3). This estimate \r\nis comparable to AR5, but the uncertainty range has been reduced \r\nprimarily due to improved estimates of ocean and anthropogenic N2O "


id: 735e49ce1a580e54a4d4bfd14bb1c8d2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17551
content:
"Figure 5.17 | Global nitrous oxide (N2O) budget (2007-2016). Values and data sources as in Table 5.3. The atmospheric stock is calculated from mean N2O concentration, \r\nmultiplying a factor of 4.79 +- 0.05 Tg ppb-1 (Prather et al., 2012). Pool sizes for the other reservoirs are largely unknown. Further details on data sources and processing are \r\navailable in the chapter data table (Table 5.SM.6)."


id: 8d9e3035f32164ebb7c769ffdd946744
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22110
content:
"decades. For the period 1960-2019, the relative contribution to the \r\ntotal effective radiative forcing (ERF) was 63% for CO2, 11% for \r\nCH4, 6% for N2O, and 17% for the halogenated species (Chapter 7; \r\nFigure 5.18). The systematic decline in the relative contribution to \r\nERF for CH4 since 1850 is caused by a slower increase rate of CH4\r\nin the recent decades, at 6, 10 and 5 ppb yr-1 during 1850-2019, \r\n1960-2019 and 2000-2019, respectively, in comparison with the \r\nincreasing rate of CO2 (at 0.7, 1.6 and 2.2 ppm yr-1, respectively) \r\nand N2O (at 0.4, 0.7 and 0.9 ppb yr-1, respectively; Figure  5.4). \r\nOwing to the shorter lifetime of CH4, the effect of a reduction in \r\nthe emissions increase rate on the ERF increase is evident at inter\u0002decadal time scales."


id: bd936cfc0f7f111278fc372b084dc902
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30614
content:
"(CH4), nitrous oxide (N2O) - were discussed in the previous sections. \r\nThis section compares the balance of the sources and sinks of these \r\nthree gases and their regional net flux contributions to the radiative \r\nforcing. CO2 has multiple residence times in the atmosphere - from one \r\nyear to many thousands of years (Box 6.1 in Ciais et al., 2013) - and \r\nN2O has a mean lifetime of 116 years. They are both long-lived GHGs, \r\nwhile CH4 has a lifetime of 9.1 years and is considered a short-lived \r\nGHG (see Chapter 2 for lifetime of GHGs, Chapter 6 for CH4 chemical \r\nlifetime, and Chapter 7 for effective radiative forcing of all GHGs)."


id: d634304a6162f2447740d41eb43dd2e3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35003
content:
"Figure 5.18 shows the contribution to radiative forcing of CO2, CH4, \r\nN2O, and the halogenated species since the 1900s to more recent "


id: 8eb3d89d0aadf2aa6b2223eb51f67dbb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22295
content:
"The Paleocene-Eocene Thermal Maximum (PETM) was an episode of \r\nglobal warming exceeding pre-industrial temperatures by 4degC-8degC \r\n(McInerney and Wing, 2011; Dunkley Jones et al., 2013) that occurred \r\n55.9-55.7  Ma. The PETM involved a  large pulse of geologic CO2\r\nreleased into the ocean-atmosphere system in 3-20 kyr (Zeebe et al., \r\n2016; Gutjahr et al., 2017; Kirtland Turner et al., 2017; Kirtland Turner, \r\n2018; Gingerich, 2019; Section 5.2.1.1). In response, observationally \r\nconstrained model simulations report an increase in atmospheric \r\nCO2 concentrations ranging from about 900  ppm to >2000  ppm \r\n(Chapter 2; Gutjahr et al., 2017; Cui and Schubert, 2018; Anagnostou \r\net al., 2020). The PETM thus provides a test for our understanding of \r\nthe ocean's response to the increase in carbon (and heat) emissions \r\nover geologically short time scales."


id: 547ca14327e1a61994e30e0d9bda954b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12140
content:
"Recent model outputs and globally distributed geochemical data \r\nreveal with medium confidence widespread ocean deoxygenation \r\nduring the PETM (Dickson et al., 2012, 2014; Winguth et al., 2012; \r\nChang et al., 2018; Remmelzwaal et al., 2019), with parts of the \r\nocean potentially becoming drastically oxygen-depleted (anoxic; \r\nYao et al., 2018; Clarkson et al., 2021). Deoxygenation affected the \r\nsurface ocean globally (including the Arctic Ocean; Sluijs et al., 2006), \r\ndue to vertical and lateral expansion of OMZs (Zhou et al., 2014) that \r\nresulted from warming and related changes in ocean stratification.\r\nExpansion of OMZs may have stimulated N2O production through \r\nwater-column (de)nitrification (Junium et al., 2018). The degree to \r\nwhich N2O production impacted PETM warming, however, has not \r\nyet been established."


id: 5f599dde737ff80f610436456a149cfc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14083
content:
"This section assesses past events of ocean acidification and \r\ndeoxygenation (Section  5.3.1), the historical trends and spatial \r\nvariability for the upper ocean (Section 5.3.2) and the ocean interior \r\n(Section  5.3.3). Future projections for ocean acidification and the \r\ndrivers in the coastal ocean are assessed in Sections  5.3.4 and \r\n5.3.5, respectively."


id: f739e901f47364587c392070a3064f82
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40872
content:
"The feedbacks associated with recovery from the PETM are uncertain, \r\nyet could include drawdown associated with silicate weathering \r\n(Zachos et al., 2005) and regrowth of terrestrial and marine organic \r\ncarbon stocks (Bowen and Zachos, 2010; Gutjahr et al., 2017)."


id: 114afff45c96b6ac2184b1a2199e6894
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 239
content:
"emissions. Nitrogen stable isotope measurements on N2O extracted \r\nfrom ice cores suggest that approximately one-third (of the order of \r\n0.7 +- 0.3TgN yr-1) of the deglacial increase in N2O emissions relates \r\nto oceanic sources (Schilt et al., 2014; H. Fischer et al., 2019)."


id: d25b92d14fc8ffed8d088e14ac322fc7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34362
content:
"The Last Deglacial Transition (LDT) is the best documented climatic \r\ntransition in the past associated with a substantial atmospheric CO2\r\nrise ranging from 190 to 265 ppm between 18-11 ka (Marcott et al., \r\n2014). The amplitude of the deglacial CO2 rise is thus on the same \r\norder of magnitude as the increase since the Industrial Revolution."


id: 3d5ad6caaba1466b9350db3bf4bb4a03
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7971
content:
"Boron isotope (d11B) data suggest a 0.15-0.05 unit decrease in sea \r\nsurface pH (Honisch and Hemming, 2005; Henehan et al., 2013) \r\nacross the LDT, an average rate of decline of about 0.002 units per \r\ncentury compared with the current rate of more than 0.1 units \r\nper century (Bopp et al., 2013; Gattuso et al., 2015). Planktonic \r\nforaminiferal shell weights decreased by 40% to 50% (Barker \r\nand Elderfield, 2002), and coccolith mass decreased by about \r\n25% (Beaufort et al., 2011) across the LDT.  Independent proxy \r\nreconstructions thus highlight with high confidence that pH values \r\ndecreased as atmospheric CO2 concentrations increased across the \r\nLDT. There is, however, low confidence in the inferred rate of ocean \r\nacidification owing to multiple sources of uncertainties affecting \r\nrates estimates based on marine sediments (Section 5.1.2.1)."


id: 9c0a63f4eed4cbfc3ff5e30bc6e5b014
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24706
content:
"Geochemical and micropaleontological evidence suggest that \r\nintermediate-depth OMZs almost vanished during the Last Glacial \r\nMaximum (LGM) (Jaccard et al., 2014). However, multiple lines of \r\nevidence suggest with medium confidence that the deep (>1500 m) \r\nocean became depleted in O2 (concentrations were possibly lower \r\nthan 50 mmol kg-1) globally (Jaccard and Galbraith, 2012; Hoogakker \r\net al., 2015, 2018; Gottschalk et al., 2016, 2020a; Anderson et al., \r\n2019) as a  combined result of sluggish ventilation of the ocean \r\nsubsurface (Gottschalk et al., 2016, 2020a; Skinner et al., 2017) and \r\na generally more efficient marine biological carbon pump (Buchanan \r\net al., 2016; Yamamoto et al., 2019; Galbraith and Skinner, 2020)."


id: 2cfa9e6c2c768699b82790ee176c8669
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5184
content:
"Overall, many of the records show a  highly variable seawater pH \r\nunderlaying strong imprints of internal climate variability (high \r\nconfidence) and, in most instances, superimposed on a decreasing \r\nd11B trend that is indicative of anthropogenic ocean acidification in \r\nrecent decades (medium confidence). The robustness of seawater \r\npH reconstructions is currently limited by the uncertainty on the \r\ncalibration of the d11B proxy in different tropical coral species."


id: 3d298ed7dc8e096d4c142530b095682a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7941
content:
"The SROCC (Section  5.2.2.3) indicated that it is virtually certain\r\nthat  the ocean has undergone acidification globally in response \r\nto ocean CO2 uptake, and concluded that pH in open ocean \r\nsurface water has changed by a  virtually certain range of -0.017 \r\nto -0.027 pH units per decade since the late 1980s. Since SROCC, \r\nevidence of the progress of acidification across all regions of the \r\noceans has been further strengthened by continued observations \r\nof seawater carbonate chemistry at ocean time series stations, \r\nand compiled shipboard studies providing temporally resolved and \r\nmethodologically consistent datasets (Jiang et al., 2019) (Figure 5.20; \r\nSupplementary Material Table 5.SM.3; Section 2.3.3.5)."


id: efcbbef6cbb5d99dc6ccf327ac5c50
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39576
content:
"In the subtropical open oceans, decreases in pH have been reported \r\nwith a  very likely rate range from -0.016 to -0.019 pH units per \r\ndecade since 1980s, which equates to approximately 4 % increase \r\nin hydrogen ion concentration ([H+]) per decade. Accordingly, the \r\nsaturation state O  (=[Ca2+][CO3\r\n2-]/Ksp) of seawater with respect to \r\ncalcium carbonate mineral aragonite has been declining at rates \r\nranging from -0.07 to -0.12 per decade (Gonzalez-Davila et al., \r\n2010; Feely et al., 2012; Bates et al., 2014; Takahashi et al., 2014; "


id: a471a5bdcaef5463370f451ec2cf7fa3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26139
content:
"In open subpolar and polar zones, the very likely range (-0.003 to \r\n-0.026 pH unit per decade) and uncertainty (up to 0.010) observed \r\nin pH decline are larger than in the subtropics, reflecting the complex \r\ninterplay between physical and biological forcing mechanisms \r\n(Olafsson et al., 2009; Midorikawa et al., 2012; Bates et al., 2014; "


id: 65437b2aec4bdd6fb60a2063022895e9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15094
content:
"Mid-latitudinal zones within the subtropical cells and tropical regions \r\npresent a  relatively deep and shallow detection, respectively. A  pH \r\ndecrease has also been observed on the Antarctic continental shelf \r\n(Hauck et al., 2010; Williams et al., 2015). Acidification is also underway \r\nin the subsurface to intermediate layers of the Arctic Ocean due to \r\nthe inflow of ventilated waters from the North Atlantic and the North \r\nPacific (Qi et al., 2017; Ulfsbo et al., 2018)."


id: e18651fab5b7828ce19f18b3f8e270f4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36948
content:
"Overall, in agreement with SROCC, it is virtually certain from these \r\nobservational studies that ocean surface waters undergo acidification \r\nglobally with the CO2 increase in the atmosphere. These sustained \r\nmeasurements over the past decades, and campaign studies of ocean \r\ncarbonate chemistry, also highlight with robust evidence that trends \r\nof acidification have been modulated by the variability and changes \r\nin physical and chemical states of ocean, including those affected by \r\nthe warming of the cryosphere, and need to be better understood."


id: 273179463d73a9e9f513984cd4e72d2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4059
content:
"These trends of acidification in the ocean interior lead to high \r\nconfidence in shoaling of the saturation horizons of calcium carbonate \r\nminerals where O  = 1. In the Pacific Ocean where the aragonite \r\nsaturation horizon is shallower (a few hundred metres to 1200 m; \r\nFigure 5.21c), the rate of its shoaling is in the order of 1-2 m yr-1\r\n(Feely et al., 2012; Ross et al., 2020). In contrast, shoaling rates of \r\n4 m yr-1 to 1710 m for 1984-2008 and of 10-15 m yr-1 to 2250 m for \r\n1991-2016 have been observed in the Iceland sea and the Irminger \r\nsea, respectively (Olafsson et al., 2009; Perez et al., 2018)."


id: 8eb70187c15e1a94ad23ee5b9b4326d7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22297
content:
"Advances in observations and modelling for ocean physics and \r\nbiogeochemistry and established knowledge of ocean carbonate \r\nchemistry show with very high confidence that anthropogenic CO2\r\ntaken up into the ocean surface layer is further spreading into the \r\nocean interior through ventilation processes, including vertical \r\nmixing, diffusion, subduction and meridional overturning circulations \r\n(Sections 2.3.3.5, 5.2.1.3 and 9.2.2.3; Sallee et al., 2012; Bopp et al., \r\n2015; Nakano et al., 2015; Iudicone et al., 2016; Toyama et al., 2017; \r\nPerez et al., 2018; Gruber et al., 2019b) and is causing acidification in \r\nthe ocean interior. The net change in oxygen consumption by aerobic \r\nrespiration of marine organisms further influences acidification by \r\nreleasing CO2 (Section  5.3.3.2; Chen et al., 2017; Breitburg et al., \r\n2018; Robinson, 2019)."


id: 828683cdf2dec343d6aa3c9ffead2432
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20093
content:
"In summary, ocean acidification is spreading into the ocean interior. \r\nIts rates at depths are controlled by the ventilation of the ocean \r\ninterior as well as anthropogenic CO2 uptake at the surface, thereby \r\ndiminishing with depth (very high confidence) (Figure 5.21). Variability \r\nin ocean circulation modulates the trend of ocean acidification at \r\ndepths through the changes in ventilation and their impacts on \r\nmetabolic CO2 content. However, the large knowledge gap around \r\nventilation changes leads to low confidence in their impacts in many \r\nocean regions (Sections 5.3.3.2; 9.2.2.3 and 9.3.2)."


id: 4f985478c2a923c54dc3b7df690b3458
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11291
content:
"Observations over past decades of basin-wide and global syntheses \r\nof ocean interior carbon show that the extent of acidification due to \r\nanthropogenic CO2 invasion tends to diminish with depth (very high \r\nconfidence) (Section 5.2.1.3.3 and Figure 5.21; Woosley et al., 2016; \r\nCarter et al., 2017; Lauvset et al., 2020). The regions of deep convection \r\nsuch as subpolar North Atlantic and Southern Ocean present the \r\ndeepest acidification detections below 2000 m (medium confidence). "


id: 2d10cf636dbe2365133f6d518934f29e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5204
content:
"As summarized in SROCC (Section  5.2.2.4), there is a  growing \r\nconsensus that between 1970 and 2010 the open ocean has \r\nvery likely lost 0.5-3.3% of its dissolved oxygen in the upper \r\n1000 m depth (Section 2.3.3.6; Helm et al., 2011; Ito et al., 2017; "


id: 9c6894069a9f4106c116b1a89910638b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24768
content:
"regions remains challenging (Levin, 2018; Oschlies et al., 2018). \r\nEarth system models (ESMs) in CMIP5 and CMIP6 corroborate the \r\ndecline in ocean oxygen, and project a continuing and accelerating \r\ndecline with a  strong impact of natural climate variability under \r\nhigh-emissions scenarios (Bopp et al., 2013; Long et al., 2016; \r\nKwiatkowski et al., 2020). However, CMIP5 models did not reproduce \r\nobserved patterns for oxygen changes in the tropical thermocline, \r\nand generally simulated only about half the oxygen loss inferred \r\nfrom observations (Oschlies et al., 2018). CMIP6 models have \r\na  more realistic simulated mean state of ocean biogeochemistry \r\nthan CMIP5 models due to improved ocean physical processes \r\nand better representation of biogeochemical processes (Seferian \r\net al., 2020). They also exhibit enhanced ocean warming as a result "


id: d4c0c78f431d93c78ed15a781fce87f1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34748
content:
"Schmidtko  et al.,  2017; Bindoff et al., 2019). Regionally, the \r\nequatorial and North Pacific, the Southern Ocean and the South \r\nAtlantic have shown the greatest oxygen loss of up to 30 mol m-2 per \r\ndecade (Schmidtko et al., 2017). Warming - via solubility reduction \r\nand circulation changes - mixing and respiration are considered the \r\nmajor drivers, with 50% of the oxygen loss for the upper 1000 m of \r\nthe global oceans attributable to the solubility reduction (Schmidtko \r\net al., 2017). Climate variability also modifies the oxygen loss on \r\ninterannual and decadal time scales especially for the tropical \r\nocean OMZs (Deutsch et al., 2011, 2014; Llanillo et al., 2013) and \r\nthe North Pacific subarctic zone (Whitney et al., 2007; Sasano et al., \r\n2018; Cummins and Ross, 2020). However, quantifying the oxygen \r\ndecline and variability and attributing them to processes in different "


id: bec5b58176c4014e4d0fcb779852172b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30830
content:
"uncertainties (Babbin et al., 2015; Trimmer et al., 2016; Landolfi et al., \r\n2017). Furthermore, the correlation between N2O and oxygen varies \r\nwith microorganisms present, nutrient concentrations, and other \r\nenvironmental variables (Voss et al., 2013)."


id: cde1d92c7808e7a4c5ed07a02c07b55c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33550
content:
"of an increase in the equilibrium climate sensitivity (ECS) of \r\nCMIP6 relative to CMIP5 models, which contributes to increased \r\nstratification and reduced subsurface ventilation (Sections  4.3.1, \r\n4.3.4, 5.3.3.2, 7.4.2, 7.5.6, 9.2.1, and TS2.4). Consequently, CMIP6 \r\nmodel ensembles reproduce the ocean deoxygenation trend \r\nof -0.30  to -1.52 mmol m-3 per decade between 1970-2010 \r\nreported in SROCC (Section 5.2.2.4) with a very likely range, and \r\nalso project 32-71% greater subsurface (100-600  m) oxygen \r\ndecline relative to their Representative Concentration Pathway \r\n(RCP) analogues in CMIP5, reaching to the likely range of decline of \r\n6.4 +- 2.9 mmol m-3 under SSP1-2.6 and 13.3 +- 5.3 mmol m-3 under \r\nSSP5-8.5, from 1870-1899 to 2080-2099 (Kwiatkowski et al., \r\n2020). It is concluded that the oxygen content of subsurface ocean \r\nis projected to transition to historically unprecedented condition \r\nwith decline over the 21st century (medium confidence)."


id: 497d17f7df86e437303022c8108468d6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10154
content:
"In summary, total oceanic N2O emissions were projected to decline \r\nby 4-12% from 2005-2100 (Martinez-Rey et al., 2015) and by 24% \r\nfrom the pre-industrial era to 2100 (Landolfi et al., 2017) under \r\nRCP8.5. However, there is low confidence in the reduction in N2O \r\nemissions to the atmosphere, because of large conceptual and \r\nparametric uncertainties, a limited number of modelling studies that \r\nexplored this process, and greater oxygen losses simulated in CMIP6 \r\nmodels than in CMIP5 models (Kwiatkowski et al., 2020)."


id: 843a1121a913a01c923b7ed8b29a7e3a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20418
content:
"In surface ocean, changes in the amplitude of seasonal variations in \r\npH are also projected to occur with high confidence. ESMs in CMIP6 \r\nshow +73 +-  12% increase in the amplitude of seasonal variation \r\nin hydrogen ion concentration ([H+]) but 10 +- 5% decrease in the \r\nseasonal variation in pH (= -log [H+]) from 1995-2014 to 2080-\r\n2099 under SSP5-8.5. The simultaneous amplification of [H+] and \r\nattenuation of pH seasonal cycles is counterintuitive but is the \r\nconsequence of a  greater increase in the annual mean [H+] due \r\nto anthropogenic CO2 invasion than the corresponding increase \r\nin its seasonal amplitude. These changes are consistent with the \r\namplification/attenuation of the seasonal variation of +81 +-16% for "


id: 96bd2f0bb49937eb11c59c45bae80116
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23724
content:
"to decrease as atmospheric CO2 decreases (Sections  5.4.5, 5.4.10 \r\nand 5.6.2.1; Mathesius et al., 2015; Tokarska and Zickfeld, 2015). \r\nHowever, because of the long time scales of the ocean turnover that \r\ntransfers CO2 from the upper to the deep ocean, excess carbon will \r\ncontinue to accumulate in the deep ocean even after a decrease in \r\natmospheric CO2 (Cao et al., 2014; Mathesius et al., 2015; Tokarska \r\nand Zickfeld, 2015; T. Li et al., 2020). There is thus high confidence\r\nthat CO2 emissions leave a long-term legacy in ocean acidification, \r\nand are therefore irreversible at multi-human generational scales, \r\neven with aggressive atmospheric CO2 removal."


id: c4e48b1a842c683df699d85446eca3ba
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31948
content:
"The coastal ocean, from the shoreline to the isobath of 200  m, is \r\nhighly heterogeneous due to the complex interplay between \r\nphysical, biogeochemical and anthropogenic factors (Gattuso et al., \r\n1998; Chen and Borges, 2009; Durr et al., 2011; Laruelle et al., 2014; \r\nMcCormack et al., 2016). These areas, according to SROCC (Bindoff \r\net al., 2019) are, with high confidence, already affected by ocean \r\nacidification and deoxygenation. This section assesses the drivers \r\nand spatial variability of acidification and deoxygenation based on \r\nnew observations and data products."


id: 44eb15e3c0c2a8dc8af2351c153d4c69
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9355
content:
"Overall, with the rise of atmospheric CO2, the physics of CO2 transfer \r\nacross the air-sea interface, the carbonate chemistry in seawater, \r\nthe trends of ocean acidification being observed in the past decades \r\n(Section 5.3.3.2) and modelling studies described in this section, it \r\nis virtually certain that ocean acidification will continue to grow. \r\nHowever, the magnitude and sign (direction) of many of ocean \r\ncarbon-climate feedbacks are still poorly constrained (Matear and \r\nLenton, 2014, 2018), leading to low confidence in their significant \r\nand long-lasting impacts on ocean acidification."


id: b71fa25e19a1d02f153db09e977fb00
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29429
content:
"Reversing the increase in atmospheric CO2 concentrations through \r\nnegative emissions (Section  5.6) will reverse ocean acidification \r\nat the sea surface (high confidence) but will not result in \r\nrapid amelioration of ocean acidification in the deeper ocean \r\n(Section 5.3.3.2). The ocean's uptake of atmospheric CO2 will start "


id: ec44f1532ccde5bf8b609c3d1c3b37ee
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38932
content:
"Since AR5, (Ciais et al., 2013) and in agreement with SROCC (IPCC, \r\n2019b), there is now high agreement (robust evidence) that coastal "


id: 55f78910dfb0037bffa36fada44ce00
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12399
content:
"temperate north-east Pacific and north-west Atlantic, the mean time \r\nof emergence for acidification is above two decades (Sutton et al., \r\n2019; Turk et al., 2019)."


id: edffab8a9a9f0e6d2f154f53e4ac7fc3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39247
content:
"ocean acidification, whether induced only by increasing atmospheric \r\nCO2 or exacerbated by eutrophication or upwelling, has negative \r\neffects on specific groups of marine organisms such as reef-building \r\ncorals, crabs, pteropods, and sessile fauna (AR6 WGII, Chapter  3; \r\nDupont et al., 2010; Bindoff et al., 2019; Bednarsek et al., 2020; \r\nOsborne et al., 2020), especially when combined with stressors \r\nsuch as temperature and deoxygenation, and potentially increased \r\nbioavailability of toxic elements such as arsenic and copper (Millero \r\net al., 2009; Boyd et al., 2015; Breitburg et al., 2018)."


id: 7b700b418bca02c6459f78ad193bb3d4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18918
content:
"Many coastal tropical areas are under heavy anthropogenic \r\neutrophication induced by the effluents from large cities, or \r\nreceive large riverine inputs of freshwater, nutrients, and organic \r\nmatter (such as Amazon, Mississippi, Orinoco, Congo, Mekong, or \r\nChangjiang rivers). Under strong eutrophication, often sub-surface \r\nand bottom waters present pH values lower than average surface \r\nopen ocean (about 8.0) because increased respiration decreases pH \r\n(high agreement, robust evidence), despite a  net atmospheric CO2\r\nsink in shallow and vertically stratified coastal areas (Kone et al., \r\n2009; Wallace et al., 2014; Cotovicz Jr. et al., 2015, 2018; Fennel and \r\nTesta, 2019; Lowe et al., 2019; Section 5.3.5.1)."


id: ed34ab22bc84a466accf622bfbe82959
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39114
content:
"There is high agreement (robust evidence) that heterogeneity implies \r\ndifferent responses of coastal regions to increasing atmospheric CO2, \r\ndecreasing seawater pH and calcium carbonate saturation state, and \r\ndeoxygenation (Duarte et al., 2013; Regnier et al., 2013; Breitburg \r\net al., 2018; Laruelle et al., 2018; Carstensen and Duarte, 2019)."


id: 3e1aec0c53e99bdc136f601eae7e9d79
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8097
content:
"There is high agreement that long-time series of observations \r\nutilizing standard methods are needed to distinguish the climate \r\nchange signal in seawater carbonate chemistry from the natural \r\nvariability of coastal sites (Duarte et al., 2013; Salisbury and Jonsson, \r\n2018; IOC, 2019; Sutton et al., 2019; Tilbrook et al., 2019; Turk et al., \r\n2019). Despite the increasing availability of data and sea-air CO2\r\nflux budgets for the coastal ocean (Sections  5.3.5.1 and 5.2.3.1), \r\nadditional long-term observations are required to constrain the \r\nglobal time of emergence of coastal acidification. There is high \r\nagreement (medium evidence) that, for the coastal subtropical to "


id: bb516eef1da338412c29b262ad14485e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30173
content:
"There is medium evidence from observations and models that \r\nthe coastal north-western Antarctic Peninsula (Southern Ocean) \r\nwill experience calcium carbonate undersaturation by 2060, \r\nconsidering that anthropogenic emissions reach an atmospheric CO2\r\nconcentration of about 500 pm at that date (Lencina-Avila et al., \r\n2018; Monteiro et al., 2020a). The synergies among warming, melt \r\nwater, sea-air CO2 equilibrium and circulation may, to some extent, "


id: d698f2413b33c01390c9370d37de7929
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35059
content:
"offset the coastal ocean acidification trends in Antarctica (Henley \r\net al., 2020). In the coastal western Arctic Ocean, there is increasing \r\nrobust evidence that ocean acidification is driven by sea-air CO2 fluxes \r\nand sea-ice melt, and increasing intrusions since the 1990s of low\u0002alkalinity Pacific water, lowering aragonite saturation state (Qi et al., \r\n2017, 2020; Cross et al., 2018). The Bering Sea (north-eastern Pacific) \r\nshows decreasing trends in calcium carbonate saturation, associated \r\nto the increasing atmospheric CO2 uptake combined with riverine \r\nfreshwater and carbon inputs (high agreement, robust evidence) \r\n(Pilcher et al., 2019; H. Sun et al., 2020)."


id: bc501f4b780689667253d7d9337af34d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30375
content:
"(Section  5.4.7), combined feedback assessment (Section  5.4.8), \r\npossible biogeochemical abrupt changes (Section 5.4.9), long-term \r\ncarbon cycle projections (Section 5.4.10), and near-term prediction of \r\nocean and land carbon sinks (5.4.11)."


id: d26d26d872fac01b9a9c5332942c91fa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34380
content:
"The spatial distribution of hypoxic areas is highly heterogeneous \r\nin the coastal ocean, and there is high agreement, robust evidence\r\nthat more severe hypoxia or anoxia is often associated with highly \r\npopulated coastal areas, or local circulation and upwelling, and \r\nseasonal stratification leading to an accumulation of organic matter \r\nin subsurface waters (Ciais et al., 2013; Rabalais et al., 2014; M. Li \r\net al., 2016; Breitburg et al., 2018; Bindoff et al., 2019; SROCC \r\nChapter 5). The causes and trends of coastal deoxygenation can only \r\nbe assessed by making available long-term time series combined \r\nwith regional modelling (Fennel and Testa, 2019), as in the California \r\ncurrent system (Wang et al., 2017), the East China Sea (Chen et al., \r\n2007; Qian et al., 2017), the Namibian or along the north-western \r\nAtlantic shelves (Claret et al., 2018). Other coastal upwelling sites \r\nsuch as the Arabian Sea display seasonal hypoxia but no worsening \r\ntrends (Gupta et al., 2016)."


id: f61e2170be20b219ee248b1dd8ea14ee
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40660
content:
"The Baltic Sea is the largest semi-enclosed sea where hypoxia is \r\nreported to have happened before the 1950s (Carstensen et al., \r\n2014; Rabalais et al., 2014; Lukawska-Matuszewska et al., 2019). \r\nThe frequency and volume of seawater inflow from the North Sea \r\ndecreased after 1950, leading to an expansion of hypoxic areas from \r\n40,000 to 60,000 km2 in combination with increasing eutrophication \r\n(Carstensen et al., 2014). From the available observations, there is \r\nrobust evidence that many areas in the Baltic Sea are experiencing \r\ndeoxygenation despite efforts to reduce nutrient loads (Lennartz \r\net al., 2014; Jokinen et al., 2018)."


id: 7b8f7ea804449d13f2adcb5404074c31
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18945
content:
"There is medium agreement (medium evidence) that simply reducing \r\nanthropogenic nutrient inputs may lead to less severe coastal \r\nhypoxic conditions, as observed in the coastal north-western Adriatic \r\nSea (Djakovac et al., 2015). However, low-oxygen sediments may \r\nremain a  long-term source of phosphorus and ammonium to the \r\nwater column, and in this way fuelling primary production (Jokinen \r\net al., 2018; Fennel and Testa, 2019; Limburg et al., 2020)."


id: e503efede864c2f70bbcdece7627173f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37584
content:
"This section covers biogeochemical feedbacks on climate change, which \r\nrepresent one of the largest sources of uncertainty in climate change \r\nprojections. The relevant processes are discussed (Sections  5.4.1 \r\nto 5.4.4), prior to discussing the simulation and projection of the \r\ncarbon cycle in Earth system models (Section  5.4.5), emergent \r\nconstraints on future projections (Section 5.4.6), non-CO2 feedbacks "


id: 2aa6219de4d691b3561293cf55144085
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4731
content:
"Our understanding of the various biological processes that affect \r\nthe strength of the CO2 fertilization effect on photosynthesis and \r\nits impact on carbon storage in vegetation and soils, (in particular \r\nregarding the limitations imposed by nitrogen and phosphorus \r\navailability), has developed since AR5 (WGI, Box  6.2). Based on \r\nconsistent behaviour across all CMIP6 ESMs, there is high confidence \r\nthat CO2 fertilization of photosynthesis acts as an important negative \r\nfeedback on anthropogenic climate change, by reducing the rate at \r\nwhich CO2 accumulates in the atmosphere. Since AR5 (WGI, Box 6.2), \r\nan increasing number of CMIP6 ESMs account for nutrient cycles. \r\nThe consistent results found in their model projections suggests with \r\nhigh confidence that limited nutrient availability will limit the CO2\r\nfertilization effect (Arora et al., 2020). The magnitude of the direct \r\nCO2 effect on land carbon uptake, and its limitation by nutrients, \r\nremains uncertain."


id: 5ebca5d5548231fcadfce87575789c4d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13957
content:
"In AR5 (WGI, Section 6.4.2) there was high agreement that CMIP5 \r\nESMs project continued ocean CO2 uptake through to 2100, with \r\nhigher uptake corresponding to higher concentration or emissions \r\npathways. There has been no significant change in the magnitude \r\nof the sensitivity of ocean carbon uptake to increasing atmospheric \r\nCO2, or in the inter-model spread, between the CMIP5 and CMIP6 era \r\n(Arora et al., 2020). The analysis from emissions and concentration\u0002driven CMIP5 model projections show that the ocean sink stops \r\ngrowing beyond 2050 across all emissions scenarios (Section 5.4.5.3). \r\nCMIP6 models also show a similar time evolution of global ocean \r\nCO2 uptake to CMIP5 models over the 21st century (Figure  5.25) \r\nwith decreasing net ocean CO2 uptake ratio to anthropogenic CO2\r\nemissions under SSP5-8.5."


id: e07b3cf2839225fae11103b09a862dff
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36748
content:
"Consistent with AR5 (WGI, Section 6.4.2), the CO2 fertilization effectis \r\nthe dominant cause for the projected increase in land carbon uptake \r\nbetween 1860 and 2100 in ESMs (Figures 5.26 and 5.27, and Table 5.5; \r\nArora et al., 2020). In the CMIP6 ensemble, the increase of land carbon \r\nstorage due to CO2 fertilization is a global phenomenon but is strongest \r\nin the tropics (Figure 5.26). The resulting increase of productivity is a key \r\ndriver of increases in vegetation and soil carbon storage. However, \r\nconsistent with earlier findings (Todd-Brown et al., 2013; Friend et al., \r\n2014; Hajima et al., 2014), processes affecting vegetation carbon-use \r\nefficiency and turnover, such as allocation changes, mortality, and \r\nvegetation structural changes, as well as the pre-industrial soil carbon \r\nturnover time, also play an important role (Arora et al., 2020)."


id: e3a579527c32e5b927868e223ffd497
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37342
content:
"Projected increases in ocean DIC due to anthropogenic CO2 uptake \r\namplify the sensitivity of carbonate system variables to perturbations \r\nof DIC in the surface ocean, for example via the amplitude of the \r\nseasonal cycle of pCO2, which impacts the mean annual air-sea fluxes \r\n(Hauck et al., 2015; Fassbender et al., 2018; Landschutzer et al., 2018; \r\nSROCC, Section 5.2.2.3). A larger amplification of the surface ocean \r\npCO2 seasonality occurs in the subtropics where pCO2 seasonality is \r\ndominated by temperature seasonality, with the summer increase \r\nin the difference in pCO2 between surface water and the overlying \r\natmosphere reaching 3matm per decade between 1990 and 2030 \r\nunder RCP8.5 (Schlunegger et al., 2019; Rodgers et al., 2020). In \r\ncontrast, the impact of biological production on the seasonal cycle of \r\npCO2 in summer in the Southern Ocean strengthens the drawdown \r\nof CO2 (Hauck et al., 2015)."


id: 3c203d577dc597323267738c81fe719
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7768
content:
"its control by leaf stomata, and the resulting soil and plant tissue \r\nwater content. Thus the direct effect of warming on photosynthesis \r\ncan be positive, negative, or invariant depending on the environmental \r\ncontext (Lin et al., 2012; Yamori et al., 2014; Smith and Dukes, 2017; \r\nGrossiord et al., 2020). Observations and models suggest that the \r\nvapour pressure deficit effects are stronger than direct temperature \r\neffects on enzyme activities (Smith et al., 2020), and that acclimation \r\nof photosynthetic optimal temperature may mitigate productivity \r\nlosses of tropical forests under climate change (Kattge and Knorr, \r\n2007; Tan et al., 2017; Kumarathunge et al., 2019). Some models have \r\nbegun to include these acclimation responses in photosynthesis and \r\nautotrophic respiration (Lombardozzi et al., 2015; Smith et al., 2015; \r\nHuntingford et al., 2017; Mercado et al., 2018)."


id: e132585b0a6b6a38d0b277e7baa1f872
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36886
content:
"Overall, there is medium confidence on three outcomes in the ocean \r\nfrom projected CO2 uptake under medium to high CO2 concentration \r\nscenarios: (i) a weakening of the buffering capacity, which impacts \r\nthe airborne fraction via the reduction of the ocean CO2 buffering \r\ncapacity due to cumulative ocean CO2 uptake, which reduces \r\nthe net ocean CO2 uptake ratio to anthropogenic CO2 emissions \r\n(Katavouta et al., 2018; Arora et al., 2020; Rodgers et al., 2020); \r\n(ii) an amplification of the seasonal cycle of CO2 variables, which \r\nimpacts both the ocean sink and ocean acidification (Hauck et al., \r\n2015); (iii) a decrease in the aragonite and calcite saturation levels in \r\nthe ocean, which negatively impacts the calcification rates of marine \r\norganisms (high confidence) and forms a negative feedback on the \r\nuptake of CO2 (McNeil and Sasse, 2016) (Cross-Chapter Box 5.3)."


id: 64e8dc10e7f60ac661b7df9e4040c8f3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15026
content:
"The SRCCL assessed that climate change is playing an increasing role \r\nin determining wildfire regimes alongside human activity (medium \r\nconfidence), with future climate variability expected to enhance the \r\nrecurrence and severity of wildfires in many biomes, such as tropical \r\nrainforests (high confidence). Projections of increased fire weather in \r\na warmer climate are widespread (Section 12.3.2.8) and may drive \r\nincreased fire frequency and severity in several regions, including \r\nArctic and boreal ecosystems (Gauthier et al., 2015; X.J.  Walker \r\net al.,  2019), Mediterranean-type ecosystems (Turco et al., 2014; \r\nJin et al., 2015), degraded tropical forests (Aragao et al., 2018), and \r\ntropical forest-savanna transition zones (Lehmann et al., 2014)."


id: fb7b78d4ae75b25172e000a6bc38eae2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41618
content:
"Wildfire is included in some CMIP6 ESMs (Table  5.4) and is thus \r\nonly partially represented in estimates of carbon-climate feedbacks \r\nfrom these models. The CMIP5 ESMs that include fire project an \r\n8-58% increase of fire carbon emissions under future scenarios, with \r\nhigher emissions under higher warming scenarios; the ensemble \r\nspread is driven by differing factors such as population density, fire \r\nmanagement, and other land-use processes (Kloster and Lasslop, \r\n2017). Fire dynamics in CMIP6 models, as evaluated in land-only \r\nconfigurations of CMIP6-generation land surface models, also show \r\nlarge variations but better agreement with observations (Teckentrup \r\net al., 2019; Hantson et al., 2020; Lasslop et al., 2020)."


id: d1a6741551de5f24fa89746c244df5df
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34234
content:
"The AR5 assessed with medium confidence that future climate \r\nchange will decrease land carbon uptake relative to the case with \r\nconstant climate, but with a  poorly constrained magnitude (AR5 \r\nWGI, Chapter  6, Executive Summary). Ongoing uncertainty in the \r\nmagnitude and geographic pattern of the feedbacks (Section 5.4.5), \r\ncontinues to support a medium confidence assessment that future \r\nclimate change will decrease land carbon uptake relative to the case \r\nwith constant climate."


id: 6fed51f5ea25d8d20da3bfebffe81c4f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 16946
content:
"Plant productivity is highly dependent on local climate. In cold \r\nenvironments, warming has generally led to an earlier onset of the \r\ngrowing season, and with it an increase in early season vegetation \r\nproductivity (e.g., Forkel et al., 2016). However, this trend is affected \r\nby the adverse effects of climate variability, and other emerging \r\nlimitations on vegetation production by water, energy and nutrients, \r\nwhich may gradually reduce the effects of warming (Piao et al., 2017; \r\nBuermann et al., 2018; Liu et al., 2019). At centennial time scales, \r\nboreal forest expansion may act as a  climate-driven carbon sink \r\n(Pugh et al., 2018)."


id: 916ae2a80e699f760ea14622a258709c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22796
content:
"et al., 2018; Varney et al., 2020), although experimental soil warming \r\nin tropical forests suggest high sensitivity of decomposition to \r\nwarming in those regions as well (Nottingham et al., 2020)."


id: dd827cbddd3c1b0703b177d32bb64371
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36239
content:
"Allen et al., 2015; McDowell et al., 2018; Grossiord et al., 2020), and \r\nthat these processes are not well represented in ESMs (Powell et al., \r\n2013; Fisher et al., 2018). An ensemble of land models that includes \r\necological processes such as forest demography shows that changes \r\nto mortality may be a more important driver of carbon dynamics than \r\nchanges to productivity (Friend et al., 2014)."


id: 82b0e7c8fc3c2f46bea09f58d4964e0e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20127
content:
"Peat soils, where thick organic layers build up due to saturated \r\nand anoxic conditions, represent another possible source of carbon \r\nto the atmosphere. Peats could dry, and decompose or burn as \r\na  result of climate change in both high (Chaudhary et al., 2020) \r\nand tropical (Cobb et al., 2017) latitudes, and in combination with \r\nanthropogenic drainage of peatlands (Warren et al., 2017). Peat \r\ncarbon dynamics are not included in the majority of CMIP6 ESMs."


id: eaef531da3f3b5893b2defad662f0dde
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38695
content:
"Overall, climate change will force widespread increases in fire weather \r\nthroughout the world (Section  12.3.2.8). Because of incomplete \r\ninclusion of fire in ESMs, a  separate compilation of fire-driven \r\ncarbon-climate feedback estimates is shown in Figure 5.29, based \r\non results from Eliseev et al. (2014a) and Harrison et al. (2018). There \r\nis low agreement in magnitude and medium agreement in sign which \r\nleads to an assessment of medium confidence that fire represents \r\na positive carbon-climate feedback, but very low confidence in the \r\nmagnitude of that feedback. Other disturbances such as tree mortality \r\nwill increase across several ecosystems (medium agreement) with \r\ndecreased vegetation carbon (medium confidence). However, the \r\nlack of model agreement and key process representation in ESMs \r\nleads to a  low confidence assessment in the projected magnitude \r\nof this feedback."


id: 957e4f5316a927f2b858f4689b3ab526
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23503
content:
"Soil microbial dynamics shift in response to temperature, giving \r\nrise to complex longer-term trophic effects that are more complex \r\nthan the short-term sensitivity of decomposition to temperature. \r\nSuch responses are observed in response to long-term warming \r\nexperiments (Melillo et al., 2017). While most CMIP6 ESMs do not \r\ninclude microbial dynamics, simplified global soil models that do \r\ninclude such dynamics show greater uncertainty in projections of \r\nsoil carbon changes, despite agreeing more closely with current \r\nobservations, than the linear models used in most ESMs (Wieder \r\net al., 2013; Guenet et al., 2018)."


id: e5bd2195f0a783dd206f45024fafa4a6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37725
content:
"Changes to soil carbon stocks in response to climate change are \r\na potentially strong positive feedback (Cox et al., 2000). Since AR5 \r\n(WGI, Section 6.4.2), progress has been made in understanding soil \r\ncarbon dynamics, and associated feedbacks. Advances include: (i) \r\nan increased understanding of and ability to quantify high-latitude \r\nsoil carbon feedbacks (Box 5.1); (ii) increased understanding of the \r\ncauses responsible for soil carbon persistence on long time scales, \r\nparticularly the interactions between decomposers and soil organic \r\nmatter and mineral assemblages (Kleber et al., 2007; Schmidt \r\net al., 2011; Luo et al., 2016); and (iii) increased understanding of \r\nsoil carbon dynamics in subsurface layers (Hicks Pries et al., 2017; \r\nBalesdent et al., 2018)."


id: e1e1ada3bc61f79ec1272966f1aaf901
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37024
content:
"The high agreement and multiple lines of evidence that warming \r\nincreases decomposition rates lead to high confidence that \r\nwarming will, overall, result in carbon losses relative to a constant \r\nclimate and contribute to the positive carbon-climate feedback \r\n(Section 5.4.8). However, the wide spread in ESM projections and the \r\nlack of model representation of key processes that may amplify or \r\nmitigate soil carbon losses on longer time scales (including microbial \r\ndynamics, permafrost, peatlands, and nutrients) lead to low confidence\r\nin the magnitude of global soil carbon losses with warming."


id: 7fe7661a2433906b054598134c0b46fb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19641
content:
"What is permafrost carbon and why should we be concerned about it?\r\nSoils in the Arctic and other cold regions contain perennially frozen layers, known as permafrost. Soils in the northern permafrost region \r\nstore a large amount of organic carbon, estimated at 1460-1600 PgC across surface soils and deeper deposits (Hugelius et al., 2014; \r\nStrauss et al., 2017; Mishra et al., 2021). Of that carbon, permafrost soils and deposits store 1070-1360 PgC, of which 300-400 PgC \r\nare in the first metre, and the rest at depth. The remaining 280-340 PgC are in permafrost-free soils within the permafrost region. \r\nThese carbon deposits have accumulated over thousands of years due to the slow rates of organic matter decomposition in frozen \r\nand/or waterlogged soil layers, but these frozen soils are highly decomposable upon thaw (Schadel et al., 2014)."


id: 577a59635b2529e3203cb13c0933d94f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12656
content:
"Is permafrost carbon already thawing and emitting greenhouse gases?\r\nThe permafrost region was a historic carbon sink over centuries to millennia (high confidence) (Loisel et al., 2014; Lindgren et al., \r\n2018). Currently though, thawing soils due to anthropogenic warming are losing carbon from the decomposition of old frozen organic \r\nmatter, as found via carbon 14 (14C) signature of respiration at sites undergoing rapid permafrost thaw (Hicks Pries et al., 2013), of \r\ndissolved organic carbon in rivers draining watersheds with permafrost thaw (Vonk et al., 2015; Wild et al., 2019), and of methane \r\n(CH4) produced in thawing lakes (Walter Anthony et al., 2016)."


id: d674f443ce44b6b133d612c9c48ac9e7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35035
content:
"Since AR5, evidence of a more active carbon cycle in the northern high-latitude regions has also been observed through the increased \r\namplitude of CO2 seasonal cycles. However, the relative roles of local sources versus influence from mid-latitudes makes it difficult to infer \r\nchanges to Arctic ecosystems from these observations (Graven et al., 2013; Forkel et al., 2016; Takata et al., 2017; Bruhwiler et al., 2021). \r\nEstimates of CO2 fluxes with atmospheric inversion models showed an enhanced seasonal cycle amplitude but no significant trends in \r\nannual total fluxes, in agreement with flux tower measurements over one decade (2004-2013) (Welp et al., 2016; Takata et al., 2017)."


id: ccec1e3430893280d53c8c26aa5a9525
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33396
content:
"Atmospheric measurements and inversions performed at the global and regional scales do not show any detectable trends in annual \r\nmean CH4 emissions from the permafrost region over the past 30 years (Jackson et al., 2020; Saunois et al., 2020; Bruhwiler et al., \r\n2021), consistent with atmospheric measurements in Alaska that showed no significant annual trends, despite significant increase in air \r\ntemperature (Sweeney et al., 2016). Atmospheric inversions and biospheric models do not show any clear trends in CH4 emissions for \r\nwetland regions of the high latitudes during the period 2000-2016 (Patra et al., 2016; Poulter et al., 2017; Jackson et al., 2020; Saunois \r\net al., 2020). Large uncertainties on wetland extent and limited data constraints place low confidence in these modelling approaches."


id: 45403517b507000643fbf4cf55dffe5e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9410
content:
"The SROCC also assessed with high confidence that CH4 fluxes have been under-observed due to their high variability at multiple scales \r\nin both space and time, and that there is a persistent mismatch between top-down and bottom-up methane budgets, with emissions \r\ncalculated by upscaling ground observations typically higher than emissions inferred from large-scale atmospheric observations \r\n(Thornton et al., 2016a; Saunois et al., 2020)."


id: 87b3e9aebc4101495d8ae39d6ba74988
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21033
content:
"In conclusion, there is high confidence that the permafrost region has acted as a historic carbon sink over centuries to millennia, and \r\nhigh confidence that some permafrost regions are currently net sources of CO2. There is robust evidence that some CH4 emissions \r\nsources for some regions have increased over the past decades (medium confidence). For the northern permafrost-wide region, \r\nno multi-decadal trend has been detected on CO2 and CH4 fluxes but, given the low resolution and sparse observations of current \r\nobservations and modelling sytems, we place low confidence in this statement."


id: 7777189cbcf13db8cd3fb1c46d4acbcc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18223
content:
"Since AR5, there have been new studies showing that permafrost thaw also leads to nitrous oxide (N2O) release from soil (Abbott and \r\nJones, 2015; Karelin et al., 2017; Wilkerson et al., 2019), a previously unaccounted source. However, this release is unquantified at the \r\npan-Arctic scale."


id: 8c8089dcdd7f720e276c9f2b20f22f29
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21903
content:
"Large areas of Alaska and Siberia are underlain by frozen, glacial-age, ice- and carbon-rich deposits, and many of these areas show \r\nevidence of thermokarst processes during Holocene warm periods. Rapid warming of high northern latitudes contributed to permafrost \r\nthaw, liberating labile organic carbon to the atmosphere (Kohler et al., 2014; Crichton et al., 2016; Winterfeld et al., 2018; Meyer et al., \r\n2019), supporting the vulnerability of these areas to further warming (Strauss et al., 2013, 2017)."


id: d56c6c4b51b06b7de47b5b7048f97b41
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34865
content:
"In conclusion, several independent lines of evidence indicate that permafrost thaw did not release vast quantities of fossil CH4\r\nassociated with the transient warming events of the LDT. This suggests that large emissions of CH4 from old carbon sources will not \r\noccur in response to future warming (medium confidence)."


id: 9af79fb63fdc9b0627f4909af7f09097
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24511
content:
"What level of emissions do we expect in the future?\r\nNear-surface permafrost is projected to decrease significantly under future global warming scenarios (high confidence) (Section 9.5.2), \r\nthus creating the potential for releasing CO2 and CH4 to the atmosphere, and act as a positive carbon-climate feedback."


id: 35070558cf42073574e1da4ea16fea64
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6575
content:
"Through the Coupled Model Intercomparison Project Phase 5 (CMIP5), Earth system models (ESMs) had not included permafrost carbon \r\ndynamics. This remains largely true in Coupled Model Intercomparison Project Phase 6 (CMIP6), with most models not representing \r\npermafrost carbon processes, a small number representing the active-layer thickening effect on decomposition (Table 5.4), and no \r\nESMs representing thermokarst or fire-permafrost-carbon interactions. The CMIP6 ensemble mean predicts a negative carbon-climate \r\nfeedback in the permafrost region. However, those that do include permafrost carbon show a positive carbon-climate feedback in the "


id: 8adbbb4060137e88e6b6d9e8b8a9aec4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21600
content:
"permafrost region (Figure 5.27). Given the current limited ESM capacity to assess permafrost feedbacks, estimates in this report are \r\nbased on published permafrost-enabled land surface model results."


id: 30b659e0275eb78ca84fe608bc8c25ab
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5824
content:
"The SROCC assessed that warming under a high-emissions scenario (RCP8.5 or similar) would result in a loss of permafrost carbon by \r\n2100 of 10s to 100s of PgC, with a maximum estimate of 240 PgC and a best estimate of 92 +- 17 PgC (Meredith et al., 2019; SROCC, \r\nFigure 3.11). Under lower emissions scenarios, Schneider von Deimling et al. (2015) estimated permafrost feedbacks of 20-58 PgC of \r\nCO2 by 2100 under an RCP2.6 scenario, and 28-92 PgC of CO2 under an RCP4.5 scenario."


id: cf9c6d7004993618f42523943b85cd40
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33884
content:
"This new assessment, based on studies included in or published since SROCC (Schaefer et al., 2014; Koven et al., 2015c; Schneider von \r\nDeimling et al., 2015; Schuur et al., 2015; MacDougall and Knutti, 2016a; Gasser et al., 2018; Yokohata et al., 2020), estimates that \r\nthe permafrost CO2 feedback per degree of global warming (Figure 5.29) is 18 [3.1 to 41, 5-95% range] PgC degC-1. The assessment \r\nis based on a  wide range of scenarios evaluated at 2100, and an assessed estimate of the permafrost CH4-climate feedback at \r\n2.8 [0.7 to 7.3] PgCeq degC-1 (Figure 5.29). This feedback affects the remaining carbon budgets for climate stabilization and is included \r\nin their assessment (Section 5.5.2)."


id: ad1fc376e381fee04231aa0ecc7fe166
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27699
content:
"Beyond 2100, models suggest that the magnitude of the permafrost carbon feedback strengthens considerably over the period \r\n2100-2300 under a high-emissions scenario (Schneider von Deimling et al., 2015; McGuire et al., 2018). Schneider von Deimling et al. \r\n(2015) estimated that thawing permafrost could release 20-40 PgC of CO2 in the period from 2100 to 2300 under an RCP2.6 scenario, \r\nand 115-172 PgC of CO2 under an RCP8.5 scenario. The multi-model ensemble (McGuire et al., 2018) projects a much wider range of \r\npermafrost soil carbon losses of 81-642 PgC (mean 314 PgC) for an RCP8.5 scenario from 2100 to 2300, and of a gain of 14 PgC to \r\na loss of 54 PgC (mean loss of 17 PgC) for an RCP4.5 scenario over the same period."


id: dbdd593c673c706f38a3fb166375d183
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35968
content:
"Methane release from permafrost thaw (including abrupt thaw) under a  high-warming RCP8.5 scenario has been estimated at \r\n836-2614 Tg CH4 over the 21st century and 2800-7400 Tg CH4 from 2100-2300 (Schneider von Deimling et al., 2015), and as \r\n5300 Tg CH4 over the 21st century and 16,000 Tg CH4 from 2100-2300 (Turetsky et al., 2020). For RCP4.5, these numbers are 538-\r\n2356 Tg CH4 until 2100 and 2000-6100 Tg CH4 from 2100-2300 (Schneider von Deimling et al., 2015), and 4100 Tg CH4 until 2100 \r\nand 10,000 Tg CH4 from 2100-2300 (Turetsky et al., 2020)."


id: 450a412476c5ca894bfd7c78e629f02b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 9373
content:
"A key uncertainty is whether permafrost carbon feedbacks scale roughly linearly with warming (Koven et al., 2015c), or instead scale at \r\na greater (MacDougall and Knutti, 2016b; McGuire et al., 2018) or smaller rate (e.g., CH4 emissions estimated by Turetsky et al., 2020). \r\nIt also remains unclear whether the permafrost carbon pool represents a coherent global tipping element of the Earth system with a single \r\nabrupt threshold (Drijfhout et al., 2015) at a given level of global warming, or a local scale tipping point without abrupt thresholds when \r\naggregated across the pan-Arctic region, as is suggested by recent model results (e.g., Koven et al., 2015a; McGuire et al., 2018)."


id: 3118d647f17e95ccf24ad3130feb6dbf
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5887
content:
"In conclusion, thawing terrestrial permafrost will lead to carbon release under a warmer world (high confidence). However, there \r\nis low confidence on the timing, magnitude and linearity of the permafrost climate feedback owing to the wide range of published \r\nestimates and the incomplete knowledge and representation in models of drivers and relationships. It is projected that CO2 released \r\nfrom permafrost will be 18 (3.1-41) PgC degC-1 by 2100, with the relative contribution of CO2 vs CH4 remaining poorly constrained. \r\nPermafrost carbon feedbacks are included among the under-represented feedbacks quantified in Figure 5.29."


id: 2dbb03541e5f783bf716de0698971e08
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5336
content:
"reduces the solubility of CO2, which increases pCO2 and increases the \r\nstratification of the mixed layer, both acting as positive feedbacks \r\nweakening the ocean sink (Section  9.2.1 and Cross-Chapter \r\nBox 5.3; Arora et al., 2020); (ii) changing the temporal and spatial \r\ncharacteristics of wind stress and storms alters mixing - entrainment \r\nin, and across the bottom of, the mixed layer (Bronselaer et al., 2018); \r\nand (iii) warming and wind stress influence the large-scale meridional \r\noverturning circulation (MOC) circulation, which modifies the rate \r\nof ventilation, storage or outgassing of ocean carbon in the ocean \r\ninterior (Section 5.2.3.1; Gruber et al., 2019b; Arora et al., 2020). The \r\nland-to-ocean riverine flux and the carbon burial in ocean sediments "


id: c8038467b993329031e6cccb31572dfe
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32498
content:
"The principal contribution to increasing global ocean carbon is the \r\nair-sea flux of CO2, which changes the dissolved inorganic carbon \r\n(DIC) inventory (Section 5.4.2; Arora et al., 2020). The processes that \r\ninfluence the variability and trends of the ocean carbon-heat nexus \r\nare assessed in Cross-Chapter Box 5.3. Climate has three important \r\nimpacts on the ocean uptake of anthropogenic CO2: (i) ocean warming "


id: 59e2a68bb90c3ee00eaa0ff1757debbb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13058
content:
"play a  minor role (low confidence) (Arora et al., 2020). Based on \r\nhigh agreement of projections by coupled climate models, there is \r\nhigh confidence that the resultant climate-carbon cycle feedbacks \r\nare positive, but the extent of the ocean sink weakening is scenario \r\ndependent (Arora et al., 2020)."


id: df70ef15aa8ce41992357a43cd457d33
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36557
content:
"SSP5-8.5 scenario. The mechanisms driving these changes vary widely \r\nbetween models due to differences in parametrization of particle \r\nformation, remineralization and plankton community structure."


id: fe1735c3b3ab2028b2a124461a08d937
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 42070
content:
"Regionally, the Southern Ocean is a  major sink of anthropogenic \r\nCO2 (Figure  5.8a), although challenges in modelling its circulation \r\nand Antarctic sea ice transport (Sections 3.4.1.2, 9.2.3.2 and 9.3.2) \r\ngenerate uncertainty in the response of its sink to future carbon-\r\nclimate feedbacks. Increased freshwater input may cause a slowdown \r\nof the lower overturning circulation, leading to increased Southern \r\nOcean biological carbon storage (Ito et al., 2015); alternatively, \r\nincreased winds may intensify the overturning circulation, reducing \r\nthe net CO2 sink in the Southern Ocean (Bronselaer et al., 2018; \r\nSaunders et al., 2018). On centennial time scales, there is thus low \r\nconfidence in the overall effect of intensifying winds in the Southern \r\nOcean on CO2 uptake."


id: db983e081775d04222f1f52837c2b4d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35923
content:
"While physical drivers control the present-day anthropogenic carbon \r\nsink, biological processes are responsible for the majority of the \r\nvertical gradient in DIC (natural carbon storage). A  small fraction \r\nof the organic carbon fixed by primary production (PP) reaches the \r\nsea floor, where it can be stored in sediments on geological time \r\nscales, making the biological carbon pump (BCP) an important \r\nmechanism for very long-term CO2 storage. Projected reductions in \r\nocean ventilation (Section  9.2.1.4) would lengthen residence time \r\nand lead to DIC accumulating in the deep ocean due to organic \r\ncarbon remineralization."


id: 880cff0f81085a40ec0a49a595620b01
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21085
content:
"Based on high agreement across multiple lines of evidence and \r\nphysical understanding there is high confidence that feedbacks to \r\nclimate will arise from alterations to the magnitude and efficiency \r\nof the BCP changing PP, and the depth of remineralization. However, \r\nthe complexity of the mechanisms involved in the export and \r\nremineralization of POC result in low confidence in the magnitude \r\nand sign of biological feedbacks to climate. Nevertheless, improved \r\nmodel representation of PP and the BCP is required (which requires "


id: 3f1246e6389d620566437513ee244355
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8285
content:
"In CMIP5 models run under RCP8.5, particulate organic carbon (POC) \r\nexport flux is projected to decline by 1-12% by 2100 (Taucher and \r\nOschlies, 2011; Laufkoetter et al., 2015). Similar values are predicted \r\nin 18 CMIP6 models, with declines of 2.5-21.5% (median -14%) or \r\n0.2-2 GtC (median -0.8 GtC) between 1900 and 2100 under the "


id: d50e4760bbddee454aa4bda67bbad3b7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34807
content:
"better observational constraints), as the contribution of biological \r\nprocesses to CO2 uptake is expected to become more significant with \r\ncontinued climate change (Hauck et al., 2015)."


id: 94f7394adc72359ff87668ab458a9e4d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23412
content:
"of the land and ocean carbon cycle models used in CMIP6 ESMs (Arora \r\net al., 2020). In CMIP6, most ocean carbon cycle models (8 of 11) track \r\nthree or more limiting nutrients (most often nitrogen, phosphorus, \r\nsilicon, iron), and include two or more phytoplankton types. More \r\nthan half of the land carbon cycle models (6 of 11) now include an \r\ninteractive nitrogen cycle, and almost half (5 of 11) represent forest \r\nfires. However, even for CMIP6, very few models explicitly represent \r\nvegetation dynamics (3 of 11) or permafrost carbon (2 of 11). Despite \r\nthese remaining limitations, the carbon cycle components of CMIP6 \r\nrepresent an advance on those in CMIP5, as they represent additional \r\nimportant processes (e.g.,  nitrogen limitations on the land carbon \r\nsink, and iron limitations on ocean ecosystems)."


id: ae7666b3e3e42a31d3a1043d07e6640c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27927
content:
"This section summarizes future projections of land and ocean \r\ncarbon sinks from the latest ESMs. ESMs are the basis for century \r\ntime-scale projections (Chapter 4), and for detection and attribution \r\nstudies (Chapter 3). These models aim to simulate the evolution of \r\nthe carbon sources and sinks on land and in the ocean, in addition \r\nto the physical components of the climate system. ESMs include \r\ninteractions between many of the processes and feedbacks described \r\nin Sections 5.4.1 to 5.4.4."


id: aea4f13b73404aa7cd3fa7d6d36d5338
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27957
content:
"ESMs can be driven by anthropogenic CO2 emissions ('emissions-driven' \r\nruns), in which case atmospheric CO2 concentration is a  predicted \r\nvariable; or by prescribed time-varying atmospheric concentrations \r\n('concentration-driven' runs). In concentration-driven runs, simulated \r\nland and ocean carbon sinks respond to the prescribed atmospheric \r\nCO2 and resulting changes in climate, but do not feed back through \r\nchanges in the atmospheric CO2 concentration. Concentration-driven \r\nruns are used to diagnose the carbon emissions consistent with \r\nthe Shared Socio-economic Pathways (SSPs) and other prescribed \r\nconcentration scenarios (Section 5.5). In this subsection we specifically \r\nanalyse results from concentration-driven ESM projections."


id: a0c6f7f9eaa90d89ac137e504da588b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25495
content:
"ESMs are now integral to the Coupled Model Intercomparison Project. \r\nModel output data from CMIP5 was analysed in AR5, while data from \r\nCMIP6 forms the basis for the analysis presented in this subsection. The \r\nCMIP5 ESMs discussed in AR5 (WGI, Section 6.4.2) produced a wide \r\nrange of projections of future CO2 (Friedlingstein et al., 2014b) primarily \r\nassociated with different magnitudes of carbon-climate and carbon\u0002concentration feedbacks (Arora et al., 2013), but also exacerbated by \r\ndifferences in the simulation of the net carbon release from land-use \r\nchange (Brovkin et al., 2013). A  key deficiency of almost all CMIP5 \r\nESMs was the neglect of nutrient limitations on CO2-fertilization of \r\nland plant photosynthesis (Section 5.4.1; Zaehle et al., 2015)."


id: a194f375518f4f254d479393cdb60adc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 25644
content:
"To give confidence in their projections, models need to be \r\ncompared to the widest possible array of observational benchmarks. \r\nThis is particularly the case for highly uncertain land carbon cycle "


id: 939d981fe59caf6a7a2bea2bb6df05c6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23176
content:
"Some CMIP6 models considered in this report now include nitrogen \r\nlimitations on land vegetation growth, along with many other added \r\nprocesses compared to CMIP5. Table 5.4 summarizes characteristics "


id: 3fe9d08ebff3d5ea27e915e802bba085
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8437
content:
"Table 5.4 | Properties of the CMIP6 Earth system models (ESMs), focusing on the land and ocean carbon cycle components of these models (Arora \r\net al., 2020). Characteristics listed under each ESM are: number of vegetation carbon pools (veg C pools); number of soil and litter carbon pools (dead C pools); number of \r\nPlant Functional Types (PFTs); whether wildfire is represented (fire); whether vegetation dynamics is represented (dynamic veg); whether permafrost carbon is represented \r\n(permafrost C); whether the nitrogen cycle is represented (nitrogen cycle); the number of phytoplankton types (phytoplankton); the number of zooplankton types (zooplankton); \r\nand the list of ocean nutrients represented (limiting nutrients)."


id: 6fa7c8e9899ad292f693b2885bef0cd1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 16901
content:
"feedbacks (Arora et al., 2013; Friedlingstein et al., 2014b). Land \r\nmodels within ESMs can be compared to multiple different datasets \r\nthat test different aspects of the models. These include fluxes, such as \r\ngross carbon uptake, and states, such as leaf area and carbon stocks, \r\nwhich influence carbon fluxes and are diagnostic of carbon turnover \r\ntimes. Comparisons can also be made between between carbon and \r\nwater cycles and other aspects of the terrestrial carbon cycle. To \r\nprovide these multiple orthogonal constraints, a model benchmarking \r\nsystem - the international land model benchmarking (ILAMB) - has \r\nbeen developed (Collier et al., 2018)."


id: 5c12c1effc581bba1ddafac6a28a5e86
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13458
content:
"The land carbon cycle components of historical ESM simulations \r\nshow a larger range, with simulated cumulative land carbon uptake \r\n(1850-2014) spanning the range from -47 to +21 GtC, compared to \r\nthe GCP estimate of -12 +- 50 GtC (Figure 5.23b). This range is due in \r\npart to the complications of simulating the difference between carbon \r\nuptake by intact ecosystems and the direct release of carbon due \r\nto land-use change (Hajima et al., 2020a). There is high confidence\r\nthat the land continues to dominate the overall uncertainty in the \r\nprojected response of the global carbon cycle to climate change."


id: f8117816fa183901a6e83be16ae5f194
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41017
content:
"Figure 5.22 shows an overview set of land (Figure 5.22a) and ocean \r\n(Figure  5.22b) benchmarks applied to both the CMIP5 and CMIP6 \r\nhistorical simulations. There is good evidence of an improvement in \r\nmodel performance from CMIP5 (in yellow) to CMIP6 (in green), \r\nin both the land and ocean, based on these benchmarks. The mean of \r\nthe CMIP6 land models outperforms or performs equivalently to the \r\nmean of the CMIP5 land models on all available metrics."


id: d563b4af134565bd49d510c7157ddd29
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34861
content:
"This section evaluates concentration-driven historical simulations \r\nof changes in land and ocean cumulative carbon uptake, against \r\nobservation-based estimates from the Global Carbon Project (GCP; \r\nLe Quere et al., 2018a). For each model, common historical land-use \r\nchanges were prescribed (Jones et al., 2016a)."


id: f861a2a285cf00f6d9d1cf11a85ae21e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 41066
content:
"Figure  5.23 shows global annual mean values from CMIP6 \r\nconcentration-driven runs for 1850 to 2014. The ocean carbon cycle \r\nmodels reproduce historical carbon uptake well, with the model range \r\nfor the global ocean carbon sink in 2014 (2.3-2.7 GtC yr-1) clustering \r\naround the central GCP estimate of 2.6 +-  0.5 GtC yr-1. Simulated \r\ncumulative ocean carbon uptake (1850-2014) ranges from 110 to \r\n166 GtC, with a model mean of 131 +- 17 PgC, which is lower than \r\nthe GCP estimate of 150 +- 25 GtC (Figure 5.23a). This suggests that \r\nCMIP6 models may slightly underestimate historical ocean carbon \r\nuptake (Watson et al., 2020)."


id: e4177c06ded9e64f0017e1a366b6dcae
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37431
content:
"It has been previously noted that AR5 models tended to overestimate \r\nland uptake in the tropics and underestimate uptake in the northern \r\nmid-latitudes, compared to inversion estimates. The inclusion of \r\nnitrogen limitations on CO2-fertilization within CMIP6 models was \r\nexpected to reduce this discrepancy (Anav et al., 2013). There is indeed \r\nsome evidence that the CMIP6 ensemble (red wedge in Figure 5.24b) \r\ncaptures the northern land carbon sink more clearly than CMIP5 "


id: df422e2806c58f4115afcfc6e8607fef
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 36532
content:
"model projections of cumulative land carbon uptake (Figure 5.25f). The \r\nfive-year ensemble mean net land carbon sink is projected to decline \r\nto 0.4 +- 1.0 GtC yr-1 by 2100 under SSP1-2.6, and to reach around \r\n5.6 +- 3.7 GtC yr-1 under SSP5-8.5 (Figure 5.25c). Cumulative net land \r\ncarbon uptake from 1850 is projected to saturate at approximately \r\n150 +- 35 GtC under SSP1-2.6, and to reach 310 +- 130 GtC by 2100 \r\nunder SSP5-8.5. Significant uncertainty remains in the future of \r\nthe global land carbon sink, but there has been a notable reduction \r\nin the model spread from CMIP5 to CMIP6."


id: 20e7e6b268d808e3aa47ac5d70dae0e1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 3012
content:
"(blue wedge in Figure 5.24b), but there remains a tendency for the \r\nESMs to place more of the global land carbon sink in the tropics than \r\nthe mid-latitudes, compared to the inversion estimates. Based on \r\na consistent signal across CMIP6 ESMs, there is medium confidence\r\nthat land carbon cycle models continue to underestimate the \r\nNorthern Hemisphere land carbon sink, when compared to estimates \r\nfrom atmospheric inversion (Ciais et al., 2019)."


id: f878f27779b9f584dec2139f991bbd60
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41074
content:
"Land and ocean carbon uptake are driven primarily by increases in \r\natmospheric CO2 (Figure 5.25). As a result, the evolution of land and \r\nocean carbon sinks differs significantly between the SSP scenarios. \r\nUnder scenarios that have greater increases in atmospheric CO2 (such \r\nas SSP5-8.5 and SSP3-7.0) the absolute values of the sinks are larger, \r\nbut the fraction of implied emissions taken up by the sinks declines \r\nthrough the 21st century. By contrast, scenarios that assume CO2\r\nstabilization in the 21st century (such as SSP1-2.6 or SSP2-4.5), have \r\nsmaller absolute sinks, but these sinks take up an increasing fraction \r\nof the implied emissions (Figure  5.25d). These general principles \r\napply to the ocean and land carbon sinks."


id: 7a3be3b1743ba25a5e571492046e984b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18700
content:
"Geographical patterns of carbon changes for four SSP scenarios are \r\nshown in Figure 5.26, with cleared areas (no diagonal lines) showing \r\nagreement on the sign of the change by at least 80% of the models. \r\nIn all scenarios the ocean sink is strongest in the Southern Ocean and \r\nNorth Atlantic. The land carbon sink occurs primarily where there are \r\npresent-day forests. In the mid- and high-northern latitudes, a carbon \r\nsink is projected as a result of the combined impacts of increasing CO2\r\nand warming (Section 5.4.5.5). Changes in land carbon storage in the \r\ntropics also depend strongly on the assumed rate of deforestation \r\nwhich varies in magnitude across the SSPs, from relatively low rates \r\nin SSP1-2.6 to relatively high rates in SSP3-7.0."


id: 8707e89802ff497f3a03e625fe8f7135
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20918
content:
"The concentration-driven CMIP6 ESMs agree well on the evolution \r\nof the global ocean carbon sink through the 21st century for four \r\nSSP scenarios (Figure 5.25). The five-year ensemble mean ocean sink \r\ndeclines to 0.6 +- 0.2 GtC yr-1 by 2100 under SSP1-2.6, and peaks \r\naround 2080 at 5.4 +- 0.4 GtC yr-1 under SSP5-8.5. Cumulative ocean \r\ncarbon uptake from 1850 is projected to saturate at approximately \r\n290 +- 30 GtC under SSP1-2.6, and to reach 520 +- 40 GtC by 2100 \r\nunder SSP5-8.5 (Figure 5.25e)."


id: 298fe4c23f0340949d2d7c9c92ca45ba
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4537
content:
"In summary, oceanic and terrestrial carbon sinks are projected \r\nto continue to grow with increasing atmospheric concentrations \r\nof CO2, but the fraction of emissions taken up by land and ocean \r\nis expected to decline as the CO2 concentration increases (high \r\nconfidence). In the ensemble mean, ESMs suggest approximately \r\nequal global land and ocean carbon uptake for each of the SSP \r\nscenarios. However, the range of model projections is much \r\nlarger for the land carbon sink. Despite the wide range of model \r\nresponses, uncertainty in atmospheric CO2 by 2100 is dominated \r\nby future anthropogenic emissions rather than carbon-climate \r\nfeedbacks (high confidence)."


id: 302ae647c6faf235da5ed3fa5eeb2a16
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5734
content:
"The ensemble mean changes in land and ocean sinks are qualitatively \r\nsimilar, but the land shows much higher interannual variability in \r\ncarbon uptake (Figure 5.25c) and also a much larger spread in the "


id: 72408d52b00b259aab0ffe566d606006
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17342
content:
"b and g values are diagnosed from idealized runs in which a 1% per \r\nyear increase in atmospheric CO2 concentration is prescribed, as for \r\nAR5 (WGI, Box  6.4; Arora et al., 2013). Values of b are calculated \r\nfrom 'biogeochemical' runs in which the prescribed CO2 increases do \r\nnot affect climate, and these are then used to isolate g  values in \r\nfully coupled runs where both climate and CO2 change (Friedlingstein \r\net al., 2003)."


id: e248245642d5499684e4d2d7df70aae
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37099
content:
"To diagnose the causes of the varying time-evolution of \r\ncarbon  sinks,  the traditional linear feedback approach is \r\nadopted (Friedlingstein et al., 2003), as used previously to analyse \r\nC4MIP (Friedlingstein et al., 2006) and CMIP5 models (Arora et al., \r\n2013). Changes in land carbon storage (DCL) and changes in ocean \r\ncarbon storage (DCo) are decomposed into contributions arising from \r\nwarming (DT) and increases in CO2 (DCO2):"


id: cb91c94752c79ce41a85b448450b5b87
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33143
content:
"where bL (bo) and gL (go) are coefficients that represent the sensitivity \r\nof land (ocean) carbon storage to changes in CO2 and global mean \r\ntemperature respectively. This feedback formalism is one of several \r\nthat have been proposed for analysing climate-carbon cycle \r\nfeedbacks (Lade et al., 2018)."


id: 3982457712a72e055318762f55e6fb0d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7329
content:
"This quasi-equilibrium framework is scenario dependent because \r\nof the time scales associated with land and ocean carbon uptake, \r\nas discussed in AR5 (WGI, Box 6.4). However, it is retained here for \r\ntraceability with AR5. This approach has been used to define a number \r\nof emergent constraints on carbon cycle feedbacks (Section  5.4.6) \r\nand to reconstruct the transient climate response to cumulative CO2\r\nemissions (TCRE) (Jones and Friedlingstein, 2020), as in Section 5.5. \r\nTo minimize the confounding effect of the scenario dependence, "


id: c6fbc228154795595d0d58fb42169139
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 32317
content:
"Table 5.5 | Diagnosed global feedback parameters for CMIP6 ESMs based \r\non 1% per year runs to 4xCO2 (Arora et al., 2020). The last two rows show the \r\nmean and standard deviation across the CMIP6 and CMIP5 models, respectively."


id: 420245c3dc45742696d487692082888d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 8811
content:
"Table 5.5 shows the global land and global ocean values of b and g for \r\neach of the CMIP6 ESMs (Arora et al., 2020). The last two rows show \r\nthe ensemble means and standard deviation across the ensemble for \r\nCMIP6 and CMIP5. In both ensembles, the largest uncertainties are \r\nin the sensitivity of land carbon storage to CO2 (bL) and the sensitivity \r\nof land carbon storage to temperature (gL). The more widespread \r\nmodelling of nitrogen limitations in CMIP6 was expected to lead \r\nto reductions in both of these feedback parameters. There is some \r\nevidence for that, with ensemble mean gL moving from -58 +-  38 \r\nGtC K-1 to -33 +-  33 GtC K-1. Between CMIP5 and CMIP6, there \r\nare also reductions in ensemble mean bo (0.82 to 0.77 GtC ppm-1), \r\nbL (0.93 to 0.89 GtC ppm-1) and go (-17.3 to -16.9 GtC K-1), but \r\nthese are progressively less significant compared to the model \r\nspread in each case."


id: daf14a7457c856496069fa352a3076e1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35806
content:
"carbon storage in the boreal zone, but has a compensating negative \r\nimpact on the carbon sink in tropical and subtropical lands, and in \r\nthe North Atlantic Ocean (g, Figure  5.27b). Overall, the ensemble \r\nmean of the CMIP6 ESMs model indicates increasing carbon storage \r\nwith CO2 in almost all locations (Figure 5.27c)."


id: 60051a1268889d509e6c83826b5470ea
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14200
content:
"Emergent constraints are based on relationships between observable \r\naspects of the current or past climate (such as trends or variability), \r\nand uncertain aspects of future climate change (such as the strength \r\nof particular feedbacks). These relationships are evident across \r\nan ensemble of models. When combined with an observational \r\nestimate of the trend or variability in the real climate, such emergent \r\nrelationships can yield 'emergent constraints' on future climate \r\nchange (Hall et al., 2019). At the time of AR5 (WGI, Section 9.8.3), \r\nthere had been relatively few applications of the technique to \r\nconstrain carbon cycle sensitivities, but there have been many studies \r\npublished since (e.g., the summary in Cox, 2019). Figure 5.28 shows \r\nsome key published emergent constraints on the carbon cycle in ESMs."


id: e62c8cd8175b1b56f5c244ac965b1c3f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 37798
content:
"In these idealized 1% per year CO2 runs, the CMIP6 models show \r\nreasonable agreement on the patterns of carbon uptake and also on \r\nthe separate impacts of CO2 increase and climate change (Figure 5.27). \r\nFor the ensemble mean, increasing atmospheric CO2 increases carbon \r\nuptake by the oceans, especially in the Southern Ocean and the North \r\nAtlantic Ocean, and on the land, especially in tropical and boreal \r\nforests (b, Figure  5.27a). Climate change further enhances land "


id: e93d5fc93bd61276216b4c04821c75df
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38392
content:
"permafrost thaw are estimated to contribute an additional CH4-\r\nclimate feedback of 0.01 [0.003 to 0.04, 5-95% range] W m-2 degC-1\r\n(limited evidence, low agreement). "


id: b70dc1f7e599b26a91674ddc92c68715
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29416
content:
"Sources and sinks of CH4 and N2O respond both directly and indirectly \r\nto atmospheric CO2 concentration and climate change, and thereby \r\ngive rise to additional biogeochemical feedbacks in the climate \r\nsystem, which may amplify or attenuate climate-carbon cycle \r\nfeedbacks (Gasser et al., 2017; Lade et al., 2018; Denisov et al., 2019). \r\nMany of these of feedbacks are only partially understood, and thus \r\nwere only partially addressed in AR5 (WGI, Sections 6.3.3, 6.3.4 and \r\n6.4.7). Since AR5, a growing body of estimates from ESMs, as well \r\nas independent modelling and observation-based studies, enable \r\nimproved estimates of the associated feedbacks."


id: 108ddc54a6ae83110d88dcd3e45ec6a1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 98
content:
"Methane release from wildfires may increase by up to a factor of 1.5 \r\nduring the 21st century (Eliseev et al., 2014a, b; Kloster and Lasslop, \r\n2017). However, given the contemporary estimate for CH4 from \r\nwildfires of no more than 16 TgCH4 yr-1 (van der Werf et al., 2017; \r\nSaunois et al., 2020), this feedback is small, adding no more than \r\n40 ppb to the atmospheric CH4 by the end of the 21st century (medium \r\nconfidence). Methane emissions from pan-Arctic freshwater bodies is \r\nalso estimated to increase by 16 TgCH4 yr-1 in the 21st century (Tan \r\nand Zhuang, 2015). Emissions from subsea and permafrost methane \r\nhydrates are not expected to change substantially in the 21st century \r\n(Section 5.4.9.1.3)."


id: ce9cb16e6f6a97deae0578287948f9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 33691
content:
"The goal of this section is to assess the climate feedback parameters \r\na, as it is defined in Section 7.4.1.1, for CH4 and N2O biogeochemical \r\nfeedbacks. The strength of the feedbacks is estimated in a  linear \r\nframework (Gregory et al., 2009), using the radiative forcing equations \r\nfor CO2, CH4 and N2O (Etminan et al., 2016). In addition to estimates \r\nfrom ESMs, the feedback parameter a is estimated from independent \r\nestimates of surface emission climate sensitivities and atmospheric \r\nbox models, following (Arneth et al., 2010; Thornhill et al., 2021). \r\nThese assessed feedback parameters are used in Section 7.4.2.5."


id: b279847b17bb724374bfde7d7b929514
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28635
content:
"Climate change will also affect N2O production in the ocean (Codispoti, \r\n2010; Freing et al., 2012; Bopp et al., 2013; Rees et al., 2016; Breider et al., \r\n2019). Model projections in the 21st century show a 4-12% decrease \r\nin ocean N2O emissions under RCP8.5 due to a combination of factors, \r\nincluding increased ocean stratification, decreased ocean productivity, \r\nand the impact of increasing atmospheric N2O abundance on the air-\r\nsea flux, corresponding to an ocean N2O climate feedback of -0.008 \r\n+-  0.002 W m-2 degC-1 (limited evidence, high agreement) (Martinez\u0002Rey et al., 2015; Landolfi et al., 2017; Battaglia and Joos, 2018b). \r\nOn millennial time scales, the ocean N2O climate feedback may be \r\npositive, owing to ocean deoxygenation and long-term increases in \r\nremineralization (Battaglia and Joos, 2018b)."


id: d348702ec64ccc7a646979aa6d412578
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34515
content:
"Based-on these studies, there is medium confidence that the \r\ncombined climate feedback parameter for CH4 and N2O is positive, \r\nbut there is low confidence in the magnitude of the estimate (0.05 \r\n[0.02 to 0.09] W m-2 degC-1, 5-95% range)."


id: 4e7d32c86826d2d95a7e18a5c4d86c81
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11084
content:
"This section assesses the magnitude of the combined biogeochemical \r\nfeedback in the climate system (Figure 5.29) by integrating evidence \r\nfrom: carbon-cycle projections represented in Earth system models \r\n(Section  5.4.5.5), independent estimates of CO2 emissions due to "


id: bb2c190fcd5401ded299be54faab3bb0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 30148
content:
"permafrost thaw (Box  5.1) and fire (Section  5.4.3.2), natural CH4\r\nand N2O emissions (Section  5.4.7), and aerosol and atmospheric \r\nchemistry (Section  6.3.6). We derive a  physical climate feedback \r\nparameter a, as defined in Section 7.4.1.1, for CO2-based feedbacks \r\nusing the linear framework proposed by Gregory et al. (2009), using \r\nthe radiative forcing equations for CO2 (Etminan et al., 2016)."


id: 38c640eb0da719922198d4f992cadf9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7191
content:
"The applicability of the linear feedback framework (Section 5.4.5.5) \r\nsuggests that large-scale biogeochemical feedbacks are approximately \r\nlinear in the forcing from changes in CO2 and climate. Nevertheless, \r\nregionally the biosphere is known to be capable of producing \r\nabrupt changes or even 'tipping points' (Higgins and Scheiter, \r\n2012; Lasslop et al., 2016). Abrupt change is defined as a  change \r\nin the system that is substantially faster than the typical rate of the \r\nchanges in its history (Section 1.4.5). A related matter is a tipping \r\npoint: a critical threshold beyond which a system reorganizes, often \r\nabruptly and/or irreversibly. Possible abrupt changes in the Earth \r\nsystem include those related to ecosystems and biogeochemistry \r\n(Lenton et al., 2008; Steffen et al., 2018): tropical and boreal forest "


id: dac8c745ecbca72611f6d61b249ac7d0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 35783
content:
"CO2 and non-CO2 biogeochemical feedbacks are an important \r\ncomponent of the assessment of TCRE and the remaining carbon \r\nbudget (Section 5.5). The feedbacks of the carbon cycle of CO2 and \r\nclimate are implicitly taken account in the TCRE assessment, because \r\nthey are represented in the various underlying lines of evidence. "


id: 8418af16544953f56bb1865b71949234
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20399
content:
"Table 5.6 | Examples of possible biogeochemical abrupt changes and tipping points in the Earth system. The fourth and sixth columns provide upper estimates \r\nof the impact of each example on the evolution of atmospheric GHGs in the 21st century. These upper estimates are therefore very unlikely but provide a useful comparison to \r\nthe impact of direct anthropogenic emissions (currently 2.5 ppm yr-1)."


id: 80af7818e816674fd16fd4754c273bf8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 19770
content:
"dieback; and release of greenhouse gases (GHGs) from permafrost \r\nand methane clathrates (Table 5.6). In this section we therefore focus \r\non estimating upper limits on the possible impact of abrupt changes on \r\nthe  evolution of atmospheric GHGs out to 2100, for comparison \r\nto the impact of direct anthropogenic emissions."


id: 74a7516a80613dee885591bae0225d87
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17760
content:
"Boreal forest dieback is not expected to change the atmospheric CO2\r\nconcentration substantially because forest loss at the south is partly \r\ncompensated by: (i) temperate forest invasion into previously boreal \r\nareas; and (ii) boreal forest gain at the north (Friend et al., 2014; \r\nKicklighter et al., 2014; Schaphoff et al., 2016) (medium confidence). \r\nAn upper estimate of this magnitude, based on statistical modelling \r\nof climate change alone, is of 27 Pg vegetation carbon loss in \r\nthe southern boreal forest, which is roughly balanced by gains in the \r\nnorthern zone (Koven, 2013). Carbon release from vegetation and \r\nsoil due to wildfires in boreal regions (Eliseev et al., 2014b; Turetsky \r\net al., 2015; X.J. Walker et al., 2019) is also not expected to change \r\nthis estimate substantially because of its small present-day value of \r\nabout 0.2 PgC yr-1 (van der Werf et al., 2017), and because of likely\r\nincreases in precipitation in boreal regions (Section 4.5.1)."


id: 2e123ed2d85c9b8adb3e5343c081909e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5379
content:
"To estimate an upper limit on the impact of Amazon forest dieback \r\non atmospheric CO2, we consider the very unlikely limiting case of \r\nnegligible direct-CO2 effects (Section  5.4.1). Emergent constraint \r\napproaches (Section 5.4.6) may be used to estimate an overall loss of \r\ntropical land carbon due to climate change alone, of around 50 PgC \r\nper degC of tropical warming (Cox et al., 2013; Wenzel et al., 2014). \r\nThis implies an upper limit to the release of tropical land carbon of \r\n<200 PgC over the 21st century (assuming tropical warming of <4degC, \r\nand no CO2-fertilization), which translates to dCO2/dt <0.5 ppm yr-1."


id: 70f3388c8ed434dd0456a417ac48709e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17134
content:
"and Eliseev, 2020), which precludes a substantial response to global \r\nwarming over the next few centuries and associated emissions."


id: f5921c2c89c7f0b9ffbf6900d3df8a78
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40568
content:
"Thus, it is very unlikely that CH4 emissions from clathrates will \r\nsubstantially warm the climate system over the next few centuries."


id: 19814389d7eb5bb258db6b9a0c4a9f7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 1697
content:
"Projecting abrupt changes is intrinsically difficult, because by \r\ndefinition abrupt changes occur in a small region of the parameter \r\nand/or forcing space. At the time of AR5 there was no available \r\nsystematic study of abrupt changes or tipping points in ESMs. An \r\nanalysis of ESMs since AR5 has identified a number of abrupt changes \r\nin the CMIP5 ensemble (Drijfhout et al., 2015; Bathiany et al., 2020). \r\nThese include abrupt changes in tropical forests and high-latitude \r\ngreening, permafrost thaw, and vegetation composition change \r\n(Bathiany et al., 2020). Most modelled abrupt changes were detected \r\nin boreal and tundra regions, with few models showing Amazon \r\nforest dieback (Bathiany et al., 2020)."


id: eddcec0421345963a372379a1d5fe5c8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39215
content:
"Based on the evidence presented in this section, we conclude that \r\nabrupt changes and tipping points in the biogeochemical cycles lead \r\nto additional uncertainty in 21st century GHG concentrations changes. \r\nHowever, these are very likely to be small compared to the uncertainty \r\nassociated with future anthropogenic emissions (high confidence)."


id: ac3c713c4e00334a49b603b6f8b628c4
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27547
content:
"Figure  5.30 shows carbon cycle changes to 2300 under three SSP \r\nscenarios with long-term extensions: SSP5-8.5, SSP5-3.4-overshoot, \r\nand SSP1-2.6, for four CMIP6 ESMs and one EMIC.  Under all three \r\nscenarios, all five models project a reversal of the terrestrial carbon cycle \r\nfrom a sink to a source. However, the reasons for these reversals under \r\nvery high emissions and low/negative emissions are  very  different. \r\nUnder the SSP5-8.5 scenario, the terrestrial carbon-climate \r\nfeedback is projected to strengthen, while the carbon-concentration "


id: 997d3b90b1b53c300b8c4c122a134387
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24232
content:
"carbon budget estimates. There is growing evidence that the potential \r\npredictive skill of air-land CO2 flux is maintained out to a lead-time \r\nof two years (Lovenduski et al., 2019b); this predictability horizon \r\nis also supported by perfect model studies (Seferian et al., 2018a; \r\nSpring and Ilyina, 2020). The origins of this interannual predictability \r\nare not yet fully understood. However, they seem to be associated \r\nwith the oscillatory behaviour of ENSO (Seferian et al., 2014) and \r\nthe drivers of terrestrial carbon flux predictability, such as ecosystem \r\nrespiration and gross primary production (Lovenduski et al., 2019a). \r\nInitialized simulations suggest that observed variability in the land \r\ncarbon sink is improved through initialization of prediction systems \r\nwith the observed state of the physical climate."


id: 27d5648e18c7a1a1cb5bebfb132a817e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 4200
content:
"The AR5 (WGI, Section  11.3.2) assessed near-term  climate \r\npredictability based on ESMs initialized from the observed \r\nclimate  state. Since AR5, a  growing number of prediction systems \r\nhave been developed based on ESMs that include the ocean and \r\nland carbon cycle components. Predictability of key physical climate \r\nvariables (assessed in Chapter  4) provides a  platform to establish \r\npredictive skill for interannual variations in the strength of the natural \r\ncarbon sinks in response to internal climate variability. In most \r\nsystems the carbon cycle components are only indirectly initialized \r\nand respond to the initialized climate variations (Li et al., 2019). This \r\nsubsection synthesizes information on predictability of the land and \r\nocean carbon sinks using both the idealized potential predictability \r\nand the actual predictability skill measures."


id: 5a2967c16b51f2f5030d00192d2464a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 13110
content:
"The predictability horizon of variations in atmospheric CO2 growth \r\nrate is not yet fully established in the literature. However, predictive \r\nskill of the land and ocean carbon sinks show a potential to establish \r\npredictability of variations in atmospheric CO2 up to two years in \r\nadvance in the initialized prediction systems, with an upper bound of \r\nup to three years in a perfect-model study (Spring and Ilyina, 2020); \r\nthis skill is primarily limited by the terrestrial carbon sink predictability."


id: 97c4186443e480b53172707b5874aadc
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 23917
content:
"Seasonal predictability of air-land CO2 flux up to 6-8 months is driven \r\nby the state of El Nino-Southern Oscillation (ENSO) (Zeng et al., \r\n2008; Betts et al., 2018). Fewer land carbon initialized predictions \r\nare available from decadal prediction systems, yet they tend to \r\noutperform the uninitialized simulations in capturing the major year\u0002to-year variations, as indicated by higher correlations with the global "


id: a6c922ae4714a27c374d390097c11d4b
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26557
content:
"forcing from CO2, and ocean heat uptake) are governed by complex \r\nmechanisms that all evolve in time (Sections 3.5, 4.3, 4.5, 5.4, and \r\n7.3, and Cross-Chapter Box 5.3; Gregory et al., 2009). Starting with \r\nan initial description in AR5 (M. Collins et al., 2013; T.F. Stocker et al., \r\n2013), a  body of literature has since expanded the understanding \r\nof physical mechanisms from which a  simple proportional \r\nrelationship between cumulative emissions of CO2 and change in \r\nglobal temperature arises - expressed in either global mean surface \r\ntemperature (GMST) or global surface air temperature (GSAT)."


id: c3a537026a2c8189a40c4a101c0b1011
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31696
content:
"Studies have focused on two key features of the transient climate \r\nresponse to cumulative CO2 emissions (TCRE) relationship: (i) why \r\nthe relationship is nearly constant in time (Goodwin et al., 2015; \r\nMacDougall and Friedlingstein, 2015; Williams et al., 2016; Ehlert \r\net al., 2017; Katavouta et al., 2018); and (ii) why, and under which \r\nconditions, the relationship is independent of the historical rate (or \r\npathway) of CO2 emissions (MacDougall, 2017; Seshadri, 2017)."


id: 9181f5ca34fd24e4647ff02c374c1558
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 22818
content:
"The land carbon cycle does not appear to play a fundamental role \r\nin the origin of the linearity and path-independence of TCRE (Goodwin \r\net al., 2015; MacDougall and Friedlingstein, 2015; Ehlert et al., 2017) \r\nbut, in contrast to the ocean sink, dominates the uncertainty in the \r\nmagnitude of TCRE by modulating the cumulative airborne fraction of \r\ncarbon (Goodwin et al., 2015; Williams et al., 2016; Katavouta et al., \r\n2018; Jones and Friedlingstein, 2020). Some terrestrial carbon cycle \r\nfeedbacks (such as the permafrost carbon feedback; Section 5.4.8, \r\nBox 5.1) have the potential to alter both the linearity and pathway \r\nindependence of TCRE, if such feedbacks significantly contribute \r\ncarbon to the atmosphere (Sections 5.5.1.2.3 and 5.4.8, and Box 5.1; \r\nMacDougall and Friedlingstein, 2015). A  recent study also shows \r\nhow the value of TCRE can depend on the effect of ocean ventilation \r\nmodulating ocean heat uptake (Katavouta et al., 2019)."


id: 6330aba852aef4ed9be5b161b0cfd635
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 14744
content:
"The question of whether, and under which conditions, the TCRE \r\nrelationship is independent of the historical rate of CO2 emissions \r\n(also referred to as 'pathway independence of TCRE') has been \r\nexamined by using simple mathematically tractable models \r\n(MacDougall, 2017; Seshadri, 2017). Based on the assumption "


id: 7778f746551f744522ba9c629d859223
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18224
content:
"Contributors: Pedro M.S. Monteiro (South Africa), Jean-Baptiste Sallee (France), Piers Foster (United Kingdom), Baylor Fox-Kemper \r\n(United States of America), Helen T. Hewitt (United Kingdom), Masao Ishii (Japan), Joeri Rogelj (United Kingdom/Belgium), Kirsten \r\nZickfeld (Canada/Germany)"


id: 36f945889571212236cd91d1b0d42f43
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6898
content:
"In the past 60  years, the ocean has taken up and stored 23 +-  5% of anthropogenic carbon emissions (medium confidence) \r\n(Section 5.2.1.3) as well as more than 90% of the heat that has accumulated in the Earth system (referred to as excess heat) since the \r\n1970s (Sections 7.2.2, 9.2.2 and 9.2.3, and Box 7.2; Frolicher et al., 2015; Talley et al., 2016; Gruber et al., 2019b; Hauck et al., 2020). The \r\ninterplay between heat and CO2 uptake by the ocean has played a major role in slowing the rate of global warming, and also provides \r\na first order influence in determining the unique properties of a metric of the coupled climate-carbon cycle response - transient \r\nclimate response to cumulative CO2 emissions (TCRE) - which is critical to setting the future remaining carbon emissions budget \r\n(Sections 5.5.1.3 and 5.5.4). This role of the ocean in the uptake of heat and anthropogenic CO2 and related feedbacks is what we "


id: 8ad4f745c0c4cbf944cd7ab6172daf2e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 21596
content:
"term the 'ocean carbon-heat nexus'. The ocean processes behind this nexus are important in shaping and understanding the near\u0002linear relationship between cumulative CO2 emissions and global warming (TCRE) as well as the uncertainties in future projections \r\nof TCRE properties (Zickfeld et al., 2016; Bronselaer and Zanna, 2020; Jones and Friedlingstein, 2020), its path independence \r\n(MacDougall, 2017), and the warming commitment after cessation of greenhouse gas emissions - the zero emissions commitment \r\n(ZEC; Section 5.5.2; Zickfeld et al., 2016; Ehlert and Zickfeld, 2017). In this box, we assess the role of the ocean and its physical and \r\nchemical thermodynamic processes that shape these striking characteristics."


id: b24e9a47f08bf4758bcde855a7c16cdb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28607
content:
"Large-scale regional and global ocean circulation shape the spatial pattern of the uptake and storage of both CO2 and heat (see \r\nFigure 5.8 for carbon; Figure 9.6 for heat observations; Section 9.2; Frolicher et al., 2015; Bronselaer and Zanna, 2020). This coherence \r\nof spatial patterns driven by the large-scale ocean circulation has three aspects. First, notwithstanding interannual-decadal variability \r\nin heat and CO2 uptake, there is a spatial coherence of the temporally integrated uptake at the air-sea boundary, particularly in the \r\nSouthern Ocean (Cross-Chapter Box 5.3, Figure 1; Talley et al., 2016; Keppler and Landschutzer, 2019; Auger et al., 2021). Second, the \r\nimportance of the meridional overturning circulation in the subsequent storage of both heat and CO2 in mode, intermediate and deep \r\nwaters of the ocean interior (Section 9.2). Third, of particular note, the roles of the North Atlantic Ocean (Section 9.2.3.1) and the "


id: 1f1933cab6588d2acb208048d3db9339
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 2680
content:
"Southern Ocean (Section 9.2.3.2) in linking the spatial pattern of air-sea fluxes, the storage of heat and carbon, and ultimately in \r\nunderstanding and predicting the sensitivity of the carbon-heat nexus to climate change (Frolicher et al., 2015; Thomas et al., 2018; \r\nWu et al., 2019)."


id: d5f60b1529f165085cb80b43ddfa5855
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34960
content:
"amounts of cumulative emissions. However, Tokarska et al. (2016) \r\nsuggested that a  large decrease in TCRE for high cumulative \r\nemissions is only associated with some EMICs; in the four ESMs \r\nanalysed in their study, the TCRE remained approximately constant \r\nup to 5000 PgC, owing to stronger declines in the efficiency of ocean \r\nheat uptake in ESMs compared to EMICs."


id: eb86336ec05c10c5e98b38c409202418
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 38798
content:
"Overall, there is high agreement between multiple lines of evidence \r\n(robust evidence) resulting in high confidence that TCRE remains \r\nconstant for the domain of increasing cumulative CO2 emissions \r\nuntil at least 1500  PgC, with medium confidence of it remaining \r\nconstant up to 3000 PgC because of less agreement across available \r\nlines of evidence."


id: ac1d78c9c43d3fb72efee4799a631475
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 27522
content:
"pathways (Huppmann et al., 2018) and noting the lack of literature \r\nthat disentangles these various contributions, there is medium \r\nevidence and high agreement resulting in medium confidence that \r\nthe TCRE remains a good predictor of CO2-induced warming when \r\napplied in the context of emissions reduction pathways, provided that \r\nZEC and long-term Earth system feedbacks are adequately accounted \r\nfor when emissions decline towards zero (see also Section 5.5.1.2.3)."


id: 84f14c5fe56fdfc7dc42656c07b49a19
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20528
content:
"considered in individual or all ESMs, could cause a further increase \r\nor decrease of TCRE (Matthews et al., 2020). These are discussed in \r\ndetail in Section 5.4, but their quantitative effects on TCRE have not \r\nyet been explored by the literature."


id: 73b704077bc19a6f28b451b36bb1388a
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17607
content:
"The AR5 (M. Collins et al., 2013) assessed that the TCRE is likely to \r\nfall in the range of 0.8degC -2.5degC per 1000 PgC (or per exagrams of \r\ncarbon, EgC-1) for cumulative emissions up to 2000 PgC, based on \r\nmultiple lines of evidence. These include estimates based on ESMs \r\nof varying complexity (Matthews et al., 2009; Gillett et al., 2013; \r\nZickfeld et al., 2013), simple climate modelling approaches (Allen \r\net al., 2009; Rogelj et al., 2012) or observational constraints and \r\nattributable warming (Gillett et al., 2013)."


id: 3064d68792bf80ed67ec33e9d88a9727
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 5770
content:
"Table 5.7 | Overview of results from studies estimating the transient climate response to cumulative CO2 emissions (TCRE). GSAT = Global mean surface air \r\ntemperature increase, SAT = surface air temperature (e.g., over land only), SST = sea surface temperature, ECS = equilibrium climate sensitivity. Studies that do not isolate the \r\nCO2-induced warming contribution in their TCRE estimates are not included."


id: 7354dd63f51bc268b7832db1b6e5edd
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17542
content:
"equilibrium climate sensitivity (ECS) or transient climate response \r\n(TCR) - is among the most important contribution to uncertainty in \r\nTCRE, with uncertainty in the strength of the land carbon feedback \r\nand ocean heat uptake or ventilation having also been identified as \r\ncrucial to uncertainty in TCRE (Matthews et al., 2009; Gillett et al., \r\n2013; Ehlert et al., 2017; MacDougall et al., 2017; R.G.  Williams \r\net al., 2017a, 2020; Katavouta et al., 2019; Arora et al., 2020; Jones \r\nand Friedlingstein, 2020; Spafford and Macdougall, 2020). Finally, \r\ninternal variability has been shown to affect the maximum accuracy \r\nof TCRE estimates by +-0.1degC per 1000 PgC (5-95% range; Tokarska \r\net al., 2020)."


id: 7281f8d40d86b353a2634c55aadb8bbb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17386
content:
"2015; Rogelj et al., 2015a, b; MacDougall, 2016; Simmons and \r\nMatthews, 2016; Ehlert et al., 2017; Matthews et al., 2017, 2021; \r\nMillar et al.,  2017b; Goodwin et al., 2018; Mengis et al., 2018; \r\nPfleiderer et al., 2018; Tokarska et al., 2018; Cain et al., 2019). These \r\ncontributing factors are integrated in an overarching assessment of \r\nremaining carbon budgets for limiting global average warming to \r\nlevels ranging from 1.5degC to 2.5degC relative to pre-industrial levels \r\nprovided in Section  5.5.2.3. Box  5.2 provides an overview of the \r\nmethodological advances since AR5 (W.J. Collins et al., 2013)."


id: 7a4e834da6bfe54931b79a301ec24f05
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18717
content:
"The AR6 Glossary (Annex VII) defines remaining carbon budgets \r\nas the maximum amount of cumulative net global anthropogenic \r\nCO2 emissions expressed from a  recent specified date that would \r\nresult in limiting global warming to a  given level with a  given \r\nprobability, taking into account the effect of other anthropogenic \r\nclimate forcers, consistent with the definition used inSR1.5 (Rogelj \r\net al., 2018b). Studies, however, apply a variety of definitions that \r\nresult in published remaining carbon budget estimates informing to \r\ncumulative emissions at the time when global-mean temperature \r\nincrease would reach, exceed, avoid, or peak at a  given warming \r\nlevel with a given probability (M. Collins et al., 2013; T.F. Stocker et al., \r\n2013; Clarke et al., 2014; Friedlingstein et al., 2014a; IPCC, 2014; \r\nRogelj et al., 2016; Millar et al., 2017b)."


id: d411d27db602d039699f365c0ebbfca9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 34644
content:
"This section provides an assessment of remaining carbon budgets \r\nconsistent with the AR6 Glossary definition (Annex VII). Given that \r\nsome feedbacks are time dependent, the values in this section \r\napply to limiting warming over the 21st century, consistent with \r\nrecent studies highlighting the usefulness of time-limited carbon \r\nbudgets (Sanderson, 2020). Irrespective of the exact definition of \r\nthe remaining carbon budget, the finding that higher cumulative \r\nCO2 emissions lead to higher temperatures implies that annual net \r\nCO2 emissions have to decline to close to zero in order to halt global \r\nwarming, whether at 1.5degC, 2degC or another level (Allen et al., 2018)."


id: 3c2c43909686c0a9b39b66b23538eb9d
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 7775
content:
"Estimates of remaining carbon budgets consistent with holding global \r\nwarming below a specific temperature threshold depend on a range \r\nof factors which are increasingly being studied and quantified. These \r\nfactors include: (i) well-understood methodological and definitional \r\nchoices (Sections  5.5.2.1 and 5.5.2.2; Friedlingstein et al., 2014a; \r\nRogelj et al., 2016, 2018b); and (ii) a set of contributing factors such \r\nas historical warming, the TCRE and its limitations, the ZEC (the \r\namount of warming projected to occur following a complete cessation \r\nof emissions; see Section 4.7.1.1), as well as contributions of non\u0002CO2 climate forcers (Section 5.5.2.2; MacDougall and Friedlingstein, "


id: 52e068cea97ce0d41dbea0859460f510
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11849
content:
"Millar et al., 2017b; Gasser et al., 2018; Lowe and Bernie, 2018; \r\nTokarska et al., 2018; Nicholls et al., 2020)."


id: f8a5d1d9e254a17a369118b332015f11
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41112
content:
"reference periods (Cross-Chapter Box 1.2) or temperature metrics \r\nand updated data products (Cross-Chapter Box  2.3) can result \r\nin a  different estimated historical warming and thus a  changed \r\nremaining carbon budget."


id: 48c79e82acb1a96f0be1a3922798c99
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10018
content:
"Recent studies suggest further changes to this framework by \r\nincluding non-linear adjustments to the TCRE contribution (Nicholls \r\net al., 2020), or including non-CO2 forcers in different ways by \r\naccounting for their different forcing effects (Matthews et al., 2021). \r\nFigure  5.31 provides a  conceptual schematic of how the various \r\nindividually assessed contributions are combined into a consolidated \r\nassessment of the remaining carbon budget. Together with estimates \r\nof historical CO2 emissions to date (Section 5.2.1), these remaining \r\ncarbon budgets provide the overall amount of cumulative CO2\r\nemissions consistent with limiting global warming to specific levels. \r\nA comparison with the approach applied in AR5 (M. Collins et al., \r\n2013; Clarke et al., 2014) is available in SR1.5 Section 2.2.2 (Rogelj \r\net al., 2018b) as well as Box 5.2."


id: a905da03235167289bd5b7e0eadd1bb5
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 26947
content:
"Remaining carbon budgets are assessed through the combination of \r\nfive separate components (Forster et al., 2018; Rogelj et al., 2018b). \r\nEach component is discussed and assessed separately in the sections \r\nbelow, based on all available lines of evidence. Box 5.1 details the \r\ndifferences compared to AR5 and SR1.5 estimates (W.J. Collins et al., \r\n2013; Rogelj et al., 2018b)."


id: c0fb9fdf2f02963a88c2faa6806d2cd7
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 31256
content:
"The first and central component for estimating remaining carbon \r\nbudgets is the TCRE. Based on the assessment in Section 5.5.1.4, an \r\nassessed likely range for TCRE of 1.0degC-2.3degC per 1000  PgC with \r\na normal distribution is used."


id: 49fb8725a37b646d825fab2d237074b2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 10261
content:
"Application of the SR1.5 method (Forster et al., 2018; Rogelj et al., \r\n2018b) with AR6-calibrated emulators (Box 7.1) suggests a median \r\nadditional non-CO2 warming contribution at the time global CO2\r\nemissions reach net zero levels of about 0.1degC-0.2degC relative to \r\n2010-2019. Uncertainty surrounding this range due to geophysical \r\nuncertainties such as non-CO2-forcing uncertainties and TCR is of the \r\norder of +-0.1degC. Differences in the choices of mitigation strategies \r\nconsidered in low-emissions scenarios (Huppmann et al., 2018) result \r\nin a potential additional variation around the central range of at least \r\n+-0.1degC (spread across scenarios, referred to as non-CO2 scenario \r\nuncertainty in Table 5.8)."


id: 50ed10ec8cd3a4175edcf895415c322c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 11517
content:
"independent Earth system feedbacks combine to a  feedback of \r\nabout 7  +- 27  PgC  K-1 (1-sigma range, or 26 +-  97  GtCO2 degC-1). \r\nOverall, Section  5.4.8 assessed there to be low confidence in the \r\nexact magnitude of these feedbacks and they represent identified \r\nadditional amplifying factors that scale with additional warming, and \r\nmostly increase the challenge of limiting global warming to or below \r\nspecific temperature levels."


id: 38445e37e1ac441b9c6e20cc15dbd8be
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 7108
content:
"Section  5.5.1.2 highlighted recent literature describing potential \r\nimpacts of Earth system feedbacks that have typically not been \r\nincluded in standard ESMs (MacDougall and Friedlingstein, \r\n2015; Schneider von Deimling et al., 2015; Schadel et al., 2016; Burke \r\net al., 2017b; Mahowald et al., 2017; Comyn-Platt et al., 2018; Gasser \r\net al., 2018; Lowe and Bernie, 2018), the most important of which \r\nis carbon release from thawing permafrost. The SR1.5 estimated \r\nunrepresented Earth system processes to result in a  reduction \r\nof remaining carbon budgets of up to 100  GtCO2 over the course \r\nof this century, and more thereafter (Rogelj et al., 2018b). Here \r\nthis assessment is updated based on the Earth system feedback \r\nassessment of Section  5.4.8 and synthesized in Figure  5.29 by \r\napplying the reverse method by Gregory et al. (2009)."


id: d0b36fb51f41aaae4260c79971ecd0a0
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 34067
content:
"The assessment in Section 5.4 and Box 5.1 highlights the different \r\nnature, magnitude and uncertainties surrounding additional \r\nEarth system feedback. The remaining carbon budgets reported in \r\nTable 5.8 account for these feedbacks, including corrections due to \r\npermafrost CO2 and CH4 feedbacks as well as those due to aerosol \r\nand atmospheric chemistry (Section 5.4.8). Two of these additional \r\nfeedbacks (tropospheric ozone and methane lifetime feedbacks) \r\nare included in the projections of non-CO2 warming carried out \r\nwith AR6-calibrated emulators (Box  7.1). The remainder of these "


id: e84a8a96d0a8399a19f62a1edf2ecda1
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"Table 5.8 | The assessed remaining carbon budget and corresponding uncertainties. Assessed estimates are provided for additional human-induced warming \r\nexpressed as global average surface air temperature since the recent past (2010-2019), which likely amounted to 0.8 to 1.3 with a best estimate of 1.07degC relative to \r\n1850-1900 (Table 3.1 in Chapter 3)."


id: 4213b677109c47c50875ab917ff83db8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"a\r\n Human-induced global surface air temperature increase between 1850-1900 and 2010-2019 is assessed at 0.8-1.3degC (likely range; Chapter 3) with a best estimate of \r\n1.07degC. Warming reflects changes in GSAT, as TCRE and other estimates are GSAT-based. Combined with a central estimate of TCRE (1.65degC EgC-1) the uncertainty in historical \r\nhuman-induced GSAT warming results in a potential variation of remaining carbon budgets of +-150 PgC or +-550 GtCO2."


id: 43302e1c6ebf199fe49fcd0f460ba799
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"f\r\n Remaining carbon budget variation due to geophysical uncertainty in forcing and temperature response of non-CO2 emissions of the order of +-0.1degC, very likely range (5-95%) \r\nof non-CO2 response (Section 5.5.2.2.3). Combined with a central estimate of TCRE (1.65degC EgC-1) this results in at least +-60 PgC or +-220 GtCO2.\r\ng\r\n The variation due to the ZEC is estimated for a central TCRE value of 1.65degC EgC-1 and a 1-sigma ZEC range of 0.19degC. In real-world pathways, the magnitude of this effect \r\nwill depend on the pace of CO2 emissions reductions to net zero."


id: 12f0cb9d451769dbbe5bf7c9613b3525
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 539
content:
"h\r\n Historical emissions uncertainty reflects the +-10% uncertainty in the historical emissions estimate since 1 January 2015."


id: 3b8aad767e2acf26b6123a75695895aa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 7657
content:
"Box 5.2 | Implications of Methodological Advancements in Estimating the Remaining Carbon \r\nBudget since the IPCC's Fifth Assessment Report (AR5)"


id: f02350e50a936a0f1e4e06af4b40df3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 39632
content:
"Methodological advancements since AR5 (M. Collins et al., 2013; IPCC, 2013b, 2014; T.F. Stocker et al., 2013; Clarke et al., 2014) \r\nresult in an updated and strengthened assessment of remaining carbon budgets. Methods and approaches at the time of AR5 are \r\ndescribed in Section  5.5.2.1. Since AR5, strengths and weaknesses of various approaches have been more clearly articulated in \r\nthe literature (e.g., in Rogelj et al., 2016; Millar et al., 2017b; Tokarska and Gillett, 2018; Matthews et al., 2020), resulting in a new \r\nconsolidated framework applied in SR1.5 (Rogelj et al., 2018b, 2019) that is also used in AR6. This framework incorporates five \r\nmethodological advancements compared to AR5, the implications of which are discussed in this box."


id: 1a11c03ef5da96a9d60abb3564154766
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"First, publications since AR5 applied methods that limit the effect of uncertainties in historical, diagnosed emissions in coupled Earth \r\nsystem models (ESMs) on estimates of the remaining carbon budget (Millar et al., 2017b; Tokarska and Gillett, 2018). These new \r\nmethods express remaining carbon budget estimates relative to a recent reference period instead of relative to the pre-industrial \r\nperiod (Millar et al., 2017b; Tokarska et al., 2019b). Estimates of the full carbon budget since the pre-industrial period can still be \r\nobtained by adding estimates of historical CO2 emissions (Table 5.1) to the estimates in Table 5.8. This methodological update resulted, \r\nall other aspects being equal, in median estimates of remaining carbon budgets being about 350-450 GtCO2 larger compared to AR5 \r\n(IPCC, 2014; Millar et al., 2017b)."


id: 988b67ce9f4b21bd26f0621e0fe6d224
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"At the time of AR5, Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al., 2012) provided global surface air temperature \r\n(GSAT) projections for the representative concentration pathways (Meinshausen et al., 2011c), which were used to determine carbon \r\nbudgets while taking into account the effects of non-CO2 forcers (T.F.  Stocker et al., 2013). Their use came with two recognized \r\nlimitations: first, the model spread of the CMIP5 represents an ensemble of opportunity with limited statistical value (Tebaldi and \r\nKnutti, 2007); and second, the evolution of non-CO2 emissions as a function of cumulative CO2 emissions can differ markedly between \r\nhigh and low emissions pathways (Meinshausen et al., 2011c; Friedlingstein et al., 2014a; Rogelj et al., 2016; Matthews et al., 2017). \r\nSolutions to these two limitations have been published since AR5 and represent the second and third methodological improvement \r\ncompared to AR5."


id: 3ed355ccef624a37e6209adf0df87ff3
created_at: 2023-04-19 13:21:35
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content:
"The third methodological improvement is a more direct estimation of the warming contribution of non-CO2 emissions, consistent with \r\npathways that bring global CO2 emissions down to net zero. Instead of deriving this contribution implicitly from the CMIP5 ensemble, \r\nclimate emulators (Meinshausen et al., 2011b; C.J. Smith et al., 2018; Schwarber et al., 2019) that are calibrated to the combined \r\nAR6 assessment (Cross-Chapter Box 7.1) are used to estimate the non-CO2 contribution across a wide variety of stringent mitigation \r\nscenarios (Huppmann et al., 2018). The specific relative effect of this advance compared to AR5 is not calculable because CMIP5 data \r\ndoes not isolate non-CO2 from CO2-induced warming."


id: 780fe4ae9831906eae485278df0efa13
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 18334
content:
"Between SR1.5 and AR6, each of the five components described in Section  5.5.2.1 and Figure  5.31 have been re-assessed (see \r\nSections 5.5.2.2.1-5.5.2.2.5). Their updated assessments in turn affect the assessment of the remaining carbon budget. The new "


id: 62018eae87e163e643625ea663b28066
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
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content:
"and narrower assessment of TCRE in AR6 compared to SR1.5 (likely range of 1.0degC-2.3degC EgC-1 compared to 0.8degC-2.5degC EgC-1, \r\nrespectively, with the same central estimate) leads to no change in median estimates and about a 50 and 100 GtCO2 increase in \r\nremaining carbon budgets estimates at the 67th percentile in AR6 compared to SR1.5 for 1.5degC and 2degC of global warming, respectively."


id: d8d7d58a94ce377ac74450b48d37d21c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 35440
content:
"All methodological improvements and new evidence combined result in median and 67th percentile remaining carbon budget \r\nestimates for limiting warming to 1.5degC being about 300-350 GtCO2 larger compared to an assessment that would use the evidence \r\nand methods available at the time of the AR5. For limiting warming to 2degC, the difference is about 400-500 GtCO2. Since SR1.5, fewer \r\nkey advancements had to be integrated. In a like-with-like comparison, the combined effects of all AR6 updates result in median \r\nremaining carbon budget estimates for limiting warming to 1.5degC and 2degC being the same and about 60 GtCO2 smaller, respectively, \r\nin AR6 compared to SR1.5. At the 67th percentile, remaining carbon budget estimates for limiting warming to 1.5degC and 2degC are about \r\n40 to 60 GtCO2 larger, respectively, mainly as a result of a narrower assessed TCRE range."


id: b0f28c0cb7cf3bb4f92b2b4ff693a35
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 28361
content:
"(Glossary). CDR and SRM are referred to as 'geoengineering' in some \r\nof the literature, and are considered separately in this report."


id: e46d5412fbaae4330b46d778230baa9
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 37479
content:
"This section assesses the implications of CDR and SRM for \r\nbiogeochemical cycles. CDR has received growing interest as an \r\nimportant mitigation option in emissions scenarios consistent with \r\nmeeting the Paris Agreement climate goals (SR1.5, SRCCL). The \r\nclimate effects of CDR and SRM are assessed in Chapter  4, and \r\na  detailed assessment of the socio-economic dimensions of these \r\noptions is presented in AR6 WGIII, Chapters 7 and 12."


id: fec62aeb038d4732e7fd72b0e5a9fefb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 42213
content:
"Carbon dioxide removal (CDR) refers to anthropogenic activities that \r\nseek to remove CO2 from the atmosphere and durably store it in \r\ngeological, terrestrial or ocean reservoirs, or in products (Glossary). \r\nCO2 is removed from the atmosphere by enhancing biological or \r\ngeochemical carbon sinks or by direct capture of CO2 from air and \r\nstorage. Solar radiation modification (SRM) refers to the intentional, \r\nplanetary-scale modification of the Earth's radiative budget with \r\nthe aim of limiting global warming. Most proposed SRM methods \r\ninvolve reducing the amount of incoming solar radiation reaching \r\nthe surface, but others also act on the longwave radiation budget by \r\nreducing optical thickness and cloud lifetime (Glossary). SRM does \r\nnot fall within the IPCC definitions of mitigation and adaptation "


id: fa82a7d9fdfd2b9379a86961174ec06e
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 41441
content:
"The scope of this section is to assess the general and methods-specific \r\neffects of CDR on the global carbon cycle and other biogeochemical \r\ncycles. The focus is on Earth system feedbacks that either amplify "


id: 804096c1216ac77fe88ac8b70d611d3f
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 19693
content:
"IPCC, 2018), SRCCL (Chapter  6, IPCC, 2019a) and SROCC (Bindoff \r\net al., 2019) for the assessment of potentials and side effects of \r\nspecific CDR methods. Emerging literature on deliberate methane \r\nremoval is also briefly discussed."


id: c72cd09f821ad962192c5e26fb4df5b8
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 32361
content:
"or reduce carbon sequestration potentials of specific CDR methods, \r\nand determine their effectiveness in reducing atmospheric CO2 and \r\nmitigating climate change. Technical carbon sequestration potentials \r\nof CDR methods are assessed on a qualitative scale; a comprehensive \r\nquantitative assessment is left to the AR6 Working Group III Report \r\n(Chapters 7 and 12). Biogeochemical and biophysical side effects of \r\nCDR methods are assessed here, while the co-benefits and trade\u0002offs for biodiversity, water and food production are briefly discussed \r\nfor completeness, but a  comprehensive assessment is left to WGII \r\n(Chapters 2 and 5) and WGIII (Chapters 7 and 12). The assessment \r\nin this chapter emphasizes literature published since the AR5 WGI \r\nreport (Chapter  6) for the assessment of the global carbon cycle \r\nresponse to CDR, and literature published since SR1.5 (Chapter  4; "


id: bc0cce9896337f9e47bf01f183545fdb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 30322
content:
"In this chapter, CDR methods are categorised by the carbon \r\ncycle processes that result in CO2 removal: (i) enhanced net \r\nbiological production and storage by land ecosystems; (ii) enhanced \r\nnet biological production and storage in the open and coastal \r\nocean; (iii) enhanced geochemical processes on land and in the \r\nocean; and (iv) direct air capture and storage by chemical processes. \r\nA  subset of CDR methods that restore or sustainably manage \r\nnatural or modified ecosystems while providing human well-being "


id: a6b5b37a082d674b5ac4a35fc3143d49
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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vector_id: 26547
content:
"Table 5.9 | Characteristics of carbon dioxide removal (CDR) methods. Termination effects refer to the possible effects of a hypothetical, sudden and sustained \r\ntermination of the CDR method."


id: a01f89db7c7fd15629f713e6c59d6e9b
created_at: 2023-04-19 13:21:35
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vector_id: 25386
content:
"and biodiversity benefits are also referred to as natural or nature\u0002based solutions (Glossary; Griscom et al., 2017, 2020; Fargione \r\net al., 2018). CDR methods commonly discussed in the literature are \r\nsummarized in Table 5.9. Other CDR options have been suggested, \r\nbut there is insufficient literature for an assessment. These include \r\nocean biomass burial, ocean downwelling, removal of CO2 from \r\nseawater with storage, and cloud alkalinization (Keller et al., \r\n2018a; GESAMP, 2019)."


id: 148072e0fb69b0a1508c30965ccd1a77
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"This subsection assesses three aspects of the climate-carbon cycle \r\nresponse to CDR: the time-dependent behaviour of CO2 fluxes \r\nin scenarios with CDR, the effectiveness of CDR in drawing down \r\natmospheric CO2 and cooling global mean temperature, and the \r\nsymmetry of the climate-carbon cycle response to positive and \r\nnegative CO2 emissions."


id: 721bb955cc8b1c2aa9881b894342a212
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"During the industrial era, CO2 emitted by the combustion of fossil fuels and land-use change has been redistributed between \r\natmosphere, land, and ocean carbon reservoirs due to carbon cycle processes (Box 5.3, Figure 1b and Figure 5.13). Over the past \r\ndecade (2010-2019), 46% of the emitted CO2 remained in the atmosphere, 23% was taken up by the ocean, and 31% by the terrestrial \r\nbiosphere (Section 5.2.1.5). When carbon dioxide removal (CDR) is applied during periods in which human activities are net CO2\r\nsources to the atmosphere, and the amount of emissions removed by CDR is smaller than the net source (net positive CO2 emissions), \r\nCDR acts to reduce the net emissions (Box 5.3 Figure 1c). In this scenario, part of the CO2 emissions in the atmosphere are removed \r\nby the land and ocean sinks, as has been the case historically."


id: de03c59415371c48e21a097fc5d429ac
created_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 36324
content:
"When CDR removes more CO2 emissions than human activities emit (net negative CO2 emissions), and atmospheric CO2 declines, the \r\nland and ocean sinks initially continue to take up CO2 from the atmosphere. This is because carbon sinks, particularly the ocean, exhibit \r\ninertia and continue to respond to the prior trajectory of rising atmospheric CO2 concentration. After some time, which is determined \r\nby the magnitude of the removal and the rate and amount of CO2 emissions prior to the CDR application, land and ocean carbon \r\nreservoirs begin to release CO2 into the atmosphere, making CDR less effective (Box 5.3, Figure 1d)."


id: 1d76aa728756fb0a45100b9fc214e712
created_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"Box 5.3, Figure 1| Schematic representation of carbon fluxes between atmosphere, land, ocean and geological reservoirs. Different system conditions \r\nare shown: (a) an unperturbed Earth system; and changes in carbon fluxes for (b) an Earth system perturbed by fossil fuel carbon dioxide (CO2) emissions; (c) an Earth \r\nsystem in which fossil fuel CO2 emissions are partially offset by carbon dioxide removal (CDR); (d) an Earth system in which CDR exceeds CO2 emissions from fossil \r\nfuels ('net negative' CO2 emissions). Carbon fluxes depicted in (a) (solid and dashed black lines) also occur in (b-d). The question mark in the land-to-ocean carbon \r\nflux perturbation in (c) and (d) indicates that the effect of CDR on this flux is unknown. Note that box sizes do not scale with the size of carbon reservoirs. Adapted \r\nfrom Keller et al. (2018a). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6)."


id: 672119d87c47855fd7001bf946e4e043
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updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"Idealized 'pulse' removal Earth system model simulations are useful \r\nfor understanding the carbon cycle response to CDR.  Figure  5.32 \r\nillustrates the response of atmospheric CO2, land and ocean carbon \r\nsinks to an instantaneous CO2 removal applied from a pre-industrial \r\nequilibrium state. Following CO2 removal from the atmosphere, \r\nthe atmospheric CO2 concentration declines rapidly at first and "


id: 365204672bc875660bd768e6034e33c6
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 6791
content:
"requires a  reference simulation to evaluate the effect of the CO2\r\nremoval. When CDR is applied from an equilibrium state, the PAF and \r\nAF are equivalent measures."


id: 5c7bad7071bcabe2bbb366fffc567b55
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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content:
"-1000 PgC). Data for the UVic ESCM is from Zickfeld et al. (2021). (b) Perturbation \r\nairborne fraction (see text for definition) for model simulations where CDR is applied \r\nfrom four Representative Concentration Pathways (RCPs) (shown on the horizontal \r\naxis in terms of their cumulative CO2 emissions during 2020-2099). Symbols indicate \r\nresults for four CDR scenarios, which differ in terms of the magnitude and rate of CDR \r\n(see Jones et al. (2016b) for details). Results are based on simulations with the Hadley \r\nCentre Simple Climate-Carbon Model and are shown for the year 2100. Data from \r\nJones et al. (2016b). Further details on data sources and processing are available in \r\nthe chapter data table (Table 5.SM.6)."


id: 9e77f998543c7b8a60df48735dd58482
created_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
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content:
"It is commonly assumed that the climate-carbon cycle response \r\nto a  negative CO2 emission (i.e.,  removal from the atmosphere) \r\nis equal in magnitude and opposite in sign to the response to \r\na  positive CO2 emission of equal magnitude -  that is, symmetric. \r\nIf the response were symmetric, a  positive CO2 emission could be \r\noffset by a  negative emission of equal magnitude. This subsection \r\nassesses the symmetry in the coupled climate-carbon cycle response "


id: 6653c2d0bedfeda81a6bb5c5d9d732a8
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index: climate_gpt_v2
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content:
"conservation initiatives, accelerating breeding for tree health and \r\nproductivity (Isabel et al., 2020)."


id: f28fe6e236f63bacf98e70a1821e0b93
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
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index: climate_gpt_v2
vector_id: 40075
content:
"In response to increasing risks to permanence of carbon stocks of some \r\ntypes of afforestation practices and the competition for land, there \r\nhas been an increasing recognition that secondary forest regrowth \r\nand restoration of degraded forests and non-forest ecosystems can \r\nplay a  large role in carbon sequestration (high confidence). The \r\nrational for this focus builds on their high carbon stocks and rates of \r\nsequestration (Griscom et al., 2017; Lewis et al., 2019; Maxwell et al., \r\n2019; Pugh et al., 2019), high resilience to disturbances (Dymond \r\net al., 2014; Messier et al., 2019), and additional benefits such as \r\nenhanced biodiversity (Strassburg et al., 2020)."


id: 53c3e2177870905b2f27455b26cdde86
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12006
content:
"The global sequestration potential of forestation varies substantially \r\ndepending on the scenario-assumptions of available land and of \r\nbackground climate (AR6 WGIII, Section 7.5). Afforestation of native \r\ngrasslands, savannas, and open-canopy woodlands leads to the \r\nundesirable loss of unique natural ecosystems with rich biodiversity, \r\ncarbon storage and other ecosystem services (Veldman et al., 2015; \r\nIPBES, 2018). Comprehensive approaches to assess the effectiveness \r\nof land-based carbon removal options need to be based on the \r\nwhole carbon cycle, covering both carbon stocks and flows, and \r\nestablishing the links between human activities and their impacts on \r\nthe biosphere and atmosphere (Keith et al., 2021)."


id: 782b904eef3247c6dbcd01ec8c7b0b16
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 18355
content:
"Biological CDR methods, introduced in Table  5.9, seek to increase \r\ncarbon storage on land by enhancing net primary productivity and/or \r\nreducing CO2 sources to the atmosphere."


id: 19e9b9dd7f485e354ab7e72b2cd29f09
created_at: 2023-04-19 13:21:35
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vector_id: 1756
content:
"Forest-based methods include afforestation, reforestation, and forest \r\nmanagement (Table 5.9). Building on previous work that emphasized \r\nthe global potentials of various options, more recent advances have \r\nfocused on the limits of those global potentials in light of ecological \r\nand climate risks that can threaten the long-term permanence of \r\ncarbon stocks (Boysen et al., 2017b; Anderegg et al., 2020). Some \r\nof those risks arise from droughts, fires, insect outbreaks, diseases, \r\nerosion, and other disturbances (Thompson et al., 2009)."


id: b536f8cb3896e8ccd6e356c17e9a1ebb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29120
content:
"Sustainable forest management can help to manage some of these \r\nvulnerabilities, while in some cases it can increase and maintain \r\nforest sinks through harvest, transfer of carbon to wood products \r\nand their use to store carbon and substitute emissions-intensive \r\nconstruction materials (Churkina et al., 2020). Forest genomics \r\ntechniques can increase the success of both reforestation and "


id: 9ad05d515f34c862a17f9cb293ea03db
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24480
content:
"In conclusion, land-based CDR methods that rely on enhanced net \r\nbiological uptake and storage of carbon, have a  wide range of \r\nbiogeochemical and biophysical side effects. These side effects can \r\n(directly or indirectly) strengthen or weaken the climate change \r\nmitigation effect of a  given method, or affect water quality and \r\nquantity, food supply and biodiversity (Figure  5.36). With the \r\nexception of weakened ocean carbon sequestration, there is low \r\nconfidence in the Earth system feedbacks of these methods. Most "


id: 8716cff404d93281d2aa4bcb8fd484eb
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 20927
content:
"methods are associated with a  range of biogeochemical and \r\nbiophysical side effects and co-benefits and trade-offs, but these \r\nare often highly dependent on local context, management regime, \r\nprior land use, and scale (high confidence). Highest co-benefits are \r\nobtained with methods that seek to restore natural ecosystems and \r\nimprove soil carbon sequestration (Figure 5.36) while highest trade\u0002off possibilities (symmetry with the highest co-benefits) occur for \r\nreforestation or afforestation with monocultures and BECCS, again \r\nwith strong dependence on scale and context (medium confidence)."


id: f8a320bda3b0a9a3e59203d9b9f969c2
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 41109
content:
"immediate threat to the integrity of coastal carbon stocks (Smale \r\net al., 2019). Blue carbon restoration seeks to increase the rate of \r\ncarbon sequestration, although restoration may be challenging, \r\nbecause of ongoing use of coastal land for human settlement, \r\nconversion to agriculture and aquaculture, shoreline hardening and \r\nport development."


id: 6972768625e5ade62b066116864fa866
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 15821
content:
"Biogeochemical factors affecting reliable quantification of the \r\nclimatic benefits of coastal vegetation include the variable production \r\nof CH4 and N2O by such ecosystems (Adams et al., 2012; Keller, 2018; \r\nRosentreter et al., 2018), uncertainties regarding the provenance \r\nof the carbon that they accumulate (Macreadie et al., 2019), and \r\nthe release of CO2 by biogenic carbonate formation in seagrass \r\necosystems (Kennedy et al., 2018). While coastal habitat restoration \r\npotentially provides significant mitigation of national emissions for \r\nsome countries (Taillardat et al., 2018; Serrano et al., 2019), the global \r\nsequestration potential of blue carbon approaches is <0.02 PgC yr-1\r\n(medium confidence) (Figure 5.36; SROCC, Section 5.5.1.2; Griscom \r\net al., 2017; Gattuso et al., 2018; GESAMP, 2019; NASEM, 2019)."


id: b6ced1807646143c6b61117201a5da06
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29362
content:
"Restoration of vegetated coastal ecosystems (sometimes referred \r\nto as 'blue carbon' -  see Glossary) refers to the potential for \r\nincreasing carbon sequestration by plant growth and burial \r\nof organic carbon in the soil of coastal wetlands (including salt \r\nmarshes and mangroves) and seagrass ecosystems. Wider usage of \r\nthe term blue carbon occurs in the literature, for example, including \r\nseaweeds (macroalgae), shelf sea sediments and open ocean \r\ncarbon exchanges. However, such systems are less amenable to \r\nmanagement, with many uncertainties relating to the permanence \r\nof their carbon stores (Windham-Myers et al., 2018; Lovelock and \r\nDuarte, 2019; SROCC, Section 5.5.1.1)."


id: 561050d5a9ad363e9507a9da22837742
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 12413
content:
"Ocean alkalinization, via the deposition of alkaline minerals \r\n(e.g., olivine) or their dissociation products (e.g., quicklime) at the \r\nocean surface, can increase surface total alkalinity and thus increase \r\nCO2 uptake and storage (Glossary; Supplementary Material Text \r\n5.SM.3; AR6 WGIII Chapter 12; GESAMP, 2019; Keller, 2019). Ocean \r\nalkalinization ameliorates surface ocean acidification (high confidence) \r\n(Hauck et al., 2016; Tran et al., 2020), but there are also negative side \r\neffects on the marine ecosystem, most of which are poorly understood \r\nor quantified (Figure 5.36 and Supplementary Materials Table 5.SM.4; \r\nBach et al., 2019). Although ocean alkalinization could potentially \r\nsequester large amounts of carbon (>=1  PgC yr-1; Figure  5.36; and \r\nSupplementary Materials Table 5.SM.5) there is no new evidence to "


id: eff7c0c076e57801d8bc7ceec3dc9636
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 39600
content:
"revisit the SROCC (SROCC Section 5.5.1.2.4) conclusion that there is \r\nlow confidence that ocean alkalinization is a viable climate change \r\nmitigation approach."


id: afe853ac0723799c74bab09d50275ad3
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 28186
content:
"Proposals to remove CH\r\n4 from the atmosphere are emerging \r\n(de Richter et al., 2017; Jackson et al., 2019). CH\r\n4 removal methods \r\nseek to capture CH\r\n4 directly from ambient air, similarly to DACCS \r\nfor CO\r\n2 using, for example, zeolite trapping, but instead of storing \r\nit, CH\r\n4 would be chemically oxidized to CO2 (Jackson et al., 2019). \r\nMethane can be also removed microbially by supporting naturally \r\noccurring processes, such as by enhancing the soil microbial uptake \r\nthrough afforestation (J. Wu et al., 2018) or by directing the venting \r\nair from a  cow barn into the soil bed of a  nearby greenhouse, \r\nutilizing microbial CH\r\n4 oxidation (Nisbet et al., 2020). Microbial CH4\r\noxidation could also be used for removal of CH\r\n4 leaked from point \r\nsources by building biocatalytic polymers which include methane\u0002oxidizing enzymes (Blanchette et al., 2016). Methane removal is, \r\nhowever, still in its infancy and the available literature is insufficient \r\nfor an assessment."


id: 9c090ea3b9f4e51535123b24bb4fc488
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 24704
content:
"CDR me\r\nAfforestationand forest m\r\nSoil carbon s\r\nBiochar\r\nBioenergy wcapture and (BECCS)\r\nPeatland resBlue carbon \r\nDirect air carand storage \r\nOcean alkaliArtificial ocea\r\nCharacteristicremoval (CDR\r\nEnhanced w\r\nOcean iron f\r\nDecades \r\nto\r\ncenturies\r\nCenturies\r\nto \r\nmillenia\r\n10 to 100\r\nthousand\r\nyears\r\nPotentially\r\npermanent\r\nTimescale of \r\ncarbon storage\r\nFigure 5.36 | Characterismethods) sequestration potfor some methods also consunderlying this classification biogeochemical, biophysical, \r\nwhether the feedbacks streincreases or decreases the mquantity, food production anavailable in the chapter data "


id: b8347801f151eecd7f8e5c4611a17302
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 29623
content:
"in response to initiation or termination of SRM. Most literature on \r\nthe biogeochemical responses to SRM focuses on stratospheric \r\naerosol injection (SAI), and only a  few studies have investigated \r\nthe biogeochemical responses to marine cloud brightening (MCB) \r\nand cirrus cloud thinning (CCT). At the time of AR5, there were only \r\na few studies on the biogeochemical responses to SRM. The main \r\nassessment of AR5 (Ciais et al., 2013) was that SRM will not interfere \r\nwith the direct biogeochemical effects of increased CO2, such as \r\nocean acidification and CO2 fertilization, but could affect the carbon "


id: 7442502c19b1d4f958293d4b299ed6aa
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 17687
content:
"This section assesses the possible consequences of solar radiation \r\nmodification (SRM) on the biosphere and global biogeochemical \r\ncycles. The SRM options and the physical climate response to SRM is \r\nassessed in detail in Section 4.6.3 and Table 4.7. Section 6.3.6 assesses \r\nthe potential effective radiative forcing of aerosol-based SRM \r\noptions and Section 8.6.3 assesses the abrupt water cycle changes "


id: f5755cf95561ac4f77c8e4fdd2a3fa3c
created_at: 2023-04-19 13:21:35
updated_at: 2023-04-19 13:21:35
content_type: text
index: climate_gpt_v2
vector_id: 40549
content:
"Figure 5.37 | Cumulative carbon dioxide (CO2) uptake by land and ocean carbon sinks in response to stratospheric sulphur dioxide (SO2) injection. Results \r\nare shown for a scenario with 50-year (2020-2069) continuous stratospheric SO2 injection at a rate of 5 Tg yr-1 appplied to a RCP4.5 baseline scenario (GeoMIP experiment G4; \r\nKravitz et al., 2011), followed by termination in year 2070. Anomalies are shown relative to RCP4.5 for the multi-model ensemble mean and for each of six Earth system models \r\n(ESMs) over the 50-year period of stratospheric SO2 injection (left-hand side), and over 20 years after termination of SO2 injection (right-hand side). Adapted from Plazzotta et al. \r\n(2019). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6)."


id: bcdc64689c7306a36adb50accf321c0c
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 30467
content:
"cycle through climate-carbon feedbacks. Overall, AR5 concluded that \r\nthe level of confidence on the effects of SRM on carbon and other \r\nbiogeochemical cycles is very low (Ciais et al., 2013). Since AR5, more \r\nmodelling work has been conducted to examine various aspects of \r\nthe global biogeochemical cycle responses to SRM. "


id: af47fb6fa5dbaad4a984dd68078fb593
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 28072
content:
"would increase the global land carbon sink relative to a  high-CO2\r\nworld without SRM (high confidence)."


id: 12c4a702adf71467e02b781ba38dfdf1
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 505
content:
"Based on available evidence, SRM with elevated CO2 would increase \r\nglobal mean NPP and carbon storage on land relative to an unperturbed \r\nclimate, mainly because of CO2 fertilization of photosynthesis (high \r\nconfidence) (Glienke et al., 2015; Tjiputra et al., 2016; Dagon and \r\nSchrag, 2019; Duan et al., 2020; C.-E. Yang et al., 2020). However, the \r\namount of increase is uncertain as it depends on the extent to which \r\nCO2 fertilization of land plants is limited by nutrient availability."


id: b6b83bd57ef6ae647becd258b40ada78
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 29348
content:
"Relative to a  high-greenhouse gas (GHG) world without solar \r\nradiation modification (SRM), SRM would affect the carbon cycles \r\nthrough changes in sunlight, climate (e.g., temperature, precipitation, \r\nsoil moisture, ocean circulation), and atmospheric chemistry \r\n(e.g.,  ozone; Section  4.6.3.3; Cao, 2018). Net SRM effects on the \r\ncarbon cycle, relative to a world without SRM, depend on the change \r\nof individual factors, and interactions among them."


id: 655c94f27dd1d41d2d586ac0b86c21e5
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 15104
content:
"Relative to a  high-CO2 world without SRM, SRM would also  have \r\ncompensating effects on crop yields. SRM is expected to \r\nhave  a  positive impact on crop yields by diminishing heat stress \r\n(Pongratz et al., 2012). However, reductions in light availability will \r\nproduce a  counteracting reduction in crop yields, especially if the \r\ncrop type does not benefit appreciably from diffuse-light fertilization \r\n(Proctor et al., 2018). The balance between these effects varies \r\nmarkedly across crop types and regions, from projected increases \r\nin maize production in China (Xia et al., 2014) to reductions in \r\ngroundnut yields in parts of India (Yang et al., 2016). Because of \r\nthese diverging results from a limited set of studies, there is overall \r\nlow confidence in the effect of SRM on crop yields."


id: 33ef4fa9225ab90553d9bd9815120b1b
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 6380
content:
"Consistent with the AR5 assessment, there is high confidence that \r\nSRM would not mitigate CO2-induced ocean acidification (Ciais \r\net al., 2013). Some studies even suggest an acceleration of deep\u0002ocean acidification as a result of ocean circulation change (Tjiputra \r\net al., 2016; Lauvset et al., 2017). There are large differences in the \r\nsimulated spatial pattern of ocean NPP change in response to SRM, \r\nwhich depends strongly on the SRM method that is considered \r\n(Partanen et al., 2016; Lauvset et al., 2017)."


id: 5949a5f489cd69b3b078062bc7beddbb
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 12948
content:
"to reduce the rate of release of CO2 and CH4 from permafrost thaw \r\n(Lee et al., 2019; Chen et al., 2020)."


id: b6ccb03cc8cf2c81022358766b789c28
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 29361
content:
"A hypothetical sudden and sustained termination of SRM would \r\ncause a rapid increase in global warming that would pose great risks \r\nto biodiversity (A.  Jones et al., 2013; McCusker et al., 2014; Trisos \r\net al., 2018) (Section  4.6.3.3). It would also weaken carbon sinks, \r\naccelerating atmospheric CO2 accumulation and inducing further \r\nwarming (Figure 5.37; Matthews and Caldeira, 2007; Tjiputra et al., \r\n2016; Muri et al., 2018; Plazzotta et al., 2019). However, a scenario with \r\ngradual phase-out of SRM under emissions reduction could reduce \r\nthe large negative effect of sudden SRM termination (MacMartin \r\net al., 2014; Keith and MacMartin, 2015; Tilmes et al., 2016), though \r\nthis would be limited by how rapidly emissions reductions can be \r\nscaled-up (Ekholm and Korhonen, 2016)."


id: fbabb7cd7ab6fc5b0b4db27127c9c187
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 41649
content:
"SAI is found to reduce global average surface ozone concentration \r\n(Xia et al., 2017) mainly as a result of aerosol-induced reduction in \r\nstratospheric ozone at polar regions, resulting in reduced transport \r\nof ozone from the stratosphere (Pitari et al., 2014; Tilmes et al., \r\n2018). The reduction in surface ozone, together with alteration to \r\nultraviolet (UV) radiation, would have important implications for \r\nvegetation response (Xia et al., 2017). A  modelling study shows \r\nthat sea salt aerosol injection for MCB would reduce hydroxyl (OH) \r\nconcentration and increase CH4 lifetime, and hence, have potential \r\nimplications for surface ozone pollution (Horowitz et al., 2020). It \r\nhas also been reported that the use of SAI to limit global mean \r\nwarming from 2degC to 1.5degC would reduce fire weather in many \r\nareas (Burton et al., 2018)."


id: c24fd0a728bc373419edcf1ee2e8c4dc
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 31468
content:
"SRM would alter the global carbon cycle through SRM-induced climate \r\neffect, such as changes in sunlight, temperature, precipitation, and \r\nocean circulation. Compared to a high-CO2 world without SRM, SRM \r\nwould enhance the net uptake of CO2 by the terrestrial biosphere \r\nand ocean, thus acting to reduce atmospheric CO2 (high confidence). \r\nSRM would also affect surface ozone, UV radiation, and atmospheric \r\nchemistry. Due to complex interplays between SRM-induced changes \r\nin direct and diffuse sunlight, temperature, the coupling of water\u0002carbon-nitrogen cycles, and atmospheric chemistry, there is large \r\nuncertainty in the overall response of the terrestrial biosphere \r\nresponse to SRM. Thus, the level of confidence on the effect of SRM \r\non carbon and other biogeochemical cycles is low."


id: 4f365d82beddec369601bc3dd7c4b247
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 11223
content:
"For decades, about half of the carbon dioxide (CO2) that human activities have emitted to the atmosphere \r\nhas been taken up by natural carbon sinks in vegetation, soils and oceans. These natural sinks of CO2 have \r\nthus roughly halved the rate at which atmospheric CO2 concentrations have increased, and therefore slowed \r\ndown global warming. However, observations show that the processes underlying this uptake are beginning to \r\nrespond to increasing CO2 in the atmosphere and climate change in a way that will weaken nature's capacity \r\nto take up CO2 in the future. Understanding of the magnitude of this change is essential for projecting how the \r\nclimate system will respond to future emissions and emissions reduction efforts."


id: 3346699fce19a6e8970b3b5d1eff965a
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 6273
content:
"Direct observations of CO2 concentrations in \r\nthe atmosphere, which began in 1958, show that the \r\natmosphere has only retained roughly half of the CO2 \r\nemitted by human activities, due to the combustion of \r\nfossil fuels and land-use change such as deforestation \r\n(FAQ 5.1, Figure 1). Natural carbon cycle processes on \r\nland and in the oceans have taken up the remainder \r\nof these emissions. These land and ocean removals or \r\n'sinks' have grown largely in proportion to the increase \r\nin CO2 emissions, taking up 31% (land) and 23% \r\n(ocean) of the emissions in 2010-2019, respectively \r\n(FAQ 5.1, Figure 1). Therefore, the average proportion \r\nof yearly CO2 emissions staying in the atmosphere \r\nhas remained roughly stable at 44% over the last six \r\ndecades, despite continuously increasing CO2 emissions \r\nfrom human activities."


id: ef732044db28b4c31e8fa7c8f6f51fc6
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 39501
content:
"No, natural carbon sinks have taken up a near constant \r\nfraction of our carbon dioxide (CO2) emissions over the \r\nlast six decades. However, this fraction is expected to \r\ndecline in the future if CO2 emissions continue to increase."


id: f899834f0e63479e7a52edf4d2cf1ebb
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 41102
content:
"FAQ 5.1, Figure  1 | Atmospheric carbon dioxide (CO2) and natural \r\ncarbon sinks. (Top) Global emissions of CO2 from human activities and the \r\ngrowth rate of CO2 in the atmosphere; (middle) the net land and ocean CO2\r\nremoval (natural sinks); and (bottom) the fraction of CO2 emitted by human \r\nactivities remaining in atmosphere from 1960 to 2019. Lines are the five \r\nyears running mean, error bars denote the uncertainty of the mean estimate. \r\nSee Table 5.SM.6 for more information on the data underlying this figure."


id: d69261f30e459ad43aa33654f3b28dd8
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 35056
content:
"several factors control how much CO2 is captured: the difference in CO2 partial pressure between the atmosphere \r\nand the surface ocean; wind speeds at the ocean surface; the chemical composition of seawater (that is, its \r\nbuffering capacity), which affects how much CO2 can be taken up; and the use of CO2 in photosynthesis by \r\nseawater microalgae. The CO2-enriched surface ocean water is transported to the deep ocean in specific zones \r\naround the globe (such as the Northern Atlantic and the Southern Ocean), effectively storing the CO2 away from \r\nthe atmosphere for many decades to centuries. The combined effect of warmer surface ocean temperatures on \r\nthese processes is to weaken the future ocean CO2 sink. "


id: c9abb19e657be5e698d6e8df67d719b6
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 32804
content:
"The ocean carbon sink is better quantified than the land sink, thanks to direct ocean and atmospheric carbon \r\nobservations. The land carbon sink is more challenging to monitor globally, because it varies widely, even \r\nregionally. There is currently no direct evidence that the natural sinks are slowing down, because observable \r\nchanges in the fraction of human emissions stored on land or in oceans are small compared to year-to-year \r\nand decadal variations of these sinks. Nevertheless, it is becoming more obvious that atmospheric and climate \r\nchanges are affecting the processes controlling the land and ocean sinks."


id: f8bd34da74656441fb0f2e2ca701f077
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 41121
content:
"Since the land and ocean sinks respond to the rise in atmospheric CO2 and to human-induced global warming, \r\nthe absolute amount of CO2 taken up by land and ocean will be affected by future CO2 emissions. This also implies \r\nthat, if countries manage to strongly reduce global CO2 emissions, or even remove CO2 from the atmosphere, \r\nthese sinks will take up less CO2 because of the reduced human perturbation of the carbon cycle. Under future \r\nhigh-warming scenarios, it is expected that the global ocean and land sinks will stop growing in the second \r\nhalf of the century as climate change increasingly affects them. Thus, the total amount of CO2 emitted to the \r\natmosphere and the responses of the natural CO2 sinks will both determine what efforts are required to limit \r\nglobal warming to a certain level (see FAQ 5.4), underscoring how important it is to understand the evolution of \r\nthese natural CO2 sinks."


id: 52795ba7a92dd0363cd103ceed2666e2
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 11795
content:
"In the Arctic, large amounts of organic carbon are stored in permafrost - ground that remains frozen throughout \r\nthe year. If significant areas of permafrost thaw as the climate warms, some of that carbon may be released \r\ninto the atmosphere in the form of carbon dioxide or methane, resulting in additional warming. Projections \r\nfrom models of permafrost ecosystems suggest that future permafrost thaw will lead to some additional \r\nwarming - enough to be important, but not enough to lead to a 'runaway warming' situation, where permafrost \r\nthaw leads to a dramatic, self-reinforcing acceleration of global warming."


id: bc12f18b94f12e2e5ffa58549f1de5ca
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 30325
content:
"The Arctic is the biggest climate-sensitive carbon pool on Earth, storing twice as much carbon in its frozen soils, \r\nor permafrost, than is currently stored in the atmosphere. As the Arctic region warms faster than anywhere else \r\non Earth, there are concerns that this warming could release greenhouse gases to the atmosphere and therefore \r\nsignificantly amplify climate change."


id: db1780a1d34405e67d5ba09a1360455f
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 35820
content:
"The carbon in the permafrost has built up over thousands of years, as dead plants have been buried and \r\naccumulated within layers of frozen soil, where the cold prevents the organic material from decomposing. As \r\nthe Arctic warms and soils thaw, the organic matter in these soils begins to decompose rapidly and return to the \r\natmosphere as either carbon dioxide or methane, which are both important greenhouse gases. Permafrost can \r\nalso thaw abruptly in a given place, due to melting ice in the ground reshaping Arctic landscapes, lakes growing \r\nand draining, and fires burning away insulating surface soil layers. Thawing of permafrost carbon has already \r\nbeen observed in the Arctic, and climate models project that much of the shallow permafrost (<3 m depth) \r\nthroughout the Arctic would thaw under moderate to high amounts of global warming (2degC-4degC)."


id: 40bab3cd7a5f8274ad5c7e145ea4f4a9
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 8574
content:
"Overall, thawing permafrost in the Arctic appears to be an important additional source of heat-trapping gases \r\nto the atmosphere, more so than undersea hydrates. Climate and carbon cycle models are beginning to consider \r\npermafrost processes. While these models disagree on the exact amount of the heat-trapping gases that will be \r\nreleased into the atmosphere, they agree that: (i) the amount of such gases released from permafrost will increase \r\nwith the amount of global warming; and (ii) the warming effect of thawing permafrost is significant enough to \r\nbe considered in estimates of the remaining carbon budgets for limiting future warming."


id: 646c6b0c6e90297de356fa13360d0d72
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 14943
content:
"Deliberate removal of carbon dioxide (CO2) from the \r\natmosphere could reverse (i.e.,  change the direction \r\nof) some aspects of climate change. However, this \r\nwill only happen if it results in a net reduction in the \r\ntotal amount of CO2 in the atmosphere, that is, if \r\ndeliberate removals are larger than emissions. Some \r\nclimate change trends, such as the increase in global \r\nsurface temperature, would start to reverse within \r\na  few years. Other aspects of climate change would \r\ntake decades (e.g.,  permafrost thawing) or centuries \r\n(e.g., acidification of the deep ocean) to reverse, and \r\nsome, such as sea level rise, would take centuries to \r\nmillennia to change direction."


id: fc09e2baafed94dec38770801107535
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 41705
content:
"Removing more carbon dioxide (CO2) from the atmosphere \r\nthan is emitted into it could reverse some aspects of climate \r\nchange, but some changes would continue in their current \r\ndirection for decades to millennia."


id: f159889a55db84760635554c5f3c1d0e
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 39846
content:
"In the absence of deliberate CO2 removal, the CO2\r\nconcentration in the atmosphere (a measure of \r\nthe amount of CO2 in the atmosphere) results from \r\na  balance between human-caused CO2 release and \r\nthe removal of CO2 by natural processes on land and \r\nin the ocean (natural 'carbon sinks'; see FAQ 5.1). \r\nIf  CO2 release exceeds removal by carbon sinks, the \r\nCO2 concentration in the atmosphere would increase; "


id: d41f248791e65447bdda544094a6d6b8
created_at: 2023-04-19 13:21:36
updated_at: 2023-04-19 13:21:36
content_type: text
index: climate_gpt_v2
vector_id: 34650
content:
"FAQ 5.3, Figure 1 | Changes in aspects of climate change in response \r\nto a  peak and decline in the atmospheric CO2 concentration (top \r\npanel). The vertical grey dashed line indicates the time of peak CO2\r\nconcentration in all panels. It shows that the reversal of global surface warming \r\nlags the decrease in the atmospheric CO2 concentration by a few years, the \r\nreversal of permafrost area decline lags the decrease in atmospheric CO2 by \r\ndecades, and ocean thermal expansion continues for several centuries. The \r\nquantitative information in the figure (i.e., numbers on vertical axes) is not to \r\nbe emphasized as it results from simulations with just one model and will be \r\ndifferent for other models. The qualitative behaviour, however, can be expected \r\nto be largely model independent."


