Accuracy assessment and analysis for GPT2

GPT(global pressure and temperature) is a global empirical model usually used to provide temperature and pressure for the determination of tropospheric delay, there are some weakness to GPT, these have been improved with a new empirical model named GPT2, which not only improves the accuracy of temperature and pressure, but also provides specific humidity, water vapor pressure, mapping function coefficients and other tropospheric parameters, and no accuracy analysis of GPT2 has been made until now. In this paper high-precision meteorological data from ECWMF and NOAA were used to test and analyze the accuracy of temperature, pressure and water vapor pressure expressed by GPT2, testing results show that the mean Bias of temperature is -0.59℃, average RMS is 3.82℃; absolute value of average Bias of pressure and water vapor pressure are less than 1 mb, GPT2 pressure has average RMS of 7 mb, and water vapor pressure no more than 3 mb, accuracy is different in different latitudes, all of them have obvious seasonality. In conclusion, GPT2 model has high accuracy and stability on global scale. © 2015, Surveying and Mapping Press. All right reserved.