Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask? [PDF]
J Adv Model Earth Syst, 2021 Gallup SM +6 more
europepmc +1 more source
Dynamic Stochastic Superresolution of sparsely observed turbulent systems [PDF]
, 2013 Branicki, M., Majda, A.J.
core +1 more source
Vegetation forcing modulates global land monsoon and water resources in a CO2-enriched climate. [PDF]
Nat Commun, 2020 Cui J +7 more
europepmc +1 more source
Representing Mesoscale Variability in Superparameterized Climate models
, 2021 Fredrik Jansson +6 more
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Surface-Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest. [PDF]
J Adv Model Earth Syst, 2019 Baker IT +8 more
europepmc +1 more source
Effects of explicit atmospheric convection at high CO2. [PDF]
Proc Natl Acad Sci U S A, 2014 Arnold NP +6 more
europepmc +1 more source
Deep learning to represent subgrid processes in climate models. [PDF]
Proc Natl Acad Sci U S A, 2018 Rasp S, Pritchard MS, Gentine P.
europepmc +1 more source
Stochastic superparameterization in a one-dimensional model for wave turbulence [PDF]
Communications in Mathematical Sciences, 2014 Ian G. Grooms, Andrew J. Majda
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Global Cloud-Resolving Models [PDF]
Global cloud-resolving models (GCRMs) are a new category of atmospheric global models designed to solve different flavors of the nonhydrostatic equations through the use of kilometer-scale global meshes. GCRMs make it possible to explicitly simulate deep
Düben, Peter +6 more
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Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model. [PDF]
J Adv Model Earth Syst, 2018 Kooperman GJ +3 more
europepmc +1 more source