Upper Troposphere Warming Amplification over the Tibetan Plateau

对流层 气候学 高原(数学) 环境科学 全球变暖 大气科学 地质学 气候变化 海洋学 数学 数学分析
作者
Yuying Wei,Yuwei Wang,Zhenghui Lu,Yi Huang,Huang Fei
出处
期刊:Journal of Climate [American Meteorological Society]
卷期号:38 (19): 5335-5348 被引量:1
标识
DOI:10.1175/jcli-d-24-0567.1
摘要

Abstract The Tibetan Plateau (TP) has experienced significant warming since 1980, with greater surface warming than the global average. While previous studies have focused primarily on surface temperature, we identified significant warming amplification in the upper troposphere over the TP, centered around 250 hPa, with a warming rate of approximately 0.31 K decade −1 , faster than the rates observed at comparable latitudes. Using fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5), Japanese 55-year Reanalysis (JRA-55), and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis datasets and the energy budget analysis method, we attribute this warming amplification to various physical processes, with convection contributing about 0.24 K decade −1 and clouds adding about 0.13 K decade −1 . In contrast, water vapor and dynamical processes exert a substantial cooling effect that partially offsets the warming. Upper-tropospheric warming is evident in all four seasons, contributing to the overall annual-mean warming trend, with the greatest contribution occurring in autumn, reaching 0.37 K decade −1 , and the smallest in winter at 0.25 K decade −1 . Although the warming magnitudes across the four seasons are similar, the underlying mechanisms differ. In spring and summer, convection is the primary driver, while in autumn and winter, dynamical processes contribute most. Despite differences in the specific values of each contributing factor, all three datasets consistently show that convection plays a significant role in shaping the temperature patterns over the TP. Improving convection simulation in models is crucial for producing more accurate projections of future temperature trends in this region.
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