LAUSR

针对平流层大气观测资料稀少的问题，提出利用同化卫星臭氧观测改进全球数值天气预报效果的方法。将复杂的臭氧资料同化问题转换为一个以大气运动控制方程为约束条件的大规模最优化问题，并实现了SCIAMACHY卫星臭氧观测的全球四维变分资料同化。试验结果表明:由于卫星臭氧观测资料同化的引入，一定程度上提高了地面报和探空报的同化利用率，总气柱臭氧含量预报场的分布具有明显变化，对南北半球形势场预报技巧评分具有一定幅度的提高。 In order to solve the problems of being short of stratospheric atmospheric observations, a method of improving the global numerical weather prediction (NWP) qualities is proposed by assimilating satellite ozone data. The complex problem of ozone data assimilation is transformed into a large-scale optimization problem constrained by the governing equations of atmospheric motion, and the global four-dimensional variational data assimilation of ozone from SCIAMACHY remote sensor is implemented to produce initial fields for global NWP model. The numerical experimental results show that the utilization rates of surface and sounding observations have been upgraded to a certain extent due to the introduction of satellite ozone data assimilation, and the distribution of the ozone prediction field changes obviously. Furthermore, the forecast skills in the northern and southern hemispheres are improved a lot by carrying out the statistical verification.