the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Solar forcing for CMIP6 (v3.2)
Bernd Funke
Monika E. Andersson
Luke Barnard
Jürg Beer
Paul Charbonneau
Mark A. Clilverd
Thierry Dudok de Wit
Margit Haberreiter
Aaron Hendry
Charles H. Jackman
Matthieu Kretzschmar
Tim Kruschke
Markus Kunze
Ulrike Langematz
Daniel R. Marsh
Amanda C. Maycock
Stergios Misios
Craig J. Rodger
Adam A. Scaife
Annika Seppälä
Ming Shangguan
Miriam Sinnhuber
Kleareti Tourpali
Ilya Usoskin
Max van de Kamp
Pekka T. Verronen
Stefan Versick
Related authors
ignorosphere. Here, intriguing and complex processes govern the deposition and transport of energy. The aim is to quantify this energy by measuring effects caused by electrodynamic processes in this region. The concept is based on a mother satellite that carries a suite of instruments, along with smaller satellites carrying a subset of instruments that are released into the atmosphere.
best-fit modeland the measurements suggest that chemical reactions involving O2 and O(3P) might occur differently than is usually assumed in literature. This considerably affects the derived abundances of O(3P) and H, which in turn might influence air temperature and winds of the whole atmosphere.
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.