Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Guo, Xiaojun; Huang, Jianbin; Luo, Yong; Zhao, Zongci; Xu, Ying

doi:10.1007/s00704-015-1718-1

Cited by 114 publications

(78 citation statements)

References 60 publications

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“…China has undergone frequent heat waves in recent decades (e.g., Ding et al, 2010;Guo et al, 2016;Luo & Lau, 2017;Lu & Chen, 2016;Wang et al, 2017). Using the observational data from 512 meteorological stations over China during 1961, Ding et al (2010 found a remarkably increasing trend of heat wave events after the 1990s.…”

Section: Introductionmentioning

confidence: 99%

Heat Waves in China: Definitions, Leading Patterns, and Connections to Large‐Scale Atmospheric Circulation and SSTs

et al. 2017

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Based on the daily maximum temperatures (Tmax) from 587 surface observation stations in China during 1959–2013, heat waves are detected using both absolute and relative definitions. The spatiotemporal variations of heat wave occurrence/duration/amplitude are compared between the two definitions. Considering the significant differences in regional climatology, relative threshold is more meaningful to detect the local extremes. By utilizing the empirical orthogonal function, the integral index heat wave total intensity is decomposed into three dominant modes: interdecadal (ID), interannual‐tripole (IA‐TR), and interannual‐dipole (IA‐DP) modes. The ID mode shows uniform anomalies over the whole China, with the maximum in north, and its corresponding time series depict notable interdecadal variations with a turning point around mid‐1990s. The IA‐DP mode exhibits opposite‐signed anomalies over north and south China. The IA‐TR mode shows an anomalous tripole pattern with negative anomalies over central China and positive anomalies over north and south China in its positive phase. Both the IA‐DP and IA‐TR patterns are more obvious since mid‐1990s with mainly year‐to‐year variations before that. All the three modes are controlled by anomalous high‐pressure systems, which are accompanied by local‐scale dry land conditions. The diabatic heating associated with anomalous convective activities over tropical western Pacific triggers Rossby wave trains propagating northward along the East Asia, which causes abnormal heat waves through descending motion over the high‐pressure nodes. In turn, the severe convections are generated by enhanced Walker circulation in the tropical Pacific due to warming and/or cooling sea surface temperature (SST) anomalies in the tropical western and eastern Pacific, respectively.

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Section: Introductionmentioning

confidence: 99%

Heat Waves in China: Definitions, Leading Patterns, and Connections to Large‐Scale Atmospheric Circulation and SSTs

et al. 2017

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“…The time period from 1971 to 2000 (total 30 years) has been adopted as the baseline period, and the time period from 1861 to 1880 (total 20 years) has been selected to represent the pre-industrial timeframe (Meehl et al 2012). The reasons for choosing this pre-industrial period are explicitly elucidated in Guo et al (2016).…”

Section: Selection Of the Analyzed Time Periodmentioning

confidence: 99%

“…At the 21st Conference of the Parties (COP21) held in Paris in December 2015, the goal to limit the warming target below 1.5°C was explicitly identified and included in the final accepted draft of the Paris agreement (Kanitkar 2015). According to climate model projection results, the global mean temperature rise is expected to reach the 4, 4.5, and 5°C warming targets by the end of twenty-first century (Zhang et al 2013a;Guo et al 2016). Thus, it is imperative that researchers investigate the variation in precipitation extremes across China using these higher warming targets.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, it is imperative that researchers investigate the variation in precipitation extremes across China using these higher warming targets. Guo et al (2016) have shown that heat waves over China will be more frequent, longer lasting, and more intense as the global warming target increases from 1.5 to 5°C. Future changes in precipitation events are more complicated than changes in temperature (Luo et al 2005).…”

Section: Introductionmentioning

confidence: 99%

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Projection of precipitation extremes for eight global warming targets by 17 CMIP5 models

et al. 2016

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Based on the historical and future outputs of 17 coupled model intercomparison project phase 5 (CMIP5) models, simulation of the precipitation extremes in China was evaluated under baseline climate condition compared to a gridded daily observation dataset CN05.1. The variations in precipitation extremes for eight global warming targets were also projected. The 17 individual models and the multi-model ensemble accurately reproduced the spatial distribution of precipitation extremes, although they were limited in their ability to capture the temporal characteristics. A notable dry bias existed in Southeast China, while a wet bias was present in North and Northwest China. The precipitation extremes in China were projected to be more frequent and more intense as global temperature rise reached the 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0°C warming targets. The projected percentage changes in the annual number of days with precipitation [50 mm (R50) and total precipitation during days in which the daily precipitation exceeds the 99th percentile (R99p) are projected to increase by 25.81 and 69.14 % relative to the baseline climate for a 1.5°C warming target, and by 95.52 and 162.00 % for a 4.0°C warming target, respectively. As the global mean temperature rise increased from 1.5 to 5°C, the subregions considerably affected by the East Asian summer monsoon (e.g., Southwest China, South China, and the Yangtze-Huai River Valley) were projected to experience a more dramatic increase in extreme precipitation events, in both number of days and intensity, while North and Northwest China were projected to suffer from relatively slight increases. The model uncertainties in the projected precipitation extremes in China by 17 CMIP5 models increase as global temperature rise increases.

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“…() indicated that the annual mean surface temperatures over the Millennium Silk Road regions were projected to be about 1.2°C higher than in the reference period 1986–2005. Several studies have also discussed impacts of the 1.5 and 2°C global warming targets on the climate change over China (e.g., Guo et al ., ; ; Jiang et al ., ; Fu et al ., ; Shi et al ., ). Notice that most of the above studies employed the transient simulations to analyse climate changes in a 1.5 and 2°C warmer world.…”

Section: Introductionmentioning

confidence: 99%

Projected changes in mid–high‐latitude Eurasian climate during boreal spring in a 1.5 and 2°C warmer world

Chen

et al. 2019

Intl Journal of Climatology

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This study examines projected changes in surface air temperature (SAT) and precipitation over mid–high latitudes of Eurasia during boreal spring in a 1.5/2°C warmer world (relative to pre‐industrial level) using historical, RCP4.5 and RCP8.5 simulations from 16 climate models of the Coupled Model Intercomparison Project Phase 5. Results show that spatial patterns of spring SAT and precipitation changes over Eurasia in the 1.5/2°C warmer world relative to the current climate (1979–2005) are similar between the two RCPs, but with a slightly larger amplitude in the RCP8.5. Spring SAT warmings over Eurasia are faster than the global annual mean. Amplitudes of the spring Eurasian SAT warmings are larger over higher latitudes. An additional 0.5°C global warming leads to extra spring Eurasian SAT warmings, with the magnitude larger than 0.5°C. Changes in the spring maximum temperature are comparable to the mean temperature changes both in the 1.5 and 2°C warming targets. Significant increases in the mean and extreme precipitation are only seen over parts of Eurasia. An additional 0.5°C global warming does not lead to obvious changes in the mean and extreme spring precipitation. Further analyses show that there are large uncertainties in the projected changes in the inter‐annual variability of the Eurasian spring SAT and precipitation.

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Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Cited by 114 publications

References 60 publications

Heat Waves in China: Definitions, Leading Patterns, and Connections to Large‐Scale Atmospheric Circulation and SSTs

Heat Waves in China: Definitions, Leading Patterns, and Connections to Large‐Scale Atmospheric Circulation and SSTs

Projection of precipitation extremes for eight global warming targets by 17 CMIP5 models

Projected changes in mid–high‐latitude Eurasian climate during boreal spring in a 1.5 and 2°C warmer world

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