Statistical verification of numerical weather prediction models for quantitative precipitation forecast
In this study, the potential of two numerical weather prediction (NWP) models in quantitative precipitation forecasting over a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models...
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Published in | 2011 IEEE Colloquium on Humanities, Science and Engineering pp. 88 - 92 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2011
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Subjects | |
Online Access | Get full text |
ISBN | 1467300217 9781467300216 |
DOI | 10.1109/CHUSER.2011.6163865 |
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Summary: | In this study, the potential of two numerical weather prediction (NWP) models in quantitative precipitation forecasting over a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models are statistically verified with the observed rain in Kelantan River Basin, Malaysia. The statistical verification indicates that the root mean squared error (RMSE) increases for higher rainfall rate, though the models have performed quite satisfactorily in certain cases during heavy rainfalls that cause flood. It is also shown that the longer the rainfall forecast duration, the higher the probability of detection (POD) and the lesser probability to be the false alarm ratio (FAR). |
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ISBN: | 1467300217 9781467300216 |
DOI: | 10.1109/CHUSER.2011.6163865 |