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| Titel |
HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts" |
| VerfasserIn |
F. Wetterhall, F. Pappenberger, L. Alfieri, H. L. Cloke, J. Thielen-del Pozo, S. Balabanova, J. Daňhelka, A. Vogelbacher, P. Salamon, I. Carrasco, A. J. Cabrera-Tordera, M. Corzo-Toscano, M. Garcia-Padilla, R. J. Garcia-Sanchez, C. Ardilouze, S. Jurela, B. Terek, A. Csik, J. Casey, G. Stankūnavičius, V. Ceres, E. Sprokkereef, J. Stam, E. Anghel, D. Vladikovic, C. Alionte Eklund, N. Hjerdt, H. Djerv, F. Holmberg, J. Nilsson, K. Nyström, M. Sušnik, M. Hazlinger, M. Holubecka |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 11 ; Nr. 17, no. 11 (2013-11-07), S.4389-4399 |
| Datensatznummer |
250085986
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| Publikation (Nr.) |
 copernicus.org/hess-17-4389-2013.pdf |
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| Zusammenfassung |
| Hydrological ensemble prediction systems (HEPS) have in recent years been
increasingly used for the operational forecasting of floods by European
hydrometeorological agencies. The most obvious advantage of HEPS is that
more of the uncertainty in the modelling system can be assessed. In
addition, ensemble prediction systems generally have better skill than
deterministic systems both in the terms of the mean forecast performance and
the potential forecasting of extreme events. Research efforts have so far
mostly been devoted to the improvement of the physical and technical aspects
of the model systems, such as increased resolution in time and space and
better description of physical processes. Developments like these are
certainly needed; however, in this paper we argue that there are other areas
of HEPS that need urgent attention. This was also the result from a
group exercise and a survey conducted to operational forecasters within the
European Flood Awareness System (EFAS) to identify the top priorities of
improvement regarding their own system. They turned out to span a range of
areas, the most popular being to include verification of an assessment of past
forecast performance, a multi-model approach for hydrological modelling, to
increase the forecast skill on the medium range (>3 days) and
more focus on education and training on the interpretation of forecasts. In
light of limited resources, we suggest a simple model to classify the
identified priorities in terms of their cost and complexity to decide in
which order to tackle them. This model is then used to create an action plan
of short-, medium- and long-term research priorities with the ultimate goal
of an optimal improvement of EFAS in particular and to spur the
development of operational HEPS in general. |
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