An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments

摘要

The local ensemble transform Kalman filter (LETKF) is applied to the GFDL Mars general circulation model (MGCM) to demonstrate the potential benefit of an advanced data assimilation method. In perfect model (aka 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. Temperature retrievals are simulated at locations that mirror the spatial distribution of the Thermal Emission Spectrometer (TES) retrievals from the Mars Global Surveyor (MGS). The LETKF converges quickly and substantially reduces the analysis and subsequent forecast errors in both temperature and velocity fields, even though only temperature observations are assimilated. The LETKF is also found to accurately estimate the magnitude of forecast uncertainties, notably those associated with the phase and amplitude of baroclinic waves along the boundary of the polar ice cap during Northern Hemisphere winter.