Improving the ocean and atmosphere in a coupled ocean–atmosphere model by assimilating satellite sea‐surface temperature and subsurface profile data

Average difference of sea surface temperature between the model simulation and the observations over months March to December for different simulation scenarios: a) Free_run, b) DA_SST, c) DA_proTS and d) DA_all.

In this work we investigated the effect of assimilating different types of ocean observations into the ocean component of a coupled ocean-atmosphere model on the fields of the ocean and the atmosphere. The Alfred-Wegener-Institute climate model (AWI-CM) was used as the coupled model to simulate the ocean as well as the atmosphere. Satellite sea surface temperature and subsurface temperature and salinity profile data were assimilated. The ocean variables sea surface height, ocean temperature, salinity and velocities were directly updated within this weakly coupled data assimilation system, while the atmosphere only reacted dynamically to the changed ocean state. The data assimilation experiments are evaluated by comparing the predicted sea surface temperature, subsurface temperature and salinity in the ocean component with ocean observation data. Further, the predicted atmosphere temperature and wind field were compared with reanalysis data from ERA-Interim. The ocean temperature and salinity are improved by all the assimilation scenarios in the coupled system. The assimilation leads to a response of the atmosphere throughout the troposphere and impacts the global atmospheric circulation. Globally the temperature and wind speed are improved in the atmosphere on average.

Read more about the research on: Tang, Q., Mu, L., Sidorenko, D., Goessling, H., Semmler, T. and Nerger, L. (2020), Improving the ocean and atmosphere in a coupled oceanatmosphere model by assimilating satellite sea surface temperature and subsurface profile data. Q J R Meteorol Soc. Accepted Author Manuscript. doi:10.1002/qj.3885