临近空间全球温度场三维变分同化

Preliminary study on 3-dimensional variational assimilation of global temperature field in near space

以TIMED\SABER红外温度探测数据为观测值,WACCM模式预报场为温度背景值,采用三维变分同化方法,获取了20~100 km临近空间范围的全球大气温度场,三维变分同化后,临近空间全球温度场的分布发生了明显的变化,经验证算法可行。利用统计学方法对同化结果进行评估,结果显示,三维变分同化后临近空间全球温度场误差整体减小,三维变分同化前的温度背景场误差最大可达17 K,三维变分同化后的温度分析场最大误差减小至7 K以内,同化效果明显。该算法可用于为临近空间大气环境预报模式提供更精确的初值场。

The near space global atmospheric temperature field from 20-100 km was achieved using 3- dimensional variational （3DVAR） assimilation method, of which the observation data was taken from TIMED／SABER temperature data and the background data was taken from WACCM model. Obvious variations could be seen in the near space global atmospheric temperature field after 3DVAR assimilation. An evaluation analysis based on statistical method was accomplished. The results indicate that the errors of the near space global atmospheric temperature field get a general decrease after 3DVAR assimilation, with the maximum error decreasing from 17 K to 7 K. The application of this 3DVAR assimilation algorithm can provide more accurate initial fields to near space atmospheric environment forecast model.