基于CMA-TRAMS模式地形高度偏差的地面气温误差订正方法研究OA北大核心CSTPCD

Based on the regression relationship between the terrain height deviation of CMA-TRAMS(China Meteorological Administration-Tropical Region Atmospheric Modeling for South China Sea)and the surface temperature error,a unitary linear regression method is utilized to evaluate three correction methods in this study,including non-grading,height deviation grading and temperature error grading,respectively,and the correction effect was evaluated.It is demonstrated that a negative linear correlation can be found between the surface temperature prediction error and the terrain height deviation,the absolute error of surface temperature forecast increases with the increase of the absolute value of terrain height deviation(especially obvious for sites with lower terrain height).but the error characteristics of surface temperature at different times are different,the stations with higher terrain height and the terrain height deviation is less than 50 m in the model usually have lower surface temperature forecast at 06:00,and vice versa.However,the prediction of surface temperature at 18:00 is generally higher,regardless of the terrain height deviation.The temperature error grading correction method of the three correction methods has the best performance in effectively reducing the error of surface temperature forecast,the accuracy rate of the temperature prediction of analysis field is 96%—99%,and 12-48 h forecast field is generally improved to above 90%.The temperature error grading correction method has the characteristics of stable regression relationship,obvious effect,wide applicability and easy operation.