P1.51
Improving Short Term Precipitation Forecasting through recognition of satellite based signatures combined with analysis of upper air and surface data
John Simko, NOAA/NESDIS, Camp Springs, MD
In most cases, short term numerical model quantitative precipitation forecast guidance for heavy rainfall events is reliable. There are times however when model precipitation forecast guidance is not quite as accurate as it could be due to its inherent limitations. Examples of these limitations include systems affecting the West Coast of the United States where the lack of data over the Pacific Ocean can have an adverse affect on model initialization and the subsequent short term precipitation forecast. Sub-grid scale processes, such as those modeled by convective parameterization schemes, can also lead to model forecast errors and poor short term rainfall forecasts. The recognition of a developing heavy rainfall event can be obtained through the Geostationary Operational Environmental Satellites (GOES) Infrared/Visible Channels along with analysis of data received from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I), the National Oceanic Atmospheric Administration (NOAA) Advanced Microwave Sounder Unit (AMSU), and the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) polar orbiting satellites. In some of these cases the use of satellite data combined with surface and upper air data analysis near the beginning of the precipitation event or even just prior to the onset of the event can improve short term quantitative precipitation forecasts in both location and quantity and serve as an alert to the potential of an excessive rainfall event.
Poster Session 1, Conference Posters
Monday, 1 August 2005, 5:30 PM-7:00 PM, Regency Ballroom
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