Editing IPCC:AR6/WGII/Chapter-10 (section)

== 10.3 Regional and Sub-regional Characteristics ==

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=== 10.3.1 Climatic Characteristics ===

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Climate characteristics in Asia are diverse covering all climate zones from tropical to polar, including mountain climate. Monsoonal winds and associated precipitation are dominant in South, Southeast and East Asia. Annual mean surface air temperature averaged over the sub-region ranges from coldest in North Asia (–3°C) to warmest in Southeast Asia (25°C) based on JRA-55 ( [[#Kobayashi--2015|Kobayashi et al., 2015]] ) climatology for 1981–2010. Most of North Asia and higher altitude is underlain by permafrost. West Asia is the driest and Southeast Asia is the wettest, with the annual precipitation averaged over the sub-region ranging about ten times from 220 mm in West Asia to 2570 mm in Southeast Asia based on GPCC ( [[#Schamm--2014|Schamm et al., 2014]] ) climatology for 1981–2010. Indonesia in Southeast Asia has the longest coastline in the world, causing this area (maritime continent) to be the wettest region ( [[#Yamanaka--2018|Yamanaka et al., 2018]] ). The Hindu Kush Himalaya (HKH) region is a biodiversity hotspot ( [[#Wester--2019|Wester et al., 2019]] ) and also has significant impacts on the Asian climate because of its orographic and thermodynamic effects ( [[#Wu--2012|Wu et al., 2012]] ).

Extreme precipitation events and related flooding occur frequently in monsoon Asia (i.e., Southeast, South and East Asia) ( [[#Mori--2021b|Mori et al., 2021b]] ). Tropical cyclones also affect East and South Asia with torrential rain, strong winds and storm surge. Floods and other weather-related hazards are causing thousands of casualties and millions of people are affected each year (CRED/UNISDR, 2019). On the other hand, droughts have long-lasting effects on agriculture and livestock threatening water security in West Asia, Central Asia and northern China ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ; [[#Seneviratne--2021|Seneviratne et al., 2021]] ). Adaptation to such extreme events has been limited in Asia.

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==== 10.3.1.1 Observed Climate Change ====

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Observations of past and current climate in Asia are assessed in IPCC WGI AR6 ( [[#IPCC--2021|IPCC, 2021]] ). Examples of observed impacts in Asia with attributed CIDs are shown in Figure 10.2. Surface temperature has increased in the past century all over Asia ( ''very high confidence'' ). Elevation-dependent warming (i.e., the warming rate is different across elevation bands is observed in HMA) ( ''medium confidence'' ) ( [[#Hock--2019|Hock et al., 2019]] ; [[#Krishnan--2019|Krishnan et al., 2019]] ). While there is an overall trend of decreasing glacier mass in HMA, there are some regional differences and even areas with a positive mass balance due to increased precipitation ( [[#Wester--2019|Wester et al., 2019]] ). Rising temperatures have resulted in an increasing trend of growing-season length. The number of hot days and warm nights continues to increase in all of Asia ( ''high confidence'' ), while cold days and nights are decreasing except in the southern part of Siberia ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). Large increases in temperature extremes are observed in West and Central Asia ( ''high confidence'' ). Temperature increase is causing strong, more frequent and longer heatwaves in South and East Asia. The 2013 East China heatwaves case is such an example ( [[#Xia--2016|Xia et al., 2016]] ). In 2016 and 2018, extreme warmth was observed in Asia for which an event-attribution study revealed that this would not have been possible without anthropogenic global warming ( ''medium confidence'' ) ( [[#Imada--2018|Imada et al., 2018]] ; [[#Imada--2019|Imada et al., 2019]] ).

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[[File:24e9b419594dd459a7ab614fbea9c2e4 IPCC_AR6_WGII_Figure_10_002.png]]

'''Figure 10.2 |''' '''Detection and attribution of observed changes in Asia.''' Levels of Evidence (E), Agreement (A) and Confidence (C) are ranked by High (H), Medium (M) or Low (L). CID: climate-impact driver. References: (1) Heatwaves ( [[#Mishra--2015|Mishra et al., 2015]] ; [[#Rohini--2016|Rohini et al., 2016]] ; [[#Chen--2017|Chen and Li, 2017]] ; [[#Panda--2017|Panda et al., 2017]] ; [[#Ross--2018|Ross et al., 2018]] ); (2) Coastal urban flooding ( [[#Dulal--2019|Dulal, 2019]] ); (3) Biodiversity and habitat loss ( [[#Wan--2019|Wan et al., 2019]] ); (4) Dust storms ( [[#Kelley--2015|Kelley et al., 2015]] ; [[#Yu--2015|Yu et al., 2015]] ; [[#Alizadeh-Choobari--2016|Alizadeh-Choobari et al., 2016]] ; [[#Nabavi--2016|Nabavi et al., 2016]] ); (5) Sea level rise (only for coastal cities) ( [[#Brammer--2014|Brammer, 2014]] ; [[#Shahid--2016|Shahid et al., 2016]] ; [[#Hens--2018|Hens et al., 2018]] ); (6) Urban heat island (UHI) effect ( [[#Choi--2014|Choi et al., 2014]] ; [[#Santamouris--2015|Santamouris, 2015]] ; [[#Estoque--2017|Estoque et al., 2017]] ; [[#Ranagalage--2017|Ranagalage et al., 2017]] ; [[#Kotharkar--2018|Kotharkar et al., 2018]] ; [[#Li--2018a|Li et al., 2018a]] ; [[#Hong--2019c|Hong et al., 2019c]] ); (7) Permafrost thawing ( [[#Shiklomanov--2017a|Shiklomanov et al., 2017a]] ; [[#Biskaborn--2019|Biskaborn et al., 2019]] ); (8) Wildfire ( [[#Schaphoff--2016|Schaphoff et al., 2016]] ; [[#Brazhnik--2017|Brazhnik et al., 2017]] ); (9) Extreme rainfall events (in urban areas) ( [[#Ali--2014|Ali et al., 2014]] ); (10) Urban drought ( [[#Gu--2015|Gu et al., 2015]] ; [[#Pervin--2020|Pervin et al., 2020]] ); (11) Primary production in ocean ( [[#Roxy--2016|Roxy et al., 2016]] ); (12) Flood-induced damages ( [[#Fengqing--2005|Fengqing et al., 2005]] ); (13) Agriculture and food systems ( [[#Heino--2018|Heino et al., 2018]] ; [[#Prabnakorn--2018|Prabnakorn et al., 2018]] ).

There are considerable regional differences in observed annual precipitation trend ( ''medium confidence'' ). Observations show a decreasing trend of the South Asian summer monsoon precipitation during the second half of the 20th century ( ''high confidence'' ) ( [[#Douville--2021|Douville et al., 2021]] ). No clear trend in precipitation is observed in high-mountain Asia ( [[#Nepal--2015|Nepal and Shrestha, 2015]] ), while a continuous shift towards a drier condition has been observed since the early 1980s in spring over the central Himalaya ( [[#Panthi--2017|Panthi et al., 2017]] ). Increase in heavy precipitation occurred recently in South Asia ( ''high confidence'' ), and in Southeast and East Asia ( ''medium confidence'' ) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). In Japan, there is no significant long-term trend in the annual precipitation, while significant increasing trend is observed in the annual number of events of heavy precipitation (daily precipitation ≥400 mm) and intense precipitation (hourly precipitation ≥50 mm) ( [[#JMA--2018|JMA, 2018]] ). Decreased precipitation and increased evapotranspiration are observed in West and Central Asia, contributing to drought conditions and decreased surface runoff.

Annual surface wind speeds have been decreasing in Asia since the 1950s ( ''high confidence'' ) ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). The observed changes in the frequency of sand and dust storms vary from region to region in Asia ( ''medium confidence'' ). The frequency and intensity of dust storms are increasing in some regions, such as West and Central Asia, due to land use and climate change ( [[#Mirzabaev--2019|Mirzabaev et al., 2019]] ). Significant decreasing trends of dust storms are observed in some parts of Inner Mongolia and over the Tibetan Plateau ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). In contrast, West Asia has witnessed more frequent and intensified dust storms affecting Iran and Persian Gulf countries in recent decades ( ''medium confidence'' ) ( [[#Nabavi--2016|Nabavi et al., 2016]] ).

There is no significant long-term trend during 1951–2017 in the numbers of tropical cyclones (TCs) with maximum winds of 66.37 km h –1 or higher forming in the western North Pacific and the South China Sea ( ''medium confidence'' ). There are substantial inter-decadal variations in basin-wide TC frequency and intensity in the western North Pacific ( [[#Lee--2020a|Lee et al., 2020a]] ). Numbers of strong TCs (maximum winds of 124.93 km h –1 or higher) also show no discernible trend since 1977 when complete wind-speed data near TC centre become available ( [[#JMA--2018|JMA, 2018]] ). According to [[#Cinco--2016|Cinco et al. (2016)]] , for TCs in the Philippines there are no significant trends in the annual number of TCs during 1951–2013. Their analysis showed that the Philippines have been affected by fewer TCs above 124.93 km h –1 , but affected more by extreme TCs (above 158.11 km h –1 ). There has been a significant northwestward shift in TC tracks since the 1980s, and a detectable poleward shift since the 1940s in the average latitude where TCs reach their peak intensity in the western North Pacific ( ''medium confidence'' ) ( [[#Lee--2020a|Lee et al., 2020a]] ).

According to [[#Bindoff--2019|Bindoff et al. (2019)]] , the oceans have warmed unabatedly since 2004, continuing the multi-decadal ocean-warming trends. Their report also summarised that there is increased agreement between coupled model simulations of anthropogenic climate change and observations of changes in ocean heat content ( ''high confidence'' ). Observed SLR around Asia over 1900–2018 is similar to the global mean sea level change of 1.7 mm yr –1 , but for the period 1993–2018, the SLR rate increased to 3.65 mm yr –1 in the Indo-Pacific region and 3.53 m yr –1 in the Northwest Pacific, compared with the global value of 3.25 mm yr –1 ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). The extreme SLR has occurred since the 1980s along the coast of China ( [[#Feng--2018b|Feng et al., 2018b]] ).

Ocean acidification continues with surface seawater pH values having shown a clear decrease by 0.01–0.09 from 1981–2011 along the Pacific coasts of Asia ( ''high confidence'' ) ( [[#Lauvset--2015|Lauvset et al., 2015]] ). For the western North Pacific along the 137°E line, the trend varies from −0.013 at 3°N to −0.021 at 30°N per decade during 1985–2017 ( [[#JMA--2018|JMA, 2018]] ). Ocean interior (about 150–800 m) pH also shows a decreasing trend with higher rates in the northern than the southern subtropics, which may be due to greater loading of atmospheric CO 2 in the former ( [[#JMA--2018|JMA, 2018]] ).

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==== 10.3.1.2 Projected Climate Change ====

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Rising temperatures increase the likelihood of the threat of heatwaves across Asia, droughts in arid and semiarid areas of West, Central and South Asia, floods in monsoon regions in South, Southeast and East Asia, and glacier melting in the HKH region ( ''high confidence'' ) ( [[#Doblas-Reyes--2021|Doblas-Reyes et al., 2021]] ; [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ; [[#Seneviratne--2021|Seneviratne et al., 2021]] ). Confidence in the direction of the projected change in CIDs in Asia are summarised in Table 12.4 of WGI AR6 [[IPCC:Wg2:Chapter:Chapter-12|Chapter 12]] ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ).

Projections of future changes in annual mean surface air temperature in Asia are qualitatively similar to those in the previous assessments with greater warming at higher latitudes (i.e., North Asia) ( ''high confidence'' ) ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). Projected surface air temperature changes in the Tibetan Plateau, Central Asia and West Asia are also significant ( ''high confidence'' ) ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). The highest levels of warming for extremely hot days are expected to occur in West and Central Asia with increased dryness of land ( ''high confidence'' ) (SR1.5). Over mountainous regions, elevation-dependent warming will continue ( ''medium confidence'' ) ( [[#Hock--2019|Hock et al., 2019]] ). Glaciers will generally shrink, but rates will vary among regions ( ''high confidence'' ) ( [[#Wester--2019|Wester et al., 2019]] ). Thawing permafrost presents a problem in northern areas of Asia, particularly Siberia ( [[#Parazoo--2018|Parazoo et al., 2018]] ). Temperature rise will be strongest in winter in most regions, while it will be the strongest on summer in the northern part of West Asia and some parts of South Asia where a desert climate prevails ( ''high confidence'' ) ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). The wet-bulb globe temperature, which is a measure of heat stress, is ''likely'' [[#footnote-011|2]] to approach critical health thresholds in West and South Asia under the RCP4.5 scenario, and in some other regions, such as East Asia, under the RCP8.5 scenario ( ''high confidence'' ) (Lee et al., 2021a; [[#Seneviratne--2021|Seneviratne et al., 2021]] ). The occurrence of extreme heatwaves will ''very likely'' increase in Asia. Projections show that a sizeable part of South Asia will experience heat stress conditions in the future ( ''high confidence'' ). It is ''virtually certain'' that cold days and nights will become fewer ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ).

Projections of future annual precipitation change are qualitatively similar to those in the previous SREX and AR5 assessments ( [[#IPCC--2021|IPCC, 2021]] ). A ''very likely'' large percentage increase in annual precipitation is projected in South and North Asia ( ''high confidence'' ) ( [[#Douville--2021|Douville et al., 2021]] ; Lee et al., 2021a). Precipitation is projected to decrease over the northwest part of the Arabian Peninsula and increase over its southern part ( ''medium confidence'' ) ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). Both heavy and intense precipitation are projected to intensify and become more frequent in South, Southeast and East Asia ( ''high confidence'' ) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). There will be a large increase in flood frequency in these monsoon regions ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ). Without further mitigation efforts, this will lead to continued loss of lives and infrastructure. SR1.5 assessed higher risk from heavy precipitation events at 2°C compared with 1.5°C of global warming in East Asia. A large ensemble-modelling study shows that future warming is expected to further increase winter precipitation, and extreme weather events, such as rain-on-snow, will result in an increase in extreme runoff in Japan ( ''low confidence'' ) ( [[#Ohba--2020|Ohba and Kawase, 2020]] ). Furthermore, the earlier snowmelt will affect energy supply by hydropower.

Monsoon land precipitation ''likely'' will increase in East, Southeast and South Asia mainly due to increasing moisture convergence by elevated temperature ( ''high confidence'' ); however, there is ''low confidence'' in the magnitude and detailed spatial patterns of precipitation changes at the sub-regional scale in East Asia ( [[#Doblas-Reyes--2021|Doblas-Reyes et al., 2021]] ). Increasing land–sea thermal contrast and resultant lower tropospheric circulation changes, together with increasing moisture, are projected to intensify the South Asian summer monsoon precipitation ( ''medium confidence'' ). Anthropogenic aerosols greatly modify sub-regional precipitation changes, and their spatio-temporal changes are uncertain ( [[#Douville--2021|Douville et al., 2021]] ). Monsoonal winds will generally become weaker in a future warming world with different magnitudes across regions ( ''medium confidence'' ). Future changes in sand and dust storms are uncertain.

The global proportion of very intense TCs (category 4–5) will increase under higher levels of global warming ( ''medium to high confidence'' ). Mean global TC precipitation rate will increase ( ''medium to high confidence'' ). Models suggest a reduction in TC frequency but an increase in the proportion of very intense TCs over the western North Pacific in the future; however, some individual studies project an increase in western North Pacific TC frequency ( ''medium confidence'' ) ( [[#Cha--2020|Cha et al., 2020]] ). In the western North Pacific, some models project a poleward expansion of the latitude of maximum TC intensity, leading to a future increase in intense TC frequency south of Japan ( ''medium confidence'' ) ( [[#Yoshida--2017|Yoshida et al., 2017]] ).

Relative SLR associated with climate change in Asia will range from 0.3–0.5 m in SSP1-2.6 to 0.7–0.8 m in SSP5-8.5 for 2081–2100 relative to 1995–2014 ( [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ). In coastal regions, evaluation of SLR is necessary at the regional scale to assess the impacts on coastal sectors. [[#Liu--2016c|Liu et al. (2016c)]] investigated the regional-scale SLR using dynamic downscaling from the three global-climate models in the western North Pacific. In their projection in the case following the RCP8.5 scenario, the regional sea level rises along Honshu Island in Japan during 2081–2100 relative to 1981–2000 are 6–25 cm higher than the global mean SLR due to the dynamic response of the ocean circulation. For the impact assessment of coastal hazards, the total SLR included extreme events due to storm surge and high ocean waves, which are influenced by the changes in TCs ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). [[#Mori--2016|Mori and Takemi (2016)]] summarised the characteristics of TCs in the western Pacific in the past and in the future, and the extreme value of significant wave height increased in several regions. There is considerable increase in the return levels along the China coast under 2.0°C warming compared with that under the 1.5°C warming scenario ( [[#Feng--2018b|Feng et al., 2018b]] ).

Ocean acidification will continue over the 21st century ( ''virtually certain'' ) (SROCC). Projected decrease in global surface ocean pH from 1986–2005 to 2081–2100 is about 0.145 under RCP4.5 (Lee et al., 2021a).

Diverse and complex climate characteristics in Asia limit climate models’ ability to reasonably simulate the current climate and project its future change ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ).

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=== 10.3.2 Ecological Characteristics ===

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Ecosystems in Asia are characterised by a variety of climate and topographic effects, and can be divided into several distinct areas (Figure 10.3). In addition, valuable ecosystem services provide vital support for human well-being and sustainable development ( [[#IPBES--2018|IPBES, 2018]] ).

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[[File:f80f90796733063255516b4ba82ff4c6 IPCC_AR6_WGII_Figure_10_003.png]]

'''Figure 10.3 |''' '''Terrestrial ecoregions, large marine ecosystems and major fishing areas of Asia.''' Large marine ecosystems: ''26'' Mediterranean Sea; ''32'' Arabian Sea; ''33'' Red Sea; ''34'' Bay of Bengal; ''35'' Gulf of Thailand; ''36'' South China Sea; ''37'' Sulu-Celebes Sea; ''38'' Indonesian Sea; ''47'' East China Sea; ''48'' Yellow Sea; ''49'' Kuroshio Current; ''50'' Sea of Japan; ''51'' Oyashio Current; ''52'' Sea of Okhotsk; ''53'' West Bering Sea; ''54'' Northern Bering and Chukchi seas; ''56'' East Siberian Sea; ''57'' Laptev Sea; ''58'' Kara Sea; ''62'' Black Sea. Developed after [[#Olson--2001|Olson et al. (2001)]] , [[#NOAA--2010|NOAA (2010)]] and [[#FAO--2019|FAO (2019)]] , and made with Natural Earth. Natural Earth is a public domain map dataset archive available at https://www.naturalearthdata.com/ . The software used for generating the map was ArcGIS 10.0. Note that the map is for illustrative purposes only.

Boreal forests and tundra dominate in North Asia: deserts and xeric shrublands in Central and West Asia; and alpine ecosystems in the HKH, Tian Shan, Altai-Sayan, Ural and Caucasus mountain regions. Human-transformed landscapes occupy most parts of other sub-regions. The remaining natural ecosystems in East Asia are temperate broadleaf and mixed forests, and there are subtropical evergreen forests, deserts and grasslands in the West Asia. South Asia has tropical forests and semi-deserts in the northwest, and Southeast Asia is covered mainly by tropical forests (Figure 10.3).

Ocean and coastal regions in Asia have various ecological characteristics, such as high productivity in arctic and subpolar regions, large biodiversity in tropical regions and unique systems in marginal seas. In the atlas of WGI AR6, the ocean biomes in Asia are divided into six sub-regions (WGI AR6 Figure Atlas.4) ( [[#Gutiérrez--2021|Gutiérrez et al., 2021]] ). For the coastal region, the concept of the large marine ecosystem (e.g., see [[#Sherman--1994|Sherman, 1994]] ) provides the biological characteristics of each marginal/semi-enclosed region and the regions characterised by boundary current system.

Biodiversity and ecosystem services play a critical role in socioeconomic development as well as the cultural and spiritual fulfilment of the Asian population ( [[#IPBES--2018|IPBES, 2018]] ). For example, species richness reaches its maximum in the ‘coral triangle’ of Southeast Asia (central Philippines and central Indonesia) (IPCA, 2017), and the extent of mangrove forests in Asia is about 38.7% of the global total ( [[#Bunting--2018|Bunting et al., 2018]] ). These coastal ecosystems provide multiple ecosystem services related to food production by fisheries/aquaculture, carbon sequestration, coastal protection and tourism/recreation ( [[#Ruckelshaus--2013|Ruckelshaus et al., 2013]] ).

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=== 10.3.3 Demographics and Socioeconomic Characteristics ===

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In the six sub-regions of Asia, nature and biophysical impacts of climate change are observed in three climate-change hotspots where strong climate signals and high concentrations of vulnerable people are present, namely in semiarid, glacial-fed river basins and mega deltas ( [[#De%20Souza--2015|De Souza et al., 2015]] ; [[#Kilroy--2015|Kilroy, 2015]] ; [[#Szabo--2016b|Szabo et al., 2016b]] ). The impacts of global climate events also have profound social implications, threatening human health and well-being, destabilising assets, weakening coping capacities and response infrastructures and substantially increasing the number of socially, economically and psychologically vulnerable individuals and communities ( [[#Ford--2015|Ford et al., 2015]] ).

Vulnerability to climate change varies by geography and by the economic circumstances of the exposed population ( [[#Sovacool--2017|Sovacool et al., 2017]] ). The concentration of population growth in less developed regions means that an increasing number of people live in countries with the least ability to adapt to climate change ( [[#Auffhammer--2018|Auffhammer and Kahn, 2018]] ). Bangladesh with 163 million people, an example, is one of the most vulnerable countries in the world to climate risks and natural hazards, and faces severe floods, cyclones, droughts, heatwaves and storm surges on a regular basis ( [[#Dastagir--2015|Dastagir, 2015]] ; [[#Hossain--2018|Hossain et al., 2018]] ; [[#Roy--2019|Roy and Haider, 2019]] ).

Differential human vulnerability to environmental hazards results from a range of social, economic, historical and political factors, all of which operate at multiple scales ( [[#De%20Souza--2015|De Souza et al., 2015]] ; Thomas, 2019). Climate change is expected to have serious impacts on people living within these hotspot areas, as observed from loss of food crop yields to disasters such as floods, fluctuations in seasonal water availability or other systemic effects ( [[#De%20Souza--2015|De Souza et al., 2015]] ). For instance, in South Asia, extreme climatic conditions are threatening food security; thus, agro-based economies, such as those of India and Pakistan, are the most vulnerable to climate change in this regard ( [[#Mendelsohn--2014|Mendelsohn, 2014]] ; Ahmad, 2015; [[#Kirby--2016|Kirby et al., 2016]] ; [[#Ali--2017|Ali et al., 2017]] ).

A broad-based understanding of gender vulnerability in the context of poverty and social discrimination, as well as diverse social and cultural practices in different political, geographic and historical settings, apart from climate variability along with environmental and natural risks, is central to understanding people’s capacities to cope with, and adapt to change ( [[#Morchain--2015|Morchain et al., 2015]] ; [[#Yadav--2018|Yadav and Lal, 2018]] ; [[#Rao--2019|Rao et al., 2019]] ). Studies highlight the fact that disasters do not affect people equally; mostly findings show that insufficient disaster education, inadequate protection measures and powerful cultural issues, both pre- and post-disaster, increase women’s vulnerability during and after disasters ( [[#Isik--2015|Isik et al., 2015]] ; [[#Reyes--2016|Reyes and Lu, 2016]] ; [[#Hamidazada--2019|Hamidazada et al., 2019]] ). In particular, cultural issues play a role after disasters by affecting women’s security, access to disaster aid and health care ( [[#Raju--2019|Raju, 2019]] ). There must be more nuanced understanding and examination of gender, as well as poor, disadvantaged and vulnerable groups, in vulnerability and risk assessments ( [[#Reyes--2016|Reyes and Lu, 2016]] ; Reyer, 2017; [[#Xenarios--2019|Xenarios et al., 2019]] ).

Based on the ‘World Economic Situation and Prospects as of mid-2019 Report’, the region has an estimated 400 million people living in extreme poverty below the threshold of 1.90 USD d –1 . At the higher international poverty line of 3.20 USD d –1 , the number of poor rises to 1.2 billion people, accounting for more than a quarter of the region’s total population (Holland, 2019). Beyond monetary measures, indicators of multi-dimensional aspects of poverty, most notably in Southern Asia, indicate that a large share of the population still lacks access to basic infrastructure and services ( [[#Bank--2017b|Bank, 2017b]] ).

For instance, South Asia illustrates that on average it could lose nearly 2% of its GDP by 2050, rising to a loss of nearly 9% by 2100 under a business-as-usual scenario ( [[#Ahmed--2014|Ahmed and Suphachalasai, 2014]] ). The relationship between economic outcomes and cross-sectional climate variation is confounded by regional heterogeneity, including historical effects of settlement and colonisation ( [[#Dell--2014|Dell et al., 2014]] ; [[#Newell--2018|Newell et al., 2018]] ). Climate change vulnerability may also depend on sufficient employment opportunities in the risk-prone areas, land-holding size, gender, education level, and family and community size, as observed in Nepal, Thailand and Vietnam ( [[#Baul--2015|Baul and McDonald, 2015]] ; Lebel L., 2015; [[#Phuong--2018a|Phuong et al., 2018a]] ).

As poor households are constrained in their ability to receive nutrition, schooling and health care for their children, this is greatly dampening progress in human capital development and productivity growth, both of which are critical imperatives for sustainable development ( [[#Carleton--2016|Carleton and Hsiang, 2016]] ; [[#Schlenker--2018|Schlenker and Auffhammer, 2018]] ). Studies also have shown negative impacts of climate change on several essential components of people’s livelihoods and well-being, such as water supply, food production, human health, availability of land and ecosystems ( [[#Alauddin--2013|Alauddin and Rahman, 2013]] ; [[#Arnell--2016|Arnell et al., 2016]] ; [[#Roy--2019|Roy and Haider, 2019]] ).

Major population trends of urbanisation and urban area expansion are forecast to take place in Asia. It has been mentioned that demographic change will make humanity more vulnerable to climate change, particularly in places with high poverty rates and potentially prone to systemic disruptions in the food system ( [[#Puma--2015|Puma et al., 2015]] ; [[#d’Amour--2016|d’Amour et al., 2016]] ; [[#d’Amour--2017|d’Amour et al., 2017]] ).

The urban population of the world has grown rapidly from 751 million in 1950 to 4.2 billion in 2018. Asia, despite its relatively lower level of urbanisation, is home to 54% of the world’s urban population (United [[#Nations--2019|Nations, 2019]] ). Some cities have experienced population decline in recent years. Most of these cities are located in the low-fertility countries of Asia, where overall population sizes are stagnant or declining, as observed in a few cities in Japan and the Republic of Korea (e.g., Nagasaki and Busan), which experienced a population decline between 2000 and 2018 (United [[#Nations--2019|Nations, 2019]] ). By 2030, the world is projected to have 43 megacities with more than 10 million inhabitants, most of them in developing regions. However, some of the fastest-growing urban agglomerations are cities with fewer than 1 million inhabitants, many of them located in Asia and Africa (United [[#Nations--2019|Nations, 2019]] ). Challenges with water supply, in many cases, have existed for decades (Dasgupta, 2015). Climate change increases these challenges ( [[#Hoque--2016|Hoque et al., 2016]] ). As more people inhabit urban areas, the number of people vulnerable to heat stress is thus ''likely'' to rise, a problem that will be compounded by rising temperatures due to climate change ( [[#Acharya--2018|Acharya et al., 2018]] ). Compared with rural areas, hot temperature risk is even higher in urban regions (Luo, 2018a; Ye, 2018; Setiawati Martiwi Diah, 2021).

The impact of heat in rural areas has been a blind spot so far, particularly for farmers and outdoor labourers who are increasingly exposed to high outdoor temperatures due to increased intensity in agriculture combined with changes in working hours (Tasgaonkar, 2018).

Farmers as a group have shown an increasing number of females over the years due to migration of male members into urban areas for employment, which is putting women at more severe risk in the context of climate variability ( [[#Singh--2019|Singh, 2019]] ). Women are required to acquire new capacities to manage new challenges, including risks from climate change, through capacity-building interventions to strengthen autonomous-adaptation measures ( [[#Banerjee--2019|Banerjee et al., 2019]] ; [[#James--2019|James, 2019]] ; Mishra, 2019). However, the overlapping crises of climate change and the global public health crisis of COVID-19 represent a major challenge to gender equality and sustainable development (Katherine Brickell, 2020; [[#Sultana--2021|Sultana, 2021]] ).

For vulnerable populations, such as Indigenous Peoples, older and low-income groups, women, children, people with disabilities and minorities, the health effects of climate-change-related extreme weather events can be especially devastating ( [[#McGill--2016|McGill, 2016]] ). Such populations may be more susceptible to disease, have pre-existing health conditions or live in areas that do not promote good health or well-being; for instance, loss of income and food supply shortages could lead children in rural households to nutritional deprivations that can have both immediate and lifelong impacts ( [[#Gleick--2014|Gleick, 2014]] ; [[#UNICEF--2015|UNICEF, 2015]] ). Children, already susceptible to age-related insecurities, face additional destabilising insecurities from questions about how they will cope with future climate change ( [[#Hansen--2013|Hansen et al., 2013]] ).

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