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

=== Atlas.5.1 East Asia ===

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==== Atlas.5.1.1 Key Features of the Regional Climate and Findings From Previous IPCC Assessments ====

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===== Atlas.5.1.1.1 Key Features of the Regional Climate =====

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The climatic regions defined for East Asia include central and eastern China, Japan and the Korea Peninsula (regions ECA and EAS in Figure Atlas.1 7). East Asia is significantly influenced by monsoon systems ( [[IPCC:Wg1:Chapter:Chapter-8#8.3.2.4.2|Section 8.3.2.4.2]] ). The seasonal advance or retreat of the East Asian summer monsoon (EASM) rainband is crucial to local climate. The East Asian winter monsoon (EAWM) has significant influence on the weather and climate over East Asia and plays an important role in regulating winter temperatures including strong cold events and snowstorms ( [[#Wang--2014|Wang and Chen, 2014]] ; [[#Wang--2016|Wang and Lu, 2016]] ). The East Asian monsoons exhibit considerable variability on a wide range of time scales, including notable interannual variabilities that includes an effect of the El Niño–Southern Oscillation (ENSO; [[#Wang--2000|Wang et al., 2000]] ) and the Indian Ocean Dipole (IOD; [[#Takaya--2020|Takaya et al., 2020]] ), and significant inter-decadal variabilities in the 20th century resulted from the effect of Pacific Decadal Variability (PDV; [[#Zhou--2009|Zhou et al., 2009]] ), see also [[IPCC:Wg1:Chapter:Annex-iv|Annex IV]] and Table Atlas.1. The thermal conditions of both the Tibetan Plateau and related ocean regions play key roles in modulating the intensity of the monsoon circulation. The East Asian monsoons are mainly driven by land–sea thermal contrast and, thus, are deeply affected by global climate change ( [[#Ding--2014|Ding et al., 2014]] ; [[#Gong--2018|Gong et al., 2018]] ).

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===== Atlas.5.1.1.2 Findings From Previous IPCC Assessments =====

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The findings of the IPCC AR5 ( [[#Christensen--2013|Christensen et al., 2013]] ) stated that the EASM and EAWM circulations have experienced an inter-decadal scale weakening since the 1970s, leading to a warmer climate in winter and enhanced mean precipitation along the Yangtze River Valley (30°N) but deficient mean precipitation in northern China in summer. Since the middle of the 20th century, it is ''likely'' that there has been an increasing trend in winter temperatures across much of Asia ( [[#Christensen--2013|Christensen et al., 2013]] ). The numbers of cold days and nights have decreased and the numbers of warm days and nights have increased over Asia ( [[#Hartmann--2013|Hartmann et al., 2013]] ). It is ''likely'' that there are decreasing numbers of snowfall events where increased winter temperatures have been observed ( [[#Hartmann--2013|Hartmann et al., 2013]] ). The SRCCL reports a land-use-change-induced cooling as large as –1.5°C in eastern China between 1871 and 2007 ( [[#Hartmann--2013|Hartmann et al., 2013]] ). The summer rainfall amount over East Asia shows no clear trend during the 20th century.

The IPCC AR5 ( [[#Christensen--2013|Christensen et al., 2013]] ) reports a significant increase in mean temperatures in south-eastern China, associated with a decrease in the number of frost days under the SRES A2 emissions scenario. The CMIP5 model projections indicate an increase of temperature in both boreal winter and summer over East Asia for RCP4.5. Based on CMIP5 model projections, there is ''medium confidence'' in an intensified EASM and increased summer precipitation over East Asia. More than 85% of CMIP5 models show an increase in mean precipitation of the EASM, while more than 95% of models project an increase in heavy precipitation events ( [[#Christensen--2013|Christensen et al., 2013]] ).The SROCC states that future projections of annual precipitation indicate increases of the order of 5–20% over the 21st century in many mountain regions, including the Himalaya and East Asia ( [[#Hock--2019b|Hock et al., 2019b]] ). The SR1.5 reports that statistically significant changes in heavy precipitation between 1.5°C and 2°C of global warming are found in East Asia ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ).

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==== Atlas.5.1.2 Assessment and Synthesis of Observations, Trends and Attribution ====

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Summer (June–August) mean temperature in eastern China has increased by 0.82°C since reliable observations were established in the 1950s ( [[#Sun--2014|Sun et al., 2014]] ). Based on historical meteorological observations, the best estimate of the linear trend of annual mean surface air temperature (SAT) for China with 95% uncertainty ranges is 0.38°C ± 0.05°C per decade for 1979–2015 ( [[#Li--2017|Li et al., 2017]] ). From 1960 to 2010, theincreasing trend of temperature was about 0.34°C per decade in the arid region of north-west China, higher than the average over China ( [[#Li--2012|]] [[#Li--2012|B. Li et al., 2012]] ; [[#Xu--2015|Xu et al., 2015]] ). Over South Korea, warming is 1.4–2.6 times larger than global trends. The increase is 1.90°C during 1912–2014 and 0.99°C during 1973–2014 ( [[#Park--2017|Park et al., 2017]] ) with a 25–45% urbanization contribution. The annual temperature increased in large cities at a rate of 0.29°C ± 0.08°C per decade compared with 0.11°C ± 0.08°C per decade in other stations in South Korea from 1960 to 2010 (H.-S. [[#Kim--2016|]] [[#Kim--2016|Kim et al., 2016]] ). A relatively high increase in annual mean temperature at the rate of 3.0°C per century was detected in the Tokyo metropolitan area for the period 1901–2015 ( [[#Matsumoto--2017|Matsumoto et al., 2017]] ). Trends of annual temperature for the period of 1961–2015 are shown in Figure Atlas.11. Most areas of East Asia have significant warming trends exceeding 0.1°C per decade, and the strongestwarming (0.3°C–0.4°C per decade) occurs in northern China.

Observational studies indicated significant decadal variations in the EAWM ( [[#Wang--2016|Wang and Lu, 2016]] ; [[#He--2017|He et al., 2017]] ). It weakened significantly around the late 1980s, being relatively strong during 1976–1987 and weaker during 1988–2001. The EAWM has recovered in intensity after 2004 and caused frequent and prevalent severe cold spells, as well as a number of unusually harsh cold winters in many parts of East Asia during the period 2004–2012 ( [[#Wang--2014|Wang and Chen, 2014]] ; [[#Kug--2015|Kug et al., 2015]] ; [[#Ge--2016|Ge et al., 2016]] ; [[#Gong--2018|Gong et al., 2018]] ). Negative zonal mean winter SAT anomalies were observed over the whole of East Asia from 1980 to 1988, with positive anomalies observed over high and low latitudes from 1988 to 2010 ( [[#Miao--2020|Miao and Wang, 2020]] ).

Precipitation trends over East Asia show considerable regional differences ( ''medium confidence'' ). Mean precipitation has shown negligible sensitivity to the warming trend with consequently limited overall trends in China though summer rainfall daily frequency and intensity show respectively decreasing and increasing trends from 1961 to 2014 ( [[#Zhou--2017|Zhou and Wang, 2017]] ). The summer precipitation trends over eastern China display a dipole pattern, characterized by positive anomalies in central-eastern China along the Yangtze River Valley and negative anomalies in north China since the 1950s ( [[IPCC:Wg1:Chapter:Chapter-8#8.3.2.4.2|Section 8.3.2.4.2]] ). This pattern has changed with the enhanced rainfall in the Huaihe River Valley and decreased in the regions south of the middle and lower reaches of the Yangtze River Valley since the 2000s ( [[#Liu--2012|Liu et al., 2012]] ; [[#Zhao--2015|Zhao et al., 2015]] ). The climate in north-west China changed from ‘warm–dry’ to ‘warm–wet’ condition in the mid-1980s ( [[#Peng--2017|Peng and Zhou, 2017]] ; [[#Wang--2020|Wang et al., 2020]] ), with an increased rate of annual precipitation of about 3.7% per decade from 1961 to 2015 (P. [[#Wu--2019|]] [[#Wu--2019|Wu et al., 2019]] ) and 11.2 mm per decade between 1960 and 2011 in northern Xinjiang ( [[#Xu--2015|Xu et al., 2015]] ). Mean rainfall and the number of rainy days during the Meiyu-Baiu-Changma period from June to September have increased during 1973–2015 in Korea ( [[#Lee--2017|Lee et al., 2017]] ). The precipitation trend has caused a large increase in summer precipitation at a rate of 40.6 ± 4.3 mm per decade, resulting in an increase of annual precipitation of 27.7 ± 5.5 mm per decade in South Korea from 1960 to 2010 (H.-S. [[#Kim--2016|]] [[#Kim--2016|Kim et al., 2016]] ). Precipitation amounts exhibited a slight decrease at both the annual and seasonal scales in Japan for the period 1901–2012 ( [[#Duan--2015|Duan et al., 2015]] ).

Agriculture intensification through oasis expansion in Xinjiang region has increased summer precipitation in the Tian Shan mountains ( ''high confidence'' from ''medium evidence'' with ''high agreement'' ) ( [[#Zhang--2009|Zhang et al., 2009]] , 2019b; [[#Deng--2015|Deng et al., 2015]] ; [[#Guo--2015|Guo and Li, 2015]] ; [[#Yao--2016|Yao et al., 2016]] ; [[#Xu--2018|Xu et al., 2018]] ; [[#Cai--2019|Cai et al., 2019]] ). However, there is ''very low confidence'' of the effect of oasis expansion on the temperature warming trend ( [[#Han--2013|Han and Yang, 2013]] ; [[#Li--2013|Li et al., 2013]] ; [[#Yuan--2017|Yuan et al., 2017]] ).

In the context of climate warming, intense snowfalls have hit China frequently in recent winters and have caused severe damages to the sustainability of society ( [[#Sun--2019|Sun et al., 2019]] ). Observations generally show a decrease in the frequency and an increase in the mean intensity of snowfalls in north-western, north-eastern and south-eastern China and the eastern Tibetan Plateau since the 1960s ( [[#Zhou--2018|Zhou et al., 2018]] ), but the results may depend on the objective criteria for identifying winter snowfall (J. [[#Luo--2020|]] [[#Luo--2020|Luo et al., 2020]] ).

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==== Atlas.5.1.3 Assessment of Model Performance ====

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Current climate models perform poorly insimulating the mean precipitation in East Asia, including the phase of the northward progression of the seasonal rainband (M. [[#Zhang--2018|]] [[#Zhang--2018|Zhang et al., 2018]] ). Although there has been an improvement in the simulation of mean states, interannual variability and past climate changes in the progression from CMIP3 to CMIP5, some previously documented biases (such as the ridge position of the western North Pacific Subtropical High and the associated rainfall bias) are still evident in CMIP5 models ( [[#Sperber--2013|Sperber et al., 2013]] ; [[#Zhou--2017|Zhou et al., 2017]] ). Most models capture the main characteristics of the winter mean circulation over East Asia reasonably well, but they still suffer from difficulty in predicting the interannual variability of the EAWM ( [[#Shin--2018|Shin and Moon, 2018]] ). Models have improved from CMIP5 to CMIP6 for climatological temperature and EAWM (D. [[#Jiang--2020|]] [[#Jiang--2020|Jiang et al., 2020]] ). Some CMIP6 models also show improvements in simulating the annual mean and interannual variation of precipitation ( [[#Sellar--2019|Sellar et al., 2019]] ; [[#Tatebe--2019|Tatebe et al., 2019]] ; T. [[#Wu--2019|]] [[#Wu--2019|Wu et al., 2019]] ). The performance of models is sensitive to cumulus convection schemes and horizontal resolution ( [[#Haarsma--2016|Haarsma et al., 2016]] ; [[#Wu--2017|Wu et al., 2017]] ; [[#Kusunoki--2018b|Kusunoki, 2018b]] ). High-resolution atmospheric global climate models (AGCM) successfully reproduce the intensity and the spatial pattern of the EASM rainfall ( [[#Li--2015|Li et al., 2015]] ; [[#Yao--2017|Yao et al., 2017]] ; [[#Ito--2020a|Ito et al., 2020a]] ) and improve the simulation of the diurnal cycle of precipitation rates and the probability density distributions of daily precipitation over Korea, Japan and northern China ( [[#Lin--2019|Lin et al., 2019]] ), but increasing horizontal resolution (at the typical scales used in GCMs) is not always a panacea for solving model biases ( [[#Roberts--2018|Roberts et al., 2018]] ).

Recent studies using CORDEX-EA models with resolution of about 12–25 km showed that the RCMs produce relatively more detailed regional features of the temperature distribution compared with the driving GCMs ( [[#Tang--2016|Tang et al., 2016]] ). Over China, RCMs provide more spatial details and in general reduce the biases of their driving GCMs, in particular in DJF (December–January–February) and over areas with complex topography ( [[#Wu--2020|Wu and Gao, 2020]] ). However, RCMs also show biases in simulating East Asian precipitation and its variability ( [[#Park--2016|Park et al., 2016]] ; [[#Zhou--2016|Zhou et al., 2016]] ; [[#Zou--2016|Zou and Zhou, 2016]] ), and do not always show added value compared to the driving GCMs ( [[#Li--2018b|Li et al., 2018b]] ). For example, by comparing inter-GCM and inter-RCM differences around the Japan archipelago, it was found that RCM generate relatively large differences in precipitation ( [[#Suzuki-Parker--2018|Suzuki-Parker et al., 2018]] ). The RCM multi-model ensemble produces superior simulation compared to that of a single model ( [[#Jin--2016|Jin et al., 2016]] ; D.-L. [[#Guo--2018|]] [[#Guo--2018|Guo et al., 2018]] ). A comparative study of RCMs at different spatial resolutions showed that with coarse resolution they present some limitations and high-resolution RCMs offer added value for several evaluation metrics ( [[#Park--2020|Park et al., 2020]] ).

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==== Atlas.5.1.4 Assessment and Synthesis of Projections ====

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The development of climate models provides a solid basis for projection of future monsoon changes under different global warming scenarios. Coupled model simulations indicate that East Asia and the Tibetan Plateau will ''likely'' experience higher warming than the global mean conditions across all global warming levels (Figure Atlas.1 7) and with the projected warming greater in ECA and TIB than EAS. Also, in the CMIP6 ensemble, the multi-model mean and 90th percentile warming for a given period and emissions scenario are consistently greater than in the CMIP5 ensemble. Larger warming magnitudes are projected to occur in the southern, north-western, and north-eastern regions of China, parts of Mongolia, the Korean Peninsula, and Japan than in other regions ( [[#Li--2018a|Li et al., 2018a]] ). Projections indicate winter increases in SAT over the East Asian continent and in precipitation over the northern East Asian continent with 1.5°C and 2.0°C global warming under the RCP4.5 and RCP8.5 scenarios ( [[#Miao--2020|Miao et al., 2020]] ).

Projected annual precipitation changes in the CMIP5 and CMIP6 ensembles are positive for all warming levels in ECA and TIB and for the higher warming levels in EAS. Changes in precipitation per degree Celsius global warming are larger in DJF than in JJA in ECA but show smaller seasonal difference in EAS (Figure Atlas.1 7). The EASM precipitation is projected to increase but with a complex spatial structure ( [[#Kitoh--2017|Kitoh, 2017]] ; [[#Moon--2017|Moon and Ha, 2017]] ). Simulations from CMIP5 models show that compared with the current summer climate, both SAT and precipitation increase significantly over the East Asian continent during the 1.5°C warming period (L. [[#Chen--2019|]] [[#Chen--2019|Chen et al., 2019]] ) and that the main mode of EASM precipitation changes from tripolar to dipolar ( [[#Wang--2018|Wang et al., 2018]] ). The increase in precipitable water in the wet EASM region is only slightly greater than the global average but the increase in precipitation is much greater (Z. [[#Li--2019|]] [[#Li--2019|Li et al., 2019]] ). The monsoon circulation in the lower troposphere is projected to strengthen due to the enhanced thermal forcing by the Tibetan Plateau ( [[#He--2019|He et al., 2019]] ; [[#He--2020|He and Zhou, 2020]] ), which causes the increased summer precipitation over the East Asian continent. Precipitation over eastern China increases for almost all months under global warming in projections from GCMs with different horizontal resolutions ( [[#Kusunoki--2018a|Kusunoki, 2018a]] ). Also, under RCP scenarios, in the 21st century, mean precipitation is projected to increase ( [[#Kim--2020|Kim et al., 2020]] ), especially in the late afternoons ( [[#Oh--2018|Oh and Suh, 2018]] ), over the Korean Peninsula due to global warming and associated changes in EASM. Increase in JJA mean precipitation is projected in northern East Asia consistently among the CMIP models, while northward migration of early summer East Asian rainbands such as the Meiyu-Baiu-Changma is delayed along with that of the mid-latitude westerly jet in the future ( [[#Horinouchi--2019|Horinouchi et al., 2019]] ). However, the geographical distribution of precipitation change tends to depend more on the cumulus convection scheme ( [[#Ose--2017|Ose, 2017]] ) and horizontal resolution of models rather than on SST distributions. Under the RCP4.5 and the RCP8.5 scenarios, the interannual variability in EASM rainfall is projected by the multi-model ensemble mean to increase in the 21st century ( [[#Ren--2017|Ren et al., 2017]] ). Further studies show a projected increase in heavy rainfall together with increases in rainfall intensity ( [[#Endo--2017|Endo et al., 2017]] ). Multi-model intercomparison indicates significant uncertainties in future projections of climate change in East Asia, although precipitation increases consistently across models ( [[#Zhou--2017|Zhou et al., 2017]] ). Simulations under the RCP4.5 scenario project that the number of snow days will be reduced by the end of the 21st century relative to 1986–2005, primarily owing to the decline of light snowfall events. The total amount is projected to increase in north-western China but decrease in the other sub-regions ( [[#Zhou--2018|Zhou et al., 2018]] ).

The increasing temperature trends under RCP scenarios were consistently reproduced in projections using CORDEX-EA models (Y. [[#Kim--2016|]] [[#Kim--2016|Kim et al., 2016]] ) as reported in AR5 using GCMs. However, changes in annual and seasonal mean precipitation exhibit significant inter-RCM differences with larger magnitudes and variability than in the GCMs ( [[#Ham--2016|Ham et al., 2016]] ; [[#Ozturk--2017|Ozturk et al., 2017]] ; H. [[#Sun--2018|]] [[#Sun--2018|Sun et al., 2018]] ; D. [[#Zhang--2018|]] [[#Zhang--2018|Zhang et al., 2018]] ). RCM simulations project that the Meiyu-Baiu-Changma heavy rainfall will significantly increase in northern Japan at the end of the 21st century under the RCP8.5 scenario ( [[#Osakada--2018|Osakada and Nakakita, 2018]] ), but projected precipitation amount and the number of precipitation days in summer around and over Japan differ as a result of RCM uncertainty ( [[#Suzuki-Parker--2018|Suzuki-Parker et al., 2018]] ). Annual total snowfall is projected to decrease in most parts of Japan except for Japan’s northern island under RCP2.6 ( [[#Kawase--2021|Kawase et al., 2021]] ).

Projejctions based on statistical downscaling of 37 CMIP5 GCMs for Xinjiang, China, show pronounced temperature increases of 0.27°C to 0.51°C per decade from 2021 to 2060 while precipitation changes were projected to be between –1.7% to 6.8% per decade and varying seasonally and spatially ( [[#Luo--2018|Luo et al., 2018]] ). A decrease of precipitation was projected in the western region of Xinjiang during summer. More extreme rainfall events were projected to occur during summer and autumn.

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==== Atlas.5.1.5 Summary ====

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In East Asia annual mean temperature has been increasing since the 1950s ( ''high confidence'' ). The linear trend of annual mean surface air temperature ''likely'' exceeded 0.1°C per decade over most of East Asia from 1961 to 2015. Trends of annual precipitation show considerable regional differences with areas of both increases and decreases ( ''medium confidence'' ), and with increases over north-west China and South Korea ( ''high confidence'' ). Agricultural intensification through oasis expansion in Xinjiang region has increased summer precipitation in the Tian Shan mountains ( ''high confidence'' ).

GCMs still show poor performance in simulating the mean rainfall and its variability over East Asia, especially over regions characterized by complex topography. The CMIP6 models have improved from CMIP5 for climatological temperature and winter monsoon but show little improvements for the summer monsoon. The RCMs produce relatively more detailed regional features, but do not always produce superior simulations compared with the driving GCMs.

The annual mean surface temperature over East Asia and the Tibetan Plateau will ''very likely'' increase under all emissions scenarios and GWLs. Larger warming magnitudes will ''likely'' occur in the northern part of EAS and in ECA and TIB. Precipitation is ''likely'' to increase over land in most of EAS at the end of the 21st century under higher-emissions scenarios (SSP3-7.0, RCP8.5 and SSP5-8.5) and global warming levels, and in ECA and TIB under all emissions scenarios and global warming levels. Summer precipitation increase is ''likely'' to occur in East Asia, corresponding to the strengthened summer monsoon circulation.

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