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Steele, Liam; Lewis, S. R. and Patel, M. R.
(2014).
URL: http://www-mars.lmd.jussieu.fr/oxford2014/abstract...
Abstract
Here we investigate the radiative impact of martian water ice clouds on the atmospheric temperature and circulation via the assimilation of Mars Climate Sounder (MCS) temperature and ice opacity profiles, and dust optical depths, into a Global Climate Model (GCM).
Recent observational and modelling studies have begun to reveal the importance of water ice clouds in terms of modifying the atmospheric temperature structure. Studies of temperature inversions observed by Mars Pathfinder and Mars Global Surveyor [Magalhães et al., 1999; Hinson and Wilson, 2004], surface temperature anomalies in Thermal Emission Spectrometer (TES) retrievals [Wilson et al., 2007], and more recently MCS observations [Kleinböhl et al., 2013] all suggest that clouds have important roles to play, providing local heating and cooling depending on location and time of day. Additionally, assimilation of Thermal Emission Spectrometer temperature profiles by Wilson et al., [2008] revealed the importance of clouds in modifying the temperature structure in the tropics.
Modelling studies using both 1D microphysical models and Global Climate Models (GCMs) have shown that cloud radiative effects can account for the observed temperature inversions [Colaprete and Toon, 2000], and have also demonstrated the role they play in intensifying thermal tides [Hinson and Wilson, 2004; Kleinböhl et al., 2013]. Cloud radiative effects have also been shown to increase temperatures in the tropics, and modify the meridional circulation, producing additional indirect changes to the atmospheric temperature structure [Madeleine et al., 2012]. However, as the radiative impact of clouds is dependent upon the location and time of day in which they form, the results of modelling studies will be affected by any incorrect predictions of cloud locations and opacities.
The assimilation procedure allows the ice opacity observations to be inserted into the model at their correct time and location, and with the correct opacity, producing the best state from which to analyze cloud radiative forcing. The resulting assimilated data set (covering all latitudes, longitudes and times) allows a detailed study of the atmospheric state that is not possible by using observations or models alone. The increased vertical coverage of the MCS temperature retrievals (~85 km) compared to the TES retrievals (~40 km) also allows the radiative effects of clouds to be studied to much higher altitudes than has previously been possible.
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