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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:具有区域WRF-3DVAR系统的多普勒天气雷达数据的同化:控制变量对大雨案例预测的影响

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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测是实时洪水预测系统的重要信息来源。以前的研究表明,多普勒天气雷达(DWR)观察的同化显着提高了短期降水的预测技能。然而,用于DWR同化的变分同化方法对背景误差统计中的控制变量选项的选择敏感。在这项研究中,分析了对控制变量选择在同化DWR观察中的影响改善大雨事件预测。为此目的雷达反射率和径向速度,使用气流研究和预测模型中的流函数速度电位(PSI CHI)和水平风元件(UV)控制变量选项 - 3DVAR(三维变分同化系统)同化观察。结果表明,使用紫外线控制变量选项的DWR同化改善了前12小时的高强度降水预测的技能。

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