The Spring Drought in Yunnan Province of China: Variation Characteristics, Leading Impact Factors, and Physical Mechanisms
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Published:2023-02-01
Issue:2
Volume:14
Page:294
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ISSN:2073-4433
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Container-title:Atmosphere
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language:en
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Short-container-title:Atmosphere
Author:
Gao Lu1, Han Xue1, Chen Xingrong1, Liu Boqi2ORCID, Li Yan3ORCID
Affiliation:
1. National Marine Environmental Forecasting Center, Beijing 100081, China 2. State Key Laboratory of Severe Weather, Institute of Climate System, Chinese Academy of Meteorological Sciences, Beijing 100081, China 3. College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518061, China
Abstract
Yunnan Province in Southwest China is vulnerable to droughts due to its distinctive topography and local climate. Spring drought in Yunnan (SDY), which accounts for 70% of all drought events, causes the most severe devastation. By examining the variation characteristics of droughts in Yunnan from 1961 to 2020 in terms of the standardized precipitation evapotranspiration index (SPEI), this present study shows that droughts in Yunnan have worsened in the past 60 years on different timescales. Especially, the SDY exhibits notable interannual and interdecadal variations, with no significant long-term trend, although the spring average regional temperatures have risen at a rate of 0.33 °C/10a since 1961. Here, in order to quantify the contribution of the precipitation and temperature, the two main meteorological impact factors, to the SDY under the exacerbation of climate warming, the statistical analyses reveal that precipitation plays a more crucial role than temperature in interannual and interdecadal SDY variations. Further, a diagnostic analysis of the moisture budget equation indicates that suppressed vertical moisture advection is the most important physical process affecting the reduced rainfall amount in spring, followed by the restricted horizontal water vapor transport. Meanwhile, the weak Bay of Bengal (BOB) summer monsoon, which is likely regulated by El Niño-like sea surface temperature anomalies (SSTAs) in spring, is closely linked with the SDY. This mechanism provides the possibility of SDY predictability on a seasonal scale.
Funder
National Natural Science Foundation of China National Key Research and Development Plan of China
Subject
Atmospheric Science,Environmental Science (miscellaneous)
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