综合GPS和NCEP CFSv2的区域PWV估计方法

Regional PWV Estimation Using GPS and NCEP CFSv2

利用地基GPS估计PWV(precipitable water vapor)时,除GPS观测数据外,GPS测站地表的气温和气压也是必要参数。针对我国多数GPS网并未配备相应的气象传感器的情况,利用美国环境预报中心气候预报系统第2版提供的逐6h产品,并顾及测站高程转换时的平均海平面高改正,提出一种GPS测站气象参数的插值新方法。以香港卫星定位参考站网实测GPS数据进行试验研究,结果表明,平均海平面高对地表气压的插值结果影响较大,而对地表气温的插值结果影响较小;经平均海平面高改正后,地表气压插值结果的平均均方根误差(RMSE)为1.61hPa,地表气温插值结果的平均RMSE为1.93 K;由插值气象参数估计的PWV的平均RMSE为2.76mm,验证了所提方法的有效性。

Site-specific surface meteorological data are essential to derive the precipitable water vapor （PWV） using ground-based GPS. However, many GPS networks lack co-located sensors which can be used to obtain these meteorological variables. This paper proposes a method, which involves the inter- polation of surface pressure and temperature fields obtained from the National Centers for Environ- mental Prediction （NCEP） Climate Forecast System Version 2 （CFSv2） 6-hourly products to derive these site-specific meteorological data. In addition, the significance of ellipsoid-MSL height bias cor- rection on the meteorological data was tested by considering mean sea surface height （MSSH） in our estimation. Based on Hong Kong Satellite Positioning Reference Station Network （SatRef）, the method is tested and the results indicate that, the MSSH has a significant influence on the interpolated surface pressure, while less influence on the interpolated surface temperature. The average RMSE of the interpolated surface pressure and temperature are 1.61hPa and 1.93K after the MSSH correction, respectively. The estimated PWV yields an RMSE of 2.76mm, demonstrating the effectiveness of the proposed method.