Spatial Interpolation of Atmospheric Weighted Mean Temperature Grid Products in China with Consideration of Vertical Lapse Rate

  Objectives  Atmospheric weighted mean temperature (T_m) is a key parameter of global navigation satellite system (GNSS) to retrieve precipitable water vapor (PWV). Currently, the T_m information provided by the existing T_m 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 T_m grid products with high spatial and temporal resolution, but they need to be spatially adjusted when used, and the variation of T_m 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 T_m grid products in China. The proposed method is verified with the global geodetic observing system (GGOS) atmosphere T_m grid product and the MERRA‑2 T_m 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 T_m 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 T_m 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.