Editing IPCC:AR6/WGI/Chapter-12 (section)

=== 12.4.10 Specific Zones and Hotspots ===

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This section focuses on CIDs affecting specific zones with heightened vulnerability and coherent characteristics that cut across traditional continental regions (see also [[#12.3|Section 12.3]] ). It is designed to match the structure of the Cross-Chapter Papers in the WGII Report, although polar regions were addressed in more extensive detail in Sections 12.4.8 and 12.4.9 of this Report and the Mediterranean Region will not be handled separately given that its climatic impact-drivers are discussed in Sections 12.4.1 and 12.4.5 as well as in Cross-Chapter Box 10.3.

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==== 12.4.10.1 Hotspots of Biodiversity (Land, Coasts and Oceans) ====

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Hotspots of biodiversity are defined by the AR6 WGII as ‘geographic areas with exceptionally high richness of species, including rare (endemic) species’ (WGII Cross-Chapter Paper 1). The AR6 assessment is based on 238 distinctive regions often called the ‘Global 200 ecoregions’ ( [[#Olson--2002|Olson and Dinerstein, 2002]] ).

Mean temperature increase is a major climatic impact-driver for biodiversity hotspots, and it is ''very likely'' that it will affect all hotspot areas identified in the literature, at various rates in all climate scenarios, except those located in the North Atlantic where warming is uncertain (see Chapter 4). Terrestrial ecosystems will experience an enhanced warming compared to ocean ecosystems, because land temperatures are warming faster than ocean temperatures (Chapter 4). Marine ecoregions will experience ocean acidification and temperatures that increase faster in high latitudes ( ''high confidence'' ), but critical temperature and oxygen thresholds are projected to be crossed earlier (by mid-century RCP8.5) in tropical areas ( [[#Hughes--2017a|Hughes et al., 2017a]] ; [[#Bruno--2018|Bruno et al., 2018]] ). A warming trend is also expected for freshwater ecosystems, with different local magnitudes due to combined effects of groundwater system inertia as well as hydrology changes ( [[#Knouft--2017|Knouft and Ficklin, 2017]] ). In tropical land areas, because interannual temperature variability is weak compared to mean changes, the temperature distribution range is ''likely'' to be shifted to a very different range in all projection scenarios, with unprecedented values relative to pre-industrial conditions. High climate velocities are particularly noteworthy for biodiversity hotspots given complex ecosystem dynamics and niche climates not easily replicated under shifted geographies ( [[#Burrows--2014|Burrows et al., 2014]] ; [[#Halpern--2015|Halpern et al., 2015]] ; [[#Dobrowski--2016|Dobrowski and Parks, 2016]] ). In some regions (e.g., Central Africa, Amazon, South East Asia) the mean temperature change is already beyond the normal range of variations as it has reached levels higher than three (and up to six) times larger than the standard deviation of the interannual variations ( [[#Hawkins--2020|Hawkins et al., 2020]] ). Together with global warming, land and marine heatwaves are ''very likely'' to increase in the future climate in biodiversity hotspots (Sections 12.4.1–12.4.7).

There is ''low confidence'' in broad patterns of future drying or wet trends across the land and freshwater biodiversity hotspots in the humid tropics, although drying trends have been detected and predicted in parts of the Amazon ( [[#Fu--2013|Fu et al., 2013]] ; [[#Boisier--2015|Boisier et al., 2015]] ). There is ''medium confidence'' ( ''limited evidence'' , ''high agreement'' ) that in several regions the length of the dry season has already increased and is projected to further increase in some parts of the Mediterranean, Amazonia and sub-Saharan Africa ( [[#Debortoli--2015|Debortoli et al., 2015]] ; [[#Dunning--2018|Dunning et al., 2018]] ; [[#Hochman--2018|Hochman et al., 2018]] ; [[#Saeed--2018|Saeed et al., 2018]] ). Longer dry seasons also extend the seasonal length and geographical extent of fire weather in all future scenarios ( ''medium confidence'' ) ( [[#Jolly--2015|Jolly et al., 2015]] ; [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ).

'''In conclusion, biodiversity hotspots around the world will each face unique challenges as climatic impact-drivers change. However, heat, drought and length of dry season, fire weather, sea surface temperature and deoxygenation are relevant drivers to terrestrial, freshwater and marine ecosystems, and have marked increasing trends.'''

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==== 12.4.10.2 Cities and Settlements by the Sea ====

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Cities and settlements by the sea are exposed to specific climate and climate change patterns and to compound coastal hazard risks (AR6 WGII Cross-Chapter Paper 2). The AR5 WGII found that, in general, ‘urban climate change-related risks are increasing (including rising sea levels and storm surges, heat stress, extreme precipitation, inland and coastal flooding, landslides, drought, increased aridity, water scarcity, and air pollution)’ ( [[#Revi--2014|Revi et al., 2014]] ). Since AR5 a number of studies have been carried out to understand urban climate and its change. Box 10.3 identified a continuing strong role of the urban heat island in amplifying heat extremes in cities, although changes in the urban heat island are an order of magnitude smaller than projected localized warming trends ( ''very high confidence'' ).

Coastal cities’ proximity to the sea somewhat mitigates the effect of urban heat islands ( ''high confidence'' ) ( [[#Salvati--2017|Salvati et al., 2017]] ; [[#Santamouris--2017|Santamouris et al., 2017]] ; Y. [[#Wang--2018|]] [[#Wang--2018|Wang et al., 2018]] ; [[#Martinelli--2020|Martinelli et al., 2020]] ). Cities and settlements by the sea typically experience higher humidity levels than inland regions, combining with heat to enhance heat stress and induce exceedance of critical heat stress thresholds for outdoor activities, with potential enhanced exposure to heat for informal settlements (J. [[#Wang--2019|]] [[#Wang--2019|]] [[#Wang--2019|]] [[#Wang--2019|Wang et al., 2019]] ). Such threshold exceedances are projected to increase for many coastal areas ( ''high confidence'' ), including the Persian Gulf where heat stress is projected to be extreme ( [[#Pal--2016|Pal and Eltahir, 2016]] ; [[#Ahmadalipour--2018|Ahmadalipour and Moradkhani, 2018]] ), and some low-lying areas in Europe such as the Po Valley and coastal Mediterranean areas ( [[#Coppola--2021a|Coppola et al., 2021a]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ; see also the heat stress index shown in Figure 12.4d–f).

Climate change-related variations in oceanic drivers (e.g., relative sea level, storm surge, ocean waves), combined with tropical cyclones, extreme precipitation and river flooding, are expected to lead to more frequent and more intense coastal flooding and erosion ( ''very high confidence'' ) impacting cities and settlements located especially in low-elevation coastal zones and mega-deltas ( [[#Chan--2012|Chan et al., 2012]] , 2018; [[#Karymbalis--2012|Karymbalis et al., 2012]] ; [[#Hemer--2013|Hemer et al., 2013]] ; [[#Aerts--2014|Aerts et al., 2014]] ; [[#Neumann--2015|]] [[#Neumann--2015|B. Neumann et al., 2015]] ; [[#Hauer--2016|Hauer et al., 2016]] ; [[#Ranasinghe--2016|Ranasinghe, 2016]] ; [[#Hinkel--2018|Hinkel et al., 2018]] ; [[#Mavromatidi--2018|Mavromatidi et al., 2018]] ; [[#Marcos--2019|Marcos et al., 2019]] ; see also Sections 12.3, 12.4.1–12.4.7 and 12.4.9). Coastal erosion and flooding also pose challenges to critical infrastructure such as roads, subway tunnels, electricity and phone networks, wastewater management plants and buildings ( [[#Grahn--2017|Grahn and Nyberg, 2017]] ; [[#Pregnolato--2017|Pregnolato et al., 2017]] ). Compound flooding due to simultaneous storm surges and high river flows have been found to be increasingly frequent in several cities and/or low-lying areas in Europe and the USA ( ''high confidence'' ) ( [[#Wahl--2015|Wahl et al., 2015]] ; [[#Bevacqua--2019|Bevacqua et al., 2019]] ; [[#Ganguli--2019|Ganguli and Merz, 2019]] ). [[IPCC:Wg1:Chapter:Chapter-11|Chapter 11]] found that the frequency of such compound flood events is projected to increase ( ''high confidence'' ). In addition to changes induced by sea level change, many cities and settlements by the sea are in regions where tropical cyclones are projected to become more intense and severe tropical cyclones more frequent ( ''high confidence'' ) ( [[IPCC:Wg1:Chapter:Chapter-11#11.7|Section 11.7]] ).

The SROCC highlighted coastal settlements in the Arctic as being particularly exposed to several CID changes ( [[#Magnan--2019|Magnan et al., 2019]] ). Enhanced waves, due to extended season of sea ice retreat, are projected to foster coastal flooding and erosion ( [[#12.4.9|Section 12.4.9]] ; [[#Gudmestad--2018|Gudmestad, 2018]] ; [[#Casas-Prat--2020|Casas-Prat and Wang, 2020]] ). Climate change is also affecting sea ice quality and season length along coasts of the Arctic Ocean where populations depend on sea ice for hunting or transportation ( [[#12.4.9|Section 12.4.9]] ; [[#Pearce--2015|Pearce et al., 2015]] ).

'''In summary, coastal cities and settlements are particularly affected by a number of climatic impact-drivers that have already changed and will continue to change whatever the emissions scenario. These include increases in extreme heat, pluvial floods, coastal erosion and coastal flood''' ( high confidence '''). Increasing relative sea level, compounding with increasing tropical cyclone storm surge and rainfall intensity, will increase the probability of coastal city flooding''' ( high confidence '''). Arctic coastal settlements are particularly exposed to climate change due to sea ice retreat''' ( high confidence ''').'''

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==== 12.4.10.3 Deserts and Semi-arid Areas ====

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Drylands, which include hyper-arid, arid, semi-arid and dry sub-humid areas ( [[#IPCC--2019c|IPCC, 2019c]] ), lie on all continents and cover 46% of the global land area and host more than one-third of the current population ( [[#Olsson--2019|Olsson et al., 2019]] ). [[#Huang--2016b|Huang et al. (2016b)]] found that aridity changes have helped expand dryland area by about 4% from 1948 to 2004, with the largest expansion of drylands occurring in semi-arid regions since the early 1960s. [[IPCC:Wg1:Chapter:Chapter-4#4.5.1|Section 4.5.1]] assessed ''high confidence'' of a future poleward expansion of the Hadley cell, leading to a poleward shift of dryland areas in all scenarios considered. There is no evidence of a future global trend in aridification of drylands ( [[#IPCC--2019a|IPCC, 2019a]] ), but ''high confidence'' of aridification in some areas (e.g., Mediterranean, Central America, Southern Africa; [[#IPCC--2019a|IPCC, 2019a]] ; see also Figure 12.4j–l). However, drivers of desertification largely include land-cover changes and land-use management, along with climate change ( [[#IPCC--2019a|IPCC, 2019a]] ).

Warming temperatures and extreme heat are major climatic impact-drivers with multiple potential impacts on societies, health, and habitability in semi-arid and arid regions that are already near physiological limits for outdoor activities. Semi-arid regions will ''very likely'' undergo a warming in all future scenarios ( [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] and Atlas) and ''likely'' undergo an increase in duration, magnitude and frequency of heatwaves (Chapter 11) (Figure 12.4a–c). It is ''likely'' that heat stress will be much more intense by the end of the century in many areas under all scenarios, such as deserts and semi-arid zones in Asia ( [[#Murari--2015|Murari et al., 2015]] ; [[#Mishra--2017|Mishra et al., 2017]] ), Australia and Africa ( [[#Zhao--2015|Zhao et al., 2015]] ; [[#Xia--2016|Xia et al., 2016]] ; [[#Guo--2017|Guo et al., 2017]] ; [[#Dosio--2018|Dosio et al., 2018]] ; [[#Schwingshackl--2021|Schwingshackl et al., 2021]] ), with consequences for labour productivity with respect to high heat-humidity conditions (Figure 12.4d–f).

Drought is another major climatic impact-driver for semi-arid areas, imposing major challenges on agriculture given existing water availability constraints ( [[#Kusunose--2014|Kusunose and Lybbert, 2014]] ; [[#Barlow--2016|Barlow et al., 2016]] ; [[#Otto--2018|Otto et al., 2018]] ). Over the period 1961–2013, the annual area of drylands in drought has increased, on average by slightly more than 1% per year, with large interannual variability ( [[#Olsson--2019|Olsson et al., 2019]] ). In general, droughts have increased in several arid and semi-arid areas over the last decades ( ''medium confidence'' ), and are ''likely'' to increase in the future as indicated by a number of indices calculated from climate ( [[#Liu--2018b|Liu et al., 2018b]] ; [[#Zkhiri--2019|Zkhiri et al., 2019]] ; [[#Coppola--2021b|Coppola et al., 2021b]] ; [[#Driouech--2021|Driouech et al., 2021]] ; see also Figure 12.4j–l).

Deserts and semi-arid areas are prone to dust storms, which can drive impacts on health and several other sectors (X. [[#Zhang--2016|]] [[#Zhang--2016|Zhang et al., 2016]] ; [[#Tong--2017|Tong et al., 2017]] ). The SRCCL indicated that the evolution of dust under climate change is uncertain ( [[#Mirzabaev--2019|Mirzabaev et al., 2019]] ), and there is a lack of evidence and agreement of a change in their frequency or intensity so far in most regions (Sections 12.4.1–12.4.9). Model projections of future changes in dust are hindered by the uncertainties in future regional wind and precipitation as the climate warms ( [[#Evan--2016|Evan et al., 2016]] ); in the effect of CO <sub>2</sub> fertilization on source extent ( [[#Huang--2017|Huang et al., 2017]] ); and in the impact of human activities upon the land surface ( [[#Ginoux--2012|Ginoux et al., 2012]] ; see Chapter 10). Projected trends in dust storms and dust loads in deserts and semi-arid areas vary from region to region. Dust loadings are expected to decrease over most of the Sahara and Sahel ( ''low confidence'' ) ( [[#12.4.1|Section 12.4.1]] ), increase over Mexico and the south-west USA ( ''medium confidence'' ) ( [[#12.4.6|Section 12.4.6]] ), and there is ''low confidence'' of a future trend due to climate change in other continents (Sections 12.4.2–12.4.5).

'''In conclusion, desert and semi-arid areas are strongly affected by climatic impact-drivers such as extreme heat, drought and dust storms. Heat hazards are''' very likely '''increasing in all future climate scenarios, but uncertainty remains regarding any broadly consistent future changes in other climatic impact-drivers for deserts and semi-arid regions.'''

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==== 12.4.10.4 Mountains ====

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Mountains cover about 30% of the land areas on Earth (not counting Antarctica) and deliver a number of vital services to humanity (WGII Cross-Chapter Paper 5; [[#IPCC--2019b|IPCC, 2019b]] ). Climate change in high mountains was addressed in SROCC, which emphasized changes in several climatic impact-drivers. These included an observed general decline in low-elevation snow cover, glaciers and permafrost ( ''high confidence'' ), which induced changes in natural hazards such as decrease in slope stability ( ''high confidence'' ), changes to the frequency of glacial lake outbursts ( ''limited evidence'' ), and climate effects on other climatic impact-drivers (avalanche, rain-on-snow floods) with various degrees of confidence ( [[#Hock--2019|Hock et al., 2019]] ).

There is a growing body of literature indicating elevation-dependent warming (EDW; different rates of warming by altitude although not necessarily increasing with altitude) in several mountain regions but not globally ( [[#Hock--2019|Hock et al., 2019]] ; [[#Pepin--2019|Pepin et al., 2019]] ; [[#Ahmed--2020|Ahmed et al., 2020]] ; [[#Li--2020|]] [[#Li--2020|]] [[#Li--2020|B. Li et al., 2020]] ; [[#Williamson--2020|Williamson et al., 2020]] ; [[#You--2020|You et al., 2020]] ; [[#Micu--2021|Micu et al., 2021]] ). Statistically significant elevational enhancement to long-term trends in maximum near-surface air temperatures and diurnal temperature range were observed in southern central Himalaya and in the Swiss Alps ( [[#Rottler--2019|Rottler et al., 2019]] ; [[#Thakuri--2019|Thakuri et al., 2019]] ). [[#Aguilar-Lome--2019|Aguilar-Lome et al. (2019)]] reported that winter daytime land surface temperatures in the Andean region between 7°S and 20°S show the strongest trends at higher elevations: +1.7°C per decade above 5000 m above sea level. [[#Palazzi--2019|Palazzi et al. (2019)]] identified changes in albedo and downward thermal radiation as key drivers of EDW according to the simulation outputs of a high-spatial-resolution model in three important mountainous areas: the Colorado Rocky Mountains, the Greater Alpine Region and the Himalayas–Tibetan Plateau, but mechanisms for EDW remain complex ( [[#Hock--2019|Hock et al., 2019]] ). Warming is also affecting mountain lake surface temperatures, increasing probabilities of ice-free winters and the frequency and duration of ‘lake heatwaves’ ( ''high confidence'' ) ( [[#O’Reilly--2015|O’Reilly et al., 2015]] ; [[#Woolway--2020|Woolway et al., 2020]] , 2021) with a high variability from lake to lake.

Elevation-dependent warming could speed up the observed, rapid upward shifts of the freezing level height (FLH) in several mountainous regions of the world and lead to faster changes in the snowline, the glacier equilibrium-line altitude and the snow/rain transition height ( ''high confidence'' ). In the Indus, Ganges and Brahmaputra basins in Asia, the FLH is projected to rise at a rate of 4.4 to 10.0 m yr <sup>–1</sup> under RCP8.5 ( [[#Viste--2015|Viste and Sorteberg, 2015]] ). In the Argentinian Andes, FLH is projected under RCP8.5 to move up more than twice as much by 2070 as during the entire Holocene under the worst case scenario ( [[#Drewes--2018|Drewes et al., 2018]] ). On the western slope of the subtropical Andes (30°S–38°S) in central Chile, the mean value of the free tropospheric height of the 0°C isotherm under wet conditions is projected to be close to or higher than the upper quartile of the distribution in the current climate, towards the end of the century and under RCP8.5 ( [[#Mardones--2020|Mardones and Garreaud, 2020]] ). In the Alps and the Pyrenees, [[#Spandre--2019|Spandre et al. (2019)]] projected a rise in the natural snow elevation of between 200–300 m and 400–600 m by mid-century under RCP2.6 and RCP8.5, respectively. In the same region, the environmental equilibrium-line altitude is projected to exceed the maximum elevation of 69%, 81% and 92% of the glaciers by the end of the century under RCPs 2.6, 4.5 and 8.5, respectively ( [[#Žebre--2021|Žebre et al., 2021]] ).

Orographic effects enhance convection and stratiform heavy precipitation (due to uplift) and make mountains prone to extreme precipitation events. These events are projected to increase in major mountainous regions (Alps, parts of the Andes, British Columbia, North-Western North America, Calabria, Carpathian, Hindu-Kush-Himalaya, Rocky Mountains, Umbria; ''medium'' to ''high confidence'' depending on location), with potential cascading consequences of floods, landslides and lake outbursts in mountainous areas in all scenarios ( ''medium confidence'' ) ( [[IPCC:Wg1:Chapter:Chapter-11|Chapter 11]] and Sections 12.4.1–12.4.9; [[#Geertsema--2006|Geertsema et al., 2006]] ; [[#Gaire--2015|Gaire et al., 2015]] ; [[#Kim--2015|Kim et al., 2015]] ; [[#Ciabatta--2016|Ciabatta et al., 2016]] ; [[#Gariano--2016|Gariano and Guzzetti, 2016]] ; [[#Kharuk--2016|Kharuk et al., 2016]] ; [[#Syed--2016|Syed and Al Amin, 2016]] ; [[#Cloutier--2017|Cloutier et al., 2017]] ; [[#Gądek--2017|Gądek et al., 2017]] ; [[#Jurchescu--2017|Jurchescu et al., 2017]] ; [[#Rajczak--2017|Rajczak and Schär, 2017]] ; [[#Alvioli--2018|Alvioli et al., 2018]] ; [[#Coe--2018|Coe et al., 2018]] ; [[#Schlögl--2018|Schlögl and Matulla, 2018]] ; C.-W. [[#Chen--2019|]] [[#Chen--2019|Chen et al., 2019]] ; [[#Handwerger--2019|Handwerger et al., 2019]] ; [[#Hock--2019|Hock et al., 2019]] ; [[#Patton--2019|Patton et al., 2019]] ; [[#Vaidya--2019|Vaidya et al., 2019]] ; [[#Kirschbaum--2020|Kirschbaum et al., 2020]] ; [[#Coppola--2021b|Coppola et al., 2021b]] ).

Declines in low-elevation snow depth and seasonal extent are projected for all SSP-RCPs (see Sections 12.4.1–12.4.6), along with reductions in mountain glacier surface area, increases in permafrost temperature, decreases in permafrost thickness, changes in lake and river ice, changes in the amount and seasonality of streamflows and hydrologic droughts in snow-dominated and glacier-fed river basins (e.g., in Central Asia; [[#Sorg--2014|Sorg et al., 2014]] ; [[#Reyer--2017b|Reyer et al., 2017b]] ) ( ''medium confidence'' ), and decreases in the stability of mountain slopes and snowfields. Glacier recession could lead to the creation of new glacial lakes in places like the Himalaya-Karakoram region ( [[#Linsbauer--2016|Linsbauer et al., 2016]] ) and in Alaska and Canada ( [[#Carrivick--2016|Carrivick and Tweed, 2016]] ; [[#Harrison--2018|Harrison et al., 2018]] ) ( ''medium confidence'' ). With increasing temperature and precipitation these can increase the occurrence of glacier lake outburst floods and landslides over moraine-dammed lakes ( ''high confidence'' ) ( [[#Carey--2012|Carey et al., 2012]] ; [[#Rojas--2014|Rojas et al., 2014]] ; [[#Iribarren%20Anacona--2015|Iribarren Anacona et al., 2015]] ; [[#Cook--2016|Cook et al., 2016]] ; [[#Haeberli--2017|Haeberli et al., 2017]] ; [[#Kapitsa--2017|Kapitsa et al., 2017]] ; [[#Narama--2018|Narama et al., 2018]] ; [[#Wilson--2018|Wilson et al., 2018]] ; [[#Drenkhan--2019|Drenkhan et al., 2019]] ; S. [[#Wang--2020|]] [[#Wang--2020|Wang et al., 2020]] ).

'''In conclusion, mountains face complex challenges from specific climatic impact-drivers drastically influenced by climate change: regional elevation-dependent warming''' ( high confidence '''), low-to-mid-altitude snow cover and sno''' '''w-sea''' '''son decrease even as some high elevations see more snow''' ( high confidence '''), glacier mass reduction and permafrost thawing''' ( high confidence '''), and increases in extreme precipitation and floods in most parts of major mountain ranges''' ( medium confidence ''').'''

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==== 12.4.10.5 Tropical Forests ====

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Tropical forests, which are among the world’s most biologically diverse ecosystems, are essentially located in Central and South America, Africa and South East Asia (AR6 WGII Cross-Chapter Paper 7). The AR5 and SR1.5 indicated several specific climatic impact-driver changes that are particularly important to tropical forests: mean temperature increase, long-term drying trends (including shifts in the length of the dry season), prolonged drought, wildfires and surface CO <sub>2</sub> increase for inland forests ( [[#IPCC--2013|IPCC, 2013]] , 2018). The SRCCL assessed an enhanced risk and severity of wildfires in tropical rainforests ( ''high confidence'' ), but fires are not only a natural process but are also affected by deforestation and other human influences ( [[#IPCC--2019a|IPCC, 2019a]] ).

Temperature is rising in all tropical regions covered with forests and will ''very likely'' continue to rise, reaching levels unprecendented in recent decades as the temperature trends rapidly emerge from weak historical interannual variability (Sections 12.4.1–12.4.4 and 12.5.2; see also [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] and Atlas).

Regional patterns of increasing drought or unusual wet and dry periods are predicted with agreement over many climate models such as over the Amazon basin ( [[#Boisier--2015|Boisier et al., 2015]] ; [[#Duffy--2015|Duffy et al., 2015]] ; [[#Zulkafli--2016|Zulkafli et al., 2016]] ; [[#Coppola--2021b|Coppola et al., 2021b]] ). There is ''medium confidence'' ( ''limited evidence'' , ''high agreement'' ) that in several tropical-forest regions (e.g., Amazonia, West Africa) the dry season length has increased ( [[#Fu--2013|Fu et al., 2013]] ; [[#Debortoli--2015|Debortoli et al., 2015]] ; [[#Saeed--2017|Saeed et al., 2017]] ; [[#Dunning--2018|Dunning et al., 2018]] ; [[#Wadsworth--2019|Wadsworth et al., 2019]] ), and there is ''low confidence'' ( ''limited evidence'' ) that deforestation influences the shift in the onset of the wet season in south Amazonia ( [[#Leite-Filho--2019|Leite-Filho et al., 2019]] ). In contrast, the wet season is increasing in northern Australia tropical forests ( [[#Catto--2012|Catto et al., 2012]] ).

Tropical forests typically reach peak fire weather conditions in the dry season ( [[#Taufik--2017|Taufik et al., 2017]] ), in particular during long-lived droughts ( [[#Brando--2014|Brando et al., 2014]] ; [[#Marengo--2018|Marengo et al., 2018]] ), with consequences for tree mortality, forest and carbon sink loss ( [[#Brando--2019|Brando et al., 2019]] ), and on the hydrological cycle in South America ( [[#Martinez--2014|Martinez and Dominguez, 2014]] ; [[#Espinoza--2020|Espinoza et al., 2020]] ). Observations and reanalyses over the past three to four decades, combined into fire risk indices, show that the fire weather season length has been increasing by about 20% globally ( [[#Jolly--2015|Jolly et al., 2015]] ), and this index exhibits particularly high trend values over tropical forest areas of South and Central America and Africa. There is generally ''low confidence'' in future projections of general fire weather risk evolution in tropical forests and evolutions depend on the region ( [[#Abatzoglou--2019|Abatzoglou et al., 2019]] ). Over the Amazon basin the fire risk increase is projected to emerge well before 2050 while for other equatorial forests no significant evolution is found. In Savanna areas the risk increase is found to be more general.

'''In conclusion, most tropical forests are challenged by a mix of emerging warming trends that are particularly large in comparison to historical variability''' ( medium confidence '''). Water cycle changes bring prolonged drought, longer dry seasons, and increased fire weather to many tropical forests, with plants also responding to CO''' <sub>2</sub> '''increases''' ( medium confidence ''').'''

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