the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
David M. Lawrence
Yoshihide Wada
Ting Tang
Erik Kluzek
Sam Rabin
Steven J. De Hertog
Inne Vanderkelen
Wim Thiery
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green manureto reducing or removing the use of N fertilizer in global agricultural systems, considering different climate conditions, management practices, and land-use change scenarios.
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
ecosystem services. The overall impacts are strongest in future scenarios with more severe climate change, high population growth, and/or resource-intensive lifestyles.
We differentiate between uncertainties stemming from climatic driving data or from physical process parameterization, and show how these uncertainties vary seasonally and inter-annually, and how estimates are subject to the definition of permafrost used.
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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.