Reconciling Martian ozone with model photochemistry: new insights from an uncertainty propagation study

Le résumé fourni par la source

Ozone is a key trace gas of the Martian atmosphere. It is produced through the photolysis of carbon dioxide followed by a three-body reaction between atomic and molecular oxygen. Its primary sinks are photodissociation, which recycles lighter odd oxygen (Ox) species, and gas-phase reactions with odd-hydrogen (HOx) species, which are produced by water vapour photolysis.Many previous studies have shown that current Mars atmospheric general circulation models (GCMs) fail to reproduce the ozone columns observed by Mars Express and Mars Reconnaissance Orbiter studies (e.g. [1,2]), typically underestimating them by a factor of two [3].To help bridge the gap between models and observations, some studies examined the influence of various factors on the modelled ozone, including heterogeneous chemistry on water ice and dust aerosols, reaction rates, or radiative transfer [1,2]. These adjustments led to some local and temporally limited improvements, but often increased discrepancies elsewhere, suggesting that key processes may still be missing from Martian GCMs.In this study, we adopt a different approach by investigating the propagation of chemical uncertainties using the 1-D sub-model of the Mars Planetary Climate Model (MPCM). We conducted a global sensitivity study using Monte Carlo simulations in which all reaction rates were randomly varied within their measured or estimated uncertainty ranges. Then, we identified correlations between the volume mixing ratios of key species (Ox and HOx) and reaction rates variations, which allowed us to determine which reactions most strongly influenced model outputs. We then adjusted the rates of these key reactions within the full GCM and found that doing so significantly improves simulated ozone VMRs relative to observations from the Atmospheric Chemistry Suite (ACS) onboard the ExoMars Trace Gas Orbiter (TGO). Based on our analysis, we recommend an assessment of these key reaction rates under relevant conditions, along with their implementation in GCMs, to better constrain the remaining discrepancies between models and observations. References:[1] Lefèvre, F., A. Trokhimovskiy, A. Fedorova, L. Baggio, G. Lacombe, A. Määttänen, J.‐L. Bertaux, et al., JGR: Planets 126, no. 4 (2021)[2] Daerden, F., Crowley, J. N., Neary, L., Smith, M. D., Loeffler, M. J., Clancy, R. T., et al., JGR: Planets, 128, (2023)[3] Olsen, K. S., A. A. Fedorova, A. Trokhimovskiy, F. Montmessin, F. Lefèvre, O. Korablev, L. Baggio, et al., JGR: Planets 127, no. 10 (2022)

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.