Abstract:
Objectives Atmospheric weighted mean temperature (Tm) is a key parameter of global navigation satellite system (GNSS) to retrieve precipitable water vapor (PWV). Currently, the Tm information provided by the existing Tm model is hard to capture its diurnal cycle variation, thus its application in high time resolution GNSS PWV estimation is limited. Atmospheric reanalysis data can provide Tm grid products with high spatial and temporal resolution, but they need to be spatially adjusted when used, and the variation of Tm in elevation is much greater than that in horizontal direction.
Methods Moreover, for the highly undulating terrain in China, a spatial interpolation method which considering the vertical lapse rate is proposed for Tm grid products in China. The proposed method is verified with the global geodetic observing system (GGOS) atmosphere Tm grid product and the MERRA‑2 Tm grid product provided by national aeronautics and space administration using the data of 89 radiosonde stations distributed in China as reference values.
Results The results show that: (1) In spatial interpolation of Tm grid products considering vertical lapse rate, the performance of inverse distance weighted method is better than that of bilinear interpolation method, and the biases of the Tm grid products of GGOS atmospheric center and MERRA‑2 in China are 0.72 K and 0.23 K, respectively, and the root mean square errors are 1.94 K and 1.87 K, respectively. (2) The performance of spatial interpolation which considering the vertical lapse rate is significantly better than that without vertical lapse rate, especially in western China where the terrain is undulating.
Conclusions Therefore, the spatial interpolation method which considering the vertical lapse rate has important applications in high-precision and high-resolution GNSS water vapor remote sensing for China.
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