The water cycle in the general circulation model of the martian atmosphere

Abstract

Within the numerical general-circulation model of the Martian atmosphere MAOAM (Martian Atmosphere: Observation and Modeling), we have developed the water cycle block, which is an essential component of modern general circulation models of the Martian atmosphere. The MAOAM model has a spectral dynamic core and successfully predicts the temperature regime on Mars through the use of physical parameterizations typical of both terrestrial and Martian models. We have achieved stable computation for three Martian years, while maintaining a conservative advection scheme taking into account the water–ice phase transitions, water exchange between the atmosphere and surface, and corrections for the vertical velocities of ice particles due to sedimentation. The studies show a strong dependence of the amount of water that is actively involved in the water cycle on the initial data, model temperatures, and the mechanism of water exchange between the atmosphere and the surface. The general pattern and seasonal asymmetry of the water cycle depends on the size of ice particles, the albedo, and the thermal inertia of the planet’s surface. One of the modeling tasks, which results from a comparison of the model data with those of the TES experiment on board Mars Global Surveyor, is the increase in the total mass of water vapor in the model in the aphelion season and decrease in the mass of water ice clouds at the poles. The surface evaporation scheme, which takes into account the turbulent rise of water vapor, on the one hand, leads to the most complete evaporation of ice from the surface in the summer season in the northern hemisphere and, on the other hand, supersaturates the atmosphere with ice due to the vigorous evaporation, which leads to worse consistency between the amount of the precipitated atmospheric ice and the experimental data. The full evaporation of ice from the surface increases the model sensitivity to the size of the polar cap; therefore, the increase in the latter leads to better results. The use of a more accurate dust scenario changes the model temperatures, which also strongly affects the water cycle.