What is the Mars Climate Database ?

Purpose

When planning spacecraft missions to Mars, detailed information about environmental conditions on the planet is vital to reduce the chances of mission failure and to aid in the optimization of the design process. For example, aerobraking or aerocapture maneuvers require detailed knowledge of atmospheric density; when placing landers on the surface of the planet, the wind shear can be a crucial factor; and extremes of temperature in the atmosphere and on the surface must be known to prevent electronic and mechanical failures. Similarly, climatological statistics are also of great value and interest for members of the scientific community who need realistic data to study any subject related to the Martian atmosphere and climate. For example, the database has been used to study cloud microphysics, chemistry, geodesy, meso-scale circulation, spacecraft data interpretation, etc.

Construction

Previous so-called ``engineering models'' (e.g. ``MarsGRAM'') used for mission design were based on compilations of observational statistics with simple interpolation schemes to provide estimates of climate variables at any time and any geographical location. Unfortunately, the available observational data on Mars are sparse and incomplete in both space and time, leading to great uncertainties for locations, times, seasons and years for which no data is available.

A different approach has been used here. The database has been produced from a set of numerical simulation of Mars's climate and atmospheric circulation conducted with a General Circulation Model (GCM). GCMs are widely used for weather forecasting and climate studies for the Earth. The Mars GCMs have been extensively validated using available observational data and we believe that they represent the current best knowledge of the state of the Martian atmosphere given the observations and the physical laws which govern the atmospheric circulation and surface conditions on the planet.

Contents

Table 1: Variables stored in database mean data files.

Mean variable	symbol	units	2-D or 3-D
Atmospheric temperature	t	K	3-D
Zonal (East-West) wind	u	m s$^{-1}$	3-D
Meridional (North-South) wind	v	m s$^{-1}$	3-D
Atmospheric density	rho	kg m$^{-3}$	3-D
Boundary layer eddy kinetic energy	q2	m$^2$ s$^{-2}$	3-D
Surface pressure	ps	Pa	2-D
Surface temperature	tsurf	K	2-D
LW (thermal IR) radiative flux to surface	fluxsurf_lw	W m$^{-2}$	2-D
SW (solar) radiative flux to surface	fluxsurf_sw	W m$^{-2}$	2-D
LW (thermal IR) radiative flux to space	fluxtop_lw	W m$^{-2}$	2-D
SW (solar) radiative flux to space	fluxtop_sw	W m$^{-2}$	2-D
CO$_2$ ice cover	co2ice	kg m$^{-2}$	2-D
Surface emissivity	emis	none	2-D

The MCD contains simulated data (temperature, wind, density, pressure, radiative fluxes, etc. See Table 1) stored on a $5^\circ \times 5^\circ$ longitude-latitude grid¹from the surface up to an approximate altitude of 120km (above 120 km, pressure and density can be estimated using the database access softwares).

The vertical coordinate for the 3D variables is defined as

$$\sigma~=~\frac{p}{p_0}$$ (1)

where $p$ is the atmospheric pressure and $p_0$ is the surface pressure. Thus $\sigma$ is 1 at the surface and 0 at infinity and the $\sigma$ levels follow the model orography. There are 32 sigma levels, with the first four level are at about 5, 20, 50 and 115 m whereas the upper level is around 120 km.

Fields are averaged and stored 12 times a day, for 12 Martian ``seasons'' to give a comprehensive representation of the annual and diurnal cycles. Each season covers 30$^o$ in solar longitude ($L_s$), and are typically 50-70 days long. In other words, at every grid-point, the database contains 12 "typical" days, one for each season. In addition, information on the variability of the data within one season or within one grid-point are also stored in the database. Software tools are provided to reconstruct and synthetized this variability (section 5).