Alex is working with Yangang Liu (DOE BNL) and Leo Donner (NOAA GFDL/Princeton University) on improving parameterizations of convection and boundary layer processes and seeking ways to couple them to parameterizations of cloud microphysics. The ultimate goal of his work is implementation of these schemes in to the GFDL climate model. Alex is stationed at the NOAA Geophysical Fluid Dynamics Laboratory in Princeton, NJ.
Kogan Y.L. and A. A. Belochitski, 2012: Parameterization of Cloud Mirophysics Based on Full Integral Moments, Journal of Atmospheric Sciences, 69, pp. 2229–2242, doi:10.1175/JAS-D-11-0268.1.
Belochitski A., P. Binev, R. DeVore, M. Fox-Rabinovitz, V. Krasnopolsky, and P. Lamby, 2011: Tree Approximation of the Long-Wave Radiation Parameterization in the NCAR CAM Global Climate Model, Journal of Computational and Applied Mathematics, 236, pp. 447-460, doi:10.1016/j.cam.2011.07.013.
Krasnopolsky V.M., M.S. Fox-Rabinovitz, Y.-T. Hou, S.J. Lord, and A.A. Belochitski, 2010: Accurate and Fast Neural Network Emulations of Model Radiation for the NCEP Coupled Climate Forecast System: Climate Simulations and Seasonal Predictions, Monthly Weather Review, 138, pp. 1822-1842, doi: 10.1175/2009MWR3149.1.
Krasnopolsky V. M., M. S. Fox-Rabinovitz, and A. A. Belochitski, 2008: Decadal Climate Simulations Using Accurate and Fast Neural Network Emulation of Full, Long-, and Short-wave Model Radiation, Monthly Weather Review, 136, pp. 683-3695, doi: 10.1175/2008MWR2385.1.
Fox-Rabinovitz, M., J. Cote, B. Dugas, M. Deque, J. McGregor, and A. Belochitski, 2008: Stretched-grid Model Intercomparison Project: Decadal Regional Climate Simulations with Enhanced Variable and Uniform-resolution GCMs, Meteorology and Atmospheric Physics, 100, pp. 159-178, doi:10.1007/s00703-008-0301-z.
V. M. Krasnopolsky, M.S. Fox-Rabinovitz, H.L. Tolman, and A. A. Belochitski, 2008: Neural Network Approach for Robust and Fast Calculation of Physical Processes in Numerical Environmental Models: Compound Parameterization with a Quality Control of Larger Errors, Neural Networks, 21, pp. 535-543, doi:10.1016/j.neunet.2007.12.019.
Chubarenko, B. V., L. Ch. Lund-Hansen, and A. A. Belochitski, 2002: Comparative Analysis of Potential Wind-wave Impact on Bottom Sediments in the Vistula and Curonian Lagoons. Baltica: an International Yearbook on Geology, Geomor- phology and Paleogeography of the Baltic Sea. Vol. 15, pp. 30-39., http://www.geo.lt/geo/uploads/media/30-39.pdf.
Fox-Rabinovitz M., V. Krasnopolsky, P. Rasch, Y. Kogan, and A. A. Belochitski, 2011: Development of Ensemble Neural Network Convection Parameterizations for Climate Models Using ARM Data, 21st ASR Science Team Meeting, March 28-April 1, 2011, San Antonio, TX.
V. M. Krasnopolsky, M.S. Fox-Rabinovitz,, and A. A. Belochitski, 2008: Ensembles of Numerical Climate and Weather Prediction Models Using Neural Network Emulations of Model Physics, IEEE World Congress on Artificial Intelligence, Hong Kong, June 1-6, 2008, CD-ROM, pp. 1524-1531.
Belochitski A. A. and Y. L. Kogan, 2006: Relationship Between m-Mode Gamma Type Cloud Drop Size Distributions and Their Integral Moments, Eos Trans. AGU, Jt. Assem. Suppl., 87(36).
Krasnopolsky V.M., A.A. Belochitski, Y.-T. Hou, S.J. Lord, and F. Yang, 2012: Accurate and Fast Neural Network Emulations of Long and Short Wave Radiation for the NCEP Global Forecast System Model, NCEP Office Note 471, Camp Springs, MD.
Krasnopolsky V., M. Fox-Rabinovitz, A. A. Belochitski, P. Rasch, P. Blossey, and Y. Kogan, 2011: Development of Neural Network Convection Parameterizations for Climate and NWP Models Using Cloud Resolving Model Simulations, NCEP Office Note 469, Camp Springs, MD.