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首页> 外文期刊>Advances in Water Resources >Assimilation of Doppler Weather Radar data with a regional WRF-3DVAR system: Impact of control variables on forecasts of a heavy rainfall case
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Assimilation of Doppler Weather Radar data with a regional WRF-3DVAR system: Impact of control variables on forecasts of a heavy rainfall case

机译:多普勒天气雷达数据与区域WRF-3DVAR系统的同化:控制变量对暴雨案例预报的影响

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摘要

Short-term precipitation forecasts from numerical weather prediction models are a vital source of information for real-time flood forecasting systems. Previous studies show that assimilation of Doppler Weather Radar (DWR) observations significantly improves the forecast skill of short-term precipitation. However, the variational assimilation methods used for DWR assimilation are sensitive to the selection of control variable options in background error statistics. In this study, the impact of control variable choices in assimilating DWR observations for improving the forecast of heavy rainfall event is analysed. For this purpose radar reflectivity and radial velocity, observations are assimilated using stream function velocity potential (psi chi) and horizontal wind components (uv) control variable options in Weather Research and Forecast model - 3DVAR (three-dimensional variational assimilation system). The results show that DWR assimilation using uv control variable option has improved the skill of first 12 h of high intensity precipitation forecasts.
机译:来自数值天气预报模型的短期降水预报是实时洪水预报系统的重要信息来源。先前的研究表明,多普勒天气雷达(DWR)观测资料的同化显着提高了短期降水的预报技能。但是,用于DWR同化的变分同化方法对背景误差统计中控制变量选项的选择很敏感。在这项研究中,分析了控制变量选择对​​DWR观测值的吸收对改善强降雨事件预报的影响。为此,在天气研究和预报模型-3DVAR(三维变分同化系统)中,使用流函数速度势(psi chi)和水平风分量(uv)控制变量选项对观测值进行同化。结果表明,使用uv控制变量选项进行的DWR同化提高了高强度降水预报的前12 h的技巧。

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