Results 11 to 20 of about 7,980 (145)

The Impact of a Stochastic Parameterization Scheme on Climate Sensitivity in EC‐Earth [PDF]

Journal of Geophysical Research: Atmospheres, 2019
AbstractStochastic schemes, designed to represent unresolved subgrid‐scale variability, are frequently used in short and medium‐range weather forecasts, where they are found to improve several aspects of the model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long‐term climate. In this paper, we
Strommen, K., Watson, P. A. G., Palmer, T. N.   +2 more
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Stochastic parameterization of column physics using generative adversarial networks

Environmental Data Science, 2022
We demonstrate the use of a probabilistic machine-learning technique to develop stochastic parameterizations of atmospheric column physics. After suitable preprocessing of NASA’s Modern-Era Retrospective analysis for Research and Applications, version 2 (
Balasubramanya T. Nadiga, Xiaoming Sun, Cody Nash   +2 more
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Stochastic parameterization of the time-relaxation model of turbulence

Results in Applied Mathematics, 2020
We parameterize the error in the time-relaxation model of turbulence by means of a deterministic corrector with stochastic noise term that represents the unresolved effects of the small scales on the large scales.
Eric Olson
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The Stochastic GM + E Closure: A Framework for Coupling Stochastic Backscatter With the Gent and McWilliams Parameterization

Journal of Advances in Modeling Earth Systems
Ocean general circulation models (OGCMs) are often used at horizontal resolutions that preclude the appearance of mesoscale eddies. The ocean mesoscale constitutes a significant component of ocean variability, and OGCMs whose resolutions are too coarse ...
I. Grooms, N. Agarwal, G. Marques, P. J. Pegion, H. Yassin   +4 more
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Stochastic parametrization with VARX processes [PDF]

Communications in Applied Mathematics and Computational Science, 2021
In this study we investigate a data-driven stochastic methodology to parameterize small-scale features in a prototype multiscale dynamical system, the Lorenz '96 (L96) model. We propose to model the small-scale features using a vector autoregressive process with exogenous variable (VARX), estimated from given sample data.
N. Verheul (Nick), D.T. Crommelin (Daan)
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Considerations for Stochastic Convective Parameterization [PDF]

Journal of the Atmospheric Sciences, 2002
Convective parameterizations in general circulation models (GCMs) generally only aim to simulate the mean or first-order moment of convection; higher moments associated with subgrid variability are not explicitly considered. In this study, an empirically based stochastic convective parameterization is developed that uses an assumed mixed lognormal ...
Johnny Wei-Bing Lin, J. David Neelin
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Stochastic Parameterization and El Niño–Southern Oscillation [PDF]

Journal of Climate, 2017
El Niño–Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical Pacific. However, the models in the ensemble from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have large deficiencies in ENSO amplitude, spatial structure, and temporal variability. The use of stochastic parameterizations as a technique
H. M. Christensen, Judith Berner, Danielle R. B. Coleman, T. N. Palmer   +3 more
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Stochastic Parameterization: Toward a New View of Weather and Climate Models [PDF]

Bulletin of the American Meteorological Society, 2017
Abstract 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 parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty.
Berner, Judith, Achatz, Ulrich, Batté, Lauriane, Bengtsson, Lisa, Cámara, Alvaro de La, Christensen, Hannah M., Colangeli, Matteo, Coleman, Danielle R. B., Crommelin, Daan, Dolaptchiev, Stamen I., Franzke, Christian L. E., Friederichs, Petra, Imkeller, Peter, Järvinen, Heikki, Juricke, Stephan, Kitsios, Vassili, Lott, François, Lucarini, Valerio, Mahajan, Salil, Palmer, Timothy N., Penland, Cécile, Sakradzija, Mirjana, von Storch, Jin-Song, Weisheimer, Antje, Weniger, Michael, Williams, Paul D., Yano, Jun-Ichi   +26 more
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Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3) [PDF]

Geoscientific Model Development, 2016
The Plant–Craig stochastic convection parameterization (version 2.0) is implemented in the Met Office Regional Ensemble Prediction System (MOGREPS-R) and is assessed in comparison with the standard convection scheme with a simple stochastic scheme only ...
R. J. Keane, R. S. Plant, W. J. Tennant
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A Stochastic Discrete Empirical Interpolation Approach for Parameterized Systems

Symmetry, 2022
As efficient separation of variables plays a central role in model reduction for nonlinear and nonaffine parameterized systems, we propose a stochastic discrete empirical interpolation method (SDEIM) for this purpose. In our SDEIM, candidate basis functions are generated through a random sampling procedure, and the dimension of the approximation space ...
Daheng Cai, Chengbin Yao, Qifeng Liao
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