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Sensitivity Study on High-Resolution WRF Precipitation Forecast for a Heavy Rainfall Event

机译:高分辨率WRF降水预报的敏感性研究

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摘要

A high-resolution Weather Research and Forecasting (WRF) model for a heavy rainfall case is configured and the performance of the precipitation forecasting is evaluated. Sensitivity tests were carried out by changing the model configuration, such as domain size, sea surface temperature (SST) data, initial conditions, and lead time. The numerical model employs one-way nesting with horizontal resolutions of 5 km and 1 km for the outer and inner domains, respectively. The model domain includes the capital city of Seoul and its suburban megacities in South Korea. The model performance is evaluated via statistical analysis using the correlation coefficient, deviation, and root mean squared error by comparing with observational data including, but not limited to, those from ground-based instruments. The sensitivity analysis conducted here suggests that SST data show negligible influence for a short range forecasting model, the data assimilated initial conditions show the more effective results rather than the non-assimilated high resolution initial conditions, and for a given domain size of the forecasting model, an appropriate outer domain size and lead time of <6 h for a 1-km high-resolution domain should be taken into consideration when optimizing the WRF configuration for regional torrential rainfall events around Seoul and its suburban area, Korea.
机译:配置了用于大雨天气情况的高分辨率天气研究和预报(WRF)模型,并评估了降水预报的性能。通过更改模型配置(例如域大小,海面温度(SST)数据,初始条件和提前期)来进行敏感性测试。数值模型采用单向嵌套,其中外域和内域的水平分辨率分别为5 km和1 km。模型域包括首尔的首府及其在韩国的郊区特大城市。通过使用相关系数,偏差和均方根误差进行统计分析,并与包括但不限于来自地面仪器的观测数据进行比较,对模型性能进行评估。在此进行的敏感性分析表明,对于给定的预测模型域大小,SST数据对短程预测模型的影响可忽略不计,与初始条件同化的数据显示的结果要比非同化高分辨率初始条件更为有效。 ,在针对首尔及其郊区(韩国)周围的区域性暴雨事件优化WRF配置时,应考虑合适的外部区域大小和1 km高分辨率区域的小于6 h的前置时间。

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