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.
Advances in Geosciences