Exploring Ways to Reduce Biases in a Hybrid Global Climate Model With Machine‐Learned Moist Physics
Abstract In a previous study (Han et al., 2023, https://doi.org/10.1029/2022ms003508), we implemented a deep convolutional residual neural network for moist physics into the 3‐D real‐geography CAM5 and carried out a stable multi‐year integration successfully. However, the simulation has large temperature and moisture biases in high latitude troposphere
Yilun Han, Guang J. Zhang, Yong Wang
wiley +1 more source
Long‐Lived Mesoscale Convective Systems of Superparameterized CAM and the Response of CAM [PDF]
AbstractMesoscale organized convection is generally misrepresented in the large‐scale convective parameterizations used in contemporary climate models. This impacts extreme weather events (e.g., Madden‐Jullian Oscillation) and the general circulation driven by the significant amount of latent heat released from mesoscale organized convection.
Gino Chen, Ben P. Kirtman
openaire +1 more source
Surface-sampled simulations of turbulent flow at high Reynolds number
A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence to large ...
Jacobs, Christian T. +2 more
core +1 more source
Reduced-order precursors of rare events in unidirectional nonlinear water waves [PDF]
We consider the problem of short-term prediction of rare, extreme water waves in irregular unidirectional fields, a critical topic for ocean structures and naval operations.
Cousins, Will, Sapsis, Themistoklis
core +1 more source
Abstract Aerosol particles play a crucial role in the global climate by absorbing and scattering radiation and influencing cloud properties. This study explores the role of resolved convection on precipitation and subsequent removal by wet deposition of aerosol in the Community Earth System Model (CESM2.1.0) by comparing two configurations with ...
Alison Banks +3 more
wiley +1 more source
Climate Change Attribution Using Empirical Decomposition of Climatic Data
The climate change attribution problem is addressed using empirical decomposition. Cycles in solar motion and activity of 60 and 20 years were used to develop an empirical model of Earth temperature variations.
Loehle, Craig, Scafetta, Nicola
core +1 more source
Evaluation of large-eddy simulations forced with mesoscale model output for a multi-week period during a measurement campaign [PDF]
Large-eddy simulations (LESs) of a multi-week period during the HD(CP)2 (High-Definition Clouds and Precipitation for advancing Climate Prediction) Observational Prototype Experiment (HOPE) conducted in Germany are evaluated with respect to mean boundary
B. Stevens +8 more
core +4 more sources
Abstract We present a comprehensive evaluation of 13 global storm‐resolving models participating in the DYnamics of the Atmospheric general circulation Modeled On Non‐hydrostatic Domains (DYAMOND) Winter intercomparison project, focusing on their ability to simulate key atmospheric fields, such as precipitation rate, outgoing longwave radiation, and ...
Joonghyun In, Marat Khairoutdinov
wiley +1 more source
Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model
The aim of this work is the quantification and prediction of rare events characterized by extreme intensity in nonlinear waves with broad spectra. We consider a one-dimensional non- linear model with deep-water waves dispersion relation, the Majda ...
Cousins, Will, Sapsis, Themistoklis P.
core +1 more source
The shortwave radiative forcing bias of liquid and ice clouds from MODIS observations [PDF]
We present an assessment of the plane-parallel bias of the shortwave cloud radiative forcing (SWCRF) of liquid and ice clouds at 1 deg scales using global MODIS (Terra and Aqua) cloud optical property retrievals for four months of the year 2005 ...
G. Hong +4 more
core +3 more sources

