Physics – Geophysics
Scientific paper
Dec 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011agufm.p24a..01g&link_type=abstract
American Geophysical Union, Fall Meeting 2011, abstract #P24A-01
Physics
Geophysics
[4420] Nonlinear Geophysics / Chaos, [5405] Planetary Sciences: Solid Surface Planets / Atmospheres, [5445] Planetary Sciences: Solid Surface Planets / Meteorology
Scientific paper
The seasonal dependence of the predictability of the Martian atmosphere is examined using a Numerical Weather Prediction system, spacecraft observations, and the bred vector technique. Mars atmosphere analyses, created by assimilating Thermal Emission Spectrometer (TES) and Mars Climate Sounder (MCS) temperature profiles, provide the initial conditions for forecasts generated by the GFDL Mars Global Circulation Model (MGCM). Comparing longer term (1-10 sol) forecasts with observations and the latest analyses from data assimilation reveal the duration of time where Martian numerical weather prediction forecasts initialized with observations provide superior guidance than freely running model simulations; initial results in the northern hemisphere autumn indicate a predictability horizon of more than 5 sols (Greybush, 2011). In this study we examine the seasonal variation in predictability at several different times of year, which exhibit significant differences in circulation patterns, dust opacities, and the strength and location of traveling waves. The impacts of using a fixed dust distribution versus a seasonally varying dust distribution based on Thermal Emission Spectrometer (TES) observations, as well as the role of empirical bias correction, are assessed. The bred vector technique explores the locations, seasonality, and physical origins of dynamical instabilities that result in the growth of forecast errors. The application of a kinetic energy equation illuminates the role of barotropic and baroclinic processes.
Greybush Steven J.
Hoffman Matthew J.
Hoffman Ross N.
Ide Kayo
Kalnay Eugenia
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