Editing IPCC:AR6/WGI/Chapter-11 (section)

==== 11.6.5.3 Soil Moisture Deficits ====

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Areas with projected soil moisture decreases do not fully coincide with areas that have projected precipitation decreases, although there is substantial consistency in the respective patterns ( [[#Dirmeyer--2013|Dirmeyer et al., 2013]] ; [[#Berg--2018|Berg and Sheffield, 2018]] ). However, there are more regions affected by increased soil moisture deficits (Figure 11.19) than precipitation deficits (Figures 2a,b,c and Cross-Chapter Box 11.1) as a consequence of enhanced AED and the associated increased ET, as highlighted by some studies ( [[#Orlowsky--2013|Orlowsky and Seneviratne, 2013]] ; [[#Dai--2018|Dai et al., 2018]] ; [[IPCC:Wg1:Chapter:Chapter-8#8.2.2.1|Section 8.2.2.1]] ). Moisture in the top soil layer is projected to decrease more than precipitation at all warming levels ( [[#Lu--2019|Lu et al., 2019]] ), extending the regions affected by severe soil moisture deficits over most of south and central Europe ( [[#Lehner--2017|Lehner et al., 2017]] ; [[#Ruosteenoja--2018|Ruosteenoja et al., 2018]] ; [[#Samaniego--2018|Samaniego et al., 2018]] ; [[#van%20Der%20Linden--2019|van Der Linden et al., 2019]] ), southern North America ( [[#Cook--2019|Cook et al., 2019]] ), South America ( [[#Orlowsky--2013|Orlowsky and Seneviratne, 2013]] ), southern Africa ( [[#Lu--2019|Lu et al., 2019]] ), East Africa ( [[#Rowell--2015|Rowell et al., 2015]] ), Southern Australia ( [[#Kirono--2020|Kirono et al., 2020]] ), India ( [[#Mishra--2014a|Mishra et al., 2014a]] ) and East Asia (Figure 11.19; [[#Cheng--2015|Cheng et al., 2015]] ). Projected changes in total soil moisture display less widespread drying than those for surface soil moisture ( [[#Berg--2017a|Berg et al., 2017a]] ), but still more than for precipitation (Cross-Chapter Box 11.1, Figures 2a,b,c). The severity of droughts based on surface soil moisture in future projections is stronger than projections based on precipitation and runoff ( [[#Dai--2018|Dai et al., 2018]] ; [[#Vicente-Serrano--2020c|Vicente-Serrano et al., 2020c]] ). Nevertheless, in many parts of the world where soil moisture is projected to decrease, the signal-to-noise ratio among models is low; only the projections in the Mediterranean, Europe, the south-western USA, and southern Africa show a high signal-to-noise ratio in soil moisture projections (Figure 11.19; [[#Lu--2019|Lu et al., 2019]] ). Increases in soil moisture deficits are found to be statistically signicant at regional scale in the Mediterranean region, southern Africa and western South America for changes as small as 0.5°C in global warming, based on differences between +1.5°C and +2°C of global warming ( [[#Wartenburger--2017|Wartenburger et al., 2017]] ). Several other regions are affected when considering changes in droughts for higher changes in global warming ( [[#11.9|Section 11.9]] and Figure 11.19). Seasonal projections of drought frequency for boreal winter (December–January–February) and summer (June–July–August), from CMIP6 multi-model ensemble for 1.5°C, 2°C and 4°C global warming levels, show contrasting trends (Figure 11.19). In the boreal winter in the Northern Hemisphere, the areas affected by drying show ''high agreement'' with those characterized by an increase in meteorological drought projections (Figures 8.14 and 12.4). On the contrary, in the boreal summer, the drought frequency increases worldwide in comparison to meteorological drought projections, with large areas of the Northern Hemisphere displaying a high signal-to-noise ratio (low spead between models). This stresses the dominant influence of ET (as a result of increased AED) in intensifying agricultural and ecological droughts in the warm season in many locations, including mid- to high latitudes.

Increased soil moisture limitation and associated changes in droughts are projected to lead to increased vegetation stress affecting the global land carbon sink in ESM projections ( [[#Green--2019|Green et al., 2019]] ), with implications for projected global warming (Cross-Chapter Box 5). There is ''high confidence'' that the global land sink will become less efficient due to soil moisture limitations and associated agricultural and ecological drought conditions in some regions in higher-emissions scenarios, specially under global warming levels above 4°C; however, there is ''low confidence'' in how these water cycle feedbacks will play out in lower-emissions scenarios (at 2°C global warming or lower; Cross-Chapter Box 5.1).

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'''Figure 11.18 |''' '''Projected changes in (a) the intensity and (b) the frequency of drought under 1°C, 1.5°C, 2°C, 3°C, and 4°C global warming levels relative to the 1850–1900 baseline. (c)''' Summaries are computed for the AR6 regions in which there is at least medium confidence in an increase in agriculture/ecological drought at the 2°C global warming level (‘drying regions’), including Western North America, Central North America, North Central America, Southern Central America, Northern South America, North-Eastern South America, South American Monsoon, South-Western South America, Southern South America, West and Central Europe, Mediterranean, West Southern Africa, East Southern Africa, Madagascar, Eastern Australia, Southern Australia. Caribbean is not included in the calculation because the number of land grid points was too small. A drought event is defined as a 10-year drought event whose annual mean soil moisture was below its 10th percentile from the 1850–1900 base period. For each box plot, the horizontal line and the box represent the median and central 66% uncertainty range, respectively, of the frequency or the intensity changes across the multi-model ensemble, and the ‘whiskers’ extend to the 90% uncertainty range. The line of zero in (a) indicates no change in intensity, while the line of one in (b) indicates no change in frequency. The results are based on the multi-model ensemble estimated from simulations of global climate models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6) under different Shared Socio-economic Pathway (SSP) forcing scenarios. Intensity changes in (a) are expressed as standard deviations of the interannual variability in the period 1850–1900 of the corresponding model. For details on the methods see Supplementary Material 11.SM.2. Further details on data sources and processing are available in the chapter data table (Table 11.SM.9).

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