Oral presentations and abstracts

     In addition to H₂O, other volatile species, such as CO₂, NH₃, H₂S, SO₂, and CH₄ are regularly supplied to the Moon through cometary impacts or are created through solar wind interactions. These species have been observed in varying abundances by the Lunar CRater Observation and Sensing Satellite (LCROSS) experiment within Cabeus crater near the south pole [4]. Once delivered or produced, these molecules may migrate about the lunar surface through a series of ballistic hops and potentially accumulate within cold traps near the poles if temperatures are sufficiently low. Relative to H₂O, however, these volatiles have higher vapor pressures and thus require lower temperatures for long-term thermodynamic stability; thus, not all volatiles detected in the LCROSS plume are expected to be cold trapped in the current lunar thermal environment. CH₄, for example, which has been detected in the lunar exosphere [5], is stable at temperatures below ~25 K [6], which is too low to be cold trapped, although it can be adsorbed on the surface. Other volatiles, in contrast, such as CO₂, are stable at relatively higher temperatures (T_max < 55 K) and potentially accumulate within the coldest regions of permanent shadow. Observational evidence for CO₂ frost has recently been provided by the Lyman Alpha Mapping Project (LAMP) instrument on the Lunar Reconnaissance Orbiter (LRO) [6]. Although Diviner temperature data do not indicate significantly large regions where CO₂ is stable, micro cold traps (at cm scales) will provide additional cold trapping area.

     Modelling the diurnal and seasonal migration patterns of different exospheric volatiles can shed light on geotemporal trends in volatile dispersion and cold trapping [7, 8, 9, 10], and may additionally aid in the interpretation of orbital remote sensing data. In this work, we use a Monte Carlo model to simulate the ballistic migration of the aforementioned cometary volatiles to understand differences in their migration, destruction and cold trap capture. The model utilized here is similar to that described in Kloos et al. [11]. Individual molecules of a given volatile are placed on the surface at non-polar latitudes (equatorward of ±80°) using a randomized production scheme. The molecule is assumed to achieve instantaneous thermal equilibrium with the lunar regolith and acquire the local surface temperature. For surface locations equatorward of ±80°, temperatures are obtained using g­­­­lobal, topographically resolved Diviner temperature maps [12]. Due to the slight obliquity of the Moon (< 1.59°), however, the polar temperatures can vary significantly throughout the year. Thus, we have updated the model to include the recently available seasonal Diviner polar temperature data created by Williams et al. [13]. These maps enable more realistic simulations of the ballistic polar migration than that reported by Kloos et al. [11].

     To calculate the adsorption residence time, τ, for a molecule, we use the relationship defined by Langmuir [14]:

τ = (1/ν₀)exp(E_a/k_BT_surf),                         (1)

where ν₀ is the vibrational frequency, E_a is the activation energy and T_surf is the surface temperature. The variables ν₀  and E_a are obtained for each volatile using data from Sandford and Allamandola [15]. Once molecules are released, they inherit a velocity vector using three-dimensional cartesian coordinates, where the vector direction is randomized and the speed is drawn from an Armand distribution. Molecules ejected outward from the surface may be photodissociated through interaction with solar UV photons. Photo-destruction rates for each species are determined using data compiled by Huebner et al., [16], derived for normal sun activity. The effects of surface roughness, which may delay the pole-ward migration of molecules by increasing the number of hops at a given location, are incorporated into the model and we quantify these effects on the velocity distribution for different volatile species.

     Figure 1 shows the north and south geographic delivery patterns for H₂O, where the y-axis gives the PSR particle concentration σ_p normalized by the production rate γ. It is found that the north/south asymmetry in PSR capture reported by Kloos et al., [11] persists using the updated Diviner polar temperature data. The bulk majority (~82%) of H₂O molecules are destroyed through photolysis, while the remaining are cold trapped in PSRs (<< 1% achieve escape velocity).  Results for other volatile species will be available by the commencement of the conference.

Figure 1. Geographic trends in PSR-capture of H₂O molecules.

References

[1] Urey, 1952, Yale University Press. [2] Lawrence, 2017 JGR-Planets. [3] Paige et al., 2010, Science. [4] Colaprete et al., 2010, Science. [5] Hodges, 2016, GRL. [6] Hayne et al., 2019, LPSC Abstract (Contrib. No. 2132). [7] Butler, 1997, JGR. [8] Schorghofer, 2014, GRL 41, 4888. [9] Moores, 2016, JGR-Planets 121, 46. [10] Prem et al., 2018, Icarus 299, 31. [11] Kloos et al., 2019, JGR-Planets 124, 1935. [12] Williams et al., 2017, Icarus. [13] Williams et al., 2019, JGR-Planets 124. 2505 [14] Langmuir, 1916, Physical Review. [15] Sandford & Allamandola, 1993, Icarus 106. 478 [16] Huebner et al., 1992, Astrophysics and Space Science.

How to cite: Kloos, J., Moores, J., and Schorghofer, N.: Monte Carlo simulations of the expospheric transport of cometary volatiles on the Moon, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-388, https://doi.org/10.5194/epsc2020-388, 2020.

Habitable conditions on Earth developed in a tight connection to the evolution of terrestrial atmosphere which was strongly influenced by atmospheric escape. In this study, we investigated the evolution of the polar ion outflow from the Earth’s open field line bundle starting from mid-Archean (three gigayears ago) and to present. We performed Direct Simulation Monte Carlo (DSMC) simulations and estimated upper limits on escape rates from the Earth's polar areas assuming the present-day composition of the atmosphere. We performed two additional simulations with lower mixing ratios of oxygen of 1% and 15% to account for the composition changes after the Great Oxydation Event (GOE).

According to our estimates, the maximum loss rates due to polar outflow was reached three gigayears ago equal to 3.3 x 10²⁷ s^-1 and 2.4 x 10²⁷ s^-1 for oxygen and nitrogen, respectively. We estimate the total maximum integrated mass loss equal to 39% and 10% of the modern atmosphere's mass, for oxygen and nitrogen, respectively. We also show that escape rates increase, if the oxygen mixing ratio is decreased (GOE simulations), which is due to reduced thermospheric cooling. According to these results, the main factors that governed the polar outflow in the considered time period are the evolution of the XUV radiation of the Sun and the atmosphere's composition. The evolution of the Earth's magnetic field plays a less important role. We conclude that although the atmosphere that has a present-day composition can survive the escape due to polar outflow from 3 gigayears ago and later, a higher level of CO₂ between 3.0 and 2.0 Ga is likely necessary to reduce the escape.

How to cite: Kislyakova, K., Johnstone, C., Scherf, M., Holmström, M., Alexeev, I., Lammer, H., Khodachenko, M., and Güdel, M.: Earth’s polar outflow evolution from mid-Archean to present, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-200, https://doi.org/10.5194/epsc2020-200, 2020.

Introduction

Venus Global Climate Models (VGCM) are powerful tools to investigate the amount of data recently acquired by Venus Express (VEx) and Akatsuki missions, as well as from ground-based telescopes. Our understanding of the Venusian climate has increased with recent progresses with these models. VEx observations revealed a more variable atmosphere than expected, in particular in the “transition” region (~70-120 km) between the retrograde superrotating zonal flow (RSZ) and the day-to-night circulation. This region exhibits latitude and day-to-day variations of temperature up to 80 K above 100-km at the terminator, and apparent zonal wind velocities measured around 96-km on the Venus nighttime highly changing in space and time. Those variations are not fully explained by current 3D models and specific processes (e.g. gravity wave (GW) propagation, thermal tides, large scale planetary waves) responsible for driving them are still under investigation. The role of convectively generated GW and their impact on zonal wind and temperature in the region of aerobraking can be explored with an update version of the Institut Pierre-Simon Laplace (IPSL) VGCM, thanks to the inclusion of a stochastic non-orographic GW parameterization based on the Earth GCM.  A vertical coupling between the cloud level and the thermosphere generated by GW, modulated and periodically filtered by the oscillation of the background zonal wind associated with the Kelvin wave was recently suggested in Nara et al.2020. This mechanism can partially explain the observed variation of oxygen UV airglow in the dayside (Navarro et al.in preparation).

The IPSL VENUS GCM: data-model validation

This climate model has been used recently to investigate all regions of the Venusian atmosphere, as it covers the surface up to the thermosphere (150 km) (Gilli et al.2017; Garate-Lopez&Lebonnois2018, Navarro et al.2018). It involves a photochemical module with a simplified cloud scheme that enables the study of the composition and the coupling with the upper atmosphere, where non-LTE, EUV heating processes, molecular diffusion, play a crucial role on the thermal balance. Below 100-km, the infrared energy budget is computed based on a Net Exchange Rate formalism. The cold collar structure has been modelled when taking into account the latitudinal distribution of the cloud structure. Recent improvements in non-LTE parameterization included in the IPSL-VGCM allow a better representation of the thermal structure of Venus above 90-km. Overall, our model is able to simulate well the succession of warm and cool layers above 80-km, which is one of remarkable feature that has been systematically detected, but the intensity of the local nighttime mesospheric warm layer is about 20 K larger between 90-km and 120-km altitudes, approximately. CO₂, CO and O densities above 100-km are also in good agreement with available dataset in term of trend and order of magnitude (Gilli et al.in preparation). The region between the cloud tops and 100-110 km is still puzzling, not only because of more substancial variability, especially at nighttime in contrast with a dynamically quieter daytime, but also because our model is reproducing quite well SOIR/VEx profiles at the evening (ET) but not at the morning terminator (MT), especially at low latitudes (Fig.1). Possible interpretations of those discrepancies will be discussed (e.g wind asymmetries produced by GW drag, fine-tuning of the current parameterization,consequence of the lower’s atmosphere superrotation extending up to 95-km).

Figure 1: Example of comparison of simulated CO densities by the IPSL-VGCM (green dashed line) with retrieved measurements (blue dots) and standard deviations at equatorial latitudes (0-30N), extracted from the Venus Atmosphere from SOIR measurements at the terminator (VAST) (Vandaele et al.2016). Top: Morning terminator. Bottom: Evening terminator.

 Can we explain the observed variability by mean of 3D simulations?

Diurnal and latitudinal distribution of CO and O, together with O2 airglow are used to shed a light on the dynamics in a region poorly constrained by wind measurements and where direct measurements of winds are not possible. Several observations demonstrated that both RSZ and subsolar-to-antisolar (SS-AS) flow affect the global distribution of CO and other light species like NO/O2 airglows (e.g. Lellouch et al.2008, Moullet et al.2012,  Gerard et al.2014) at mesospheric altitudes (70-120 km). The majority of Doppler winds retrieved at mesospheric and lower thermospheric altitudes (e.g. Clancy et al.2015) also suggested the presence of a substantial retrograde zonal flow at altitudes above 90 km.

We focus here on CO which, as other light species, is expected to pile up at the converging stagnation point of the wind field (i.e. where the horizontal velocity converges to zero). This point is at the anti-solar point for pure SS-AS flow and displaced toward the morning terminator when a retrograde zonal flow is added. The position of the maximum and its magnitude depend on the relative values of equatorial velocity and a maximum cross-terminator velocity. Our simulations indicate that a weak retrograde wind is present in the mesosphere, up to about 120-km, producing the CO bulge displacement toward 2h-3h in the morning. Moreover, simulations show periodic events of transient, local maxima of O₂ nightglow at high latitudes, in agreement with observations (Hueso et al.2008, Soret et al.2014). These events are caused by the 5-day period Kelvin wave when it passes through the nightside, ejecting recombined molecular oxygen poleward.

Figure 2:  3D maps of simulated CO volume mixing ratio (contour line) and zonal wind (color) by the IPSL-VGCM at two pressure layers: 1 Pa (top panel) and 0.1 Pa (bottom panel). The star indicates the Anti-Solar point. Dotted lines represent the region were horizontal wind converges to zero.

Acknowledgments: GG was supported by European Union′s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No.796923, and by FCT through the research grants UIDB/04434/2020,UIDP/04434/2020,P-TUGA PTDC/FIS-AST/29942/2017

References: 

Garate-Lopez & Lebonnois 2018, Icarus 314,1-11; Gilli et al.2017, Icarus 281,55-72; Navarro et al.2018,Nature Geosci. 11,478-49; Nara et al.2020, JGR(Planets), 125,E006192; Clancy et al.2015,Icarus, 254,233-258; Moullet et al.2012,Vol 546,12pp;Lellouch et al.2008,PSS, 56,1355-1367; Vandaele et al. 2016,Icarus 272,48-59; Hueso et al. 2008,JGR,Vol.113;Soret et al. 2014,Icarus,217, 849-855; Gerard et al.2014,Icarus 236,902-103

How to cite: Gilli, G., Navarro, T., Lebonnois, S., Quirino, D., Silva, V., Lefevre, F., and Schubert, G.: Venus upper atmosphere revealed by a GCM: Temperature, CO, O2 and O distribution in the puzzling transition region, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-353, https://doi.org/10.5194/epsc2020-353, 2020.

Abstract

We present simulations of the ancient Martian climate with the Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) general circulation model.  We evaluate the efficacy of CO₂-H₂ and CO₂-CH₄ collision-induced absorption (CIA) in producing temperate conditions on Mars during the late Noachian-early Hesperian period near 3.7 Gya.  We additionally study the fate of liquid water if it was on the surface during that time period in history.

Geologic evidence indicates that ancient Mars supported widespread surface liquid water approximately 3.5-4 Ga (e.g., [1], [2]).  For nearly as long, climate modeling has attempted to find a self-consistent mixture of atmospheric gases with realistic atmospheric pressures that could support a hydrological cycle that is consistent with the geologic evidence (see [3] for an overview).  Despite those efforts, substantial doubt remains about the feasibility of a “warm and wet” climate that could have existed for sufficient time to produce the geologic evidence during the period of the faint young Sun. 

Recently, [4] and [5] (among others) have shown that H₂, in combination with CO₂ and CH₄, can produce efficient CIA that provides substantial warming at plausible surface pressures (i.e., <2 bar, see [6]) with modest H₂ mixing ratios.  Using the CIA tables provided by [5], we evaluate the ability to generate temperate climactic conditions on ancient Mars using the ROCKE-3D GCM.

We conduct a series of ROCKE-3D GCM [7] simulations in two broad groups that we term “dry” and “wet.”  The “dry” group consists of simulations that are run without open liquid water initialized on the surface, while the “wet” group is initialized with some amount of surface liquid water as either lakes or fully-dynamic oceans.   

The dry simulations are conducted to evaluate what mix of pressure and gases can produce global surface temperatures above the freezing point of water.  A range of pressures (from 0.5-2 bar) and H₂ mixing ratio (0-10%) are evaluated.  The wet simulations are all conducted with a surface pressure and gas mixture that is supportive of surface liquid water and is initialized with planetary water inventories from 10-500 m global equivalent layers.

Both modern topography and a plausible paleotopography (following [8]) is used to evaluate the effect of the Tharsis emplacement and true polar wander on the climate state.  We employ a stellar spectrum that is appropriate for 3.8 Ga.  All simulations are run until radiative and hydrological equilibrium are reached. 

We find that global mean surface air temperatures are only above freezing for high pressure (1.5-2 bar) and/or H₂ mixing ratios of at least 3%.  Using modern topography, the high elevations of Tharsis Montes remain below freezing, even with 2 bar surface pressure and 10% H₂. At 1 bar surface pressures, only the lowest elevation areas (e.g., Hellas Planitia) experience any above-freezing temperatures during the year, but remain below freezing on an annual average basis (Figure 1). 

Including CH₄ in the atmosphere (at 1%) produces a weak tropopause and distinct stratosphere (defined as warming temperatures with altitude), which also reduces cloud cover.  Intriguingly, simulations without CH₄ have increased cloud cover which serves as a more effective hygropause than the CH₄-induced stratosphere, which may be relevant for ancient Martian water loss to space.    

The wet simulations that employ modern topography show that water is cold-trapped onto the Tharsis plateau, leaving comparatively little water (relative to the initial planetary inventory) in an active hydrological cycle.  What water is available falls as both rain and snow onto Tharsis and near the planetary topographic dichotomy.  The initial water inventory is not predictive of the location or amount of precipitation.  However, planetary obliquity is important, with 0° obliquity showing increased amounts of precipitation, with some of it falling in locations congruent with valley network formations (e.g., [2]) (Figure 2).

We will also present ongoing simulations with paleotopography and dynamic oceans.    

Figure 1: Percent of sols with above freezing daily average surface air temperatures for 10 ROCKE3D simulations with surface pressures and CO₂ and H₂ mixing ratios identified in the panel title.  All simulations incorporate dry soil.  The black line encloses the areas with 100%. 

Figure 2.  Annual total liquid precipitation (mm) for 6 simulations initialized with surface liquid water as lakes as shown in the panel title.   

References

[1] Masursky, H. (1973),  An overview of geological results from Mariner 9, J. Geophys. Res.,  78( 20),  4009– 4030, doi:10.1029/JB078i020p04009.

[2] Hynek, B. M.,  Beach, M., and  Hoke, M. R. T. (2010),  Updated global map of Martian valley networks and implications for climate and hydrologic processes, J. Geophys. Res.,  115, E09008, doi:10.1029/2009JE003548.

[3] Wordsworth, R.D. (2016), The Climate of Early Mars, Annual Review of Earth and Planetary Science, 44, 381-408, https://doi.org/10.1146/annurev-earth-060115-012355.

[4] Ramirez, R., Kopparapu, R., Zugger, M. et al. Warming early Mars with CO2 and H2.Nature Geosci 7, 59–63 (2014). https://doi.org/10.1038/ngeo2000.

[5] Wordsworth, R.D.,  Kalugina, Y.,  Lokshtanov, S.,  Vigasin, A.,  Ehlmann, B.,  Head, J.,  Sanders, C., and  Wang, H. (2017),  Transient reducing greenhouse warming on early Mars, Geophys. Res. Lett.,  44,  665– 671, doi:10.1002/2016GL071766.

[6] Warren, A. O.,  Kite, E. S.,  Williams, J.‐P., &  Horgan, B. ( 2019).  Through the thick and thin: New constraints on Mars paleopressure history 3.8 ‐ 4 Ga from small exhumed craters. Journal of Geophysical Research: Planets,  124,  2793– 2818. https://doi.org/10.1029/2019JE006178.

[7] Way, M.J., I. Aleinov, D.S. Amundsen, M.A. Chandler, T. Clune, A.D. Del Genio, Y. Fujii, M. Kelley, N.Y. Kiang, L. Sohl, and K. Tsigaridis, 2017: Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics 1.0: A general circulation model for simulating the climates of rocky planets. Astrophys. J. Supp. Series, 231, no. 1, 12, doi:10.3847/1538-4365/aa7a06.

[8]  Bouley, S., Baratoux, D., Matsuyama, I. et al (2016). Late Tharsis formation and implications for early Mars, Nature 531, 344–34, https://doi.org/10.1038/nature17171.

How to cite: Guzewich, S., Way, M., Aleinov, I., Wolf, E., Del Genio, A., Tsigaridis, K., and Wordsworth, R.: Ancient Martian Climate with ROCKE-3D, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-109, https://doi.org/10.5194/epsc2020-109, 2020.

We report on the cloud top morphology, scale-analysis of patterns, and dynamics of ‘‘textured” local dust storms on Mars observed at the edge of the North Polar cap during the Northern Hemisphere Spring Equinox, before aphelion, using images obtained by the Visual Monitoring Camera (VMC) [1] and High Resolution Stereo Camera (HRSC) [2] onboard Mars Express. VMC images were analyzed with tools described in previous works [3-4] and HRSC images were analyzed from map-projections. 

The observations cover the period from March 3 to July 17, 2019, corresponding to the solar longitude range Ls = 350° - 55° (Martian Years 34 to 35). We observed the continuous formation of circumpolar dust patches, large frontal arc-shaped features, flushing dust storms, textured local dust storms and other forms of cloud activity at the edge of and inside the North Polar cap around latitude 60°N, a rich phenomenology typical of this season [5]. In this presentation we concentrate on the study of three textured local dust storms observed at the end of May and early June 2019. 

The observed textured storms contained cellular structure and frontal-like banding, both indicative of organized active lifting within the storm [6-7]. The first storm was centered at about 185°E, 60°N and occupied a small area of 1.75x10⁵ km². It showed three frontal bands with lengths ~ 1000 km and widths of 85 km separated by 40 km. In the interior of the storm a cellular pattern developed with a mean size of 50 km x 20 km. The second storm was centered at about 330°E, 60°N, occupied an area of 1.3x10⁶ km² and moved zonally with velocities from 20 to 45 ms^-1. A global cellular pattern covered this storm with cells of a mean size of 135 km x 60 km and inter-cell distances in the range 100-300 km. The third storm was centered at about 150°E, 65°N, occupied an area of 1.6-2.1x10⁵ km² and moved zonally with a mean velocity of 38 ms^-1. Its cellular pattern had a mean size of 70 km x 40 km. In all cases, the cell texture is anisotropic in the horizontal size (length/width, l/w~ 2) and their value is well above the atmospheric scale height (H ~ 8 km). Deep convection driven by buoyancy generated by the radiative heating of atmospheric dust is proposed to explain this structure.

References: 

[1] Ormston, T., Denis, M., Scuka, D., & Griebel, H., An ordinary camera in an extraordinary location: Outreach with the Mars Webcam. Acta Astronautica, 69, 703-713 (2011)

[2] Jaumann, R., Neukum, G., Behnke, T., Duxbury, T. C., Eichentopf, K., Flohrer, et al., The high-resolution stereo camera (HRSC) experiment on Mars Express: Instrument aspects and experiment conduct from interplanetary cruise through the nominal mission. Planetary and Space Science, 55, 928-952 (2007)

[3] Sánchez-Lavega, A., Chen-Chen, H., Ordonez-Etxeberria, I., Hueso, R., del Rio-Gaztelurrutia, T., Garro, A., & Wood, S., Limb clouds and dust on Mars from images obtained by the Visual Monitoring Camera (VMC) onboard Mars Express. Icarus, 299, 194-205 (2018)

[4] Hernández‐Bernal, J., Sánchez‐Lavega, A., del Río‐Gaztelurrutia, T., Hueso, R., Cardesín‐Moinelo, A., Ravanis, E. M., Tivov, D., & Wood, S., The 2018 Martian Global Dust Storm over the South Polar Region studied with MEx/VMC. Geophys. Research Lett., 46, 10330-10337 (2019)

[5] Kahre, M. A.,  Murphy, J. R,  Newman, C. E.,  Wilson, R. J.,  Cantor, B. A.,  Lemmon, M. T. &  Wolff, M. J., The Mars Dust Cycle. In R. Haberle, R. T. Clancy, F. Forget, M. D. Smith and R. W. Zurek (Eds.), The Atmosphere and Climate of Mars (pp. 295-337). Cambridge, U.K. Cambridge University Press. (2017)

[6] Guzewich S. D., Toigo A. D., Kulowski L., Wang H., Mars Orbiter Camera climatology of textured dust storms, Icarus, 258, 1-13 (2018)

[7] Heavens N. G., Textured Dust Storm Activity in Northeast Amazonis–Southwest Arcadia, Mars: Phenomenology and Dynamical Interpretation, J. Atmos. Sci., 74, 1011-1037 (2017)

How to cite: Sanchez-Lavega, A., Garcia-Morales, J., Hernandez-Bernal, J., delRio-Gaztelurrutia, T., Hueso, R., Ravanis, E., Cardesín-Moinelo, A., Titov, D., Wood, S., Tirsch, D., Hauber, E., and Matz, K.-D.: Patterns in textured dust storms in Mars North Pole, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-141, https://doi.org/10.5194/epsc2020-141, 2020.

1. Introduction

Dust plays a main role in the atmosphere of Mars: it has a direct impact on its thermal structure, and by absorbing and scattering the incoming solar radiation, it provides forcing to its dynamics [1]. Martian general circulation models (GCMs) and regional climate models employ two-stream approximation radiation codes to compute the internal radiation fields [2][3][4].

The objective of this work is to provide estimates of internal radiation field and heating rate differences that can be expected from two-stream codes in mesoscale dynamical models due to differences in the scattering phase function for dust aerosols. We discuss the implications in the characterisation of Mars’ dust cycle and its effects in its atmosphere and dynamics.

2. Model

The two-stream code evaluated in this work has been implemented in both GCM and mesoscale climate models e.g, [4][5][6], and it is compared with a discrete ordinates method radiation code (DISORT) using multiple streams [7].

The visible and infrared spectral regions are treated separately. The visible and near infrared (0.4 to 4.5 μm) is divided into 7 intervals, while the thermal infrared (4.5 to 1000 μm) is divided into 5 spectral intervals [2][4]. Absorption data for relevant gases are loaded from HITRAN [8] and transformed into correlated-k tables. Local and seasonal atmospheric profiles and the chemical composition are retrieved from LMD Mars Climate Database [3][9].

Dust aerosol particle optical properties are loaded from the MOPSMAP database [10] using wavelength-dependant properties obtained from [11]. Input particle physical properties (size, shape, etc.) and atmospheric dust loading for different scenarios are derived from [12][13], with dust vertical distribution following a Conrath-profile [3].

3. Methodology

Internal radiation fields and heating rates calculated with the two-stream approximation are compared with 4, 8, and 16-stream outputs from DISORT code, using detailed descriptions of dust aerosol particle phase functions [13].

4. Results

The heating rates for 3 cases with low (τ = 0.1), moderate (τ = 0.8), and high (τ = 1.5) atmospheric dust loading were calculated using the different radiation codes. For all these scenarios, the average differences between the 2, 4, and 8-stream codes with respect to the DISORT 16-stream calculations are of about 10%, 1% and 0.1%, respectively; being the performance of the implementation proportional to the number of streams used.

5. Conclusions

We are evaluating the influence of using DISORT multiple streams radiation code in regional dynamical models and its impact on the retrieved internal radiation fields and heating/cooling rates.

This is a work in progress and the latest results for a number of characteristics situations, including the study of local dust storm effects, and the influence of dust particle properties and its vertical distribution will be presented.

Acknowledgements

This work is supported by the Spanish project AYA2015-65041-P (MINECO/FEDER, UE), Grupos Gobierno Vasco IT1366-19, and Diputación Foral de Bizkaia – Aula EspaZio Gela.

References

[1] Gierasch, P.G., and Goody, R.M. (1972): J. Atmos. Sci., 29, 400-402

[2] Haberle, R.M., et al. (1999): J. Geophys. Res. 104(E13), 8957-8974

[3] Forget, F., et al. (1999): J. Geophys. Res. 104, 24155-24175

[4] Rafkin, S., and Michaels, T. (2019): Atmosphere 2019, 10 (12), 747, doi: 10.3390/atmos.10120747

[5] Toon, O.W., et al. (1989): J. Geophys. Res. 94 (D13), 16287-16301, doi: 10.1029/JD094iD13p16287

[6] Kahre, M.A., et al. (2008): Icarus 195, 576-597 doi: 10.1016/j.icarus.2008.01.023

[7] Stamnes, K., et al. (1988): Appl. Opt. 27, 2502-2509

[8] Rothman, L. S., et al. (2003): J. Quant. Spect. Rad. Tra., Vol.130, 4-50

[9] Millour, E., et al. (2015): EPSC Abstracts 10, EPSC2015-438

[10] Gasteiger, J., and Wiegner, M. (2018): Geosci. Model Dev. 11, 2739-2762, doi: 10.5194/gmd-11-2739-2018

[11] Wolff, M.J., et al. (2009): J. Geophys. Res. 114, E00D04, doi: 10.1029/2009JE003350

[12] Lemmon, M.T., et al. (2019): Geophys. Res. Lett. 46, doi: 10.1029/2019GL084407

[13] Chen-Chen, H., et al. (2019): Icarus 330, 16-29, doi: 10.1016/j.icarus.2019.04.004

How to cite: Chen-Chen, H., Pérez-Hoyos, S., and Sánchez-Lavega, A.: Study of radiative heating rates in the Martian atmosphere under different atmospheric dust loading scenarios, Europlanet Science Congress 2020, online, 21 Sep–9 Oct 2020, EPSC2020-296, https://doi.org/10.5194/epsc2020-296, 2020.