the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5
Charles Pelletier
Thierry Fichefet
Hugues Goosse
Konstanze Haubner
Samuel Helsen
Pierre-Vincent Huot
Christoph Kittel
François Klein
Sébastien Le clec'h
Nicole P. M. van Lipzig
Sylvain Marchi
François Massonnet
Pierre Mathiot
Ehsan Moravveji
Eduardo Moreno-Chamarro
Pablo Ortega
Frank Pattyn
Niels Souverijns
Guillian Van Achter
Sam Vanden Broucke
Alexander Vanhulle
Deborah Verfaillie
Lars Zipf
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Quantifying melt and freeze beneath Antarctica’s floating ice shelves is vital to understanding present-day ice-sheet behavior and its potential to contribute to future sea-level rise. We compare 10 ice-shelf/ocean computer simulations with satellite data, providing the first multi-model estimate of melting and refreezing driven by the ocean. This new estimate offers a valuable tool for assessing ice-shelf roles in current and future ice-sheet changes, informing coastal adaptation strategies.
Quantifying melt and freeze beneath Antarctica’s floating ice shelves is vital to understanding present-day ice-sheet behavior and its potential to contribute to future sea-level rise. We compare 10 ice-shelf/ocean computer simulations with satellite data, providing the first multi-model estimate of melting and refreezing driven by the ocean. This new estimate offers a valuable tool for assessing ice-shelf roles in current and future ice-sheet changes, informing coastal adaptation strategies.
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
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coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.