A study on the optimal data assimilation system for the whole neutral atmosphere
Observations in the mesosphere are sparser than those in the troposphere and stratosphere. Moreover, the model predictability is generally not sufficient to simulate behaviors of the mesosphere of the real atmosphere. Thus, global data in the real atmosphere including the mesosphere estimated by the data assimilation system is a key for quantitative evaluation of the momentum budget. However, such assimilation has not yet been well common. The purpose of this study is to develop the assimilation system so as to make global data for a wide height range from the ground to the lower thermosphere. A conventional observation dataset called PREPBUFR (available at https://rda.ucar.edu/datasets/ds337.0/) and satellite temperature retrieval data from Aura Microwave Limb Sounder (MLS; Livesey et al., 2017) were used for the assimilation. We adopted the 4-D Local Ensemble Transform Kalman Filter (4D-LETKF) developed by Miyoshi and Yamane (2006). The data assimilation was made for the time period from 10 January to 20 February 2017, when an international observation campaign called ICSOM (Interhemispheric Coupling Study by Observations and Modeling) was performed. By comparing with the MLS observation and MERRA-2 reanalysis data for the vailable height region, it was confirmed that the obtained analysis data were plausible.
Mr. Dai Koshin The University of Tokyo