Radar data assimilation of the GRAPES model and experimental results in a typhoon case |
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| Authors: | LIU Hongya XUE Jishan GU Jianfeng XU Haiming |
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| Affiliation: | Shanghai Meteorological Center, Shanghai 200030;State Key Laboratory of Severe Weather, Chinese Academy of Meteorological
Sciences, Beijing 100081;Chongqing Meteorological Bureau, Chongqing 401147;Nanjing University of Information Science & Technology, Nanjing 210044 |
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| Abstract: | Constructing β-mesoscale weather systems in initial fields remains a challenging problem in a mesoscale numerical weather prediction (NWP)
model. Without vertical velocity matching the β-mesoscale weather system, convection activities would be suppressed by downdraft and cooling caused by precipitating hydrometeors.
In this study, a method, basing on the three-dimensional variational (3DVAR) assimilation technique, was developed to obtain
reasonable structures of β-mesoscale weather systems by assimilating radar data in a next-generation NWP system named GRAPES (the Global and Regional
Assimilation and Prediction System) of China. Single-point testing indicated that assimilating radial wind significantly improved
the horizontal wind but had little effect on the vertical velocity, while assimilating the retrieved vertical velocity (taking
Richardson’s equation as the observational operator) can greatly improve the vertical motion. Experiments on a typhoon show
that assimilation of the radial wind data can greatly improve the prediction of the typhoon track, and can ameliorate precipitation
to some extent. Assimilating the retrieved vertical velocity and rainwater mixing ratio, and adjusting water vapor and cloud
water mixing ratio in the initial fields simultaneously, can significantly improve the tropical cyclone rainfall forecast
but has little effect on typhoon path. Joint assimilating these three kinds of radar data gets the best results. Taking into
account the scale of different weather systems and representation of observational data, data quality control, error setting
of background field and observation data are still requiring further in-depth study. |
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| Keywords: | 3DVAR mesoscale data assimilation vertical velocity retrieval Richardson's equation |
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