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Assessment of a multimodel ensemble against an operational hydrological forecasting system
Ensemble forecasts present an alternative to traditional deterministic forecasts by providing information about the likelihood of various outcomes. An ensemble can be constructed wherever errors are likely to occur within a hydrometeorological forecasting chain. This study compares the hydrological performance of a multimodel ensemble against deterministic forecasts issued by an operational forecasting system, in terms of accuracy and reliability. This comparison is carried out on 38 catchments in the province of Québec for more than 2 years of 6-day-ahead forecasts. The multimodel ensemble is comprised of 20 lumped conceptual models pooled together, while the reference forecast originates from an operational semi-distributed model. The results show that probabilistic forecast outperforms its deterministic counterpart and the deterministic operational forecast system, thanks to the role that each member plays inside the multimodel ensemble. This analysis demonstrates that the multimodel ensemble is potentially an operational tool, even though the specific setup for this study still suffers from underdispersion and needs to take into account additional sources of uncertainty to reach an optimal framework.
Assessment of a multimodel ensemble against an operational hydrological forecasting system
Ensemble forecasts present an alternative to traditional deterministic forecasts by providing information about the likelihood of various outcomes. An ensemble can be constructed wherever errors are likely to occur within a hydrometeorological forecasting chain. This study compares the hydrological performance of a multimodel ensemble against deterministic forecasts issued by an operational forecasting system, in terms of accuracy and reliability. This comparison is carried out on 38 catchments in the province of Québec for more than 2 years of 6-day-ahead forecasts. The multimodel ensemble is comprised of 20 lumped conceptual models pooled together, while the reference forecast originates from an operational semi-distributed model. The results show that probabilistic forecast outperforms its deterministic counterpart and the deterministic operational forecast system, thanks to the role that each member plays inside the multimodel ensemble. This analysis demonstrates that the multimodel ensemble is potentially an operational tool, even though the specific setup for this study still suffers from underdispersion and needs to take into account additional sources of uncertainty to reach an optimal framework.
Assessment of a multimodel ensemble against an operational hydrological forecasting system
Thiboult, A (author) / Anctil, F
2015
Article (Journal)
English
Local classification TIB:
385/6615
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