Analysis of the global T_m–T_s correlation and establishment of the latitude-related linear model

In this study,the correlation between Tm,a key variable in GNSS water vapor inversion,and surface temperature(Ts)was calculated on a global scale based on the global geodetic observing system(GGOS)atmosphere Tmdata and European centre for medium-range weather forecasts(ECMWF)surface temperature data.The results show that their correlation is mainly affected by latitudes,and the correlation is stronger at high latitudes and weaker at low latitudes.Although the correlation is relatively weak in the tropic areas,the temperature changes so little in a year in these areas that we can still achieve good Tmresults by linear regression model.Based on these facts,‘‘GGOS atmosphere’’Tmdata and ECMWF Tsdata from 2005 to2011 were used to establish the global latitude-related linear regression model.The new model has root mean square error(RMSE)of 3.2,3.3,and 4.4 K,respectively,compared with respect to the‘‘GGOS atmosphere’’data,COSMIC data,and radiosonde data and is more accurate than the Bevis Tm–Tsrelationship.

Analysis of the global T m–T s correlation and establishment of the latitude-related linear model

In this study, the correlation between T _m, a key variable in GNSS water vapor inversion, and surface temperature (T _s) was calculated on a global scale based on the global geodetic observing system (GGOS) atmosphere T _m data and European centre for medium-range weather forecasts (ECMWF) surface temperature data. The results show that their correlation is mainly affected by latitudes, and the correlation is stronger at high latitudes and weaker at low latitudes. Although the correlation is relatively weak in the tropic areas, the temperature changes so little in a year in these areas that we can still achieve good T _m results by linear regression model. Based on these facts, “GGOS atmosphere” T _m data and ECMWF T _s data from 2005 to 2011 were used to establish the global latitude-related linear regression model. The new model has root mean square error (RMSE) of 3.2, 3.3, and 4.4 K, respectively, compared with respect to the “GGOS atmosphere” data, COSMIC data, and radiosonde data and is more accurate than the Bevis T _m–T _s relationship.