Convective Modeling and Predictabilty Studies
{'Code': '06020102', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
{'SignBlockName': 'Robert W. Taylor', 'PO_EMAI': None, 'PO_PHON': None}
There is an inherent limit to the predictability of                        atmospheric numerical models.  The principal reason for this                    limit is generally considered to be the nonlinear interactions                  between different components of the wave spectrum; uncertainties                and errors in the wave spectrum resolvable by the model and                     errors introduced by the neglect of unresolved waves grow with                  integration in time, spreading throughout the spectrum, and                     eventually destroy the forecast.  Meteorologists now have some                  understanding of predictability of large scale models used for                  weather forecast; the spatial resolution is roughly hundreds of                 kilometers.  Numerical models for convective- and meso- scale                   meteorological events have grown in sophistication in recent                    years, the question of predictability can now be investigated.                  The spatial resolution of convective-scale models is roughly 1-2                km, and 20-100 km for mesoscale models.                                                                                                                              Under this award, Professor Droegemeier will investigate the               predictability of a convective-scale model, which has been used                 to study the dynamics of thunderstorm outflow and microbursts and               demonstrated some success in simulating these convective-scale                  events.  Besides examining the sensitivity of the model                         prediction to different aspects of the initial conditions,                      Professor Droegemeier will look for ways to initialize the model                with direct Doppler radar observations; he will also continue his               work on adapting the Piecewise Parabolic Method to meteorological               problems.
{'FirstName': 'Kelvin', 'LastName': 'Droegemeier', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kelvin K Droegemeier', 'EmailAddress': 'kkd@illinois.edu', 'NSF_ID': '000409756', 'StartDate': '02/15/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'ZipCode': '730193003', 'PhoneNumber': '4053254757', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OK04', 'ORG_UEI_NUM': 'EVTSTTLCEWS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '152200', 'Text': 'PHYSICAL METEOROLOGY'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8815371.xml'}