Physics

Geology

Climate change

Meteorology

Forcing (mathematics)

Orbiter

Atmospheric sciences

Astronomy

Geodesy

Oceanography

Machine learning

Latitude

Climate model

Geography

Longitude

Martian

Computer science

Climatology

Kriging

Environmental science

Mars Exploration Program

Astrobiology

Journal of Geophysical Research Planets

We have reconstructed longitude-latitude maps of column dust optical depth (CDOD) for Martian year (MY) 34 (May 5, 2017 --- March 23, 2019) using observations by the Mars Climate Sounder (MCS) aboard NASA's Mars Reconnaissance Orbiter spacecraft. Our methodology works by gridding standard and newly available estimates of CDOD from MCS limb observations, using the "iterative weighted binning" methodology. In this work, we reconstruct four gridded CDOD maps per sol, at different Mars Universal Times. Together with the seasonal and day-to-day variability, the use of several maps per sol allows to explore also the daily variability of CDOD in the MCS dataset, which is shown to be particularly strong during the MY 34 equinoctial Global Dust Event (GDE). Regular maps of CDOD are then produced by daily averaging and spatially interpolating the irregularly gridded maps using a standard "kriging" interpolator, and can be used as "dust scenario" for numerical model simulations. In order to understand whether the daily variability of CDOD has a physical explanation, we have carried out numerical simulations with the "Laboratoire de M\'et\'eorologie Dynamique" Mars Global Climate Model. Using a "free dust" run initiated at $L_s \sim 210^\circ$ with the corresponding kriged map, but subsequently free of further CDOD forcing, we show that the model is able to account for some of the observed daily variability in CDOD. The model serves also to confirm that the use of the MY 34 daily-averaged dust scenario in a GCM produces results consistent with those obtained for the MY 25 GDE.

Martian Year 34 Column Dust Climatology from Mars Climate Sounder Observations: Reconstructed Maps and Model Simulations