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

=== 11.1.6 Effects of Regional-scale Processes and Forcings and Feedbacks on Changes in Extremes ===

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At the local and regional scales, changes in extremes are strongly modulated by local and regional feedbacks (SRCCL, [[#Jia--2019|Jia et al., 2019]] ; [[#Seneviratne--2013|Seneviratne et al., 2013]] ; [[#Miralles--2014a|Miralles et al., 2014a]] ; [[#Lorenz--2016|Lorenz et al., 2016]] ; [[#Vogel--2017|Vogel et al., 2017]] ), changes in large-scale circulation patterns ( [[#11.1.5|Section 11.1.5]] ), and regional forcings such as changes in land use or aerosol concentrations (Chapters 3 and 7; [[#Findell--2017|Findell et al., 2017]] ; [[#Hirsch--2017|Hirsch et al., 2017]] , 2018; [[#Thiery--2017|Thiery et al., 2017]] ; Z. [[#Wang--2017|]] [[#Wang--2017|Wang et al., 2017]] b). In some cases, such responses may also include non-local effects (e.g., [[#de%20Vrese--2016|de Vrese et al., 2016]] ; [[#Persad--2018|Persad and Caldeira, 2018]] ; [[#Miralles--2019|Miralles et al., 2019]] ; [[#Schumacher--2019|Schumacher et al., 2019]] ). Regional-scale forcing and feedbacks often affect temperature distributions asymmetrically, with generally higher effects for the hottest percentiles ( [[#11.3|Section 11.3]] ).

Land use can affect regional extremes, in particular hot extremes, in several ways ( ''high confidence'' ). This includes effects of land management (e.g., cropland intensification, irrigation, double cropping) as well as of land cover changes (deforestation; Sections 11.3.2 and 11.6). Some of these processes are not well represented (e.g., effects of forest cover on diurnal temperature cycle) or not integrated (e.g., irrigation) in climate models (Sections 11.3.2 and 11.3.3). Overall, the effects of land-use forcing may be particularly relevant in the context of low-emissions scenarios, which include large land-use modifications, for instance those associated with the expansion of biofuels, bioenergy with carbon capture and storage, or re-/afforestation to ensure negative emissions, as well as with the expansion of food production (e.g., SR1.5, Chapter 3; Cross-Chapter Box 5.1 in this Report; [[#van%20Vuuren--2011|van Vuuren et al., 2011]] ; [[#Hirsch--2018|Hirsch et al., 2018]] ). There are also effects on the water cycle through freshwater use ( [[#11.6|Section 11.6]] and Cross-Chapter Box 5.1).

Aerosol forcing also has a strong regional footprint associated with regional emissions, which affects temperature and precipitation extremes ( ''high confidence'' ) (Sections 11.3 and 11.4). From around the 1950s to 1980s, enhanced aerosol loadings led to regional cooling due to decreased global solar radiation (‘global dimming’) which was followed by a phase of ‘global brightening’ due to a reduction in aerosol loadings (Chapters 3 and 7; [[#Wild--2005|Wild et al., 2005]] ). [[#King--2016b|King et al. (2016b)]] show that aerosol-induced cooling delayed the timing of a significant human contribution to record-breaking heat extremes in some regions. However, the decreased aerosol loading since the 1990s has led to an accelerated warming of hot extremes in some regions. Based on Earth system model (ESM) simulations, [[#Dong--2017|Dong et al. (2017)]] suggest that a substantial fraction of the warming of the annual hottest days in Western Europe since the mid-1990s has been due to decreases in aerosol concentrations in the region. [[#Dong--2016b|Dong et al. (2016b)]] also identify non-local effects of decreases in aerosol concentrations in Western Europe, which they estimate played a dominant role in the warming of the hottest daytime temperatures in north-east Asia since the mid-1990s, via induced coupled atmosphere–land surface and cloud feedbacks, rather than a direct impact of anthropogenic aerosol changes on cloud condensation nuclei.

In addition to regional forcings, regional feedback mechanisms can also substantially affect extremes ( ''high confidence'' ) (Sections 11.3, 11.4 and 11.6). In particular, soil moisture feedbacks play an important role for extremes in several mid-latitude regions, leading to a marked additional warming of hot extremes compared to mean global warming ( [[#Seneviratne--2016|Seneviratne et al., 2016]] ; [[#Bathiany--2018|Bathiany et al., 2018]] ; [[#Miralles--2019|Miralles et al., 2019]] ), which is superimposed on the known land–sea contrast in mean warming ( [[#Vogel--2017|Vogel et al., 2017]] ). Soil moisture–atmosphere feedbacks also affect drought development ( [[#11.6|Section 11.6]] ). Additionally, effects of land surface conditions on circulation patterns have also been reported ( [[#Koster--2016|Koster et al., 2016]] ; [[#Sato--2019|Sato and Nakamura, 2019]] ). These regional feedbacks are also associated with substantial spread in models ( [[#11.3|Section 11.3]] ), and contribute to the identified higher spread of regional projections of temperature extremes as a function of global warming, compared with the spread resulting from the differences in projected global warming (global transient climate responses) in climate models ( [[#Seneviratne--2020|Seneviratne and Hauser, 2020]] ). In addition, there are also feedbacks between soil moisture content and precipitation occurrence, generally characterized by negative spatial feedbacks and positive local feedbacks (Taylor et al., 2012; [[#Guillod--2015|Guillod et al., 2015]] ). Climate model projections suggest that these feedbacks are relevant for projected changes in heavy precipitation ( [[#Seneviratne--2013|Seneviratne et al., 2013]] ). However, there is evidence that climate models do not capture the correct sign of the soil moisture–precipitation feedbacks in several regions, in particular spatially, and/or in some cases also temporally (Taylor et al., 2012; [[#Moon--2019|Moon et al., 2019]] ). In the Northern Hemisphere high latitudes, the snow- and ice-albedo feedback, along with other factors, is projected to largely amplify temperature increases (e.g., [[#Pithan--2014|Pithan and Mauritsen, 2014]] ), although the effect on temperature extremes is still unclear. It also remains unclear whether snow-albedo feedbacks in mountainous regions might have an effect on temperature and precipitation extremes (e.g., [[#Gobiet--2014|Gobiet et al., 2014]] ). However, these feedbacks play an important role in projected changes in high-latitude warming ( [[#Hall--2006|Hall and Qu, 2006]] ), and, in particular, in changes in cold extremes in these regions ( [[#11.3|Section 11.3]] ).

Finally, extreme events may also regionally amplify one another. For example, this is the case for heatwaves and droughts, with high temperatures and stronger radiative forcing leading to drying tendencies on land due to increased evapotranspiration ( [[#11.6|Section 11.6]] ), and drier soils then inducing decreased evapotranspiration and higher sensible heat flux and hot temperatures (Box 11.1, [[#11.8|Section 11.8]] ; [[#Seneviratne--2013|Seneviratne et al., 2013]] ; [[#Miralles--2014a|Miralles et al., 2014a]] ; [[#Vogel--2017|Vogel et al., 2017]] ; [[#Zscheischler--2017|Zscheischler and Seneviratne, 2017]] ; S. [[#Zhou--2019|]] [[#Zhou--2019|Zhou et al., 2019]] ; [[#Kong--2020|Kong et al., 2020]] ).

In summary, regional forcings and feedbacks – in particular those associated with land use and aerosol forcings – and soil-moisture–temperature, soil moisture–precipitation, and snow/ice–albedo–temperature feedbacks, play an important role in modulating regional changes in extremes. These can also lead to a higher warming of extreme temperatures compared to mean temperature ( ''high confidence'' ), and possibly cooling in some regions ( ''medium confidence'' ). However, there is only ''medium confidence'' in the representation of the associated processes in state-of-the-art ESMs.

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