Assessment and Assimilation of FY-3 Humidity Sounders and Imager in the UK Met Office Global Model
China’s FengYun 3 (FY-3) polar orbiting satellites are set to become an important source of observational data for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies over the next two decades. As part of the Climate Science for Service Partnership China (CSSP China) program, FY-3B Microwave Humidity Sounder 1 (MWHS-1) and FY-3C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation. This represents the first time observations from China’s polar orbiting satellites have been used in the UK’s global NWP model. Since 2016, continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies. Nonetheless, MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%, respectively, and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%. The observations from the Microwave Radiation Imager (MWRI) also are a potentially significant source of benefits for NWP models, but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation. This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data.
Key wordsMicrowave Humidity Sounder Microwave Radiation Imager numerical weather prediction
中国风云3号极轨卫星在未来二十年将作为重要的观测资料源, 用于数值天气预报、大气再分析产品和气候监测研究. 本项研究作为“面向服务伙伴的气候科学”(CSSP中国)的内容之一, 对风云3B微波探测器1(MWHS-1)和3C微波探测器2(MWHS-2)的观测资料作了系统评估, 同时对其进行了业务数值预报模式的同化分析.
本项研究给出了首次用于英国全球数值天气预报模式的中国极轨卫星观测结果. 自2016起, 连续数据质量检验表明上述卫星资料的偶然偏差变化是与影响仪器平台加热系统和其它瞬时异常的能量供给方案有关. 尽管存在这些偏差, MWHS-1和MWHS-2依然可以分别显著地减少24小时预报偏差0.3%和0.6%, 而两个资料结合使用后可使24小时预报偏差减少1%. 微波成像仪观测(MWRI)也是对数值天气预报有重要帮助的资料源, 但该仪器半轨道检测到的与太阳辐射有关的偏差不利于该资料的数据同化应用. 本项研究还介绍了英国气象局开发用于未来MWRI资料同化的订正算法的基本原理.
关键词微波湿度仪 微波辐射成像仪 数值天气预报
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This work and its contributors (Fabien CARMINATI, Brett CANDY and William BELL) were supported by the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.
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