Toward Applications of Stochastic Dynamic Prediction
{'Code': '06020107', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
{'SignBlockName': 'Pamela L. Stephens', 'PO_EMAI': None, 'PO_PHON': None}
The purpose of this research is to advance the theory and                  application of stochastic dynamic prediction (SDP).  SDP                        equations predict the mean and other statistical properties of                  an infinite ensemble of points in phase space.  Current                         deterministic prediction models provide forecasts of the                        future state of the atmosphere, but these forecasts are less                    than perfect due to uncertainties in the initial conditions                     and in the model dynamics.  Ideally, one also would like to be                  able to estimate the quality of the forecast.  SDP may provide                  a way to do so.  The benefits are obvious.  The feasibility is                  uncertain due to the magnitude of the computations involved and                 the complexity of the physics of the atmosphere.  The PI plans                  to explore certain aspects of the problem using several                         promising approaches developed by himself and Dr. Philip                        Thompson of the National Center for Atmospheric Research.                            The results of this research have potential application                    in a wide variety of fields involving fluid motions.
{'FirstName': 'Rex', 'LastName': 'Fleming', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rex J Fleming', 'EmailAddress': None, 'PI_PHON': None, 'NSF_ID': '000403533', 'StartDate': '07/15/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
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[{'Code': '1527', 'Text': 'LARGE-SCALE DYNAMIC METEOROLOG'}, {'Code': '5730', 'Text': 'GLOBAL ATMOSPHERIC RESEARCH'}]
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