Abstract
Atmospheric local-to-regional dispersion models are widely used on Earth to predict and study the effects of chemical species emitted into the atmosphere and to contextualize sparse data acquired at particular locations and/or times. However, to date, no local-to-regional dispersion models for Mars have been developed; only mesoscale/microscale meteorological models have some dispersion and chemical capabilities, but they do not offer the versatility of a dedicated atmospheric dispersion model when studying the dispersion of chemical species in the atmosphere, as it is performed on Earth. Here, a new three-dimensional local-to-regional-scale Eulerian atmospheric dispersion model for Mars (DISVERMAR) that can simulate emissions to the Martian atmosphere from particular locations or regions including chemical loss and predefined deposition rates, is presented. The model can deal with topography and non-uniform grids. As a case study, the model is applied to the simulation of methane spikes as detected by NASA’s Mars Science Laboratory (MSL); this choice is made given the strong interest in and controversy regarding the detection and variability of this chemical species on Mars.
Highlights
Chemical species emitted into the atmosphere can travel hundreds or even thousands of kilometers from their source location
2 Methods The developed three-dimensional numerical model solves the advection–diffusion equation in an Eulerian framework, which is suitable for the local-to-regional scale in which DISVERMAR will operate, including planetary boundary layer (PBL) studies and chemistry (Leelossy et al 2014 and references therein):
3.1 Validation of the numerical model DISVERMAR has been verified against scenarios with analytical solution
Summary
Chemical species emitted into the atmosphere can travel hundreds or even thousands of kilometers from their source location Their distributions can have a strong impact on the availability of species in the context of atmospheric chemistry. General circulation models (GCMs) on Mars, which typically have resolutions of the order of 1o of latitude and longitude (e.g., Richardson et al 2007), usually include routines for computing the distribution of passive tracers. In some cases, such models have been extended to deal with chemistry (e.g., Lefèvre and Forget 2009); these models have proven to be an essential tool for studying the Martian atmosphere, the atmospheric dynamics and chemistry, dust, and water cycles on Mars. Mesoscale/microscale models, or GCMs with zoom capabilities, have successfully operated in this scale for weather forecasting on Earth
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