Mar 6, 2012 - [3] The Martian water cycle is one of the main cycles which is strongly correlated with the thermal structure of the atmosphere on Mars.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, VOL. 4, M03001. doi:10.1029/2011MS000069, 2012
Modeling the hydrological cycle on Mars G. Machtoub Received 13 March 2011; revised 15 December 2011; accepted 13 January 2012; published 6 March 2012.
The study provides a detailed analysis of the hydrological cycle on Mars simulated with a newly developed microphysical model, incorporated in a spectral Mars General Circulation Model. The modeled hydrological cycle is compared well with simulations of other global climate models. The simulated seasonal migration of water vapor, circulation instability, and the high degree of temporal variability of localized water vapor outbursts are shown closely consistent with recent observations. The microphysical parameterization provides a significant improvement in the modeling of ice clouds evolved over the tropics and major ancient volcanoes on Mars. The most significant difference between the simulations presented here and other GCM results is the level at which the water ice clouds are found. The model findings also support interpretation of observed thermal anomalies in the Martian tropics during northern spring and summer seasons.
[1]
Citation: Machtoub, G. (2012), Modeling the hydrological cycle on Mars, J. Adv. Model. Earth Syst., 4, M03001, doi:10.1029/2011MS000069
1. Introduction [2] Mars is the fourth planet from the Sun and is home to the highest ice clouds ever found above the surface of a planet [Mateshvili et al., 2007]. Its climate has some similarities with that of Earth, such as the observable weather patterns, and seasonal ice caps. From a terrestrial perspective, studies of the hydrological water cycle is important as it reflects the surface weathering and climate. The thermal structure and pressure that shape the atmosphere of Mars are similar to those found in the Earth’s stratosphere. Atmospheric dynamics of the two planets is controlled by many of the same physical processes, yet there are some differences in describing their circulations. Mars rotates at approximately the same rate as Earth, and its orbit around the Sun takes 669 sols (about two Earth years). The eccentricity of Mars’ orbit is higher than that of Earth, resulting in a significant difference between the maximum solar insolation on the northern and southern hemisphere [Barlow, 2008]. [3] The Martian water cycle is one of the main cycles which is strongly correlated with the thermal structure of the atmosphere on Mars. The northern polar region is considered to be the primary water reservoir and the most suitable place to observe the daily variability and outbursts of the water vapor in the Martian atmosphere [Smith, 2002, 2004; Smith et al., 2003; Pankine et al., 2009]. A few studies have focused on the evolution of Max Planck Institute for Solar System Research, KatlenburgLindau, Germany. Copyright 2012 by the American Geophysical Union 1942-2466/12/2011MS000069
tropical water ice clouds and analysis of the temporal variability of localized concentrations of water vapor near the residual polar caps. Several global climate models provided some interpretations but still need improvements to resolve considerable discrepancies with the recent atmospheric observations on Mars [McCleese et al., 2010; Benson et al., 2010; Kleinbo¨hl et al., 2009]. It is not clear yet which mechanisms other than the regolith govern the localized temporal variations of water vapor in the Martian atmosphere during the sublimation seasons of the polar caps. One discrepancy between models and observations is an underestimate of the altitude at which the tropical water ice clouds formed. The published climate models predicted the ice cloud belt as lower and thicker than shown in the observations by the Mars Climate Sounder (MCS) on Mars Reconnaissance Orbiter [Heavens et al., 2010]. The uncertainty in the estimation of the water vapor condensation level may also affect the intensity of the meridional circulation as both wind velocity and direction change with altitude. [4] In this work, we conduct a detailed study of the water cycle with a new version of the MAOAM General Circulation Model (MGCM) [Hartogh et al., 2005] based on a spectral solver that makes the model more efficient to accurately compute derivatives and solve the wave dynamics with conserved energy and angular momentum at a minimum computational cost [Simmons and Burridge, 1981; Becker and Schmitz, 2003]. For the purpose of the present study, the model is coupled to a microphysical cloud scheme to well reproduce the hydrologic cycle. The model employs an advective transport of two dynamical tracers: water vapor and ice, and implements a microphysical parameterizations based on size variation of ice crystals. The
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model findings are compared with simulations of other climate models and recent observations. The model description is outlined in Section 2, simulations of water vapor transport and circulations are presented in Section 3, and analysis of the predicted water ice clouds is presented in Section 4.
2. Model Description [5] The new spectral version of the MAOAM-GCM is a redesigned version of the KMCM [Becker and von Savigny, 2010]. The model is adapted to the circulation of the Martian atmosphere using the physics parameterizations which is reported in the earlier grid version of the MGCM [Hartogh et al., 2005; Medvedev and Hartogh, 2007]. Table 1 provides the parametrizations used in the circulation model for Mars compared to those of Earth [Barlow, 2008; Read and Lewis, 2005]. The model includes a non-LTE radiation scheme for CO2 heating and cooling. The model has the necessary parameterizations associated with the realistic Martian topography based on MOLA data, such as albedo and thermal inertia distributions at the surface, CO2 condensation/sublimation processes, and accounts for radiative heating and cooling by the CO2 gas and atmospheric dust in visible and infrared wavelengths [Smith, 2002]. Atmospheric dust distributions are consistent with the dust opacity distributions according to the MGS-TES and Viking observations [Smith, 2004]. The radiative fluxes are calculated using the 2-stream method to account for scattering, absorption, and emission by the atmospheric dust [Kuroda et al., 2007]. The radiative fluxes are constrained by the dust parameters and the particle size distribution [Toon et al., 1977; Tomasko et al., 1999; Forget et al., 1999]. The dust has a vertical profile in equilibrium with sedimentation and mixing process [Conrath, 1981; Kuroda et al., 2007]. The mean radius of dust nuclei rd0 is about 0.8 mm at saturation latitude. The model simulations are performed at T21 spectral resolution (64X32 grid points in longitude and latitude) on 50 vertical levels, covering the lower atmosphere from the ground to about 120 km). Table 1.
The Model Parameterization for Mars and Earth
Parameters
Unit
Distance from sun AU Equatorial radius 103m Mean orbital radius 1011 m Rotation rate 1025 s21 Year length Earth days Year length sol Solar day, sol(s) Planetary obliquity Orbital eccentricity Equilibrium temperature K Surface temperature K Surface gravity m s22 Mean surface pressure Pa Gas constant M2 s22 K21 Mean solar constant W m22 Scale height km Bond albedo
Mars
Earth
1.38–1.67 3.396 2.28 7.888 686.98 668.6 88775 25.19 0.093 210 140–300 3.72 600 192 589 10.3 0.25
0.98–1.02 6.378 1.50 7.294 365.24 365.24 86400 23.93 0.017 256 230–315 9.81 101300 287 1367 7.5 0.306
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The vertical grid is given by hybrid coordinates, which reduce to terrain-following s-coordinates in the lower atmosphere, and to pressure levels at the upper layers. [6] The model incorporates the Martian water cycle using our newly developed microphysical cloud scheme. During each time step, connection with the cloud scheme is established. The scheme defines the water source [Montmessin et al., 2004] and has parameterizations related to a combination of microphysical processes such as ice cloud formation, surface ice deposition, sublimation, sedimentation, and atmospheric transport. The spatially varying distribution of water is used in describing these processes [Pruppacher and Klett, 1998]. [7] The ice formation is based on heterogeneous nucleation followed by a diffusional growth through the condensation process [Gadsden and Schroeder, 1989; Hunten et al., 1980; Rossow, 1978; Pruppacher, 1995]. The phase transformation of a vapor into solid phase is controlled by the saturation ratio S defined in terms of the actual pressure of water vapor Pv and the saturation pressure Psat: SðrÞ~Pv =Psat ðrÞ:
ð1Þ
[8] According to Kelvin effect, the saturation vapor pressure Psat is influenced by changes in the atmospheric temperature T and the radius r of a spherical ice particle [Pruppacher and Klett, 1998]: 2ms Psat ~P? exp , ð2Þ kb Trr [9] where P‘ is the saturation pressure of water vapor over a plane ice surface, m is the mass of a water molecule, r is the ice density, and kb is the Boltzmann constant. The P‘ is defined according to Kirchhoff formula [Gadsden and Schroeder, 1989] as loge P? ~28:548{
6077:4 : T
ð3Þ
[10] The s denotes the surface tension which is a function of the mean particle size and temperature [Tolman, 1949; Turko and Lo, 1982; Hale and Plummer, 1974] as follows: s~
0:141{1:5 10{4 T , 1z2g=r
ð4Þ
[11] where g is an empirical factor (1.5.10210 m). Whenever an air is supersaturated (S.1), the condensation on dust nuclei continues as long as the atmospheric temperature is low enough and sufficient water vapor is available. As the atmospheric condition approaches the S51 level, the ice particle grows to its maximum size and then starts to sublimate as it falls below that level. [12] The mean size distribution of the formed water ice clouds varies with the amount of available dust nuclei, the dust mean radius, and the atmospheric mass of water ice [Rossow, 1978; Pruppacher and Klett, 1998]. 2 of 13
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The diffusional growth which describes the rate of change of a mass M of water vapor with the vapor flux may be written as dM ~4prD ðr{rsat ðT ÞÞ, dt
ð5Þ
[13] where D1 is the corrected molecular diffusivity. An alternative expression in terms of vapor pressure and temperature can be obtained using the equation of state where r~P=
