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Your search keyword '"Thielen Del Pozo, J."' showing total 3 results
Start Over Author "Thielen Del Pozo, J." Topic weather forecasting
3 results on '"Thielen Del Pozo, J."'

1. JOINING FORCES IN A GLOBAL FLOOD PARTNERSHIP

Author

De Groeve, T., Thielen-del Pozo, J., Brakenridge, R., Adler, R., Alfieri, L., Kull, D., Lindsay, F., Imperiali, O., Pappenberger, F., Rudari, R., Salamon, P., Villars, N., and Wyjad, K.

Published
2015

2. The reduction continuous rank probability score for evaluating discharge forecasts from hydrological ensemble prediction systems

Author

Trinh, B.N., Thielen del-Pozo, J., Thirel, G., European Commission - Joint Research Centre [Ispra] (JRC), Hydrosystèmes et Bioprocédés (UR HBAN), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), and Hydrosystèmes et bioprocédés (UR HBAN)

Subjects
PREVISION DE DEBIT, STATISTICAL UNCERTAINTY, PREVISION DE CRUE, MODELE PROBABILISTE, INCERTITUDE, STREAMFLOW FORECAST, WEATHER FORECASTING, PREVISION METEOROLOGIQUE, HYDROLOGICAL FORECAST, PREVISION HYDROLOGIQUE, [SDE]Environmental Sciences, PROBABILISTIC MODEL, FLOOD FORECAST
Abstract

International audience; Ensemble prediction system (EPS) meteorological forecasts are increasingly being used as input to hydrological models in order to extend flood-warning lead-times and to improve forecasts and the knowledge of their uncertainty. Probabilistic skill scores classically used in meteorology are usually also utilized for assessing the quality of hydrological ensemble forecasts. However, the different river discharge magnitudes can make difficult the interpretation and comparisons of these scores, as it is for the continuous rank probability score (CRPS). In this letter, a novel 'Reduction' CRPS (RCRPS), which takes into account the different river discharge magnitudes, is proposed, and its usefulness is exhibited.

Published
2013

3. The reduction continuous rank probability score for evaluating discharge forecasts from hydrological ensemble prediction systems

Author

Trinh, B.N., Thielen del-Pozo, J., Thirel, Guillaume, European Commission - Joint Research Centre [Ispra] (JRC), Hydrosystèmes et bioprocédés (UR HBAN), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), and Hydrosystèmes et Bioprocédés (UR HBAN)

Subjects
PREVISION DE DEBIT, STATISTICAL UNCERTAINTY, PREVISION DE CRUE, MODELE PROBABILISTE, INCERTITUDE, WEATHER FORECASTING, STREAMFLOW FORECAST, PREVISION METEOROLOGIQUE, HYDROLOGICAL FORECAST, PREVISION HYDROLOGIQUE, [SDE]Environmental Sciences, PROBABILISTIC MODEL, FLOOD FORECAST
Abstract

Ensemble Prediction System (EPS) meteorological forecasts are increasingly being used as input to hydrological models in order to extend floodwarning leadtimes and to improve forecasts and the knowledge of their uncertainty. Probabilistic skill scores classically used in meteorology are usually also utilized for assessing the quality of hydrological ensemble forecasts. However, the different river discharge magnitudes can make difficult the interpretation and comparisons of these scores, as it is for the Continuous Rank Probability Score (CRPS). In this letter, a novel ‘Reduction’ CRPS (RCRPS), which takes into account the different river discharge magnitudes, is proposed, and its usefulness is exhibited., JRC.H.7-Climate Risk Management

Published
2012

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