Periodic Reporting for period 1 - POLARISO (A new isotope-enabled climate model dedicated to polar studies, to reconstruct Antarctic climate variability and improve sea level rise projections)
Reporting period: 2019-11-01 to 2021-10-31
The rate of Antarctic ice loss reached 20% of the global sea level rise in 2012–2017. This acceleration of ice fluxes toward the ocean is attributed to the coupling between large scale atmospheric patterns, ocean circulation and ice sheet dynamics. Intensive research efforts are in place to better understanding and modelling of this complex coupled climate system. However, the extremely sparse instrumental deployment preceding the most recent 40 years is a major limitation for the evaluation of global climate models used for climate projections, as several 30-year observational windows are required for a proper evaluation of circulation patterns, climate modes variability, and coupled ocean-atmosphere dynamics. Consequently, the greatest uncertainty in simulating the future of the Antarctic ice sheet is due to the lack of observational constraints that are required to evaluate and improve large scale climate variability in global climate models.
While the remoteness and harsh climate of the Antarctic region hampered instrumental deployment, the cold climate and large ice sheet make Antarctica a unique site for reconstructing past climates from ice cores. In addition to reconstruction of large temperature changes from temperature-isotope relationships, isotopic signals also reflect dynamics of the whole water cycle (e.g. moisture sources, trajectory of the moist air, polar processes, see Figure). For the last few centuries, ice cores extracted at high-accumulation margin sites have high potential to contain records of large scale climate modes from annual to seasonal temporal resolutions over the recent centuries, but this richness comes with high complexity, as it involves the whole water cycle pathway. This makes the use of climate models equipped with water stable isotopes a necessary step for linking the isotopic signal at the ice sheet surface to local polar processes and large scale circulation patterns. Consequently, the key for reconstructing past climate circulation patterns from ice cores and for evaluating their representation in global climate models is to use a back-and-forth method between models and data:
(1) use isotopic and other instrumental data to evaluate isotope-enabled models;
(2) use isotope-enabled models to relate the isotopic signal to climate modes;
(3) use climate modes derived from ice cores to evaluate global climate models.
The POLARISO main objective is to relate the isotopic signal recorded in the Antarctic snow to large scale climate modes. This is a fundamental step toward new reconstructions from ice cores of the Antarctic climate variability over the recent centuries which can be used to evaluate global climate models. For this we combine modelling and experimental advances to remove the two main limitations of state-of-the-art approaches: A) we significantly reduce the uncertainties related to unresolved polar processes in climate models by implementing water stable isotopes in a polar-oriented regional climate model, and B) we evaluate this model with new observations of the isotopic composition of atmospheric water vapor and snowfall measured in Antarctica before deposition in the snowpack.
The methodology proposed for achieving the above-mentioned objectives is:
Step 1: implement water stable isotopes in a polar-oriented regional climate model;
Step 2: evaluate the model with new continuous isotopic measurements in the water vapor and snow;
Step 3: identify the large scale drivers of the isotope variability at the Antarctic surface in the model.
At the end of the POLARISO project, I advanced on Steps 1 and 2, while Step 3 is planed to be achieved in the forthcoming years.
While the remoteness and harsh climate of the Antarctic region hampered instrumental deployment, the cold climate and large ice sheet make Antarctica a unique site for reconstructing past climates from ice cores. In addition to reconstruction of large temperature changes from temperature-isotope relationships, isotopic signals also reflect dynamics of the whole water cycle (e.g. moisture sources, trajectory of the moist air, polar processes, see Figure). For the last few centuries, ice cores extracted at high-accumulation margin sites have high potential to contain records of large scale climate modes from annual to seasonal temporal resolutions over the recent centuries, but this richness comes with high complexity, as it involves the whole water cycle pathway. This makes the use of climate models equipped with water stable isotopes a necessary step for linking the isotopic signal at the ice sheet surface to local polar processes and large scale circulation patterns. Consequently, the key for reconstructing past climate circulation patterns from ice cores and for evaluating their representation in global climate models is to use a back-and-forth method between models and data:
(1) use isotopic and other instrumental data to evaluate isotope-enabled models;
(2) use isotope-enabled models to relate the isotopic signal to climate modes;
(3) use climate modes derived from ice cores to evaluate global climate models.
The POLARISO main objective is to relate the isotopic signal recorded in the Antarctic snow to large scale climate modes. This is a fundamental step toward new reconstructions from ice cores of the Antarctic climate variability over the recent centuries which can be used to evaluate global climate models. For this we combine modelling and experimental advances to remove the two main limitations of state-of-the-art approaches: A) we significantly reduce the uncertainties related to unresolved polar processes in climate models by implementing water stable isotopes in a polar-oriented regional climate model, and B) we evaluate this model with new observations of the isotopic composition of atmospheric water vapor and snowfall measured in Antarctica before deposition in the snowpack.
The methodology proposed for achieving the above-mentioned objectives is:
Step 1: implement water stable isotopes in a polar-oriented regional climate model;
Step 2: evaluate the model with new continuous isotopic measurements in the water vapor and snow;
Step 3: identify the large scale drivers of the isotope variability at the Antarctic surface in the model.
At the end of the POLARISO project, I advanced on Steps 1 and 2, while Step 3 is planed to be achieved in the forthcoming years.
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.
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.
My current research objectives are in continuity with the POLARISO project. During the next years, I will pursue my effort to combine model evaluation and isotope interpretation for diagnosing the physical processes at the origin of model-data discrepancy. Once MARiso is fully operational and evaluated, I aim to quantify the local and large scale drivers of the isotope variability at the ice sheet surface and identify optimal locations which could enable retrieving relevant climate mode variability from ice cores.