the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multi-variate factorisation of numerical simulations
Deepak Chandan
Alan M. Haywood
George M. Lunt
Jonathan C. Rougier
Ulrich Salzmann
Gavin A. Schmidt
Paul J. Valdes
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bulkequilibrium climate sensitivity (∼3 to 4.5°C) fall within the range predicted by the IPCC AR5 Report. This work improves our understanding of two key climate metrics during the early Paleogene.
atlaswill provide insights into the mechanisms that control past warm climate states.
bulkequilibrium climate sensitivity (∼3 to 4.5°C) fall within the range predicted by the IPCC AR5 Report. This work improves our understanding of two key climate metrics during the early Paleogene.
atlaswill provide insights into the mechanisms that control past warm climate states.
tuning). Tuning uses degrees of freedom allowed by uncertainties in model approximations to modify parameters to make the simulation better align with some selected observed target(s). We describe how these tuning targets, parameters, and philosophy vary across six US modeling centers in order to increase the transparency of the practice.
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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.
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swapping in and outdifferent values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.