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dc.contributor.authorFranz, Kristie J.
dc.contributor.authorHartmann, Holly C.
dc.contributor.authorSorooshian, Soroosh
dc.contributor.authorBales, Roger
dc.date.accessioned2016-07-07T22:22:22Z
dc.date.available2016-07-07T22:22:22Z
dc.date.issued2003-01
dc.identifier.urihttp://hdl.handle.net/10150/615761
dc.description.abstractThe National Weather Service (NWS) developed the Ensemble Streamflow Prediction (ESP) system to generate probabilistic water supply forecasts that consist of an ensemble of streamflow traces (scenarios) conditioned on the initial states of the basin. Uncertainty information available from ESP may be more useful to risk-based decision makers than what is currently provided by linear regression forecasts. Because the use of ESP has been limited to date, there are few operational forecasts available for verification. Therefore, it was necessary to generate simulated operational ESP forecasts to test the forecasting procedure's potential to enhance current forecasting techniques. Simulated historical forecasts were generated for 14 forecast points in the Colorado River basin. The median and best forecast traces were analyzed as representations of ESP deterministic forecasts. General scalar statistics were used to evaluate these traces. The probability information contained in the entire ensemble was analyzed using probabilistic and conditional verification methods. It was found that the information contained in the median trace is limited and that choosing one trace is not the optimal use of ESP forecast information. ESP provides a probabilistic forecast that performs better than a probabilistic forecast based on climatology. In addition, ESP can provide accurate information about the magnitude of future streamflow discharge even at lead times of up to seven months. With shorter lead times (2-3 months), the forecasts become more informative and accurate.
dc.description.sponsorshipPrimary financial support for this research was provided by the Climate Assessment for the Southwest Project (CLIMAS) under the NOAA Grant #NA86GP0061 from the NOAA Office of Global Programs. Partial supported was provided by the National Science Foundation Science and Technology Center for "Sustainability of Semi - Arid Hydrology and Riparian Areas" (SAHRA), Agreement No. EAR -9876800; the Hydrologic Data Information System (HyDIS) program; a partial grant from the National Science Foundation Graduate Research Trainee Program; and the University of Arizona Graduate College Fellowship.en
dc.language.isoen_USen
dc.publisherDepartment of Hydrology and Water Resources, University of Arizona (Tucson, AZ)en
dc.relation.ispartofseriesTechnical Reports on Hydrology and Water Resources, No. 03-010en
dc.rightsCopyright © Arizona Board of Regentsen
dc.sourceProvided by the Department of Hydrology and Water Resources.en
dc.titleEvaluation of national weather service ensemble streamflow predictions (ESP) for the Colorado river basinen_US
dc.typetexten
dc.typeTechnical Reporten
dc.contributor.departmentDepartment of Hydrology & Water Resources, The University of Arizonaen
dc.description.collectioninformationThis title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.en
refterms.dateFOA2018-04-26T01:45:13Z
html.description.abstractThe National Weather Service (NWS) developed the Ensemble Streamflow Prediction (ESP) system to generate probabilistic water supply forecasts that consist of an ensemble of streamflow traces (scenarios) conditioned on the initial states of the basin. Uncertainty information available from ESP may be more useful to risk-based decision makers than what is currently provided by linear regression forecasts. Because the use of ESP has been limited to date, there are few operational forecasts available for verification. Therefore, it was necessary to generate simulated operational ESP forecasts to test the forecasting procedure's potential to enhance current forecasting techniques. Simulated historical forecasts were generated for 14 forecast points in the Colorado River basin. The median and best forecast traces were analyzed as representations of ESP deterministic forecasts. General scalar statistics were used to evaluate these traces. The probability information contained in the entire ensemble was analyzed using probabilistic and conditional verification methods. It was found that the information contained in the median trace is limited and that choosing one trace is not the optimal use of ESP forecast information. ESP provides a probabilistic forecast that performs better than a probabilistic forecast based on climatology. In addition, ESP can provide accurate information about the magnitude of future streamflow discharge even at lead times of up to seven months. With shorter lead times (2-3 months), the forecasts become more informative and accurate.


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