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气象:2024,50(3):357-369
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基于印度洋海温信号的我国西北地区东部夏季降水组合降尺度预测方法研究
朱晓炜,李清泉,孙银川,王璠,王岱,高睿娜,刘颖
(中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室,银川 750002; 宁夏回族自治区气候中心,银川 750002;中国气象局气候预测研究重点开放实验室,国家气候中心,北京 100081;南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心,南京 210044)
A Hybrid Downscaling Scheme for Predicting Summer Precipitation in Eastern Part of Northwest China Based on Indian Ocean SST
ZHU Xiaowei,LI Qingquan,SUN Yinchuan,WANG Fan,WANG Dai,GAO Ruina,LIU Ying
(Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002; Ningxia Climate Centre, Yinchuan 750002;CMA Key Laboratory for Climate Prediction Studies, National Climate Centre, Beijing 100081;Key Laboratory of Meteorological Disaster, Ministry of Education International Joint Laboratory on Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044)
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投稿时间:2022-11-03    修订日期:2023-11-30
中文摘要: 利用国家气候中心第二代气候模式预测业务系统(BCC-CPSv2)预测产品,引入印度洋海温信号,采用组合降尺度方法建立了西北地区东部汛期降水预测模型。该预测模型对1991—2017年西北地区东部夏季降水的回报技巧较BCC-CPSv2预测技巧显著提高,空间相关系数由0.42提高到0.75,均方根误差明显减小,最多下降达80%。预测模型对降水空间分布型的预测能力较好,很好地回报了典型年份(1987年和2010年)夏季的降水距平百分率分布。通过抓住气象变量的空间分布特征,组合降尺度方法可以修正动力模式产品的预测误差,为西北地区东部夏季降水预测提供科学依据和技术支持,具有较好的应用前景。
Abstract:By using the prediction products of the Beijing Climate Centre Second-Generation Climate Prediction Model System (BCC-CPSv2) and a hybrid downscaling method as well as the Indian Ocean SST signals, this paper establishes a summer precipitation prediction model for eastern part of Northwest China. Relative to BCC-CPSv2 model, the prediction skill of this model is significantly improved for the summer precipitation in eastern part of Northwest China from 1991 to 2017. The spatial correlation coefficient increases from 0.42 to 0.75, and the root mean square error decreases obviously, down most by 80%. The model has better prediction ability for the spatial distribution pattern of precipitation anomaly percentage, such as for the distributions of the summer precipitation anomaly percentages in 1987 and 2010. By grasping the spatial distribution characteristics of meteorological variables, this prediction method can correct the prediction errors of dynamic model products and provide scientific basis and technical support for summer precipitation prediction in eastern part of Northwest China, so it is expected to have a good application prospect.
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基金项目:第二次青藏高原综合科学考察研究项目(2019QZKK0208)、中国科学院战略性先导科技专项(XDA20100304)、国家自然科学基金重大项目(41790471)、国家重点基础研究发展计划(2016YFA0602200)、中国气象局创新发展专项(CXFZ2021J024)、中国气象局旱区特色农业气象灾害监测预警与风险管理重点实验室指令性项目(CAMP-201905)、宁夏重点研发计划(2022CMG03058、2022BEG02020)和宁夏自然科学基金项目(2022AAC03673)共同资助
Author NameAffiliation
ZHU Xiaowei Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002 Ningxia Climate Centre, Yinchuan 750002 
LI Qingquan CMA Key Laboratory for Climate Prediction Studies, National Climate Centre, Beijing 100081
Key Laboratory of Meteorological Disaster Ministry of Education International Joint Laboratory on Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 
SUN Yinchuan Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002 Ningxia Climate Centre, Yinchuan 750002 
WANG Fan Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002 Ningxia Climate Centre, Yinchuan 750002 
WANG Dai Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002 Ningxia Climate Centre, Yinchuan 750002 
GAO Ruina Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002 Ningxia Climate Centre, Yinchuan 750002 
LIU Ying CMA Key Laboratory for Climate Prediction Studies, National Climate Centre, Beijing 100081 
引用文本:
朱晓炜,李清泉,孙银川,王璠,王岱,高睿娜,刘颖,2024.基于印度洋海温信号的我国西北地区东部夏季降水组合降尺度预测方法研究[J].气象,50(3):357-369.
ZHU Xiaowei,LI Qingquan,SUN Yinchuan,WANG Fan,WANG Dai,GAO Ruina,LIU Ying,2024.A Hybrid Downscaling Scheme for Predicting Summer Precipitation in Eastern Part of Northwest China Based on Indian Ocean SST[J].Meteor Mon,50(3):357-369.