Ongoing breakthroughs in convective parameterization
C Rio, AD Del Genio, F Hourdin - Current Climate Change Reports, 2019 - Springer
Abstract Purpose of Review While the increase of computer power mobilizes a part of the
atmospheric modeling community toward models with explicit convection or based on …
atmospheric modeling community toward models with explicit convection or based on …
Deep learning to represent subgrid processes in climate models
S Rasp, MS Pritchard… - Proceedings of the …, 2018 - National Acad Sciences
The representation of nonlinear subgrid processes, especially clouds, has been a major
source of uncertainty in climate models for decades. Cloud-resolving models better …
source of uncertainty in climate models for decades. Cloud-resolving models better …
Earth system modeling 2.0: A blueprint for models that learn from observations and targeted high‐resolution simulations
Climate projections continue to be marred by large uncertainties, which originate in
processes that need to be parameterized, such as clouds, convection, and ecosystems. But …
processes that need to be parameterized, such as clouds, convection, and ecosystems. But …
Atmospheric convection
Convective parameterization is the long-lasting bottleneck of global climate modelling and
one of the most difficult problems in atmospheric sciences. Uncertainty in convective …
one of the most difficult problems in atmospheric sciences. Uncertainty in convective …
Stochastic parameterization: Toward a new view of weather and climate models
The last decade has seen the success of stochastic parameterizations in short-term, medium-
range, and seasonal forecasts: operational weather centers now routinely use stochastic …
range, and seasonal forecasts: operational weather centers now routinely use stochastic …
The navy global environmental model
TF Hogan, M Liu, JA Ridout, MS Peng, TR Whitcomb… - Oceanography, 2014 - JSTOR
ABSTRACT On February 13, 2013, the US Navy's weather forecast system reached a
milestone when the NAVy Global Environmental Model (NAVGEM) replaced the Navy …
milestone when the NAVy Global Environmental Model (NAVGEM) replaced the Navy …
Machine learning for stochastic parameterization: Generative adversarial networks in the Lorenz'96 model
DJ Gagne, HM Christensen… - Journal of Advances …, 2020 - Wiley Online Library
Stochastic parameterizations account for uncertainty in the representation of unresolved
subgrid processes by sampling from the distribution of possible subgrid forcings. Some …
subgrid processes by sampling from the distribution of possible subgrid forcings. Some …
Process‐based climate model development harnessing machine learning: I. A calibration tool for parameterization improvement
F Couvreux, F Hourdin, D Williamson… - Journal of Advances …, 2021 - Wiley Online Library
The development of parameterizations is a major task in the development of weather and
climate models. Model improvement has been slow in the past decades, due to the difficulty …
climate models. Model improvement has been slow in the past decades, due to the difficulty …
Representation of boundary-layer processes in numerical weather prediction and climate models
JM Edwards, ACM Beljaars, AAM Holtslag… - Boundary-Layer …, 2020 - Springer
Boundary-layer schemes are essential components of numerical weather-forecasting and
climate models. From simple beginnings 50 years ago, they have grown in sophistication …
climate models. From simple beginnings 50 years ago, they have grown in sophistication …
An extended eddy‐diffusivity mass‐flux scheme for unified representation of subgrid‐scale turbulence and convection
Large‐scale weather forecasting and climate models are beginning to reach horizontal
resolutions of kilometers, at which common assumptions made in existing parameterization …
resolutions of kilometers, at which common assumptions made in existing parameterization …