Editing IPCC:AR6/WGII/Chapter-4 (section)

=== 4.4.1 Projected Changes in Precipitation, Evapotranspiration and Soil Moisture ===

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==== 4.4.1.1 Projected Changes in Precipitation ====

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WGI ( [[#Douville--2021|Douville et al., 2021]] ) concludes with ''high confidence'' that without large-scale reduction in GHG emissions, global warming is projected to cause substantial changes in the water cycle at both global and regional scales. However, WGI also noted large uncertainties in many aspects of regional water cycle projections by climate models. Water cycle variability and extremes are projected to increase faster than average changes in most regions of the world and under all emission scenarios ( ''high confidence'' ). The concept of ‘wetter regions get wetter, drier regions get drier’ from AR5 ( [[#Collins--2013)|Collins et al., 2013)]] is assessed by AR6 WGI ( [[#Douville--2021|Douville et al., 2021]] ) as too simplistic. WGI ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ) further concludes that heavy precipitation will generally become more frequent and more intense with additional global warming.

In the CMIP6 multi-model ensemble, as in previous generations of ensembles, the projected changes in annual mean precipitation vary substantially across the world. Importantly, in most land regions, the future changes are subject to high uncertainty even in the sign of the projected change ( ''high confidence'' ). Figure 4.10 illustrates this using the 5th, 50th and 95th percentile changes across the ensemble at individual grid points. For any given location, the range of projected changes generally increases with global warming ( ''high confidence'' ).

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'''Figure 4.10 |''' '''Projected percentage changes in annual mean precipitation at global warming levels (GWLs) of 4°C (top), 2°C (middle) and 1''' '''.''' '''5°C (bottom) for the CMIP6 multi-model ensemble of GCMs driven by the SSP5-8.5 scenario.''' For any given GWL, similar ranges of changes are seen with other scenarios that reach that GWL, and the difference between scenarios is smaller than the ensemble uncertainty ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). The distribution of outcomes is shown at local scales with the 5th, 50th and 95th percentile precipitation changes in individual grid boxes. Note that these are uncertainties at the individual point and are not spatially coherent, that is, they do not represent plausible global patterns of change. Results for 1.5°C, 2°C and 4°C global warming are defined as 20-year means relative to 1850–1900 and use 40, 40 and 31 ensemble members, respectively, due to some members not reaching 4°C global warming.

For example, in parts of the Indian sub-continent, the projected changes in mean precipitation at 1.5°C global warming range from a 10–20% decrease to a 40–50% increase. The multi-model median change is close to zero. Most other regions show a smaller range of changes (except for very dry regions where a small absolute change in precipitation appears as a larger percentage change). Nevertheless, across most global land regions, both increases and decreases in precipitation are projected across the ensemble. At 1.5°C global warming, a complete consensus on increased precipitation is seen only in the central and eastern Sahel, south-central Asia, parts of Greenland and Antarctica, and the far northern regions of North America and Asia, with projected increases in the latter ranging up to 20–30%. No land regions see a complete consensus on decreased precipitation, but South America, southern Africa and the Mediterranean region show a stronger consensus towards reduced precipitation.

The geographical patterns of local agreement/disagreement in projected precipitation change remain broadly similar with increased global warming, but the range of uncertainty generally increases ( ''high confidence'' ). For example, in northeastern Amazonia, the driest projections increase from a 10% decrease at 1.5°C global warming to a 40% decrease at 4°C global warming. In comparison, the wettest projections remain at up to a 10% increase. In the far north of North America and Asia, the higher end of projected increases in precipitation extends to approximately 40–60%. A few regions are projected to see a shift in the consensus on the sign of the change. These include parts of the Indian sub-continent where at 4°C global warming, the projected changes shift to a consensus on increased precipitation ranging between a few percent to over 70%.

Notably, the multi-model median change in precipitation is relatively small in many regions—less than 10% over most of the global land surface at 1.5°C global warming. In contrast, in many locations, the 5 th to 95 th percentile range can include changes that are much larger changes than the median and also changes that are relatively large but opposite in sign. At 4°C global warming, the median projected changes are larger, ranging from a 20% decrease to a 40% increase (excluding very dry areas, where percentage changes can be much larger due to very small baseline values), but nevertheless often remain a poor indicator of the range of changes across the ensemble. Therefore, use of the median or mean projected changes for future adaptation decisions could substantially underestimate the risk of large changes in precipitation. It could mean that the risk of the opposite sign of changes is not accounted for. Indeed, for mean precipitation, different multi-model ensembles can show different levels of significance of the central estimate of change ( [[#Uhe--2021|Uhe et al., 2021]] : Figure 4.11a). Consequently, information on the range of possible outcomes can be valued by users for effectively informing risk assessments ( [[#Lowe--2018|Lowe et al., 2018]] ).

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'''Figure 4.11 |''' '''Agreement between different multi-model ensembles on significant changes in (a) annual mean precipitation and (b) annual maximum 1-d precipitation (Rx1day) at 2°C global warming (Uhe et a''' '''l.''' ''', 2021).''' Using central estimates from five ensembles of climate models (CMIP5, CMIP6, HAPPI, HELIX and UKCP18) using different models and different experimental designs for the ensembles, the maps show the number of ensembles for which the central estimate shows a significant drying or wetting change at 2°C global warming relative to pre-industrial levels. The different ensembles reach 2°C global warming at different times. The projected changes are aggregated over the new climatic regions defined for IPCC AR6 ( [[#Iturbide--2020|Iturbide et al., 2020]] ). Hatched regions show where different ensembles project significant changes in opposite directions, i.e., there is no agreement on either drying or wetting. Regions with thick outlines are where CMIP6 disagrees with three of the other four ensembles on the significance of the change, highlighting where over-relying on CMIP6 alone may not fully represent the level of confidence in the projections.

There is a stronger consensus on changes in heavy precipitation than mean precipitation within individual ensembles such as CMIP6 (Figure 4.12) and especially between the means of the different ensembles (Figure 4.11b). At 4°C global warming, the 50th percentile projection is for increased annual maximum 1-d precipitation over virtually all global land, with the median increase being over 20% for a majority of the land. The 95 th percentile increase is 20–40% over most mid-latitude areas and at least 40-–70% over the tropics and subtropics, exceeding 80% over western Amazonia, central Africa and most of the Indian sub-continent. The 5 th percentile also shows an increase over most global land; in other words, decreased heavy precipitation has less than a 5% probability in these regions (Figure 4.12a), although decreases remain possible but of low probability in some regions, particularly northern South America and northern and western Africa. At the 50th and 95th percentiles, similar global patterns of change are projected at 2°C and 1.5°C global warming, with smaller local magnitudes (Figure 4.12e,f,h,i). At the 5 th percentile, decreased Rx1day is seen over much larger land areas (Figure 4.12d,g), which may be a result of internal climate variability being relatively larger than the long-term trend at lower GWLs. In CMIP5, precipitation extremes are projected to be ''more likely'' to increase than to decrease on average over both the humid and arid regions of the world, but with larger uncertainty in arid areas ( [[#Donat--2019|Donat et al., 2019]] ).

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'''Figure 4.12 |''' '''Projected percentage changes in annual maximum daily precipitation (Rx1day) averaged over 20 years centred at the time of first passing (a–c) 4°C, (d–f) 2°C and (g–i) 1''' '''.''' '''5°C global warming levels (GWLs) relative to 1851–1900.''' Results are based on simulations from the CMIP6 multi-model ensemble under the SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios. Uncertainties in the projections are quantified with the (a, d, g) 5th, (b, e, h) 50th and (c, f, i) 95th percentile local values from the ensemble at each GWL. Note that these are uncertainties at the individual point and are not spatially coherent, that is, they do not represent plausible global patterns of change. The 50th percentile maps (b, e, h) present the same data over land as Figure 11.16 of [[#Seneviratne--2021|Seneviratne et al. (2021)]] . The numbers on the left indicate the number of simulations included at each warming level, including multiple realisations from some models with varying initial conditions, depending on data availability. Results for the 1.5°C GWL include 37 unique models. Fewer models and realisations are available for the 2°C and 4°C GWLs, as fewer scenarios and/or models reach those warming levels. For individual models, the global patterns of changes are very similar across scenarios, and any differences between scenarios are smaller than the ensemble uncertainty for an individual scenario. The CMIP6 projections of changes in mean and extreme precipitation are discussed in more detail by WGI ( [[#Doblas-Reyes--2021|Doblas-Reyes et al., 2021]] ; [[#Seneviratne--2021|Seneviratne et al., 2021]] ).

In the 50th percentile projections at 4°C global warming, dry spells are projected to become up to 40 d longer in South America and southern Africa and up to 20 d shorter in large parts of Asia (Figure 4.13a,b,c). In most regions, the projected changes in dry spell lengths are highly uncertain. In southern Africa, the increase in dry spell length ranges from 10 d to over 40 d. In northeast Asia, dry spells are projected to become shorter by up to 20–30 d. In much of South America, dry spells could increase by over 40 d or decrease by over 10 d. Similar global patterns with smaller magnitudes of change are projected for 2°C and 1.5°C global warming in all three percentiles (Figure 4.13d,e,f,g,h,i).

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'''Figure 4.13 |''' '''As Figure 4.''' '''12 for projected changes in annual consecutive dry days (CDD), the highest number of days yr''' –1 '''with precipitation &lt; 1 mm.''' The 50th percentile maps (b, e, h) present the same data as Figure 11.19a,b,c of [[#Seneviratne--2021|Seneviratne et al. (2021)]] .

Taken together, these projections of more intense precipitation and changes in the length of dry spells give a clear picture of increasingly volatile precipitation regimes, with many regions seeing both longer dry spells and heavier events when precipitation does occur ( ''high confidence'' ).

The critical knowledge gap for precipitation projections is the ability to make precise projections. With such large uncertainties in many regions, climate model projections can inform risk assessments, but cannot provide confident predictions of specific outcomes.

In summary, the annual mean precipitation range is projected to increase or decrease by up to 40% or more at 4°C global warming over many land areas. The ranges of projected precipitation changes are smaller at lower levels of global warming ( ''high confidence'' ). Either an increase or decrease is possible in most regions, but there is an agreement among models on the increase in the far north ( ''high confidence'' ). There is a stronger model consensus on heavy precipitation increasing with global warming over most land areas ( ''high confidence'' ). There are widely varying projections of change in dry spell length ( ''high confidence'' ), but in regions with increasing projected dry spells, the potential increase is larger at higher levels of global warming ( ''high confidence'' ).

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==== 4.4.1.2 Projected Changes in Evapotranspiration ====

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AR5 ( [[#Collins--2013)|Collins et al., 2013)]] found that the CMIP5 model projections of ET increases or decreases followed the same pattern over land as precipitation projections, with additional impacts of reduced transpiration due to plant stomatal closure in response to rising CO 2 concentrations. AR6 WGI ( [[#Douville--2021|Douville et al., 2021]] ) assessed that it is ''very likely'' that ET will increase over land, with regional exceptions in drying areas.

In most CMIP5 and CMIP6 models, projected ET changes are driven not just by meteorological conditions and soil moisture but also by plant physiological responses to elevated CO 2 , which themselves influence meteorology and soil moisture through surface fluxes ( [[#Halladay--2017|Halladay and Good, 2017]] ; [[#Lemordant--2019|Lemordant and Gentine, 2019]] ). Elevated CO 2 causes stomatal closure which decreases ET, but also increases leaf area index (LAI) which in turn increases ET, but these do not necessarily compensate ( [[#Skinner--2017|Skinner et al., 2017]] ). Higher LAI increases transpiration, depleting soil moisture but increasing shading, thus reducing soil evaporation ( [[#Skinner--2017|Skinner et al., 2017]] ), but LAI may not increase in areas where it is already high ( [[#Lemordant--2018|Lemordant et al., 2018]] ). Projected ET decreases from physiological effects alone are widespread but greatest in tropical forests ( [[#Swann--2016|Swann et al., 2016]] ; [[#Kooperman--2018|Kooperman et al., 2018]] ).

Future changes in regional ET are therefore highly uncertain. The CMIP6 multi-model ensemble projects changes in ET varying both in magnitude and sign across the ensemble members (Figure 4.14). At 4°C global warming, the ensemble median projection shows increased ET of approximately 25% in mid/high latitudes but decreases of up to 10% across most of tropical South America, southern Africa and Australia. These CMIP6 ensemble projections resemble ET changes projected by the CMIP5 ensemble, except over central Africa and Southeast Asia ( [[#Berg--2019|Berg and Sheffield, 2019]] ). However, the ensemble ranges are wide and include both increases and decreases in projected ET in many locations, with mid-latitude ET increases being up to approximately 50% and ET decreases in southern Africa being up to approximately 30%. Projected changes are proportionally smaller at lower levels of global warming, while patterns of change remain similar.

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'''Figure 4.14 |''' '''Projected percentage changes in annual mean ET at global warming levels (GWLs) of 4°C (top), 2°C (middle) and 1''' '''.''' '''5°C (bottom) for the CMIP6 multi-model ensemble of GCMs driven by SSP5-8.5 concentrations.''' The distribution of outcomes is shown at local scales with the 5th, 50th and 95th percentile ET changes in individual grid boxes. Note that these are uncertainties at the individual point and are not spatially coherent, that is, they do not represent plausible global patterns of change. Results for 1.5°C, 2°C and 4°C global warming are defined as 20-year means relative to 1850–1900 and use 40, 40 and 31 ensemble members, respectively, due to some members not reaching 4°C global warming.

The relative importance of the physiological and radiative effects of CO 2 on future ET is a crucial knowledge gap, partly because many ESM land surface schemes still use representations of this process based on older experimental studies. Furthermore, large-scale experimental studies using free-air CO 2 enrichment (FACE) techniques to constrain the models have not yet been performed in certain critical ecosystems, such as tropical forests. Finally, uncertainties in equilibrium climate sensitivity (ECS) imply uncertainties in the CO 2 concentration accompanying any given level of warming (Betts and McNeall, 2018).

In summary, the sign of projected ET change depends on region, but there is ''medium confidence'' that ET will increase in the global mean and mid/high latitudes and decrease in northern South America and southern Africa. In addition, the impacts of rising CO 2 concentrations on plant stomata and leaf area play a role in model projections of ET change ( ''high confidence'' ), but there is ''low confidence'' in their overall contribution to global ET change.

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==== 4.4.1.3 Projected Changes in Soil Moisture ====

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AR5 ( [[#Collins--2013)|Collins et al., 2013)]] mainly focused on surface (upper 10 cm) soil moisture, summarising multi-model projections of 21st century annual mean soil moisture changes as broadly decreasing in the subtropics and Mediterranean region and increasing in east Africa and central Asia across the RCPs, with the changes tending to become stronger as global warming increases. AR6 WGI ( [[#Douville--2021|Douville et al., 2021]] ) draw broadly similar conclusions based on new ESMs, noting that compared to CMIP5, the CMIP6 models project more consistent drying in the Amazon basin, Siberia, westernmost North Africa and southwestern Australia. WGI ( [[#Douville--2021|Douville et al., 2021]] ) also note that soil moisture in the upper 10 cm shows more widespread drying than in the total soil column.

The CMIP6 multi-model ensemble of ESMs show varying levels of consensus on projected changes in surface soil moisture with global warming (Figure 4.15). As in CMIP5 ( [[#Cheng--2017|Cheng et al., 2017]] ), uncertainties are substantial, often associated with uncertainties in projected regional precipitation changes ( [[#4.4.1.1|Section 4.4.1.1]] ), and in most regions, both increases and decreases are projected across the ensemble. In the far north of North America and Asia, projected changes in soil moisture at 4°C global warming range from a 20–30% decrease to an increase of 30–40%. In northern mid-latitudes, projections range from a 10–20% decrease to an increase of 20–30%, except for eastern North America, where the projected changes (both increases and decreases) are less than 10%, and western Europe and the Mediterranean where there is a stronger consensus towards decreased soil moisture of up to 25%. South America, southern Africa and Asia also show a stronger consensus towards decreased soil moisture of up to 40% or more in some regions.

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'''Figure 4.15 |''' '''Projected percentage changes in annual mean total column soil moisture relative to 1981–2010 at global warming levels (GWLs) of 4°C (top), 2°C (middle) and 1''' '''.''' '''5°C (bottom) for the CMIP6 multi-model ensemble of GCMs driven by SSP5-8.5 concentrations.''' The distribution of outcomes is shown at local scales with the 5th, 50th and 95th percentile soil moisture changes in individual grid boxes. Note that these are uncertainties at individual points and are not spatially coherent, that is, they do not represent plausible global patterns of change. Results for 1.5°C, 2°C and 4°C global warming are defined as 20-year means relative to 1850–1900 and use 34, 34 and 26 ensemble members, respectively, due to some members not reaching 4°C global warming. Fewer models are shown here than in Figure 4.10 on precipitation and Figure 4.14 on ET because some do not provide soil moisture output.

Most CMIP6 models simulate direct CO 2 effects on plant transpiration, which has been shown to be a strong influence on projected future changes in soil moisture ( [[#Milly--2016|Milly and Dunne, 2016]] ). Approaches that neglect this process project greater decreases in soil moisture availability than the climate models ( [[#Roderick--2015|Roderick et al., 2015]] ; [[#Swann--2016|Swann et al., 2016]] ). Therefore, although several studies project increased global aridity and dryland expansion ( [[#Feng--2013|Feng and Fu, 2013]] ; [[#Sherwood--2014|Sherwood and Fu, 2014]] ; [[#Huang--2016a|Huang et al., 2016a]] ), these may overestimate future drying (Berg et al., 2017). Nevertheless, land surface models, including vegetation responses to CO 2, still project reduced soil moisture in many regions ( [[#Grillakis--2019|Grillakis, 2019]] ).

A critical knowledge gap concerns the relative importance of climate and CO 2 physiological effects on soil moisture, in relation to uncertainties in climate sensitivity. For a given level of global warming, the relative importance of climate effects and the direct effects of CO 2 on transpiration depend on the CO 2 concentration accompanying that level of warming (Betts and McNeall, 2018). Some CMIP6 models have very high climate sensitivities ( [[#Meehl--2020|Meehl et al., 2020]] ), which are assessed as being of low probability on the basis of other lines of evidence ( [[#Sherwood--2020|Sherwood et al., 2020]] ). This means that the CO 2 concentration accompanying specific global warming levels may be too low and lead to overly large projections of soil moisture decrease in those models.

In summary, projected soil moisture changes increase with levels of global warming ( ''high confidence'' ), although there remains substantial disagreement on specific regional changes. In the CMIP6 multi-model ensemble at 4°C global warming, decreased soil moisture of up to 40% is projected in Amazonia, southern Africa and western Europe in all models ( ''high confidence'' ). In all other regions, there is no consensus on the sign of projected soil moisture changes, and projected changes at 4°C global warming include decreases of up to 30% and increases of up to 40%. Projected changes are smaller at lower levels of global warming, with similar geographical patterns of change.

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