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Ensemble Hydrometeorological Forecasts Using WRF Hourly QPF and TopModel for a Middle Watershed
Author(s) -
Leonardo Calvetti,
Augusto José Pereira Filho
Publication year - 2014
Publication title -
advances in meteorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 32
eISSN - 1687-9317
pISSN - 1687-9309
DOI - 10.1155/2014/484120
Subject(s) - weather research and forecasting model , hydrometeorology , quantitative precipitation forecast , predictability , precipitation , meteorology , climatology , environmental science , watershed , ensemble forecasting , forecast skill , data assimilation , geography , computer science , statistics , mathematics , machine learning , geology
Quantitative precipitation forecasts (QPFs) were obtained from ensembles of the weather and research forecasting (WRF) model\udfor the Iguac¸u river watershed (IRW) in southern Brazil. Thirty-two rainfall events between 2005 and 2010 were simulated with\udten configurations of WRF. These rainfall events range from local to synoptic scale convection and caused a significant increase\udin the level of the Iguac¸u river. In the average, the ensembles yielded up to 20% better skill than single WRF forecasts for the\udevents analyzed.WRF ensembles also allow estimating the predictability through the dispersion of the forecasts providing relevant\udinformation for decision-making. Phase errors of ensemble forecasts are larger than amplitude errors.More complex microphysics\udparameterizations yielded better QPFs with smaller phase errors. QPFs were fed to IRWhydrological model with similar phase and\udamplitude errors. It is suggested that lagged QPFs might reduce phase errorsSIMEPARCNPq - 201341/2009-3, 304033/2011-

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