Ensembles, Predictability, Assimilation and Reanalysis on Mars

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Wednesday, 7 January 2015
Steven J. Greybush, Penn State Univ., University Park, PA; and R. N. Hoffman, R. J. Wilson, Y. Zhao, M. J. Hoffman, K. Ide, T. Miyoshi, and E. Kalnay

Eugenia Kalnay's career has expanded outward to three planets: Venus, Earth, and Mars. This presentation describes the contributions of Eugenia Kalnay and her collaborators at University of Maryland, Penn State, AER, GFDL, and NASA to the science of Mars weather and climate. Spacecraft observations of temperature and aerosol are assimilated into a Mars Global Climate Model (MGCM) using the Local Ensemble Transform Kalman Filter (LETKF). Several unique aspects of the Martian circulation and observing system required innovations in data assimilation techniques. The resulting product is a multi-year reanalysis of temperatures, winds, surface pressure, and aerosol, enabling the chronicling of traveling weather systems, thermal tides, and dust storms and their interannual variability. The application of bred vectors and a kinetic energy equation reveal the dynamical origins of atmospheric instabilities, and the predictability of Mars weather forecasts are assessed.