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  • 软件名称:基于WRF模式的多源遥感降水资料数据同化研究
  • 软件大小: 0.00 B
  • 软件评级: ★★★
  • 开 发 商: 任静,潘小多
  • 软件来源: 《遥感技术与应用》
  • 解压密码:www.gissky.net

资源简介

摘要: 基于WRF模式和四维变分同化4Dvar系统分别同化了从2015年7月1日0时至7月4日0时的TRMM 3B42(Tropical Rainfall Measuring Mission)、GPM (Global Precipitation Measurement)和FY\|2G降水资料,并用HiWATER(Heihe Watershed Allied Telemetry Experimental Research)实验的气象站观测资料对结果进行验证。研究结果表明:与控制实验相比,同化多源遥感降水资料可提高降水模拟的精度,同化实验的降水均方根误差在0~4 mm之间,其中同化GPM降水资料的结果最优,均方根误差在0.5~1.5 mm;4类实验对2 m处相对湿度的模拟普遍低于真实观测,相对湿度均方根误差均在10%~50%,且同化GPM降水资料更有利于QCLOUD(Cloud water mixing ratio)、QVAPOR(Vapor water mixing ratio)、QRAIN(Rain mixing ratio)等变量的模拟;同化降水资料对风场模拟的影响极为复杂,不同降水资料的同化结果在黑河上、中和下流域各有优势。在整个流域内10 m处6 h平均风速的实验值都明显地高于实际观测,其中同化GPM实验结果较好,均方根误差在1.5~3 m/s。与TRMM 3B42和FY\|2G降水资料相比,GPM降水资料更能捕捉到微量降水和固态降水。因此,同化GPM降水资料更有利于降水,湿度和风速的模拟。 关键词: TRMM 3B42;GPM;FY\;  2G降水资料;WRF-4Dvar系统     Abstract: Weather research and forecasting model and four\|dimensional variational(4Dvar)data assimilation system were used to assimilate Tropical Rainfall Measuring 3B42 precipitation dataset(TRMM 3B42),Global Precipitation Measurement dataset(GPM)and FY\|2G precipitation dataset during 1 July to 4 July 2015.The results showed that:(1)assimilation of the satellite precipitation datasets does improve the forecasting of precipitation,because all assimilation precipitation RMSE are in(0,1),and assimilating GPM dataset is superior than others;(2)the results of  2 m relative humidity from all experiments underestimated real observations,and 2 m relative humidity RMSE(units %)were in(10,50).Moreover,assimilating GPM provides an advantage in estimating various air moisture conditions;(3)Although the impact of assimilating precipitation datasets were complex for simulating 10 m wind speed,results of 10 m wind speed experiments were overestimated\|the real observation and the RMSE were in 1.5~3 m/s.In conclusion,GPM precipitation datasets assimilation was good for simulating precipitation,relative humidity and 10 m wind speed.

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