Ensemble Kalman Filter Data Assimilation for the Martian Atmosphere

Details Ensemble Kalman Filter Data Assimilation for the Martian Atmosphere Ensemble Kalman Filter Data Assimilation for the Martian Atmosphere

Sep 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009dps....41.4408h&link_type=abstract

American Astronomical Society, DPS meeting #41, #44.08

Astronomy and Astrophysics

Astronomy

Scientific paper

A data assimilation system provides a means of optimally combining information from sparse observations and an atmospheric model to provide an accurate depiction of the state of a planetary atmosphere. Here a Mars General Circulation Model (MGCM) is coupled with the local ensemble transform Kalman filter (LETKF) as the basis of an advanced data assimilation system for Mars. Identical twin experiments, in which observations are generated synthetically from a nature run of the MGCM to approximate the spatial distribution of PDS TES profiles, explore the potential of ensemble data assimilation for the Martian atmosphere.
The experiments find that the LETKF is able to correct errors in the Martian atmospheric model and improve the state estimates of the temperature and wind fields, even in the absence of wind 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 60 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.

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