GPS可降水汽与MODIS可降水汽回归性分析

地基GPS可反演大气可降水汽,为气象预报提供高精度的大气水汽数据。然而GPS观测仅可以提供离散点的水汽值,MODIS却可以提供空间连续变化的水汽值,但MODIS水汽反演误差的存在使其不能满足气象预报的精度要求,因此两种遥感水汽的融合研究尤为必要。基于此,该文利用西安2006年7月-2009年7月7期GPS观测数据、地面气象实测数据和对应的MODIS数据,研究了GPS与MODIS两种遥感水汽间的回归关系,在考虑水汽的季节性变化的基础上建立了两者的回归模型,并由此建立了直接对MODIS反演水汽值的校正模型。根据多个经验模型,确定了西安GPS湿延迟与GPS可降水汽的比值:夏季取6.00、冬季取6.52。

Regression Analysis between GPS PWV and MODIS PWV

As one of important space remote sensing technology,GPS can provide high-precision values of atmospheric water vapor.Especially with the widespread establishment of ground-based GPS system,GPS water vapor has became one of main data sources for weather forecasting.But GPS observations can only provide water vapor values on discrete points.However,MODIS can provide continuous change information of water vapor in space.But there are some errors in the inversion of MODIS water vapor,which leads that its accuracy can not meet the requirements of weather forecasting.So it is very important and necessary to study the integration of these two kinds remote-sensing water vapor.For this problem,the regression relationship between MODIS PWV and GPS PWV has been studied with the GPS observation data,ground meteorological data and corresponding MODIS data.Considering the seasonal variations of water vapor,the regression model between MODIS PWV and GPS PWV has been established.The direct correction model of MODIS water vapor has also been established at the same time.So reference values for the integration study of GPS and MODIS water vapor are provided in this paper.Meanwhile,the ratio GPS zenith wet delay to GPS precipitable water vapour has been identified in Xi'an form a number of empirical models,which shall be taken as 6.52 in winter and 6.00 in summer.