Atmospheric Weighted Mean Temperature Modeling for Australia

  Objectives  Atmospheric weighted average temperature T_m is essential for calculating water vapour conversion factor and atmospheric precipitation.

  Methods  Based on the global geodetic observing system(GGOS) Atmosphere T_m grid data and European centre for medium-range weather forecasts (ECMWF) 2 m temperature data from 2007 to 2017, a T_m model (qTm) suitable for Australia was established and the seasonal and daily variation of T_m residuals was taken into account. In addition, GGOS Atmosphere T_m grid data and radiosonde data in 2018 were selected to evaluate the model.

  Results  The results reveal that the qTm model is more accurate and applicable in the Australian region. Compared with GGOS Atmosphere T_m, the annual average Bias and RMSE(root mean square error) of the qTm model are －0.31 K and 1.97 K, respectively. While compared to the GPT2w(global pressure and temperature 2 wet)-1 and GPT2w-5, RMSE of qTm model increased by 21.8% and 25.9%, respectively. qTm model values are more consistent with sounding integral values, and the model's annual average Bias and RMSE are －0.44 K and 2.45 K, respectively. Compared with GPT2w-1 and GPT2w-5, they increased by 10.2% and 11.8%, respectively.

  Conclusions  The qTm model can provide accurate T_m values for the Australian region and is a basis for the region's atmospheric moisture analysis and El Niño studies.