APPROACH TO THE MAPPING OF WATER ENVIRONMENT ON PRESENT
MARS – VALIDATION OF POSSIBLE WATER VAPOR EMISSION FROM
RECURRING SLOPE LINEAE USING A GCM
T. Kuroda1,2 (tkuroda@tohoku.ac.jp), H. Kurokawa3, S. Aoki4, H. Nakagawa1, and M. Kobayashi1
1
Department of Geophysics, Graduate School of Science, Tohoku University, Sendai, Japan. 2Division for the
Establishment of Frontier Sciences, Organization for Advanced Studies, Tohoku University, Sendai, Japan.
3
Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan. 4Department of Complexity
Science and Engineering, The University of Tokyo, Kashiwa, Japan.

Introduction:
Identification and mapping of the surface and
underground water environment on present Mars
are important to investigate the existence of life and
reserve water resources for future manned missions.
Especially, the recurring slope lineae (RSL), dark
streaks which appear on steep slopes such as the
edge of craters in specific seasons [1], have been
noticed as important targets as possible water
sources on the surface of Mars. Although the
formation mechanisms of RSL are still under
discussion, it might be related to the flow of liquid
(salty or pure) water. We have simulated the
possible water vapor emission and expansion from
RSL using a Mars global climate model (MGCM)
[2].

Method:
We used a high-resolution coordinate of
DRAMATIC (Dynamics, RAdiation, MAterial
Transport, and their mutual InteraCtions) MGCM
[3] which has a horizontal resolution of ~1.1
degrees (~67 km) and 53 σ-levels with σ = 0.9995,
0.9998, 0.9955, 0.992, and 0.9875 for the lowest
five layers, corresponding to approximately 5, 20,
45, 80, and 125 m above the surface respectively, to
well resolve the planetary boundary layer (PBL).
We have performed six scenarios in which the water
vapor was emitted from one of five representing
grid points which include RSL (in CAP, VM, and
SML regions [4], see Figure 1), and investigated
the qualitative and quantitative transport of water
vapor. For each scenario the emission from one
RSL (area of 0.1 m2) was assumed, and the
emission rate was defined as 0.1 mm h-1 if the
surface temperature exceeded 238 K in CAP and
VM (assuming salty water), while as 1 mm h-1 if the
surface temperature exceeded 273 K in SML
(assuming pure water) [5].
Table 1 summarizes the emission points and Ls
periods for the six scenarios, as well as the surface
temperature and pressure conditions during the
emission runs (for 20 Sols). Note that the seasonal

and latitudinal variations of dust opacity was
defined with ‘MY26 dust scenario’ [6], and the
difference of daytime surface temperature between
MGCM and MGS-TES observation [6] for MY26
was within 8 K for each scenario.

Figure 1. Locations of five emission points
(background map: MGS-MOLA data [7]).

Table 1. Properties of the six scenarios performed
in this study.
Mean surface Mean emission
Point and period pressure during time length per
emission [Pa]
a Sol [h]
(a) CAP
880
9.88
Ls=50°~59°
(b) VM
625
7.05
Ls=130°~140°
(c) VM
Ls=320°~331°
(d) SML1
Ls=289°~301°
(e) SML2
Ls=289°~301°
(f) SML3
Ls=289°~301°

689

9.85

513

8.50

522

8.18

905

7.68

Results:
Figure 2 shows the snapshots of the simulation
results of water vapor emissions from each
emission point (corresponding movies are available

in [2]). Our results showed that the column
densities of emitted water vapor from one RSL did
not exceed 1/300 of the background column density
of water vapor (MGS-TES observations in MY26
[8]) for each scenario. Focusing on the movements
of emitted water vapor, daytime lifting of water
vapor was seen up to ~10 km altitude with the
vatically low variations of potential temperatures,
depending on the surrounding topographic
condition. Note that we did not need to consider the
condensation of emitted water vapor, since the
water vapor mixing ratio in the PBL did not reach
the saturation level for each scenario.

(c)

(a)

(d)

(b)

(e)

(f)

Figure 2. Snapshots of the water vapor distributions
emitted from one RSL and atmospheric/surface
conditions at the localtime of ~5PM in the 20th sol
of simulation. (a)-(f) corresponds to the scenarios
listed in Table 1.
(top left) Column density of emitted water from
one RSL (shades) and the wind field of ~5 m
altitude (gray arrows, index is as displayed in the
right bottom). The crossover point of two white
lines shows the emission point and black contours
denote the topography.
(top right) Surface temperature (shades) with the
threshold temperature of emission (238 K or 273 K
depending on the location, black thick contour).
Gray contours denote the topography.
(bottom row) Longitude-altitude (left) and
latitude-altitude (right) cross-sections of the mixing
ratio of emitted water (shades), potential
temperature defined at 6.1 hPa (black contours),
and horizontal (zonal or meridional) -vertical wind
fields (gray arrows, index is as displayed in the
right bottom, vertical velocity is multiplied by 50).

Discussions and future plans:
Our simulation results showed that it would be
quite severe to quantitatively detect the emitted
water from single RSL by remote-sensing
observations even if RSL have a wet origin [2].
However, 475 RSL has been found on Mars,
especially concentrative in CAP and VN regions [4],
so the actual amount of emission in those regions
could be rather higher than the simulation results.
Also, it should be noted that the emitted water
vapor tended to accumulate in basins and valleys, as
indicated in Figures 2e and 2f. We plan to perform
the simulations using a regional mesoscale model
with higher horizontal resolution of topography,
which will show the contrast of water vapor
distibutions affected by the km-scale deviations of
topography which could not be represented in our

current simulation.
Moreover, we are implementing the absorption of
water vapor by regolith and vertical transport of
subsurface water including the emission of
underground ice into the MGCM with water cycle
[9] for the global mapping of water vapor
distributions on Mars, in addition to the emissions
from RSL. In the presentation we plan show the
preliminary results of global water mapping with
the effects of regolith.

Acknowledgements:
This work is supported by the Japan Society for the
Promotion of Science (JSPS) KAKENHI Grant
Numbers 17H06457, 19H01960, 19H05072,
18H04453, 19H00707, 19K03980, 20H04605,
20KK0080, 21H04514, and 21K13976, as well as
the Fusion Oriented REsearch for disruptive
Science and Technology (FOREST) program of
Japan Science and Technology agency (JST). The
model runs were performed using the Fujitsu
PRIMERGY
CX600M1/CX1640M1
(Oakforest-PACS) at the Information Technology
Center, The University of Tokyo.

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