Evaluation of Winter Near-surface 2 m Temperature around the Hengduan Mountains in Southwest China Simulated by ECMWF

Abstract

Based on the hourly product of CLDAS （CMA Land Data Assimilation System） in 2021， this study is to evaluate the prediction capacity of the global high-resolution deterministic numerical prediction product ECMWF （European Center for Medium Weather Forecasting） for winter mean near-surface 2 m temperature of complex terrain region around the Hengduan mountains in southwest China by starting from winter average temperature， daily variation， and diurnal temperature range.And this study compares the temperature deviation characteristics of near-surface 2 m temperature in different topographic regions by distinguishing between high terrain region （the Western Sichuan Plateau） and low terrain region （the southern Sichuan Basin）.The results show that： （1） The ECMWF model can reasonably predict the spatial distribution characteristics of the winter mean near-surface 2 m temperature around the Hengduan mountains in southwest China， but the deviation distribution is related to the terrain height.With the increase of the terrain height， the prediction deviation tends to increase.（2） The ECMWF model well reproduces the daily variation characteristics of winter mean near-surface 2 m temperature around the Hengduan mountains in southwest China， with the peak time appearing at 14:00 （Beijing Time）.The prediction deviation of temperature at various times varies at different terrain heights.The maximum negative deviation of the western Sichuan Plateau and the Hengduan mountain regions occurs in the afternoon， while the maximum negative deviation of the south Sichuan Basin occurs in the morning.At the same time， the prediction deviation at each moment in high terrain areas is greater than the prediction deviation at each moment in low terrain areas.（3） The ECMWF model can reasonably predict for the spatial distribution of winter mean near-surface 2 m temperature over different terrain at various times during the day， but the deviations have diurnal variation characteristics.Especially in the high terrain region of the Hengduan mountain regions， there are different characteristics of cold and warm deviations at various times.（4） The area with large forecast bias of diurnal temperature range is generally the area with frequent Quasi-stationary front activities in Kunming.For the days （A total of 90 days， from December 1， 2021 to February 28， 2022） with large diurnal temperature range， the prediction deviation of winter mean near-surface 2 m temperature in this area is greater than the days with small diurnal temperature range.What’s more， the prediction deviation of diurnal temperature range is relatively unstable in the area with large forecast bias of diurnal temperature range.

Keywords

• model prediction bias
• around the hengduan mountain regions
• near-surface 2 m temperature
• daily variation
• diurnal temperature range