Assessing atmospheric predictability on Mars using numerical weather prediction and data assimilation

Rogberg, P.; Read, P. L.; Lewis, S. R. and Montabone, L. (2010). Assessing atmospheric predictability on Mars using numerical weather prediction and data assimilation. Quarterly Journal of the Royal Meteorological Society, 136(651) pp. 1614–1635.




The intrinsic and practical predictability of the Martian atmosphere is determined by use of a comprehensive numerical circulation model and ensemble forecasting techniques. Initial conditions were derived for various seasons of the Martian climate from newly available assimilations of global observations of temperature and dust optical depth in the Martian atmosphere, obtained by the Thermal Emission Spectrometer (TES) instrument on the Mars Global Surveyor orbiter. A range of initial value forecasts were obtained and the growth rate of forecast errors measured against the assimilated reanalysis were determined as a function of season during the period from the late martian year 24 to early 27 (from May 1999 to August 2004). %Error growth rates during two Mars years were calculated from an ensemble. The intra-ensemble growth rates confirm earlier stand-alone model results, indicating that internal baroclinic transients lead to significant chaotic growth of model `error' on time scales of 3-10 sols only during northern hemisphere autumn and winter seasons. At other seasons, ensembles retain coherence at least over several 10s of sols. Imperfections in dust distribution and coupling with other aerosols can lead to large errors in the dust field when it evolves rapidly. Owing to the very short time scale on Mars, these errors can lead to rapid divergence of the entire ensemble from the observed atmospheric state. These results demonstrates the importance of even relatively small errors in the aerosol fields and so in the computed radiative balance of the Martian atmosphere for deterministic forecasts throughout the Martian year, including times at which baroclinic transients are inactive.

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