检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:Linbin HE Weiyi PENG Yu ZHANG Shiguang MIAO Siqi CHEN Jiajing LI Duanzhou SHAO Xutao ZHANG
机构地区:[1]College of Ocean and Meteorology,Guangdong Ocean University,Zhanjiang 524088,China [2]Chinese Academy of Meteorology Sciences,Beijing 100081,China [3]Institute of Urban Meteorology,China Meteorological Administration,Beijing 100089,China [4]School of Marine Sciences,Nanjing University of Information Science and Technology,Nanjing 210044,China [5]Dalian Marine Center,Ministry of Nature Resources of the People's Republic of China,Dalian 116001,China
出 处:《Advances in Atmospheric Sciences》2024年第11期2173-2191,共19页大气科学进展(英文版)
基 金:jointly supported by the Guangdong Province University Student Innovation and Entrepreneurship Project (580520049);the Guangdong Ocean University Scientific Research Startup Fund (R20021);the Key Laboratory of Plateau and Basin Rainstorm and Drought Disasters in Sichuan Province Open Research Fund (SZKT201902)。
摘 要:This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.
关 键 词:adaptive observation ensemble transform sensitivity data assimilation rainfall
分 类 号:P426.62[天文地球—大气科学及气象学]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.244