Advances in Ensemble-Based Data Assimilation for Planetary Atmospheres Applications

Ensemble-based data assimilation techniques have been expanded beyond terrestrial applications, to the atmospheres of Mars and even Venus. Learning from commonalities, differences, and challenges in this frontier area can provide insights to Earth-based applications and technique development; these topics were recently discussed at the first workshops focused on planetary atmospheres data assimilation. This presentation will explore these issues, with a particular focus on building a successful data assimilation system for Mars. The Ensemble Mars Atmosphere Reanalysis System (EMARS) dataset spans over a decade, reconstructing the state of the Martian atmosphere at hourly resolution by assimilating spacecraft observations into a Mars Global Climate Model (MGCM) using the Local Ensemble Transform Kalman Filter (LETKF). Particular challenges for Mars include observational limitations, model error, the importance of both chaotic and forced error growth on a fast radiative timescale, physical phenomena resonating on the time scale of assimilation intervals, consideration of a coupled atmosphere – aerosol system, and dynamical correlations on a global scale. These challenges encourage innovation in assimilation system applications, enabling Martian reanalyses to be able to study diverse phenomena including transient eddies, thermal tides, the polar vortex and transport, and dust storms.