受云影响的卫星红外高光谱资料同化在台风数值预报中的研究

Satellite hyperspectral infrared radiance (IR) measurements can provide atmospheric temperature and humidity information at high vertical resolutions, which are important to the numerical prediction of tropical cyclones. However, the direct assimilation of hyperspectral IR has not been fully applied in typhoon forecasting due to the problem of cloud. The key to solving the problem of cloud-affected infrared data assimilation is to improve the simulation of infrared radiances under cloudy-sky conditions. This project will conduct the hyperspectral IR data assimilation research on the Cross-track Infrared Sounder (CrIS) onboard Suomi-NPP satellite. Focusing on improving the model background cloud structures, this study uses cloud liquid/ice water retrieved from satellite microwave measurements to constrain the model three-dimensional cloud structures, so that the simulated infrared radiances in cloud regions can be improved. Based on cloud classification, the cloud effect on the “observed minus simulated” brightness temperature departures for different types of CrIS channels are examined, under the circumstances of cumulus cloud, stratus cloud, cirrus cloud and multi-type cloud. A new cloud-dependent quality control scheme with dynamic thresholds will be developed, and the feasibility of assimilating hyperspectral IR under the influences of different cloud types will be also explored. Furthermore, we will modify the bias correction scheme for cloudy-sky condition, with the consideration of including cloud effect in the traditional clear-sky bias correction scheme. After all, this study will develop the direct assimilation method for hyperspectral IR data under cloudy conditions for typhoon prediction. The improved efficiency to use satellite radiance data will contribute to enhancing the forecast skill on typhoon track, intensity and precipitation.

卫星红外高光谱观测能够提供高垂直分辨率的大气温度和湿度信息，对于台风数值预报具有重要意义，然而云的影响导致红外高光谱辐射资料的直接同化未能在台风预报中得到充分应用，解决问题的关键在于改善有云环境下的辐射亮温模拟。本项目以Suomi-NPP卫星/CrIS资料为研究对象，从改善模式背景云结构的角度出发，利用卫星微波反演的云水和云冰来约束模式的三维云结构，以期提高辐射传输模式对云区红外辐射的模拟水平；基于云分类，研究积云、层云、卷云和复杂云等情况下，云效应对红外高光谱各通道“观测-模拟”亮温差的影响，发展随云类变化的动态质量控制方法，探索台风天气过程中红外高光谱资料在不同云类影响下的适应性同化；此外，在晴空偏差订正方案中考虑云的影响，发展云区偏差订正方案。本项目将建立适用于台风预报的有云条件下的红外高光谱资料直接同化方法，提高台风预报中的卫星资料利用率，提升台风路径、强度和降水预报水平。

本项目研究了有云影响下的卫星红外高光谱资料在台风数值预报中的同化方法。项目以Suomi-NPP极轨卫星/CrIS资料为研究对象，从改善有云环境下的辐射亮温模拟入手，建立了卫星微波反演的云水和云冰资料的同化方法，用来约束模式的三维云结构，从而改进模式背景场云廓线的真实性，提高辐射传输模式对云区红外辐射的模拟水平。在构建微波云水物质约束下的红外高光谱辐射模拟方案过程中，我们在集合-变分同化框架下发展了云水路径、云冰路径和雨水路径的观测算子，研发了考虑云水、云冰、雨水、雪和霰等多种水凝物的集合背景误差协方差并将其引入集合-变分同化方案。在微波云水信息约束的帮助下，新方案有效降低了红外辐射模拟偏差和均方根误差，批量统计结果表明，CrIS长波段CO2通道，长波段窗区通道，中波段H2O通道和短波段CO2通道和短波段窗区通道的模拟偏差分别降低44%，52%，38%，63%和75%，全天候卫星红外同化的资料利用率显著提升。基于该方案，进一步发展了随云类变化的动态质量控制方法，研究了不同模式云微物理方案对层云、积云、高积云、卷云和卷积云等云类的影响，及云效应对红外高光谱各通道“观测-模拟”亮温差的影响，发展了适应性质量控制同化方案；最终，项目建立了适用于台风预报的有云条件下的红外高光谱资料同化方法，提升了台风降水预报水平。