Projection on Antarctic Temperature Extremes from the CMIP6 Multimodel Ensemble under Different Scenarios

Jiangping Zhu aState Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
bUniversity of Chinese Academy of Sciences, Beijing, China

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Aihong Xie aState Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

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Xiang Qin aState Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

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Shimeng Wang aState Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China

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Bing Xu cWeather Modification Office of Liaoning Province, Shenyang, China

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YiCheng Wang dLanzhou Central Meteorological Observatory, Lanzhou, China

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Abstract

Global warming has been accelerating the frequency and intensity of climate extremes, and has had an immense influence on the economy and society, but attention is seldom paid to future Antarctic temperature extremes. This study investigates five surface extreme temperature indices derived from the multimodel ensemble mean (MMEM) based on 14 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) under the shared socioeconomic pathways (SSPs) of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. In Antarctica, the variations in extreme temperature indices exhibit regional and seasonal differences. The diurnal temperature range (DTR) usually illustrates a downward trend, particularly for the Antarctic Peninsula and Antarctic coast, and the strongest change occurs in austral summer. In all cases, the annual highest minimum/maximum temperature (TNx/TXx) increases faster in inland Antarctica. Antarctic amplification of extreme temperature indices is detected and is strongest at the lowest maximum temperature (TXn). At the Antarctic Peninsula, TXx amplification only appears in winter. Great DTR amplification appears along the Antarctic coast and is strongest in summer and weakest in winter. The changes in extreme temperature indices indicate the accelerated Antarctic warming in future scenarios.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Aihong Xie, xieaihong@nieer.ac.cn, xieaih@lzb.ac.cn

Abstract

Global warming has been accelerating the frequency and intensity of climate extremes, and has had an immense influence on the economy and society, but attention is seldom paid to future Antarctic temperature extremes. This study investigates five surface extreme temperature indices derived from the multimodel ensemble mean (MMEM) based on 14 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) under the shared socioeconomic pathways (SSPs) of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. In Antarctica, the variations in extreme temperature indices exhibit regional and seasonal differences. The diurnal temperature range (DTR) usually illustrates a downward trend, particularly for the Antarctic Peninsula and Antarctic coast, and the strongest change occurs in austral summer. In all cases, the annual highest minimum/maximum temperature (TNx/TXx) increases faster in inland Antarctica. Antarctic amplification of extreme temperature indices is detected and is strongest at the lowest maximum temperature (TXn). At the Antarctic Peninsula, TXx amplification only appears in winter. Great DTR amplification appears along the Antarctic coast and is strongest in summer and weakest in winter. The changes in extreme temperature indices indicate the accelerated Antarctic warming in future scenarios.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Aihong Xie, xieaihong@nieer.ac.cn, xieaih@lzb.ac.cn

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