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

Matthew J. Hoffman, Steven J. Greybush, R. John Wilson, Gyorgyi Gyarmati, Ross N. Hoffman, Eugenia Kalnay, Kayo Ide, Eric J. Kostelich, Takemasa Miyoshi, Istvan Szunyogh

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Abstract

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.

Original languageEnglish (US)
Pages (from-to)470-481
Number of pages12
JournalIcarus
Volume209
Issue number2
DOIs
StatePublished - Oct 1 2010

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All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Cite this

Hoffman, M. J., Greybush, S. J., John Wilson, R., Gyarmati, G., Hoffman, R. N., Kalnay, E., Ide, K., Kostelich, E. J., Miyoshi, T., & Szunyogh, I. (2010). An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments. Icarus, 209(2), 470-481. https://doi.org/10.1016/j.icarus.2010.03.034