Atmospheric weighted mean temperature modeling for Japan

Due to the frequent occurrence of natural disasters, complex changes in water vapor characteristics, and sparse sounding stations in Japan, it restricts the acquisition of high-precision water vapor, and lacks a high-precision Tm model in this area. In view of this article adopts the 2009 to 2016 Global Geodetic Observing System (GGOS) weighted average temperature (T_m) with the ERA-Interim 2 m T_s grid data, a new T_m model (JQTm model) suitable for the Japanese region that takes into account the seasonal variation of the T_m residual and the daily cycle variation is established. In addition, using the data of 13 sounding stations and 110 GGOS Atmosphere T_m grids in Japan in 2017, the accuracy of the newly established JQTm model in this paper is evaluated in Japan. The study found that compared with the GGOS Atmosphere T_m grid data, the bias and root mean square error (RMSE) of the JQTm model are 0.15 K and 1.92 K, respectively. The RMSE is 41.16% (1.33 K) and 44.41% (1.53 K) higher than the GPT2w-1 and GPT2w-5 models, respectively. Compared with the sounding data, the bias and RMSE of the JQTm model are –0.66 K and 2.14 K, respectively. The RMSE is 28.43% (0.85 K) and 29.61% (0.90 K) higher than the Bevis model, GPT2w-1 model, and GPT2w-5 model, respectively. The JQTm model can provide high-precision T_m values for the Japanese region and provide an important basis for studying atmospheric water vapor and extreme weather in this region.