For Step 1, I implemented isotopes in the polar-oriented regional climate model MAR, an atmospheric model used and evaluated to simulate the Antarctic climate. The MAR model offers new opportunities to improve the modelling of water isotopic composition in Antarctica, thanks to its fine representation of polar processes. As an exemple, MAR explicitly models super-saturation which is of importance for transient kinetic isotope fractionation. MAR also includes explicit exchanges of mass between liquid and solid cloud particles and water vapor and drifting snow , which impacts the snow isotopic composition. Finally, sublimation of precipitation in the katabatic layer is a key component of the mass balance of the Antarctic ice sheet, a process which is well modelled in MAR. Water isotopes are now distributed with the MAR code (gitlab, branch mariso). The implementation is still ongoing and will continue during the next months. In 2022, water isotopes will be included in the main MAR branch (gitlab, master branch) and followed by a publication in Geoscientific Model Development.
For Step 2, despite the implementation of water isotopes in MAR not being fully operational yet, I began the interpretation of water isotope measurements acquired continuously in the atmospheric water vapor, snowfall, and surface snow since 2018 by the GLACCIOS team at the two French Antarctic stations Dumont d'Urville and Dome C (locations in Figure). Continuous isotopic measurements are made possible since the 2010’s thanks to recent developments in spectroscopy. The GLACCIOS team has pioneered these observations in Antarctica, which is challenging in this extremely dry and cold environment. Under this project, I supervised the Master thesis of C. Davrinche who focused on an atmospheric river event reaching Dome C in December 2018. Following her work to characterize this event, I performed a water vapor mass budget in the boundary layer using observations and simulations from the regional atmospheric model MAR, ran with and without drifting snow. The presence of mixed-phase clouds during the event induced a significant increase in downward longwave radiative fluxes, which led to high turbulent mixing in the boundary layer and to heavy drifting snow (white-out conditions). Using MAR simulations, we show that a significant part of the atmospheric water vapor originates from sublimation of drifting snow particles removed from the snowpack in the lower 100 m above the surface. Consequently, the isotopic signal monitored in water vapor during this atmospheric river event reflects both long-range moisture advection and interactions between the boundary layer and the snowpack. Only specific meteorological conditions driven by the atmospheric river can explain these strong interactions.
The project and these results have been presented at 3 confenrences (AGU 2019, IARC 2020 and vEGU 2021). I participated to 7 workshops along the project, 5 of them related to the field of water isotopes and paleoclimate, a new scientific community I am now fully part on thanks to this project. I also contributed and designed outreach activities at destination to elementary and middle-school pupils (5 classes), and to the Science Week.