High resolution numerical weather prediction over the Indian subcontinent |
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| Authors: | T S V Vijaya Kumar T N Krishnamurti |
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| Institution: | (1) Department of Meteorology, Florida State University, 32306-4520 Tallahassee, Fl, USA;(2) Present address: Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, Maryland, USA |
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| Abstract: | In this study, the Florida State University Global Spectral Model (FSUGSM), in association with a high-resolution nested regional
spectral model (FSUNRSM), is used for short-range weather forecasts over the Indian domain. Three-day forecasts for each day
of August 1998 were performed using different versions of the FSUGSM and FSUNRSM and were compared with the observed fields
(analysis) obtained from the European Center for Medium Range Weather Forecasts (ECMWF). The impact of physical initialization
(a procedure that assimilates observed rain rates into the model atmosphere through a set of reverse algorithms) on rainfall
forecasts was examined in detail. A very high nowcasting skill for precipitation is obtained through the use of high-resolution
physical initialization applied at the regional model level. Higher skills in wind and precipitation forecasts over the Indian
summer monsoon region are achieved using this version of the regional model with physical initialization.
A relatively new concept, called the ‘multimodel/multianalysis superensemble’ is described in this paper and is applied for
the wind and precipitation forecasts over the Indian subcontinent. Large improvement in forecast skills of wind at 850 hPa
level over the Indian subcontinent is shown possible through the use of the multimodel superensemble. The multianalysis superensemble
approach that uses the latest satellite data from the Tropical Rainfall Measuring Mission (TRMM) and the Defense Meteorological
Satellite Program (DMSP) has shown significant improvement in the skills of precipitation forecasts over the Indian monsoon
region. |
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| Keywords: | Numerical weather prediction spectral modeling physical initialization high resolution regional models multimodel superensemble forecasts |
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