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Physical Sciences and Mathematics Commons™
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Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Ensemble Prediction And Data Assimilation For Operational Hydrology, Dong-Jun Seo, Yuqiong Liu, Hamid Moradkhani, Albrecht Weerts
Ensemble Prediction And Data Assimilation For Operational Hydrology, Dong-Jun Seo, Yuqiong Liu, Hamid Moradkhani, Albrecht Weerts
Civil and Environmental Engineering Faculty Publications and Presentations
This special section in the Journal of Hydrology will discuss the need for advancing hydrologic ensemble prediction and DA.
Toward A Reliable Prediction Of Seasonal Forecast Uncertainty: Addressing Model And Initial Condition Uncertainty With Ensemble Data Assimilation And Sequential Bayesian Combination, Caleb Matthew Dechant, Hamid Moradkhani
Toward A Reliable Prediction Of Seasonal Forecast Uncertainty: Addressing Model And Initial Condition Uncertainty With Ensemble Data Assimilation And Sequential Bayesian Combination, Caleb Matthew Dechant, Hamid Moradkhani
Civil and Environmental Engineering Faculty Publications and Presentations
Uncertainties are an unfortunate yet inevitable part of any forecasting system. Within the context of seasonal hydrologic predictions, these uncertainties can be attributed to three causes: imperfect characterization of initial conditions, an incomplete knowledge of future climate and errors within computational models. This study proposes a method to account for all threes sources of uncertainty, providing a framework to reduce uncertainty and accurately convey persistent predictive uncertainty. In currently available forecast products, only a partial accounting of uncertainty is performed, with the focus primarily on meteorological forcing. For example, the Ensemble Streamflow Prediction (ESP) technique uses meteorological climatology to estimate …