the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 May 2023
Sensitivity analysis of a Martian atmospheric column model with data from Mars Science Laboratory
Ari-Matti Harri
Mark Paton
Jouni Polkko
Maria Hieta
Hannu Savijärvi
Abstract. An extensive sensitivity analysis was performed for a horizontally homogeneous and hydrostatic 1-D column model at the Mars Science Laboratory (MSL) location. Model experiments were compared with observations from the Curiosity Rover Environmental Monitoring Station humidity (REMS-H) device. Based on our earlier column model investigations, model surface temperature and pressure, dust optical depth (τ) and column precipitable water content (PWC) were the initial parameters that we investigated by our sensitivity analysis. Our analysis suggests that the most sensitive initial parameters for the column model temperature profile are τ and the surface temperature. The initial value of PWC does not affect the temperature profile of the model, but it is the most important parameter for the humidity profile. The initial value of τ also seems to have some effect on the humidity profile of the model. Based on our analysis, variations in surface pressure initialization are negligible for the model’s humidity and temperature predictions. The model simulations are generally in good agreement with the observations. Our analysis suggest that a slightly different shape of the model’s initial humidity profile could yield better results in the predicted water vapor volume mixing ratios at 1.6 m.
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Joonas Leino et al.
Status: open (extended)
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CC1: 'Comment on egusphere-2023-846', Franck Montmessin, 10 Aug 2023
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This article presents a sensitivity study conducted with a 1D-model developed to simulate a column of atmosphere on Mars. The model includes a variety of physical processes intended to represent those to which the column is submitted at various timescales (convection, radiation, exchanges with the regolith).
The main ambition is to address the impact that some parameters have in the predictions of the model; namely temperature, relative humidity and water vapor mixing ratio. As this model has already been applied to interpret data produced by atmospheric sensors on board the Mars Science Laboratory rover (Curiosity), this work should enable the model to be used more effectively in the future, and its main limitations to be better understood.
While this paper represents a solid and valuable effort to explore the behavior of a model used to interpret Curiosity's atmospheric and surface data, it does not answer any particular scientific question and will primarily serve as a reference for the future use of the 1D model.
For this reason, the scientific contribution of the manuscript seems rather weak, while its technical value is beyond doubt.
This consideration aside, the article is concise and well-structured, but suffers from several flaws which are listed below:
-It is not clear how the conclusions drawn from this study will impact on the future use of the 1D model. Some conclusions could have been avoided, as they merely confirm things already known and presented in the introduction (the negligible role of sensible and latent heat on surface temperature), while others could have been used to extend the study to arguably more representative cases (MCD). The question that should be addressed is how the findings will change the strategy for the interpretation of MSL data.
-The role of regolith has long been an open question in the Mars water cycle community, since several Martian climate models have successfully reproduced the main features of the Mars water cycle in the absence of regolith. It is understood that the 1D model used here is based on the assumption that regolith plays an active and important role in the concentration of water vapor near the surface, which should deserve some more justification, especially in the context of contradicting results from 3D climate. Another unquestioned phenomenon concerns condensation and the formation of fogs. This is not mentioned in the manuscript, something that should be clarified by the authors. In particular, it would be interesting whether there is a competition between adsorption and condensation in the early morning
-half of the graphs show a comparison between various model results as a function of altitude. Yet they should only emphasize the altitude at which the measurements are made (1.6 m) and not show T and VMR profiles up to 5 km while most of the diurnal variations occur in the first hundreds of meters .
Specific comments (numbers refer to line numbers in the text):
26: 1) one of its unique features, compared to Earth, is also its 95% composition.
28: 2) sensible heat is negligible for the surface, but not for the atmosphere (matters for the BL)
87: “and average of the T” remove of
129+: PWC should be expressed in precipitable microns, pr-um.
141: the few ChemCam observations could have been expanded by many more data from orbiters
Fig4: 1) is condensation included in the model?
2) limit altitude axis to below 250 m
3) since the text emphasizes the lack of reliability of VMR for Low RH data; RH plots should be added to let the readers see when VMR should be ignored. Alternatively, the authors could mark points when unreliable.
202: nighttime H2O VMR for Ls 271° after dusk is not well reproduced at all. Any comment?
206: It should be stressed that Chemcam cannot directly measure the H2O VMR at 1.6 m, and its value is essentially an extrapolation based on strong assumptions that the MCD, for instance, could contradict. It is clear from the graphs that H2O vmr deduced from RH measurements are made in a layer marked by a strong yet very shallow gradient. Chemcam has no sensitivity to that region of the atmosphere.
216: Since it was already discussed in previous works using the same model, why is it the MCD has not been employed to initialize the moisture profile?
222: “initial” implies these parameters can evolve during the run. “Fixed” parameters see more appropriate
Citation: https://doi.org/10.5194/egusphere-2023-846-CC1
Joonas Leino et al.
Joonas Leino et al.
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