The Verification of SWCWARMS Model in Southwest of China

Using national observation data and automatic station precipitation data， based on objective statistical methods，the prediction ability of the precipitation（ 24h cumulative rainfall）， the surface elements（2m temperature，10m wind） and the height element（such as wind， temperature， height） in southwest China in 2016 of SWCWARMS model and GRAPES model were evaluated and compared， the main conclusions are as follows.（1） the SWCWARMS model is better than the GRAPES model in moderate to heavy rain forecast， 24h light rain and torrential rain ，48h torrential rain are worse than the GRAPES model， while the SWCWARMSmodel has empty forecast problems.（2）the 2m temperature of SWCWARMSmodel is below to observation， and the 10m wind speed of SWCWARMSmodel in autumn and winter is more than observation，the quarterly average RMSE of 2m temperature， 10m zonal wind and meridional wind of SWCWARMSmodel is less than GRAPESmodel， however， the monthly average RMSE of 2m temperature（72h） is larger than the GRAPESmodel in August， and the forecast of the near-surface temperature field is better than the 10m wind field.（3）the temperature field prediction by two models is better than the height field and wind field，SWCWARMS model predicts that the middle tropospheric geopotential height field and temperature field are lower than observation，the prediction of the temperature field and the height field in summer and autumn is better than the GRAPRSmodel.On the 500hPa，except in 2，11 ～12 （24h）， the RMSE of temperature from SWCWARMS model are less than GRAPRSmodel on other months and other forecast aging，the prediction of height field is better than that of GRAPRSmodel in spring and summer， the RMSE is greater than the GRAPRSmodel in autumn and winter.On the850hPa，the SWCWARMSmodel predicts the RMSE of wind field is smaller the GRAPRSmodel in spring and summer，and the RMSE of the wind field in winter half year is greater than that of the summer half year，the frequency of the RMSE of SWCWARMS model greater than GRAPES model is increased in winter half year.