Journal of Advances in Modeling Earth Systems · 2022 · 46 citations · 51 references
Natural SciencesEarth SciencesHigh-performance ComputingAtmospheric ScienceClimate ScienceClimatologyClimate ModelingCloud DynamicsCloud FeedbacksCloud ParameterizationLarge-eddy SimulationRadiative ForcingCloud Feedback ParameterizationCloud Turbulence ParameterizationCumulus ParameterizationLarge-eddy Simulation Of Cloud TurbulenceLarge-eddy Simulation Of ConvectionParameterization Of Cloud-turbulence InteractionsRadiative Effects Of Low CloudsShortwave Cloud Feedback
Abstract Advances in high‐performance computing have enabled large‐eddy simulations (LES) of turbulence, convection, and clouds. However, their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed, with relatively few canonical LES available so far. The purpose of this paper is to begin creating a public LES library that expands the training data available for calibrating and evaluating GCM parameterizations. To do so, we use an experimental setup in which LES are driven by large‐scale forcings from GCMs, which in principle can be used at any location, any time of year, and in any climate state. We use this setup to create a library of LES of clouds across the tropics and subtropics, in the present and in a warmer climate, with a focus on the transition from stratocumulus to shallow cumulus over the East Pacific. The LES results are relatively insensitive to the choice of host GCM driving the LES. Driven with large‐scale forcing under global warming, the LES simulate a positive but weak shortwave cloud feedback, adding to the accumulating evidence that low clouds amplify global warming.
51
GENERAL CIRCULATION EXPERIMENTS WITH THE PRIMITIVE EQUATIONS
Joseph Smagorinsky · Monthly Weather Review · 1963 · 13.8K citations
Causes of Higher Climate Sensitivity in CMIP6 Models
Mark D. Zelinka, Timothy A. Myers, Daniel T. McCoy et al. · Geophysical Research Letters · 2020 · 1.8K citations · Full text