Editing IPCC:AR6/WGI/Chapter-8 (section)

==== 8.2.3.2 Processes Determining Heavy Precipitation and Flooding ====

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Evidence that heavy precipitation events (from sub-daily up to seasonal time scales) intensify as the planet warms has strengthened since AR5 ( [[IPCC:Wg1:Chapter:Chapter-11#11.4|Section 11.4]] , Box 11.1 and Cross-Chapter Box 3.2) based on improved physical understanding, extensive modelling and increasing observational corroboration ( [[#O’Gorman--2015|O’Gorman, 2015]] ; [[#Fischer--2016|Fischer and Knutti, 2016]] ; [[#Neelin--2017|Neelin et al., 2017]] ). There is ''robust evidence'' , with ''medium agreement'' across a range of modelling and observational studies, of thermodynamic intensification of wet seasons ( [[#Chou--2013|Chou et al., 2013]] ; [[#Liu--2013|Liu and Allan, 2013]] ; [[#Dunning--2018|Dunning et al., 2018]] ; [[#Lan--2019|Lan et al., 2019]] ; [[#Zhang--2019|Zhang and Fueglistaler, 2019]] ). Extreme daily precipitation is expected to increase at close to the 7% °C <sup>–1</sup> increase in the near-surface atmospheric moisture-holding capacity determined by the Clausius–Clapeyron equation ( [[IPCC:Wg1:Chapter:Chapter-11#11.4|Section 11.4]] , Figure 8.4), with ''limited evidence'' that higher rates apply for shorter duration precipitation events ( [[#Formayer--2017|Formayer and Fritz, 2017]] ; Lenderink et al. , 2017; Ali et al. , 2018; Guerreiro et al. , 2018; Burdanowitz et al. , 2019; W. Zhang et al. , 2019a) . However, observed estimates sample multiple synoptic weather states, mixing thermodynamic and dynamic factors, so are not directly relatable to climate change responses ( [[#Bao--2017|Bao et al., 2017]] ; [[#Drobinski--2018|Drobinski et al., 2018]] ). The contrasting spatial scales sampled by the observations and models (from global to cloud resolving) explain the large range of daily and sub-daily precipitation scaling with temperature assessed in Figure 8.4.

Since AR5, advances in understanding the expected changes in intense rainfall at the sub-daily time scale ( [[IPCC:Wg1:Chapter:Chapter-11#11.4|Section 11.4]] , Figure 8.4) are provided by idealized or high resolution model experiments and observations ( [[#Westra--2014|Westra et al., 2014]] ; [[#Fowler--2021|Fowler et al., 2021]] ). There is ''robust evidence'' from simplified calculations, convection resolving models and observations that thermodynamics drives an increase in convective available potential energy (CAPE) with warming and therefore the intensity of convective storms ( [[#Singh--2013|Singh and O’Gorman, 2013]] ; [[#Romps--2016|Romps, 2016]] ; [[#Barbero--2019|Barbero et al., 2019]] ). Also, declining relative humidity over land (Sections 2.3.1.3.2 and 8.2.2.1) increases lifting condensation level, thereby delaying but intensifying convective systems ( [[#Louf--2019|Louf et al., 2019]] ; J. [[#Chen--2020|]] [[#Chen--2020|Chen et al., 2020]] a). Larger systems are linked with increasing tropopause height ( [[#Lenderink--2017|Lenderink et al., 2017]] ) that can also amplify storm precipitation ( [[#Prein--2017|Prein et al., 2017]] ). However, the heaviest rainfall is not necessarily associated with the most intense (deepest) storms based on satellite data ( [[#Hamada--2015|Hamada et al., 2015]] ; [[#Hamada--2018|Hamada and Takayabu, 2018]] ). Precipitation intensification can exceed thermodynamic expectations where and when additional latent heating invigorates individual storms ( [[IPCC:Wg1:Chapter:Chapter-11#11.4.1|Section 11.4.1]] ) as implied by ''medium agreement'' across modelling and observational studies (Berg et al. , 2013; Molnar et al. , 2015; Scoccimarro et al. , 2015; Prein et al. , 2017; [[#Zhou--2017|Zhou and Wang, 2017]] ; Nie et al. , 2018; Kendon et al. , 2019; Z. Zhang et al. , 2019) . This intensification depends on time of day, based on convection-permitting simulations (E.P. [[#Meredith--2019|]] [[#Meredith--2019|Meredith et al., 2019]] ).

Intensification of sub-daily rainfall is inhibited in regions and seasons where available moisture is limited ( [[#Prein--2017|Prein et al., 2017]] ). However, a fixed threshold temperature above which precipitation is limited by moisture availability is not supported by modelling evidence ( [[#Neelin--2017|Neelin et al., 2017]] ; [[#Prein--2017|Prein et al., 2017]] ). Enhanced latent heating within storms can also suppress convection at larger scales due to atmospheric stabilization as demonstrated with high resolution, idealized and large ensemble modelling studies (Loriaux et al. , 2017; Chan et al. , 2018; Nie et al. , 2018; Tandon et al. , 2018; Kendon et al. , 2019) . Stability is also increased by the direct radiative heating effect of higher CO <sub>2</sub> concentrations ( [[#Baker--2018|Baker et al., 2018]] ) and influenced by aerosol effects on the atmospheric energy budget and cloud development (Box 8.1). Since AR5, modelling evidence shows increases in convective precipitation extremes are limited by droplet/ice fall speeds (Singh and [[#O’Gorman--2014|O’Gorman, 2014]] ; [[#Sandvik--2018|Sandvik et al., 2018]] ) but these processes are only crudely represented ( [[#Tapiador--2019a|Tapiador et al., 2019a]] ). Idealized regional and coupled global models combined with ''limited'' observational ''evidence'' shows that instantaneous precipitation extremes are sensitive to microphysical processes, while daily extremes are determined more by the degree of convective aggregation ( [[#Bao--2019|Bao and Sherwood, 2019]] ; [[#Pendergrass--2020a|Pendergrass, 2020a]] ).

Dynamical changes modify and can dominate thermodynamic drivers of local rainfall and flood hazard change (Box 11.1). For example, increased land – ocean temperature gradients ( [[#8.2.2.2|Section 8.2.2.2]] ) explain more intense rain from convective systems over the Sahel based on satellite data since the 1980s ( [[#Taylor--2017|Taylor et al., 2017]] ) and dynamical feedbacks can invigorate active to break phase transition over India ( [[#Karmakar--2017|Karmakar et al., 2017]] ; [[#Roxy--2017|Roxy et al., 2017]] ). Satellite data shows long-lived, organized mesoscale convective systems contribute disproportionally to extreme tropical precipitation ( [[#Roca--2020|Roca and Fiolleau, 2020]] ). Since AR5, the spatial variability in soil moisture has been linked with the timing and location of convective rainfall by altering the partitioning between latent and sensible heating. This was demonstrated for the Sahel, Europe and India in observations (C.M. [[#Taylor--2013|Taylor et al., 2013]] ; [[#Taylor--2015|Taylor, 2015]] ; [[#Petrova--2018|Petrova et al., 2018]] ; [[#Barton--2020|Barton et al., 2020]] ; [[#Klein--2020|Klein and Taylor, 2020]] ) but depends on the moisture-convergence regime ( [[#Welty--2020|Welty et al., 2020]] ). Only high-resolution convection-permitting models can capture the sub-grid scale mechanisms for convective initiation ( C.M. Taylor et al. , 2013; H. Moon et al. , 2019 ). There is ''medium evidence'' that greater tropical cyclone rainfall totals can be caused by dynamical feedbacks ( [[#Chauvin--2017|Chauvin et al., 2017]] ) and slower propagation speed as tropical circulation weakens ( [[#Kossin--2018|Kossin, 2018]] ). These processes amplify the thermodynamic intensification of rainfall ( [[IPCC:Wg1:Chapter:Chapter-11#11.7.1.2|Section 11.7.1.2]] ), yet observational support is weak ( [[#Chan--2019|Chan, 2019]] ; [[#Lanzante--2019|Lanzante, 2019]] ; I.J. Moon et al. , 2019; Knutson et al. , 2020) . Slower decay following landfall, explained by larger stores of heat and moisture at higher SSTs, can also amplify rainfall amount based on observations and modelling ( [[#Li--2020|Li and Chakraborty, 2020]] ). Rainfall intensity from the outer rain bands of tropical cyclones is also increased by aerosol – cloud interactions (Box 8.1).

The amount and intensity of rainfall within extratropical storms is expected to increase with atmospheric moisture. This is particularly evident for atmospheric rivers (see Glossary) and research since AR5 has confirmed their link with flooding and terrestrial water storage ( [[#Froidevaux--2016|Froidevaux and Martius, 2016]] ; Paltan et al. , 2017; [[#Waliser--2017|Waliser and Guan, 2017]] ; Adusumilli et al. , 2019; Ionita et al. , 2020; Payne et al. , 2020) . There is ''robust evidence'' based on simple physics and detailed modelling that extratropical cyclone rainfall, including atmospheric river events, will intensify through increased atmospheric moisture flux ( [[#Lavers--2013|Lavers et al., 2013]] ; [[#Ramos--2016|Ramos et al., 2016]] ; [[#Yettella--2017|Yettella and Kay, 2017]] ; V. [[#Espinoza--2018|]] [[#Espinoza--2018|Espinoza et al., 2018]] ; [[#Algarra--2020|Algarra et al., 2020]] ; [[#Xu--2020|Xu et al., 2020]] ; [[#Zavadoff--2020|Zavadoff and Kirtman, 2020]] ; [[#Zhao--2020|Zhao, 2020]] ), although changes in dynamical aspects will modify responses regionally ( [[#8.4.2.8|Section 8.4.2.8]] ). For example, stronger latitudinal temperature gradients in the high-latitude upper troposphere drive increased extratropical storm speed around 30°N – 70°N based on CMIP5 simulations ( [[#Dwyer--2017|Dwyer and O’Gorman, 2017]] ), causing reduced precipitation accumulation.

The response of flood hazard to changing rainfall characteristics depends on time and space scale and the nature of the land surface ( [[IPCC:Wg1:Chapter:Chapter-11#11.5.1|Section 11.5.1]] and FAQ 8.2). Sustained and heavy rainfall can lead to widespread flooding and landslides while intensification of short-duration intense rainfall can increase the severity and frequency of flash flooding ( [[#Marengo--2013|Marengo et al., 2013]] ; [[#Chan--2016|Chan et al., 2016]] ; [[#Gariano--2016|Gariano and Guzzetti, 2016]] ; [[#Sandvik--2018|Sandvik et al., 2018]] ). Flooding events in many tropical regions (e.g., north-western South America, southern Africa and Australasia) are associated with ENSO variability ( [[#Emerton--2017|Emerton et al., 2017]] ; [[#Takahashi--2019|Takahashi and Martínez, 2019]] ; [[#Pabón-Caicedo--2020|Pabón-Caicedo et al., 2020]] ) and amplified by thermodynamic increases in water vapour. Flood hazard from heavy rainfall is modulated by snowmelt ( [[#8.2.3.1|Section 8.2.3.1]] ), vegetation characteristics ( [[#Page--2020|Page et al., 2020]] ; [[#Murphy--2021|Murphy et al., 2021]] ) and direct human intervention (Sections 8.2.3.4 and FAQ 8.2) but also can be compounded by sea level rise (Sections 4.3.2.2 and 9.6.4) in coastal and delta regions ( [[#Bevacqua--2019|Bevacqua et al., 2019]] ; [[#Ganguli--2019|Ganguli and Merz, 2019]] ; [[#Eilander--2020|Eilander et al., 2020]] ). Antecedent soil moisture conditions are an important modulator of flooding ( [[IPCC:Wg1:Chapter:Chapter-11#11.5.1|Section 11.5.1]] ) but become less important for smaller catchments and for more severe floods ( [[#Wasko--2019|Wasko and Nathan, 2019]] ). Depleted soil moisture after more intense dry seasons ( [[#8.2.2.1|Section 8.2.2.1]] ) can allow greater uptake of wet season rainfall before soils saturate. Since AR5, evidence confirms that more intense rainfall increases the proportion of runoff and reservoir recharge relative to infiltration into the soil ( [[#Eekhout--2018|Eekhout et al., 2018]] ; [[#Yin--2018|Yin et al., 2018]] ). More intense but less frequent storms ( [[#Kendon--2019|Kendon et al., 2019]] ) favour focused groundwater recharge through leakage from surface waters (R.G. [[#Taylor--2013|Taylor et al., 2013]] a; [[#Cuthbert--2019a|Cuthbert et al., 2019a]] ) and runoff and flash flooding where the percolation capacity of the soil is exceeded ( [[#Yin--2018|Yin et al., 2018]] ).

Increased severity of flooding on larger, more slowly-responding rivers is expected as precipitation accumulations increase during persistent wet events over a season. This can occur where atmospheric blocking patterns repeatedly steer extratropical cyclones across large river catchments, as identified for NH mid-latitudes and Asia ( [[#Takahashi--2015|Takahashi et al., 2015]] ; [[#Pfleiderer--2018|Pfleiderer et al., 2018]] ; [[#Zhou--2018|Zhou et al., 2018]] ; [[#Blöschl--2019|Blöschl et al., 2019]] ; [[#Lenggenhager--2019|Lenggenhager et al., 2019]] ; [[#Nikumbh--2019|Nikumbh et al., 2019]] ; [[#Zanardo--2019|Zanardo et al., 2019]] ), although groundwater flooding and antecedent conditions including soil moisture and snowmelt also play a role ( [[#Muchan--2015|Muchan et al., 2015]] ; [[#Berghuijs--2019|Berghuijs et al., 2019]] ). Increased atmospheric moisture amplifies the severity of these events when they occur in a warmer climate, yet drivers of change in the occurrence of blocking patterns, stationary waves and jet stream position are not well understood ( [[#8.2.2.2|Section 8.2.2.2]] and Cross-Chapter Box 10.1).

In summary, there is ''very high confidence'' that heavy precipitation events will become more intense in a warming climate. There is ''high confidence'' that increased moisture and its convergence within extratropical and tropical cyclones and storms will increase rainfall totals during wet events at close to the 7% °C <sup>–1</sup> Thermodynamic response, with ''low confidence'' of higher rates for sub-daily intensities. There is ''medium confidence'' that more intense but less frequent rainfall increases the proportion of rainfall leading to surface runoff and focused groundwater recharge from temporary water bodies. There is ''low confidence'' in how the frequency of flooding will change regionally as it is strongly dependent on catchment characteristics, antecedent conditions and how atmospheric circulation systems respond to climate change, which is less certain than thermodynamic drivers ( [[IPCC:Wg1:Chapter:Chapter-11#11.5|Section 11.5]] ). However, there is ''high confidence'' that increases in precipitation intensity and amount during very wet events (from sub-daily up to seasonal time scales) will intensify severe flooding when these extremes occur.

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