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

=== 11.4.1 Mechanisms and Drivers ===

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The SREX (Chapter 3, [[#Seneviratne--2012|Seneviratne et al., 2012]] ) assessed changes in heavy precipitation in the context of the effects of thermodynamic and dynamic changes. Box 11.1 assesses thermodynamic and dynamic changes in a warming world to aid the understanding of changes in observations and projections in some extremes and the sources of uncertainties (see also [[IPCC:Wg1:Chapter:Chapter-8#8.2.3.2|Section 8.2.3.2]] ). In general, warming increases the atmospheric water-holding capacity following the Clausius–Clapeyron (C-C) relation. This thermodynamic effect results in an increase in extreme precipitation at a similar rate at the global scale. On a regional scale, changes in extreme precipitation are further modulated by dynamic changes (Box 11.1).

Large-scale modes of variability, such as the North Atlantic Oscillation (NAO), El Niño–Southern Oscillation (ENSO), Atlantic Multi-decadal Variability (AMV), and Pacific Decadal Variability (PDV) (Annex IV), modulate precipitation extremes through changes in environmental conditions or embedded storms ( [[IPCC:Wg1:Chapter:Chapter-8#8.3.2|Section 8.3.2]] ). Latent heating can invigorate these storms ( [[#Nie--2018|Nie et al., 2018]] ; Z. [[#Zhang--2019|]] [[#Zhang--2019|]] [[#Zhang--2019|]] [[#Zhang--2019|Zhang et al., 2019]] a); changes in dynamics can increase precipitation intensity above that expected from the C-C scaling rate (Sections 8.2.3.2 and 11.7; Box 11.1). Additionally, the efficiency of converting atmospheric moisture into precipitation can change as a result of cloud microphysical adjustment to warming,resulting in changes in the characteristics of extreme precipitation; but changes in precipitation efficiency in a warming world are highly uncertain ( [[#Sui--2020|Sui et al., 2020]] ).

It is difficult to separate the effect of global warming from internal variability inthe observed changes in the modes of variability ( [[IPCC:Wg1:Chapter:Chapter-2#2.4|Section 2.4]] ). Future projections of modes of variability are highly uncertain [[IPCC:Wg1:Chapter:Chapter-4#4.3.3|Section 4.3.3]] ),resulting in uncertainty in regional projections of extreme precipitation. Future warming may amplify monsoonal extreme precipitation. Changes in extreme storms, including tropical/extratropical cyclones and severe convective storms, result in changes in extreme precipitation ( [[#11.7|Section 11.7]] ). Also, changes in sea surface temperatures (SSTs) alter land–sea contrast, leading to changes in precipitation extremes near coastal regions. For example, the projected larger SST increase near the coasts of East Asia and India can result in heavier rainfall near these coastal areas from tropical cyclones ( [[#Mei--2016|Mei and Xie, 2016]] ) or torrential rains ( [[#Manda--2014|Manda et al., 2014]] ). The warming in the western Indian Ocean is associated with increases in moisture surges on the low-level monsoon westerlies towards the Indian subcontinent, which may lead to an increase in the occurrence of precipitation extremes over central India ( [[#Krishnan--2016|Krishnan et al., 2016]] ; [[#Roxy--2017|Roxy et al., 2017]] ).

Decreases in atmospheric aerosols results in warming and thus an increase in extreme precipitation ( [[#Samset--2018|Samset et al., 2018]] ; [[#Sillmann--2019|Sillmann et al., 2019]] ). Changes in atmospheric aerosols also result in dynamic changes such as in tropical cyclones ( [[#Takahashi--2017|Takahashi et al., 2017]] ; [[#Strong--2018|Strong et al., 2018]] ). Uncertainty in the projections of future aerosol emissions results in additional uncertainty in the heavy precipitation projections of the 21st century ( [[#Lin--2016|Lin et al., 2016]] ).

There has been new evidence of the effect of local land-use and land-cover change on heavy precipitation. There is a growing set of literature linking increases in heavy precipitation in urban centres to urbanization ( [[#Argüeso--2016|Argüeso et al., 2016]] ; Y. [[#Zhang--2019|]] [[#Zhang--2019|]] [[#Zhang--2019|]] [[#Zhang--2019|Zhang et al., 2019]] b). Urbanization intensifies extreme precipitation, especially in the afternoon and early evening, over the urban area and its downwind region ( ''medium confidence'' ) (Box 10.3). There are four possible mechanisms: (i) increases in atmospheric moisture due to horizontal convergence of air associated with the urban heat island effect ( [[#Shastri--2015|Shastri et al., 2015]] ; [[#Argüeso--2016|Argüeso et al., 2016]] ); (ii) increases in condensation due to urban aerosol emissions ( [[#Han--2011|Han et al., 2011]] ; [[#Sarangi--2017|Sarangi et al., 2017]] ); (iii) aerosol pollution that impacts cloud microphysics (Box 8.1; [[#Schmid--2017|Schmid and Niyogi, 2017]] ); and (iv) urban structures that impede atmospheric motion (Shepherd, 2013; [[#Ganeshan--2015|Ganeshan and Murtugudde, 2015]] ; [[#Paul--2018|Paul et al., 2018]] ). Other local forcing, including reservoirs ( [[#Woldemichael--2012|Woldemichael et al., 2012]] ), irrigation ( [[#Devanand--2019|Devanand et al., 2019]] ), or large-scale land-use and land-cover change ( [[#Odoulami--2019|Odoulami et al., 2019]] ), can also affect local extreme precipitation.

In summary, precipitation extremes are controlled by both thermodynamic and dynamic processes. Warming-induced thermodynamic change results in an increase in extreme precipitation, at a rate that closely follows the C-C relationship at the global scale ( ''high confidence'' ). The effects of warming-induced changes in dynamic drivers on extreme precipitation are more complicated, difficult to quantify, and are an uncertain aspect of projections. Precipitation extremes are also affected by forcings other than changes in greenhouse gases, including changes in aerosols, land-use and land-cover change, and urbanization ( ''mediu'' ''m confidence'' ).

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