Martian Atmospheric Data Assimilation Using an Ensemble Kalman Filter

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Tuesday, 19 January 2010: 2:15 PM
B213 (GWCC)
Matthew J. Hoffman, Rochester Institute of Technology, Rochester, NY; and S. J. Greybush, R. J. Wilson, G. Gyarmati, R. N. Hoffman, K. Ide, E. J. Kostelich, T. Miyoshi, I. Szunyogh, and E. Kalnay

As a first step towards the assimilation of real observations of the Martian atmosphere using an advanced data assimilation method, the local ensemble transform Kalman filter (LETKF) is applied here to the NASA/NOAA Mars general circulation model. In identical twin experiments, simulated observations are used to assess the performance of the LETKF-MGCM system and to determine the dependence of the assimilation on observational data coverage. Observations of temperature are simulated at locations that mirror the distribution of the Thermal Emission Spectrograph (TES) observations from the Mars Global Surveyor (MGS) and LETKF performance is evaluated. In perfect model Observing System Simulation Experiments (OSSEs), the filter converges quickly and reduces substantially the analysis and subsequent forecast errors in both temperature and velocity fields, even in the absence of velocity observations. The error in the state estimate quickly reduces to below the observation error, and both the forecast and subsequent analysis errors remain low for the duration of a 55 day simulation. Large-scale baroclinic waves along the Northern (winter) Hemisphere temperature front and instabilities in the upper atmosphere zonal wind jet are two predominant sources of error in the MGCM-LETKF system. This study forms the first step toward creating the MGCM-LETKF Martian Atmosphere Reanalysis, which will be incorporating real observations obtained from the MGS TES instrument.