The Estimation Of Precipitation By FY-2 Satellite And AMSU-B Microwave Data On Heilongjiang

The quantificational rainfall is estimated by data from FY-2 satellite and AMSU-B microwave on NOAA with the two methods as well as testing, and discussing their error, and the improved method was giving in this dissertation. In order to quantitative estimation results obvious, microwave material satellite inversion precipitation method is modified combination the stationary satellite data on the base of above mentioned.The method of Static satellite estimates of precipitation is cloud index method, which get the rainfall estimation by stepwise regression method with the cloud top brightness temperature. The method of Microwave material inversion rainfall precipitation is based on the directly detection for particles, which has clearly physical meaning. In this method, the cumulus clouds model must be established to get microwave equation at first, and the estimation of precipitation is inversed through channels matched. The method of Static satellite data combining microwave material estimates precipitation through the inversion of microwave material, and the encryption Automatic Rainfall Station data is used to verify the inversed results. If we get a better results and then, the main precipitation area and precipitation grades is confirmed. Thus, we can use the method of stationary infrared satellite rainfall estimation to trace the convective cloud cluster, determine the moving direction and speed of the precipitation area as well as the variation of rainfall intensity.Two method of estimation the rainfall were tested with several cases of rainstorm which occurred in HeilongJiang Province, The mainly results as follwing:(1) The method of Static satellite estimation is a rapid method on estiamating rainfall for all meteorological offices due to the Static satellite data acquisition is convenient and FY-2 static infrared satellite images are the basic material. The extremely inhomogeneous spatial distribution of precipitation produced by strong convective clouds will increase the degree of error; The method of microwave material to estimate the quantitatively precipitation is satisfaction duing to high spatial resolution and clearly physical meaning, for users, it would not get a time fine precipitation estimation because of the limitation of getting microwave data. The method of combined the Static satellite data and microwave material to estimate precipitation not only meet high temporal and spatial resolution, but also estimate the quantitative precipitation at achieve timed and fixed point.(2) The accuracy rate of estimation of precipitation using FY-2 static infrared satellite is higher for precipitation rate which below 1mm per hour and no precipitation area, which is about 65-70% for precipitation rate between 10 and 24.9mm per hour. When the precipitation rate reached 25mm per hour, the estimated accuracy rate is very low, about 30%. The method of microwave material inversion precipitation effect get a better results, the estimated accuracy rate can reach 50% for precipitation rate larger than 20mm per hour and 75% for basic accuracy rate. The combination of two methods can not only achieve the accuracy rate of microwave material for precipitation's estimation but also do real-time corrections on the variation of precipitation intensity by Static satellite data.(3) The large estimation error of FY-2 infrared satellite estimated rainfall may be caused by the following factors:â‘ The difference of precipitation is obvious in different locations even within the same pixel and the representation of ground rainfall stations record have itself errors;â‘¡The estimated results are often small for the blooming and disspating cloud cluster, especially for short-time heavy rainfall which are often larger for the initial period of the cloud cluster;â‘¢The temperature at cloud top could not show the water vapor characters of abundant moisture conditions which can caused the stronger precipitation intensity, the estimated results is smaller in this condition; The estimated precipitation intensity is stronger in the poor water vapor condition.