Compution and Application of Rainstorm Surface Rainfall Based on Radar Data in Shanghai
The computing method of rainstorm surface rainfall is studied based on the grid product of hourly quantitative precipitation estimation (QPE) of radar data and the automatic weather station (AWS) quality control rainfall data in Shanghai. The computing method is that the radar estimated rainfall of the AWS in rainstorm area, which was obtained from the radar QPE mean of 9 grid points around the AWS, is used to calculate the difference between the rainfall and the radar estimated rainfall of the AWS. The difference field is interpolated into the same grid point of radar precipitation estimation using Kriging interpolation method. The hourly rainfall of grid points is the sum of the residual interpolation data and the radar rainfall estimation of grid points. The average absolute error of QPE and measured rainfall of 24 typical rainstorm cases of all stations is reduced by 27% after correction. The average error of QPE and measured rainfall of main precipitation sections and process rainfall of national weather stations for two typical rainstorms are reduced by 33%-39% and 34%-59% respectively after correction. The value and graph of hourly and process surface rainfall and administrative district as well as water conservancy onesided rainfall of the 24 typical rainstorms from 2007 to 2015 are calculated and drawn according to the rainfall of grid points using above computing method. Finally, the automated computing inquiry system of rainstorm surface rainfall based on radar data is produced using the development tools of Visual Studio Microsoft 2012 and Microsoft Visual Studio software relying on NET Framework.4.0 Software development platform. This system will be used for realtime querying and calculation.