M. Fox-Rabinovitz

发表

Stretched-grid Model Intercomparison Project: decadal regional climate simulations with enhanced variable and uniform-resolution GCMs

J. Cote, M. Déqué, J. McGregor, 2008 .

A Finite-Difference GCM Dynamical Core with a Variable-Resolution Stretched Grid

Georgiy L. Stenchikov, Michael S. Fox-Rabinovitz, Lawrence L. Takacs, 1997 .

New Approach to Calculation of Atmospheric Model Physics: Accurate and Fast Neural Network Emulation of Longwave Radiation in a Climate Model

D. Chalikov, V. Krasnopolsky, M. Fox-Rabinovitz, 2005 .

Variable resolution general circulation models: Stretched‐grid model intercomparison project (SGMIP)

Jean Côté, Michael S. Fox-Rabinovitz, M. Déqué, 2006 .

A Variable-Resolution Stretched-Grid General Circulation Model: Regional Climate Simulation

Michael S. Fox-Rabinovitz, Lawrence L. Takacs, Max J. Suarez, 2001 .

Simulation of anomalous regional climate events with a variable‐resolution stretched‐grid GCM

M. Fox-Rabinovitz, 2000 .

Robustness of the NN Approach to emulating atmospheric long wave radiation in complex climate models

V. Krasnopolsky, M. Fox-Rabinovitz, M. Chou, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Regional stretched grid generation and its application to the NCAR RegCM

F. Giorgi, M. Fox-Rabinovitz, J. Qian, 1999 .

Variable-Resolution GCMs for Regional Climate Modeling: Stretched-Grid Model Intercomparison Project (SGMIP)

M. Déqué, J. Côté, M. Fox-Rabinovitz, 2006 .

Computational Dispersion Properties of 3-D Staggered Grids for Hydrostatic and Non-Hydrostatic Atmospheric Models

M. Fox-Rabinovitz, 1996 .

4 ON PIRCS MODELS ' CONSISTENCY OF DYNAMICS WITH PRECIPITATION

G. Grell, F. Giorgi, R. Pielke, 2001 .

Complex hybrid models combining deterministic and machine learning components as a new synergetic paradigm in numerical climate modeling and weather prediction

V. Krasnopolsky, M. Fox-Rabinovitz, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

M. Suárez, W. Sawyer, L. Takacs, 1999 .

Global simulation of tropospheric ozone using the University of Maryland Chemical Transport Model (UMD-CTM): 1. Model description and evaluation

G. Stenchikov, D. Allen, K. Pickering, 2004 .

A Multiyear Ensemble Simulation of the U.S. Climate with a Stretched-Grid GCM

E. Berbery, L. Takacs, M. Fox-Rabinovitz, 2005 .

Multiscale Diagnosis of the North American Monsoon System Using a Variable-Resolution GCM.

E. Berbery, M. Fox-Rabinovitz, 2003 .

A variable‐resolution stretched‐grid general circulation model and data assimilation system with multiple areas of interest: Studying the anomalous regional climate events of 1998

Michael S. Fox-Rabinovitz, Lawrence L. Takacs, L. Takacs, 2002 .

A Uniform- and Variable-Resolution Stretched-Grid GCM Dynamical Core with Realistic Orography

Georgiy L. Stenchikov, Michael S. Fox-Rabinovitz, Lawrence L. Takacs, 2000 .

Evaluation of pollutant outflow and CO sources during TRACE‐P using model‐calculated, aircraft‐based, and Measurements of Pollution in the Troposphere (MOPITT)‐derived CO concentrations

D. Allen, K. Pickering, M. Fox-Rabinovitz, 2004 .

Global simulation of tropospheric ozone using the University of Maryland Chemical Transport Model (UMD‐CTM): 2. Regional transport and chemistry over the central United States using a stretched grid

Georgiy L. Stenchikov, Michael S. Fox-Rabinovitz, Kenneth E. Pickering, 2004 .

Accurate and Fast Neural Network Emulations of Model Radiation for the NCEP Coupled Climate Forecast System: Climate Simulations and Seasonal Predictions*

Stephen J. Lord, Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, 2010 .

Tree approximation of the long wave radiation parameterization in the NCAR CAM global climate model

Ronald A. DeVore, Vladimir M. Krasnopolsky, Peter Binev, 2011, J. Comput. Appl. Math..

Using Ensemble of Neural Networks to Learn Stochastic Convection Parameterizations for Climate and Numerical Weather Prediction Models from Data Simulated by a Cloud Resolving Model

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, Alexei A. Belochitski, 2013, Adv. Artif. Neural Syst..

Consistent vertical and horizontal resolution

Michael S. Fox-Rabinovitz, R. Lindzen, M. Fox-Rabinovitz, 1989 .

Complex hybrid models combining deterministic and machine learning components for numerical climate modeling and weather prediction

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, V. Krasnopolsky, 2006, Neural Networks.

Consistent vertical and horizontal resolution. [for internal gravity waves study]

R. Lindzen, M. Fox-Rabinovitz, 1989 .

Using neural network emulations of model physics in numerical model ensembles

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, Alexei A. Belochitski, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Numerical Experiments on Consistent Horizontal and Vertical Resolution for Atmospheric Models and Observing Systems

R. Lindzen, M. Fox-Rabinovitz, 1992 .

Decadal Climate Simulations Using Accurate and Fast Neural Network Emulation of Full, Longwave and Shortwave, Radiation*

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, Alexei A. Belochitski, 2008 .

Development of neural network convection parameterizations for numerical climate and weather prediction models using cloud resolving model simulations

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, Alexei A. Belochitski, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Development of neural network convection parameterizations for climate and NWP models using Cloud Resolving Model simulations

Philip J. Rasch, V. M. Krasnopolʹsky, Alexei Anatolevich Belochitski, 2011 .

Variable-Resolution GCMs for Regional Climate Modeling: Stretched-Grid Model Intercomparison Project (SGMIP)

M. Déqué, J. Côté, M. Fox-Rabinovitz, 2006 .

A new synergetic paradigm in environmental numerical modeling: Hybrid models combining deterministic and machine learning components

Vladimir M. Krasnopolsky, Michael S. Fox-Rabinovitz, V. Krasnopolsky, 2006 .

Using adaptive learning techniques for fast and accurate approximation of physics in numerical models

V.M. Krasnopolsky, M. Fox-Rabinovitz, D. Chalikov, 2003, The 3rd International Workshop on Scientific Use of Submarine Cables and Related Technologies, 2003..