The Experts below are selected from a list of 204 Experts worldwide ranked by ideXlab platform
Florian Pappenberger - One of the best experts on this subject based on the ideXlab platform.
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Connecting science, operations and decision-making when communicating uncertainty in hydro-Meteorological Forecasting
2020Co-Authors: Maria-helena Ramos, Florian PappenbergerAbstract:<p>Almost ten years ago, we published a paper where we raised the question whether effective communication of uncertainty in hydro-Meteorological forecasts was an impossible mission (Ramos et al. Meteorol. Appl. 17: 223&#8211;235, 2010, DOI: 10.1002/met.202). We wanted to understand if the multiple ways of interpreting uncertainty, as well as the multiple users and Forecasting situations affecting forecast display and confidence, could hamper probabilistic forecast communication in operational hydrological Forecasting. We looked at the main general interconnections present in a typical flood Forecasting and alert chain, the challenges of extracting meaningful information from probabilistic forecasts and the way ensemble forecasts were effectively used in flood warning and decision-making. At the end, we were optimistic to say that the &#8220;mission is not impossible, although the tasks to be executed might be difficult to accomplish.&#8221; Here, we discuss a follow-up question: what have we accomplished in terms of communicating uncertainty in hydrological forecasts in practice, and contributing to better inform decision-making? The impact of forecasts, in terms of, for instance, anticipation of extreme events and crisis management, depends on how good they are but also on how they are understood and used in practice. This requires connecting science, operations and decision-making through the Forecasting chain. We present some experiments with role-play games and benchmarking skilful streamflow forecasts developed to better understand the way probabilistic predictions can support decisions, and discuss where successes were achieved and challenges remain.</p>
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developing a global operational seasonal hydro Meteorological Forecasting system glofas seasonal v1 0
Geoscientific Model Development, 2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Elisabeth Stephens, Peter Salamon, Florian PappenbergerAbstract:Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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Developing a global operational seasonal hydro-Meteorological Forecasting system: GloFAS v2.2 Seasonal v1.0
2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Peter Salamon, Elisabeth M. Stephens, Florian PappenbergerAbstract:<p><strong>Abstract.</strong> Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.</p>
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Forecast convergence score: a forecaster's approach to analysing hydro-Meteorological forecast systems.
Advances in Geosciences, 2011Co-Authors: Florian Pappenberger, Hannah Cloke, Konrad Bogner, Fredrik Wetterhall, Y. He, Jutta ThielenAbstract:In this paper the properties of a hydro-Meteorological Forecasting system for Forecasting river flows have been analysed using a probabilistic forecast convergence score (FCS). The focus on fixed event forecasts provides a forecaster's approach to system behaviour and adds an important perspective to the suite of forecast verification tools commonly used in this field. A low FCS indicates a more consistent forecast. It can be demonstrated that the FCS annual maximum decreases over the last 10 years. With lead time, the FCS of the ensemble forecast decreases whereas the control and high resolution forecast increase. The FCS is influenced by the lead time, threshold and catchment size and location. It indicates that one should use seasonality based decision rules to issue flood warnings.
Christel Prudhomme - One of the best experts on this subject based on the ideXlab platform.
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developing a global operational seasonal hydro Meteorological Forecasting system glofas seasonal v1 0
Geoscientific Model Development, 2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Elisabeth Stephens, Peter Salamon, Florian PappenbergerAbstract:Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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Developing a global operational seasonal hydro-Meteorological Forecasting system: GloFAS v2.2 Seasonal v1.0
2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Peter Salamon, Elisabeth M. Stephens, Florian PappenbergerAbstract:<p><strong>Abstract.</strong> Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.</p>
Rebecca Emerton - One of the best experts on this subject based on the ideXlab platform.
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developing a global operational seasonal hydro Meteorological Forecasting system glofas seasonal v1 0
Geoscientific Model Development, 2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Elisabeth Stephens, Peter Salamon, Florian PappenbergerAbstract:Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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Developing a global operational seasonal hydro-Meteorological Forecasting system: GloFAS v2.2 Seasonal v1.0
2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Peter Salamon, Elisabeth M. Stephens, Florian PappenbergerAbstract:<p><strong>Abstract.</strong> Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.</p>
Hannah Cloke - One of the best experts on this subject based on the ideXlab platform.
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developing a global operational seasonal hydro Meteorological Forecasting system glofas seasonal v1 0
Geoscientific Model Development, 2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Elisabeth Stephens, Peter Salamon, Florian PappenbergerAbstract:Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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Developing a global operational seasonal hydro-Meteorological Forecasting system: GloFAS v2.2 Seasonal v1.0
2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Peter Salamon, Elisabeth M. Stephens, Florian PappenbergerAbstract:<p><strong>Abstract.</strong> Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.</p>
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Forecast convergence score: a forecaster's approach to analysing hydro-Meteorological forecast systems.
Advances in Geosciences, 2011Co-Authors: Florian Pappenberger, Hannah Cloke, Konrad Bogner, Fredrik Wetterhall, Y. He, Jutta ThielenAbstract:In this paper the properties of a hydro-Meteorological Forecasting system for Forecasting river flows have been analysed using a probabilistic forecast convergence score (FCS). The focus on fixed event forecasts provides a forecaster's approach to system behaviour and adds an important perspective to the suite of forecast verification tools commonly used in this field. A low FCS indicates a more consistent forecast. It can be demonstrated that the FCS annual maximum decreases over the last 10 years. With lead time, the FCS of the ensemble forecast decreases whereas the control and high resolution forecast increase. The FCS is influenced by the lead time, threshold and catchment size and location. It indicates that one should use seasonality based decision rules to issue flood warnings.
Ervin Zsoter - One of the best experts on this subject based on the ideXlab platform.
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developing a global operational seasonal hydro Meteorological Forecasting system glofas seasonal v1 0
Geoscientific Model Development, 2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Elisabeth Stephens, Peter Salamon, Florian PappenbergerAbstract:Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.
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Developing a global operational seasonal hydro-Meteorological Forecasting system: GloFAS v2.2 Seasonal v1.0
2018Co-Authors: Rebecca Emerton, Ervin Zsoter, Louise Arnal, Hannah Cloke, D Muraro, Christel Prudhomme, Peter Salamon, Elisabeth M. Stephens, Florian PappenbergerAbstract:<p><strong>Abstract.</strong> Global overviews of upcoming flood and drought events are key for many applications, including disaster risk reduction initiatives. Seasonal forecasts are designed to provide early indications of such events weeks, or even months, in advance, but seasonal forecasts for hydrological variables at large or global scales are few and far between. Here, we present the first operational global scale seasonal hydro-Meteorological Forecasting system: GloFAS-Seasonal. Developed as an extension of the Global Flood Awareness System (GloFAS), GloFAS-Seasonal couples seasonal Meteorological forecasts from ECMWF with a hydrological model, to provide openly available probabilistic forecasts of river flow out to 4 months ahead for the global river network. This system has potential benefits not only for disaster risk reduction through early awareness of floods and droughts, but also for water-related sectors such as agriculture and water resources management, in particular for regions where no other Forecasting system exists. We describe the key hydro-Meteorological components and computational framework of GloFAS-Seasonal, alongside the forecast products available, before discussing initial evaluation results and next steps.</p>
