In this paper, we study the relationship between the covariability of the Indian summer monsoon (ISM) and East Asian summer monsoon (EASM) and the rainy season precipitation anomaly in the Mekong River basin (MRB) using ERA-Interim reanalysis data and precipitation from the Climate Hazards Group Infrared Precipitation station for 1981-2016. The results indicate that the interannual variability of the rainy season precipitation in the MRB is significantly modulated by the ISM and EASM covariability. Herein, the ISM mainly influences the rainy season precipitation west of the MRB, and the EASM mainly influences the rainy season precipitation over the southeastern MRB. When the Bay of Bengal (BOB) and South China Sea (SCS) are dominated by positive anomalies of diabatic heating associated with a stronger ISM and EASM, the anomalous westerly winds in the BOB and significantly anomalous easterly winds in the SCS, which carry more warm-wet air, induce a stronger than normal convergence and upward motion in the MRB. This results in much heavier rainy season precipitation in the MRB. Model runs with a linear baroclinic model confirm the observational analysis results.
机构:State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics,Institute of Atmospheric Physics,Chinese Academy of Sciences
机构:
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Li X.
Li Q.
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Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Li Q.
Ding Y.
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China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Ding Y.
Yang S.
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机构:
School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), ZhuhaiCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Yang S.
Dong L.
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School of Atmospheric Sciences and Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), ZhuhaiCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Dong L.
Yu J.
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China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Yu J.
Shen X.
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Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), ZhuhaiCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Shen X.
Wu Q.
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China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
Wu Q.
Sun X.
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China Meteorological Administration Key Laboratory for Climate Prediction Studies, National Climate Center, BeijingCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters / Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing
机构:
Chinese Acad Meteorol Sci, China Meteorol Adm, State Key Lab Severe Weather, Beijing, Peoples R ChinaNanjing Univ Informat Sci & Technol, Key Lab Meteorol Disaster, Minist Educ, Nanjing 210044, Jiangsu, Peoples R China
机构:
Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China
Lin, Zhongda
Wang, Bin
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机构:
Univ Hawaii Manoa, Int Pacific Res Ctr, Honolulu, HI 96822 USA
Univ Hawaii Manoa, Dept Meteorol, Honolulu, HI 96822 USA
Nanjing Univ Informat Sci & Technol, Earth Syst Modelling Ctr, Nanjing, Jiangsu, Peoples R ChinaChinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China