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Assimilation and Simulation of Typhoon Rusa (2002) Using the WRF System

机译:使用WRF系统对鲁萨台风(2002)的同化和模拟

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Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002).The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-kn horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa's track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation.
机译:利用最近开发的天气研究和预报(WRF)3DVAR和WRF模型,进行了台风Rusa(2002)的初始化和模拟的数值实验.WRF 3DVAR中使用的观测数据是常规的全球电信系统(GTS)数据。和韩国自动气象站(AWS)地面观测。通过国家气象中心(NMC)方法进行的背景误差统计(BES)具有两种不同的分辨率,即来自NCEP全球模型的210公里水平网格空间和来自韩国运行预报的10公里水平分辨率。为了提高从WRF 3DVAR分析初始化的WRF仿真的性能,通过WRF 3DVAR控制变量,流函数,速度势,不平衡压力和比湿度对通过递归滤波器在水平背景误差协方差中使用的标度长度进行了调整。 。针对不同的背景误差统计数据和不同的观测数据进行的实验表明,随后的24小时WRF模式预报对台风Rusa的径迹和降水都对初始场产生了显着影响。将AWS数据与调整后的背景误差统计数据进行同化,可以更好地预测台风径迹及其降水。

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