GNSS-assisted FY-3 satellite atmospheric precipitable water retrieval method
Atmospheric water vapor is one of the important parameters in troposphere and has been widely used for short-term weather warning and long-term climate monitoring.The medium resolution spectral imager(MERSI)carried by FY-3 series satellites can be used for atmospheric water vapor monitoring,however,the atmospheric transmittance parameters are under-estimated and the regression coefficients of water vapor and atmospheric transmittance are selected empirically when retrieving precipitable water vapor(PWV),which cannot meet the requirements of high-precision PWV applications such as short-term and imminent rainfall monitoring and numerical assimilation.Therefore,this paper proposes a high-precision PWV retrieval al-gorithm assisted by the global navigation satellite system(GNSS)for the FY-3 L1 data.This method introduces high-precision GNSS-derived PWV as the regression fitting parameter of the atmospheric transmittance calculation model,and assists the FY-3 L1 data to accurately estimate the model regression coefficients of PWV and atmospheric transmittance.In addition,this method considers the seasonal and elevation impact on PWV retrieval,and retrieves the PWV according to the season and cor-rects the FY-3-L1 PWV bias caused by the underestimation of some atmospheric transmittance parameters using digital eleva-tion model.The L1 data of the FY-3 A satellite(FY-3A)and the data of 260 GNSS stations of the China crustal movement ob-servation network in the Chinese region over the period of 2013 to 2014 were selected for the experiment.Results show that the GNSS-assisted FY-3 series satellite PWV retrieval algorithm proposed in this paper is superior to the traditional method(FY-3A-L2 PWV),and its overall accuracy improvement rate is 74.5％,and a more reliable and robust PWV grid product can be obtained,and it is of great significance for short-term and imminent rainfall monitoring and numerical assimilation.
万方数据
维普
