Articles | Volume 32, issue 3
https://doi.org/10.5194/npg-32-329-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-32-329-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulation and data assimilation in an idealized coupled atmosphere–ocean–sea ice floe model with cloud effects
Changhong Mou
Department of Mathematics, Purdue University, West Lafayette, Indiana, USA
Samuel N. Stechmann
Department of Mathematics, University of Wisconsin–Madison, Madison, Wisconsin, USA
Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
Nan Chen
CORRESPONDING AUTHOR
Department of Mathematics, University of Wisconsin–Madison, Madison, Wisconsin, USA
Related authors
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Scott Hottovy and Samuel N. Stechmann
Nonlin. Processes Geophys., 30, 85–100, https://doi.org/10.5194/npg-30-85-2023, https://doi.org/10.5194/npg-30-85-2023, 2023
Short summary
Short summary
Rainfall is erratic and difficult to predict. Thus, random models are often used to describe rainfall events. Since many of these random models are based more on statistics than physical laws, it is desirable to develop connections between the random statistical models and the underlying physics of rain. Here, a physics-based model is shown to converge to a statistics-based model, which helps to provide a physical basis for the statistics-based model.
Jason Louis Turner and Samuel N. Stechmann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-257, https://doi.org/10.5194/gmd-2020-257, 2020
Revised manuscript not accepted
Short summary
Short summary
EZ Parallel is a Fortran Message Passing Interface library designed to allow users to easily and quickly turn their serial code into a parallel one for the purpose of obtaining simulations with higher resolutions or larger domain sizes in a shorter amount of time. In tests of the parallelized code, the strong scaling efficiency for the finite difference code is seen to be roughly 80% to 90%, which is achieved by adding roughly only 10 new lines to the serial code.
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Short summary
Sea ice is crucial in the climate system, especially in the Marginal Ice Zone (MIZ). As the MIZ expands, understanding its dynamics is essential for predicting climate impacts. This paper addresses the largely overlooked role of clouds, developing an idealized atmosphere–ocean–ice model with cloud effects, tackling both simulation and data assimilation. The results imply the potential of integrating idealized models with data assimilation for understanding Arctic dynamics and predictions.
Sea ice is crucial in the climate system, especially in the Marginal Ice Zone (MIZ). As the MIZ...