Editing IPCC:AR6/SRCCL/Chapter-2 (section)

=== 2.2.5 Climate extremes and their impact on land functioning ===

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Extreme weather events are generally defined as the upper or lower statistical tails of the observed range of values of climate variables or climate indicators (e.g., temperature/rainfall or drought/aridity indices respectively). Previous IPCC reports have reported with ''high confidence'' on the increase of many types of observed extreme temperature events (Seneviratne et al. 2012 <sup>[[#fn:r183|183]]</sup> ; Hartmann et al. 2013b <sup>[[#fn:r184|184]]</sup> ; Hoegh-Guldberg et al. 2018 <sup>[[#fn:r185|185]]</sup> ). However, as a result of observational constraints, increases in precipitation extremes are ''less confident'' , except in observations-rich regions with dense, long-lived station networks, such as Europe and North America, where there have been likely increases in the frequency or intensity of heavy rainfall.

Extreme events occur across a wide range of time and space scales (Figure 2.3) and may include individual, relatively short-lived weather events (e.g., extreme thunderstorms storms) or a combination or accumulation of non-extreme events (Colwell et al. 2008b <sup>[[#fn:r186|186]]</sup> ; Handmer et al. 2012 <sup>[[#fn:r187|187]]</sup> ), for example, moderate rainfall in a saturated catchment having the flood peak at mean high tide (Leonard et al. 2014 <sup>[[#fn:r188|188]]</sup> ). Combinatory processes leading to a significant impact are referred to as a compound event and are a function of the nature and number of physical climate and land variables, biological agents such as pests and disease, the range of spatial and temporal scales, the strength of dependence between processes and the perspective of the stakeholder who defines the impact (Leonard et al. 2014 <sup>[[#fn:r189|189]]</sup> ; Millar and Stephenson 2015 <sup>[[#fn:r190|190]]</sup> ). Currently, there is ''low confidence'' in the impact of compound events on land as the multi-disciplinary approaches needed to address the problem are few (Zscheischler et al. 2018 <sup>[[#fn:r191|191]]</sup> ) and the rarity of compound extreme climatic events renders the analysis of impacts difficult.

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'''Figure 2.3'''

<span id="spatial-and-temporal-scales-of-typical-extreme-weather-and-climate-events-and-the-biological-systems-they-impact-shaded-grey.individuals-populations-and-ecosystems-within-these-space-time-ranges-respond-to-relevant-climate-stressors.-orange-blue-labels-indicate-an-increase-decrease-in-the-frequency-or-intensity-of-the-event-with-bold-font-reflecting-confidence-in-the-change.-non-bold"></span>
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'''Spatial and temporal scales of typical extreme weather and climate events and the biological systems they impact (shaded grey).Individuals, populations and ecosystems within these space-time ranges respond to relevant climate stressors. Orange (blue) labels indicate an increase (decrease) in the frequency or intensity of the event, with bold font reflecting confidence in the change. Non-bold […]'''
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[[File:1c706d64ed3ffc0e76a790971e467699 Figure-2.3-1024x612.jpg]]

Spatial and temporal scales of typical extreme weather and climate events and the biological systems they impact (shaded grey).Individuals, populations and ecosystems within these space-time ranges respond to relevant climate stressors. Orange (blue) labels indicate an increase (decrease) in the frequency or intensity of the event, with bold font reflecting confidence in the change. Non-bold black labels indicate low confidence in observed changes in frequency or intensity of these events. Each event type indicated in the figure is likely to affect biological systems at all temporal and spatial scales located to the left and below the specific event position in the figure. From Ummenhofer and Meehl (2017 <sup>[[#fn:r192|192]]</sup> ).

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<div id="section-2-2-5-1-changes-in-extreme-temperatures-heatwaves-and-drought"></div>

<span id="changes-in-extreme-temperatures-heatwaves-and-drought"></span>
==== 2.2.5.1 Changes in extreme temperatures, heatwaves and drought ====

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It is ''very likely'' that most land areas have experienced a decrease in the number of cold days and nights, and an increase in the number of warm days and unusually hot nights (Orlowsky and Seneviratne 2012 <sup>[[#fn:r193|193]]</sup> ; Seneviratne et al. 2012 <sup>[[#fn:r194|194]]</sup> ; Mishra et al. 2015 <sup>[[#fn:r195|195]]</sup> ; Ye et al. 2018 <sup>[[#fn:r196|196]]</sup> ). Although there is no consensus definition of heatwaves, as some heatwave indices have relative thresholds and others absolute thresholds, trends between indices of the same type show that recent heat-related events have been made more frequent or more intense due to anthropogenic GHG emissions in most land regions (Lewis and Karoly 2013 <sup>[[#fn:r197|197]]</sup> ; Smith et al. 2013b <sup>[[#fn:r198|198]]</sup> ; Scherer and Diffenbaugh 2014 <sup>[[#fn:r199|199]]</sup> ; Fischer and Knutti 2015 <sup>[[#fn:r200|200]]</sup> ; Ceccherini et al. 2016 <sup>[[#fn:r201|201]]</sup> ; King et al. 2016 <sup>[[#fn:r202|202]]</sup> ; Bador et al. 2016 <sup>[[#fn:r203|203]]</sup> ; Stott et al. 2016 <sup>[[#fn:r204|204]]</sup> ; King 2017 <sup>[[#fn:r205|205]]</sup> ; Hoegh-Guldberg et al. 2018 <sup>[[#fn:r206|206]]</sup> ). Globally, 50–80% of the land fraction is projected to experience significantly more intense hot extremes than historically recorded (Fischer and Knutti 2014 <sup>[[#fn:r207|207]]</sup> ; Diffenbaugh et al. 2015 <sup>[[#fn:r208|208]]</sup> ; Seneviratne et al. 2016 <sup>[[#fn:r209|209]]</sup> ). There is ''high confidence'' that heatwaves will increase in frequency, intensity and duration into the 21st century (Russo et al. 2016 <sup>[[#fn:r210|210]]</sup> ; Ceccherini et al. 2017 <sup>[[#fn:r211|211]]</sup> ; Herrera-Estrada and Sheffield 2017 <sup>[[#fn:r212|212]]</sup> ) and under high emission scenarios, heatwaves by the end of the century may become extremely long (more than 60 consecutive days) and frequent (once every two years) in Europe, North America, South America, Africa, Indonesia, the Middle East, South and Southeast Asia and Australia (Rusticucci 2012 <sup>[[#fn:r213|213]]</sup> ; Cowan et al. 2014 <sup>[[#fn:r214|214]]</sup> ; Russo et al. 2014 <sup>[[#fn:r215|215]]</sup> ; Scherer and Diffenbaugh 2014 <sup>[[#fn:r216|216]]</sup> ; Pal and Eltahir 2016 <sup>[[#fn:r217|217]]</sup> ; Rusticucci et al. 2016 <sup>[[#fn:r218|218]]</sup> ; Schär 2016 <sup>[[#fn:r219|219]]</sup> ; Teng et al. 2016 <sup>[[#fn:r220|220]]</sup> ; Dosio 2017 <sup>[[#fn:r221|221]]</sup> ; Mora et al. 2017 <sup>[[#fn:r222|222]]</sup> ; Dosio et al. 2018 <sup>[[#fn:r223|223]]</sup> ; Lehner et al. 2018 <sup>[[#fn:r224|224]]</sup> ; Lhotka et al. 2018 <sup>[[#fn:r225|225]]</sup> ; Lopez et al. 2018 <sup>[[#fn:r226|226]]</sup> ; Tabari and Willems 2018 <sup>[[#fn:r227|227]]</sup> ). Furthermore, unusual heatwave conditions today will occur regularly by 2040 under the RCP 8.5 scenario (Russo et al. 2016 <sup>[[#fn:r228|228]]</sup> ). The intensity of heat events may be modulated by land cover and soil characteristics (Miralles et al. 2014 <sup>[[#fn:r229|229]]</sup> ; Lemordant et al. 2016 <sup>[[#fn:r230|230]]</sup> ; Ramarao et al. 2016 <sup>[[#fn:r231|231]]</sup> ). Where temperature increase results in decreased soil moisture, latent heat flux is reduced while sensible heat fluxes are increased, allowing surface air temperature to rise further. However, this feedback may be diminished if the land surface is irrigated through enhanced evapotranspiration (Mueller et al. 2015 <sup>[[#fn:r232|232]]</sup> ; Siebert et al. 2017 <sup>[[#fn:r233|233]]</sup> ) (Section 2.5.2.2).

Drought (IPCC 2013c <sup>[[#fn:r234|234]]</sup> ), including megadroughts of the last century, for example, the Dustbowl drought (Hegerl et al. 2018 <sup>[[#fn:r235|235]]</sup> ) (Chapter 5), is a normal component of climate variability (Hoerling et al. 2010; Dai 2011 <sup>[[#fn:r236|236]]</sup> ) and may be seasonal, multi-year (Van Dijk et al. 2013 <sup>[[#fn:r237|237]]</sup> ) or multi-decadal (Hulme 2001 <sup>[[#fn:r238|238]]</sup> ) with increasing degrees of impact on regional activities. This inter-annual variability is controlled particularity through remote sea surface temperature (SST) forcings, such as the Inter-decadal Pacific Oscillation (IPO) and the Atlantic Multi-decadal Oscillation (AMO), El Niño/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD), that cause drought as a result of reduced rainfall (Kelley et al. 2015 <sup>[[#fn:r239|239]]</sup> ; Dai 2011 <sup>[[#fn:r240|240]]</sup> ; Hoell et al. 2017 <sup>[[#fn:r241|241]]</sup> ; Espinoza et al. 2018 <sup>[[#fn:r242|242]]</sup> ). In some cases however, large scale SST modes do not fully explain the severity of drought some recent event attribution studies have identified a climate change fingerprint in several regional droughts, for example, the western Amazon (Erfanian et al. 2017 <sup>[[#fn:r243|243]]</sup> ), southern Africa (Funk et al. 2018 <sup>[[#fn:r244|244]]</sup> ; Yuan et al. 2018 <sup>[[#fn:r245|245]]</sup> ), southern Europe and the Mediterranean including North Africa (Kelley et al. 2015 <sup>[[#fn:r246|246]]</sup> ; Wilcox et al. 2018 <sup>[[#fn:r247|247]]</sup> ), parts of North America (Williams et al. 2015 <sup>[[#fn:r248|248]]</sup> ; Mote et al. 2016 <sup>[[#fn:r249|249]]</sup> ), Russia (Otto et al. 2012 <sup>[[#fn:r250|250]]</sup> ), India (Ramarao et al. 2015 <sup>[[#fn:r251|251]]</sup> ) and Australia (Lewis and Karoly 2013 <sup>[[#fn:r252|252]]</sup> ).

Long-term global trends in drought are difficult to determine because of this natural variability, potential deficiencies in drought indices (especially in how evapotranspiration is treated) and the quality and availability of precipitation data (Sheffield et al. 2012 <sup>[[#fn:r253|253]]</sup> ; Dai 2013 <sup>[[#fn:r254|254]]</sup> ; Trenberth et al. 2014 <sup>[[#fn:r255|255]]</sup> ; Nicholls and Seneviratne 2015 <sup>[[#fn:r256|256]]</sup> ; Mukherjee et al. 2018 <sup>[[#fn:r257|257]]</sup> ). However, regional trends in frequency and intensity of drought are evident in several parts of the world, particularly in low latitude land areas, such as the Mediterranean, North Africa and the Middle East (Vicente-Serrano et al. 2014 <sup>[[#fn:r258|258]]</sup> ; Spinoni et al. 2015a <sup>[[#fn:r259|259]]</sup> ; Dai and Zhao 2017 <sup>[[#fn:r260|260]]</sup> ; Páscoa et al. 2017 <sup>[[#fn:r261|261]]</sup> ), many regions of sub-Saharan Africa (Masih et al. 2014 <sup>[[#fn:r262|262]]</sup> ; Dai and Zhao 2017 <sup>[[#fn:r263|263]]</sup> ), central China (Wang et al. 2017e <sup>[[#fn:r264|264]]</sup> ), the southern Amazon (Fu et al. 2013 <sup>[[#fn:r265|265]]</sup> ; Espinoza et al. 2018 <sup>[[#fn:r266|266]]</sup> ), India (Ramarao et al. 2016 <sup>[[#fn:r267|267]]</sup> ), east and south Asia, parts of North America and eastern Australia (Dai and Zhao 2017 <sup>[[#fn:r268|268]]</sup> ). A recent analysis of 4500 meteorological droughts globally found increased drought frequency over the East Coast of the USA, Amazonia and north-eastern Brazil, Patagonia, the Mediterranean region, most of Africa and north-eastern China with decreased drought frequency over northern Argentina, Uruguay and northern Europe (Spinoni et al. 2019 <sup>[[#fn:r269|269]]</sup> ). The study also found drought intensity has become more severe over north-western USA, parts of Patagonia and southern Chile, the Sahel, the Congo River basin, southern Europe, north-eastern China, and south-eastern Australia, whereas the eastern USA, south-eastern Brazil, northern Europe, and central- northern Australia experienced less severe droughts. In addition to the IPCC SR15 assessment of ''medium confidence'' in increased drying over the Mediterranean region (Hoegh-Guldberg et al. 2018 <sup>[[#fn:r270|270]]</sup> ), it is further assessed with ''medium confidence'' that frequency and intensity of droughts in Amazonia, north-eastern Brazil, Patagonia, most of Africa, and north-eastern China has increased.

There is ''low confidence'' in how large-scale modes of variability will respond to a warming climate (Deser et al. 2012 <sup>[[#fn:r271|271]]</sup> ; Liu 2012 <sup>[[#fn:r272|272]]</sup> ; Christensen et al. 2013 <sup>[[#fn:r273|273]]</sup> ; Hegerl et al. 2015 <sup>[[#fn:r274|274]]</sup> ; Newman et al. 2016 <sup>[[#fn:r275|275]]</sup> ). Although, there is evidence for an increased frequency of extreme ENSO events, such as the 1997/98 El Niño and 1988/89 La Niña (Cai et al. 2014a <sup>[[#fn:r276|276]]</sup> , 2015 <sup>[[#fn:r277|277]]</sup> ) and extreme positive phases of the IOD (Christensen et al. 2013 <sup>[[#fn:r278|278]]</sup> ; Cai et al. 2014b <sup>[[#fn:r279|279]]</sup> ). However, the assessment by the SR15 was retained on an increased regional drought risk ( ''medium confidence'' ), specifically over the Mediterranean and South Africa at both 1.5°C and 2°C warming levels compared to present day, with drought risk at 2°C being significantly higher than at 1.5°C (Hoegh-Guldberg et al. 2018 <sup>[[#fn:r280|280]]</sup> ).

<div id="section-2-2-5-2-impacts-of-heat-extremes-and-drought-on-land"></div>

<span id="impacts-of-heat-extremes-and-drought-on-land"></span>
==== 2.2.5.2 Impacts of heat extremes and drought on land ====

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There is ''high confidence'' that heat extremes such as unusually hot nights, extremely high daytime temperatures, heatwaves and drought are damaging to crop production (Chapter 5). Extreme heat events impact a wide variety of tree functions including reduced photosynthesis, increased photooxidative stress, leaves abscise, a decreased growth rate of remaining leaves and decreased growth of the whole tree (Teskey et al. 2015 <sup>[[#fn:r281|281]]</sup> ). Although trees are more resilient to heat stress than grasslands (Teuling et al. 2010 <sup>[[#fn:r282|282]]</sup> ), it has been observed that different types of forest (e.g., needleleaf vs broadleaf) respond differently to drought and heatwaves (Babst et al. 2012 <sup>[[#fn:r283|283]]</sup> ). For example, in the Turkish Anatolian forests net primary productivity (NPP) generally decreased during drought and heatwave events between 2000 and 2010 but in a few other regions, NPP of needle leaf forests increased (Erşahin et al. 2016 <sup>[[#fn:r284|284]]</sup> ). However, forests may become less resilient to heat stress in future due to the long recovery period required to replace lost biomass and the projected increased frequency of heat and drought events (Frank et al. 2015a <sup>[[#fn:r285|285]]</sup> ; McDowell and Allen 2015 <sup>[[#fn:r286|286]]</sup> ; Johnstone et al. 2016 <sup>[[#fn:r287|287]]</sup> ; Stevens-Rumann et al. 2018 <sup>[[#fn:r288|288]]</sup> ). Additionally, widespread regional tree mortality may be triggered directly by drought and heat stress (including warm winters) and exacerbated by insect outbreak and fire (Neuvonen et al. 1999 <sup>[[#fn:r289|289]]</sup> ; Breshears et al. 2005 <sup>[[#fn:r290|290]]</sup> ; Berg et al. 2006 <sup>[[#fn:r291|291]]</sup> ; Soja et al. 2007 <sup>[[#fn:r292|292]]</sup> ; Kurz et al. 2008 <sup>[[#fn:r293|293]]</sup> ; Allen et al. 2010 <sup>[[#fn:r294|294]]</sup> ).

Gross primary production (GPP) and soil respiration form the first and second largest carbon fluxes from terrestrial ecosystems to the atmosphere in the global carbon cycle (Beer et al. 2010 <sup>[[#fn:r295|295]]</sup> ; Bond- Lamberty and Thomson 2010 <sup>[[#fn:r296|296]]</sup> ). Heat extremes impact the carbon cycle through altering these and change ecosystem-atmosphere CO <sub>2</sub> fluxes and the ecosystem carbon balance. Compound heat and drought events result in a stronger carbon sink reduction compared to single-factor extremes as GPP is strongly reduced and ecosystem respiration less so (Reichstein et al. 2013 <sup>[[#fn:r297|297]]</sup> ; Von Buttlar et al. 2018 <sup>[[#fn:r298|298]]</sup> ). In forest biomes, however, GPP may increase temporarily as a result of increased insolation and photosynthetic activity as was seen during the 2015–2016 ENSO related drought over Amazonia (Zhu et al. 2018 <sup>[[#fn:r299|299]]</sup> ). Longer extreme events (heatwave or drought or both) result in a greater reduction in carbon sequestration and may also reverse long-term carbon sinks (Ciais et al. 2005 <sup>[[#fn:r300|300]]</sup> ; Phillips et al. 2009 <sup>[[#fn:r301|301]]</sup> ; Wolf et al. 2016b <sup>[[#fn:r302|302]]</sup> ; Ummenhofer and Meehl 2017 <sup>[[#fn:r303|303]]</sup> ; Von Buttlar et al. 2018 <sup>[[#fn:r304|304]]</sup> ; Reichstein et al. 2013 <sup>[[#fn:r305|305]]</sup> ). Furthermore, extreme heat events may impact the carbon cycle beyond the lifetime of the event. These lagged effects can slow down or accelerate the carbon cycle: it will slow down if reduced vegetation productivity and/or widespread mortality after an extreme drought are not compensated by regeneration, or speed up if productive tree and shrub seedlings cause rapid regrowth after windthrow or fire (Frank et al. 2015a <sup>[[#fn:r306|306]]</sup> ). Although some ecosystems may demonstrate resilience to a single heat climate stressor like drought (e.g., forests), compound effects of, for example, deforestation, fire and drought, potentially can result in changes to regional precipitation patterns and river discharge, losses of carbon storage and a transition to a disturbance-dominated regime (Davidson et al. 2012 <sup>[[#fn:r307|307]]</sup> ). Additionally, adaptation to seasonal drought may be overwhelmed by multi-year drought and their legacy effects (Brando et al. 2008 <sup>[[#fn:r308|308]]</sup> ; da Costa et al. 2010 <sup>[[#fn:r309|309]]</sup> ).

Under medium- and high-emission scenarios, global warming will exacerbate heat stress, thereby amplifying deficits in soil moisture and runoff despite uncertain precipitation changes (Ficklin and Novick 2017 <sup>[[#fn:r310|310]]</sup> ; Berg and Sheffield 2018 <sup>[[#fn:r311|311]]</sup> ; Cook et al. 2018 <sup>[[#fn:r312|312]]</sup> ; Dai et al. 2018 <sup>[[#fn:r313|313]]</sup> ; Engelbrecht et al. 2015 <sup>[[#fn:r314|314]]</sup> ; Ramarao et al. 2015 <sup>[[#fn:r315|315]]</sup> ; Grillakis 2019 <sup>[[#fn:r316|316]]</sup> ). This will  increase the rate of drying causing drought to set in quicker, become more intense and widespread, last longer and could result in an increased global aridity (Dai 2011 <sup>[[#fn:r317|317]]</sup> ; Prudhomme et al. 2014 <sup>[[#fn:r318|318]]</sup> ).

The projected changes in the frequency and intensity of extreme temperatures and drought is expected to result in decreased carbon sequestration by ecosystems and degradation of ecosystems health and loss of resilience (Trumbore et al. 2015 <sup>[[#fn:r319|319]]</sup> ). Also affected are many aspects of land functioning and type including agricultural productivity (Lesk et al. 2016 <sup>[[#fn:r320|320]]</sup> ), hydrology (Mosley 2015 <sup>[[#fn:r321|321]]</sup> ; Van Loon and Laaha 2015 <sup>[[#fn:r322|322]]</sup> ), vegetation productivity and distribution (Xu et al. 2011 <sup>[[#fn:r323|323]]</sup> ; Zhou et al. 2014 <sup>[[#fn:r324|324]]</sup> ), carbon fluxes and stocks, and other biogeochemical cycles (Frank et al. 2015b <sup>[[#fn:r325|325]]</sup> ; Doughty et al. 2015 <sup>[[#fn:r326|326]]</sup> ; Schlesinger et al. 2016 <sup>[[#fn:r327|327]]</sup> ). Carbon stocks are particularly vulnerable to extreme events due to their large carbon pools and fluxes, potentially large lagged impacts and long recovery times to regain lost stocks (Frank et al. 2015a <sup>[[#fn:r328|328]]</sup> ) (Section 2.2).

<div id="section-2-2-5-3-changes-in-heavy-precipitation"></div>

<span id="changes-in-heavy-precipitation"></span>
==== 2.2.5.3 Changes in heavy precipitation ====

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A large number of extreme rainfall events have been documented over the past decades (Coumou and Rahmstorf 2012 <sup>[[#fn:r329|329]]</sup> ; Seneviratne et al. 2012 <sup>[[#fn:r330|330]]</sup> ; Trenberth 2012 <sup>[[#fn:r331|331]]</sup> ; Westra et al. 2013 <sup>[[#fn:r332|332]]</sup> ; Espinoza et al. 2014 <sup>[[#fn:r333|333]]</sup> ; Guhathakurta et al. 2017 <sup>[[#fn:r334|334]]</sup> ; Taylor et al. 2017 <sup>[[#fn:r335|335]]</sup> ; Thompson et al. 2017 <sup>[[#fn:r336|336]]</sup> ; Zilli et al. 2017 <sup>[[#fn:r337|337]]</sup> ). The observed shift in the trend distribution of precipitation extremes is more distinct than for annual mean precipitation and the global land fraction experiencing more intense precipitation events is larger than expected from internal variability (Fischer and Knutti 2014 <sup>[[#fn:r338|338]]</sup> ; Espinoza et al. 2018 <sup>[[#fn:r339|339]]</sup> ; Fischer et al. 2013 <sup>[[#fn:r340|340]]</sup> ). As a result of global warming, the number of record-breaking rainfall events globally has increased significantly by 12% during the period 1981–2010 compared to those expected due to natural multi-decadal climate variability (Lehmann et al. 2015 <sup>[[#fn:r341|341]]</sup> ). The IPCC SR15 reports robust increases in observed precipitation extremes for annual maximum 1-day precipitation (RX1day) and consecutive 5-day precipitation (RX5day) (Hoegh-Guldberg et al. 2018 <sup>[[#fn:r342|342]]</sup> ; Schleussner et al. 2017 <sup>[[#fn:r343|343]]</sup> ). A number of extreme rainfall events have been attributed to human influence (Min et al. 2011 <sup>[[#fn:r344|344]]</sup> ; Pall et al. 2011 <sup>[[#fn:r345|345]]</sup> ; Sippel and Otto 2014 <sup>[[#fn:r346|346]]</sup> ; Trenberth et al. 2015 <sup>[[#fn:r347|347]]</sup> ; Krishnan et al. 2016 <sup>[[#fn:r348|348]]</sup> ) and the largest fraction of anthropogenic influence is evident in the most rare and extreme events (Fischer and Knutti 2014 <sup>[[#fn:r349|349]]</sup> ).

A warming climate is expected to intensify the hydrological cycle as a warmer climate facilitates more water vapour in the atmosphere, as approximated by the Clausius-Clapeyron (C-C) relationship, with subsequent effects on regional extreme precipitation events (Christensen and Christensen 2003 <sup>[[#fn:r350|350]]</sup> ; Pall et al. 2007 <sup>[[#fn:r351|351]]</sup> ; Berg et al. 2013 <sup>[[#fn:r352|352]]</sup> ; Wu et al. 2013 <sup>[[#fn:r353|353]]</sup> ; Guhathakurta et al. 2017 <sup>[[#fn:r354|354]]</sup> ; Thompson et al. 2017 <sup>[[#fn:r355|355]]</sup> ; Taylor et al. 2017 <sup>[[#fn:r356|356]]</sup> ; Zilli et al. 2017 <sup>[[#fn:r357|357]]</sup> ; Manola et al. 2018 <sup>[[#fn:r358|358]]</sup> ). Furthermore, changes to the dynamics of the atmosphere amplify or weaken future precipitation extremes at the regional scale (O’Gorman 2015 <sup>[[#fn:r359|359]]</sup> ; Pfahl et al. 2017 <sup>[[#fn:r360|360]]</sup> ). Continued anthropogenic warming is very likely to increase the frequency and intensity of extreme rainfall in many regions of the globe (Seneviratne et al. 2012 <sup>[[#fn:r361|361]]</sup> ; Mohan and Rajeevan 2017 <sup>[[#fn:r362|362]]</sup> ; Prein et al. 2017 <sup>[[#fn:r363|363]]</sup> ; Stott et al. 2016 <sup>[[#fn:r364|364]]</sup> ) although many general circulation models (GCMs) underestimate observed increased trends in heavy precipitation suggesting a substantially stronger intensification of future heavy rainfall than the multi-model mean (Borodina et al. 2017 <sup>[[#fn:r365|365]]</sup> ; Min et al. 2011 <sup>[[#fn:r366|366]]</sup> ). Furthermore, the response of extreme convective precipitation to warming remains uncertain because GCMs and regional climate models (RCMs) are unable to explicitly simulate sub-grid scale processes such as convection, the hydrological cycle and surface fluxes and have to rely on parameterisation schemes for this (Crétat et al. 2012 <sup>[[#fn:r367|367]]</sup> ; Rossow et al. 2013 <sup>[[#fn:r368|368]]</sup> ; Wehner 2013 <sup>[[#fn:r369|369]]</sup> ; Kooperman et al. 2014 <sup>[[#fn:r370|370]]</sup> ; O’Gorman 2015 <sup>[[#fn:r371|371]]</sup> ; Larsen et al. 2016 <sup>[[#fn:r372|372]]</sup> ; Chawla et al. 2018 <sup>[[#fn:r373|373]]</sup> ; Kooperman et al. 2018 <sup>[[#fn:r374|374]]</sup> ; Maher et al. 2018 <sup>[[#fn:r375|375]]</sup> ; Rowell and Chadwick 2018 <sup>[[#fn:r376|376]]</sup> ). High-resolution RCMs that explicitly resolve convection have a better representation of extreme precipitation but are dependent on the GCM to capture the large scale environment in which the extreme event may occur (Ban et al. 2015 <sup>[[#fn:r377|377]]</sup> ; Prein et al. 2015 <sup>[[#fn:r378|378]]</sup> ; Kendon et al. 2017 <sup>[[#fn:r379|379]]</sup> ). Inter- annual variability of precipitation extremes in the convective tropics are not well captured by global models (Allan and Liu 2018 <sup>[[#fn:r380|380]]</sup> ).

There is ''low confidence'' in the detection of long-term observed and projected seasonal and daily trends of extreme snowfall. The narrow rain–snow transition temperature range at which extreme snowfall can occur is relatively insensitive to climate warming and subsequent large interdecadal variability (Kunkel et al. 2013 <sup>[[#fn:r381|381]]</sup> ; O’Gorman 2014 <sup>[[#fn:r382|382]]</sup> , 2015 <sup>[[#fn:r383|383]]</sup> ).

<div id="section-2-2-5-4-impacts-of-precipitation-extremes-on-different-land-cover-types"></div>

<span id="impacts-of-precipitation-extremes-on-different-land-cover-types"></span>
==== 2.2.5.4 Impacts of precipitation extremes on different land cover types ====

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More intense rainfall leads to water redistribution between surface and ground water in catchments as water storage in the soil decreases (green water) and runoff and reservoir inflow increases (blue water) (Liu and Yang 2010 <sup>[[#fn:r384|384]]</sup> ; Eekhout et al. 2018 <sup>[[#fn:r385|385]]</sup> ). This results in increased surface flooding and soil erosion, increased plant water stress and reduced water security, which in terms of agriculture means an increased dependency on irrigation and reservoir storage (Nainggolan et al. 2012 <sup>[[#fn:r386|386]]</sup> ; Favis-Mortlock and Mullen 2011 <sup>[[#fn:r387|387]]</sup> ; García- Ruiz et al. 2011 <sup>[[#fn:r388|388]]</sup> ; Li and Fang 2016 <sup>[[#fn:r389|389]]</sup> ; Chagas and Chaffe 2018 <sup>[[#fn:r390|390]]</sup> ). As there is high confidence of a positive correlation between global warming and future flood risk, land cover and processes are likely to be negatively impacted, particularly near rivers and in floodplains (Kundzewicz et al. 2014 <sup>[[#fn:r391|391]]</sup> ; Alfieri et al. 2016 <sup>[[#fn:r392|392]]</sup> ; Winsemius et al. 2016 <sup>[[#fn:r393|393]]</sup> ; Arnell and Gosling 2016 <sup>[[#fn:r394|394]]</sup> ; Alfieri et al. 2017 <sup>[[#fn:r395|395]]</sup> ; Wobus et al. 2017 <sup>[[#fn:r396|396]]</sup> ).

In agricultural systems, heavy precipitation and inundation can delay planting, increase soil compaction and cause crop losses through anoxia and root diseases (Posthumus et al. 2009 <sup>[[#fn:r397|397]]</sup> ). In tropical regions, flooding associated with tropical cyclones can lead to crop failure from both rainfall and storm surge. In some cases, flooding can affect yield more than drought, particularly in tropical regions (e.g., India) and in some mid/high latitude regions such as China and central and northern Europe (Zampieri et al. 2017 <sup>[[#fn:r398|398]]</sup> ). Waterlogging of croplands and soil erosion also negatively affect farm operations and block important transport routes (Vogel and Meyer 2018 <sup>[[#fn:r399|399]]</sup> ; Kundzewicz and Germany 2012 <sup>[[#fn:r400|400]]</sup> ). Flooding can be beneficial in drylands if the floodwaters infiltrate and recharge alluvial aquifers along ephemeral river pathways, extending water availability into dry seasons and drought years, and supporting riparian systems and human communities (Kundzewicz and Germany 2012; Guan et al. 2015 <sup>[[#fn:r401|401]]</sup> ). Globally, the impact of rainfall extremes on agriculture is less than that of temperature extremes and drought, although in some regions and for some crops, extreme precipitation explains a greater component of yield variability, for example, of maize in the Midwestern USA and southern Africa (Ray et al. 2015 <sup>[[#fn:r402|402]]</sup> ; Lesk et al. 2016 <sup>[[#fn:r403|403]]</sup> ; Vogel et al. 2019 <sup>[[#fn:r404|404]]</sup> ).

Although many soils on floodplains regularly suffer from inundation, the increases in the magnitude of flood events mean that new areas with no recent history of flooding are now becoming severely affected (Yellen et al. 2014 <sup>[[#fn:r405|405]]</sup> ). Surface flooding and associated soil saturation often results in decreased soil quality through nutrient loss, reduced plant productivity, stimulated microbial growth and microbial community composition, negatively impacted soil redox and increased GHG emissions (Bossio and Scow 1998 <sup>[[#fn:r406|406]]</sup> ; Niu et al. 2014 <sup>[[#fn:r407|407]]</sup> ; Barnes et al. 2018 <sup>[[#fn:r408|408]]</sup> ; Sánchez-Rodríguez et al. 2019 <sup>[[#fn:r409|409]]</sup> ). The impact of flooding on soil quality is influenced by management systems that may mitigate or exacerbate the impact. Although soils tend to recover quickly after floodwater removal, the impact of repeated extreme flood events over longer timescales on soil quality and function is unclear (Sánchez-Rodríguez et al. 2017 <sup>[[#fn:r410|410]]</sup> ).

Flooding in ecosystems may be detrimental through erosion or permanent habitat loss, or beneficial, as a flood pulse brings nutrients to downstream regions (Kundzewicz et al. 2014 <sup>[[#fn:r411|411]]</sup> ). Riparian forests can be damaged through flooding; however, increased flooding may also be of benefit to forests where upstream water demand has lowered stream flow, but this is difficult to assess and the effect of flooding on forests is not well studied (Kramer et al. 2008 <sup>[[#fn:r412|412]]</sup> ; Pawson et al. 2013 <sup>[[#fn:r413|413]]</sup> ). Forests may mitigate flooding, however flood mitigation potential is limited by soil saturation and rainfall intensity (Pilaš et al. 2011 <sup>[[#fn:r414|414]]</sup> ; Ellison et al. 2017 <sup>[[#fn:r415|415]]</sup> ). Some grassland species under heavy rainfall and soil saturated conditions responded negatively with decreased reproductive biomass and germination rates (Gellesch et al. 2017 <sup>[[#fn:r416|416]]</sup> ), however overall productivity in grasslands remains constant in response to heavy rainfall (Grant et al. 2014 <sup>[[#fn:r417|417]]</sup> ).

Extreme rainfall alters responses of soil CO <sub>2</sub> fluxes and CO <sub>2</sub> uptake by plants within ecosystems, and therefore result in changes in ecosystem carbon cycling (Fay et al. 2008 <sup>[[#fn:r418|418]]</sup> ; Frank et al. 2015a <sup>[[#fn:r419|419]]</sup> ). Extreme rainfall and flooding limits oxygen in soil which may suppress the activities of soil microbes and plant roots and lower soil respiration, therefore lowering carbon cycling (Knapp et al. 2008 <sup>[[#fn:r420|420]]</sup> ; Rich and Watt 2013 <sup>[[#fn:r421|421]]</sup> ; Philben et al. 2015 <sup>[[#fn:r422|422]]</sup> ). However, the impact of extreme rainfall on carbon fluxes in different biomes differs. For example, extreme rainfall in mesic biomes reduces soil CO <sub>2</sub> flux to the atmosphere and GPP whereas in xeric biomes the opposite is true, largely as a result of increased soil water availability (Knapp and Smith 2001 <sup>[[#fn:r423|423]]</sup> ; Heisler and Knapp 2008 <sup>[[#fn:r424|424]]</sup> ; Heisler-White et al. 2009 <sup>[[#fn:r425|425]]</sup> ; Zeppel et al. 2014 <sup>[[#fn:r426|426]]</sup> ; Xu and Wang 2016 <sup>[[#fn:r427|427]]</sup> ; Liu et al. 2017b <sup>[[#fn:r428|428]]</sup> ; Connor and Hawkes 2018 <sup>[[#fn:r429|429]]</sup> ).

As shown above GHG fluxes between the land and atmosphere are affected by climate. The next section assesses these fluxes in greater detail and the potential for land as a carbon sink.

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