Abstract
Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system (WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager (AHI) radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.
摘要
尽管高时空分辨率的雷达资料能精准地探测出风暴系统的三维结构, 但是其有效观测半径有限并且观测时段局限于降水发生之后. 作为雷达资料的有益补充, 静止卫星辐射亮温观测是能够提供快速演变的对流天气系统结构和环境场信息的主要资料来源. 本文以北方的一次强降水过程为例, 在WRFDA (Weather Research and Forecasting model data assimilation system) 同化系统中实现了 Himawari-8 红外辐射率资料 (Advanced Himawari Imager, 简称AHI) 的全空同化. 完成了偏差订正模型、 晴空条件下的云检测模型以及全空条件下的对称观测误差模型的构建. 结果显示, 使用云依赖的观测误差模型能改进云雨区AHI卫星资料的有效同化, 改善了云量和云高的分析. 通过和卫星观测和雷达观测相对比, 可以发现, AHI辐射率资料的全空同化相对于晴空同化能够改进大部分地区云雨变量特别是雪水和云中液态水. 进一步通过对比各组试验的降水结果可以发现, AHI辐射率资料的全空同化改进本次强降水过程的落区和强度预报效果最为显著.
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Acknowledgements
This research was primarily supported by the Chinese National Natural Science Foundation of China (G41805016, G41805070), the Chinese National Key R&D Program of China (2018YFC1506404, 2018YFC1506603), the research project of Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province in China (SZKT201901, SZKT20 1904), the research project of the Institute of Atmospheric Environment, China Meteorological Administration, Shenyang in China (2020SYIAE02, 2020SYIAE07).
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Article Highlights
• The simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud height.
• Assimilating all-sky AHI data improves hydrometeor specification when verified against the radar reflectivity and the AHI radiance.
• Assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity.
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Xu, D., Liu, Z., Fan, S. et al. Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China. Adv. Atmos. Sci. 38, 661–676 (2021). https://doi.org/10.1007/s00376-020-0219-z
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DOI: https://doi.org/10.1007/s00376-020-0219-z