GLOBAL MARTIAN CO2 CLOUD MODELLING IMPROVEMENTS: METEORIC FLUX AS CONDENSATION NUCLEI AND RADIATIVELY ACTIVE
CO2 CLOUDS.
C. Mathé, LATMOS/IPSL, Sorbonne université, UVSQ Université Paris-Saclay, CNRS, Paris, France. Currently
at: LMD, A. Määttänen, LATMOS/IPSL, Sorbonne université, UVSQ Université Paris-Saclay, CNRS, Paris, France,
L. Falletti, LATMOS/IPSL, Sorbonne université, UVSQ Université Paris-Saclay, CNRS, Paris, France, A. Spiga,
Laboratoire de Météorologie Dynamique / Institut Pierre-Simon Laplace (LMD/IPSL), Sorbonne Université, Centre
National de la Recherche Scientifique (CNRS), École Polytechnique, École Normale Supérieure (ENS), Paris, France.
Institut Universitaire de France (IUF), Paris, France, F. Forget, E. Millour, Laboratoire de Météorologie Dynamique
/ Institut Pierre-Simon Laplace (LMD/IPSL), Sorbonne Université, Centre National de la Recherche Scientifique
(CNRS), École Polytechnique, École Normale Supérieure (ENS), Paris, France, J. Plane, School of Chemistry, Univ.
of Leeds, Leeds, UK.

Introduction
Mars is the only place where it has been observed that
the main atmospheric constituent, carbon dioxide, condenses as clouds. Modeling these clouds remains a challenge in the community, especially for mesospheric CO2
clouds as the conditions in this layer of the atmosphere
is difficult to constrain with observations and our knowledge of the cloud formation processes in these conditions
remains limited.
The recent study on CO2 cloud modeling shows the
need for water ice clouds as cloud condensation nuclei (CCN) in the formation of CO2 mesospheric clouds
[Määttänen et al., 2022] (see also Määttänen et al.’s abstract). The climatology of the simulated clouds was
in good agreement with observations. However, no
clouds were formed during the afternoon and optical
depths of simulated clouds remained lower than observations. They supposed two missing elements for the
lack of mesospheric clouds: small-scale waves (as gravity waves) that perturb the thermal structure allowing
colder temperatures to form locally [Spiga et al., 2012,
Yigit et al., 2015], and a new source of CCN allowing to increase the optical depth of CO2 clouds. The
suggested most likely CCN source is meteoric particles
[Listowski et al., 2014, Plane et al., 2018], that have been
recently reported by Mars Atmosphere and Volatile evolutioN Mission (MAVEN) [Crismani et al., 2017].
In the [Määttänen et al., 2022]’s work, CO2 ice clouds
were radiatively passive. When CO2 ice clouds are radiatively active, atmospheric temperatures at the edge
of the winter northern polar troposphere decrease in a
few Kelvins, leading to CO2 ice clouds thickness larger
than CO2 ice clouds radiatively passive [Kuroda, 2020],
and so larger cloud particle size and reduced column
cloud opacities [Dequaire et al., 2014]. This latter author shows also that CO2 ice clouds radiatively active
do not change the CO2 cycle in its shape, but reduced
the direct deposition of CO2 ice [Dequaire et al., 2014].
We present our latest improvements on the global

martian CO2 ice cloud modeling: (i) adding the missing
source of CCN meteoric particles in collaboration with J.
Plane’s team who works on Martian meteoric flux modeling, and (ii) adding the contribution of CO2 ice clouds
on the radiative budget of the Martian atmosphere.

Models and simulations
The microphysical model of CO2 cloud formation has
been developed during the last decade at LATMOS and
includes nucleation on CCN, condensation/sublimation,
and sedimentation [Listowski et al., 2014]. CCN sources
for CO2 ice cloud formation are dust particles, H2 O ice
cloud particles, and now also meteoric particles. The
particle size distribution is described with the moment
method allowing to compute the effect of the microphysical processes on the average properties of the distribution. For more details about the microphysical processes of CO2 clouds, we invite the reader to the work
of [Listowski et al., 2013], [Listowski et al., 2014], and
[Määttänen et al., 2022].
The LMD Martian Global Climate Model (MGCM)
is based on the primitive equations of meteorology in
σ coordinates [Forget et al., 1999]. The model is described in [Navarro et al., 2014, Pottier et al., 2017], including water ice cloud microphysics. Simulations with
this MGCM can be done with different settings: by
activating or deactivating certain physical processes via
options. Regarding the microphysical CO2 cloud formation part, we describe three options used in this study:
co2useh2o option enables H2 O ice as CCN; meteo_flux
option enables meteoric particles as CCN; and activeco2ice
option enables the contribution of CO2 ice clouds in the
radiative budget.
For this study, we performed three simulations: simulation named REF to serve as a comparison with the
adding meteoric particles source as CCN; simulation
named METEOFLUX to investigate the impact of the
source of the meteoric particles as CCN; simulation

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ACKNOWLEDGEMENTS

Figure 1: Input file of the distribution of the number density
of meteoric particles used in the microphysical models. White
areas correspond to a zero value.

to METEOFLUX+RT simulation. The black solid line
is the boundary of the area inside which MCS has observed atmospheric temperatures below the CO2 condensation temperature ([Hu et al., 2012], table 4). The
black dots show available mesospheric CO2 cloud observations from several instruments [Clancy et al. 2007,
Montmessin et al., 2006, Montmessin et al., 2007, Määttänen et al., 2010, McConnochie et al., 2010, Scholten
et al., 2010, Vincendon et al., 2011, Aoki et al., 2018,
Clancy et al., 2019, Jiang et al., 2019].
The CO2 cycle for REF and METEOFLUX simulations is quite the same. However, there are more CO2
ice clouds on a wider latitude range at the end of the
year in the METEOFLUX simulation. The addition of
meteoric particles as CCN seems to not impact strongly
the CO2 ice cloud formation, but further investigations
will be brought to the conference such as CO2 ice particles size, the thickness of clouds, local time duration,
and opacities of clouds.
Contribution of CO2 ice clouds on the radiative bud-

named METEOFLUX+RT to investigate the impact of
CO2 ice cloud on the radiative budget. Meteoric particle
flux comes from [Plane et al., 2018] work and is adapted
to the radius grid of the microphysical model (Fig. 1).
All simulations were performed using a horizontal resolution grid of 5.6258◦ longitude by 3.758◦ latitude. The
atmosphere is divided into 32 vertical layers from the
surface to the top of the atmosphere (∼120 km). At
each call of physical processes (every 15 minutes), the
microphysics of CO2 cloud formation is called 50 times
leading to a time resolution of 18 seconds to resolve
the very rapid microphysical processes. We have used
a mean dust scenario, called ’climatology’, built with
observations from several instruments (more details on
[Montabone et al., 2015].

get

Figure 3 shows the zonal mean of surface temperature
on a latitude - solar longitude map. The top panel refers
to TES climatology data [Smith, 2006], the middle one
refers to METEOFLUX simulation and the bottom one
refers to METEOFLUX+RT simulation. We observed
that on the northern winter pole surface temperature increase by ∼ 20 K when we activate CO2 ice cloud on the
radiative budget, as in the southern winter pole the increased temperature is lower and ends after ∼ 2 months.
The greenhouse effect from CO2 ice clouds is predominant in the northern polar region.
Back to fig.2, the simulation METEOFLUX+RT
formed CO2 ice clouds during three main periods: ∼
5◦ - 40◦ solar longitude (sl), ∼ 170◦ - 230◦ sl, and ∼
Name
co2useh2o meteo_flux activeco2ice 330◦ - 360◦ sl. Also, the formation of CO ice clouds
2
REF
yes
at the northern winter polar region ends earlier at ∼ 20◦
METEOFLUX
yes
yes
sl with CO2 ice radiatively active than at ∼ 60◦ sl with
METEOFLUX+RT yes
yes
yes
CO2 ice clouds radiatively passive.
Activated radiatively CO2 ice clouds have a strong
Table 1: List of simulations performed for this study with
impact on the CO2 cycle, and further investigations such
activated flags: co2useh2o option enables H2 O ice as CCN;
as CO2 ice particles size, thickness of clouds, local time
meteo_flux option enables meteoric particles as CCN; and acduration, and opacities of clouds will be brought to the
tiveco2ice option enables the contribution of CO2 ice clouds
conference.
in the radiative budget.

1
Meteoric particles as CCN for CO2 cloud formation
The zonal and diurnal mean of CO2 ice column density for each simulation is shown in figure 2: the top
panel refers to REF simulation, the middle one refers
to METEOFLUX simulation and the bottom one refers

Acknowledgements

We thank the Agence National de la Recherche for
funding (projet MECCOM, ANR-18-CE31-0013). This
work was performed using HPC computing resources
from GENCI-CINES (Grant 2021-A0100110391), and
resources at the ESPRI mesocentre of the IPSL institute. This work was support from CNES (Centre Na-

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ACKNOWLEDGEMENTS

Figure 3: Zonal and diurnal mean of surface temperatures.
Top panel refers to TES observations using the climatology
data. The middle panel refers to METEOFLUX simulation.
The bottom panel refers to METEOFLUX+RT simulation.

Figure 2: Zonal and diurnal mean of column density of CO2
ice. Top panel refers to REF simulation. The middle one refers
to METEOFLUX simulation. The bottom one refers to METEOFLUX+RT simulation. See text for details.

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