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
Related authors
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.
Related subject area
Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
This study introduces a new 3D lake–ice–atmosphere coupled model that significantly improves winter climate simulations for the Great Lakes compared to traditional 1D lake model coupling. The key contribution is the identification of critical hydrodynamic processes – ice transport, heat advection, and shear-driven turbulence production – that influence lake thermal structure and ice cover and explain the superior performance of 3D lake models to their 1D counterparts.
Cited articles
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(20079 KB) - Full-text XML
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.