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1.广东省气候变化与自然灾害研究重点实验室 / 中山大学大气科学学院,广东 珠海 519082
2.南方海洋科学与工程广东省实验室(珠海),广东 珠海 519082
3.澳门海岸带生态环境国家野外科学观测研究站 / 澳门环境研究院 / 澳门科技大学创新工程学院,澳门 999078
4.中国科学院大气物理研究所云降水物理与强风暴实验室,北京 100029
5.成都信息工程大学大气科学学院,四川 成都 610225
Received:30 December 2024,
Revised:2025-05-21,
Accepted:10 June 2025,
Published Online:16 September 2025,
Published:25 September 2025
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姚乐宝,沈丹,王东海等.FY-4A卫星AGRI辐射资料直接同化对华南一次极端降水预报的影响[J].中山大学学报(自然科学版)(中英文),2025,64(05):100-115.
YAO Lebao,SHEN Dan,WANG Donghai,et al.Impact of direct assimilation of FY-4A AGRI radiance data on forecasting an extreme precipitation event in South China[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(05):100-115.
姚乐宝,沈丹,王东海等.FY-4A卫星AGRI辐射资料直接同化对华南一次极端降水预报的影响[J].中山大学学报(自然科学版)(中英文),2025,64(05):100-115. DOI: 10.13471/j.cnki.acta.snus.ZR20240371.
YAO Lebao,SHEN Dan,WANG Donghai,et al.Impact of direct assimilation of FY-4A AGRI radiance data on forecasting an extreme precipitation event in South China[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(05):100-115. DOI: 10.13471/j.cnki.acta.snus.ZR20240371.
风云四号A星(FengYun-4A,简称FY-4A)是我国新一代静止气象卫星的首发星。围绕其成像仪辐射资料的直接同化,聚焦其如何提高极端降水预报准确性及多通道组合同化是否优于单通道同化2个科学问题开展研究。基于WRF(weather research and forecasting)和GSI(gridpoint statistical interpolation)框架,采用观测算子替代方案测试了GSI同化系统在晴空条件下对FY-4A AGRI(advanced geostationary radiation imager)红外通道辐射资料的直接同化性能。设计多组同化预报试验,对比了其对1次季风低压极端强降水天气过程的循环同化和预报影响。结果表明,采用GOES-15(geostationary operational environmental satellite-15)IMAGER观测算子替代方案直接同化3.75、6.25、10.8和13.5 μm 4个FY-4A AGRI红外通道的试验,及上述方案附加采用Himawari-8 AHI(advanced himawari imager)观测算子替代方案直接同化7.1、8.55和12.0 μm 3个FY-4A AGRI红外通道的试验,可在洋面上空关键位置产生中心强度更大、水平分布范围更广、垂直涵盖层次更深厚的正水汽混合比分析增量,并在区域高分辨率数值预报中改善了低层暖湿条件,明显地提高了特大暴雨落区范围和雨带形态走向的预报准确性。
FengYun-4A (FY-4A) is China’s first next-generation geostationary meteorological satellite. This study addresses two scientific questions related to the direct assimilation of radiance data from its onboard Advanced Geostationary Radiation Imager (AGRI):1)how assimilating these observations improves the accuracy of extreme precipitation forecasts and 2)whether multi-channel joint assimilation provides better forecast performance compared to single-channel assimilation. Within the weather research and forecasting(WRF)and gridpoint statistical interpolation(GSI)framework, alternative observation operators were employed to assess the direct assimilation capability of the GSI system for FY-4A AGRI infrared radiance data under clear-sky conditions. A series of assimilation-forecast experiments were conducted to evaluate the impact of cycling assimilation on the prediction of an extreme precipitation event associated with a monsoon depression. Results indicate that experiments employing the Geostationary Operational Environmental Satellite-15 (GOES-15) IMAGER observation operator to directly assimilate four infrared channels (3.75,6.25,10.8 and 13.5 μm) from FY-4A AGRI, as well as experiments additionally incorporating the Himawari-8 Advanced Himawari Imager (AHI) observation operator for another three infrared channels (7.1, 8.55 and 12.0 μm, totaling seven channels), produce more pronounced positive analysis increments of water vapor mixing ratio. These increments exhibit greater central intensity, broader horizontal distribution, and deeper vertical coverage over critical oceanic regions. Consequently, the assimilation significantly improves the representation of low-level warm-moist conditions in regional high-resolution numerical forecasts, markedly enhancing the predicted spatial distribution and orientation of extreme precipitation events.
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