Enhancing the Value of Weather and Climate Services in Society: Identified Gaps and Needs as Outcomes of the First WMO WWRP/SERA Weather and Society Conference

Göber, Martin; Christel, Isadora; Hoffmann, David; Mooney, Carla; Rodríguez, Luis; Becker, Nico; Ebert, Elizabeth E.; Fearnley, Carina; Fundel, Vanessa J.; Geiger, Tobias; Golding, Brian; Jeurig, Jelmer; Kelman, Ilan; Kox, Thomas; Magro, France-Audrey; Perrels, Adriaan; Postigo, Julio C.; Potter, Sally H.; Robbins, Joanne; Rust, Henning W.; Schoster, Daniela; Tan, Marion Lara; Taylor, Andrea; Williams, Hywel T. P.

doi:10.1175/bams-d-22-0199.1

Cited by 8 publications

(5 citation statements)

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“…On the other hand, the transferability of knowledge and seasonal forecasting techniques for identifying solutions across local studies is crucial to maximize the global efficacy (Jackson-Blake et al 2022, Dasgupta et al 2023, Göber et al 2023. Our study highlights the significance of attributing predictability to local hydrological characteristics and enables the knowledge to be regionalized and transferred to other (ungauged) geographical locations.…”

Section: Practical Implicationsmentioning

confidence: 80%

“…Beyond the severe consequences of individual hazards (Schumacher et al 2022, Mondal et al 2023, the potential for compound and cascading effects further extends their impacts in space and time. To assist societal adaptation aiming to mitigate the effects, flood and drought early warning and hydro-climatic services are needed to provide accurate information on the impacts of water-related hazards (Merz et al 2020, Göber et al 2023, and our study contributes towards the evolution of these services.…”

Section: Practical Implicationsmentioning

confidence: 97%

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Hydrological regimes explain the seasonal predictability of streamflow extremes

Du,

Clemenzi,

Pechlivanidis

2023

Environ. Res. Lett.

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Advances in hydrological modeling and numerical weather forecasting have allowed hydro-climate services to provide accurate impact simulations and skillful forecasts that can drive decisions at the local scale. To enhance early warnings and long-term risk reduction actions, it is imperative to better understand the hydrological extremes and explore the drivers for their predictability. Here, we investigate the seasonal forecast skill of streamflow extremes over the pan-European domain, and further attribute the discrepancy in their predictability to the local river system memory as described by the hydrological regimes. Streamflow forecasts at about 35 400 basins, generated from the E-HYPE hydrological model driven with bias-adjusted ECMWF SEAS5 meteorological forcing input, are explored. Overall the results show adequate predictability for both hydrological extremes over Europe, despite the spatial variability in skill. The skill of high streamflow extreme deteriorates faster as a function of lead time than that of low extreme, with a positive skill persisting up to 12 and 20 weeks ahead for high and low extremes, respectively. A strong link between the predictability of extremes and the underlying local hydrological regime is identified through comparative analysis, indicating that systems of analogous river memory, e.g. fast or slow response to rainfall, can similarly predict the high and low streamflow extremes. The results improve our understanding of the geographical areas and periods, where the seasonal forecasts can timely provide information on very high and low streamflow conditions, including the drivers controlling their predictability. This consequently benefits regional and national organizations to embrace seasonal prediction systems and improve the capacity to act in order to reduce disaster risk and support climate adaptation.

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Section: Practical Implicationsmentioning

confidence: 80%

Section: Practical Implicationsmentioning

confidence: 97%

Hydrological regimes explain the seasonal predictability of streamflow extremes

Du,

Clemenzi,

Pechlivanidis

2023

Environ. Res. Lett.

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show abstract

“…As exposure and vulnerabilities are anticipated to rise, socio‐economic impacts are consequently expected to increase in space and time, including intensified detrimental consequences from compound and cascading effects affecting various sectors simultaneously (Brás et al, 2021; de Brito, 2021; Schumacher et al, 2022). This highlights the urgency for targeted adaptation actions that can lead to drought mitigation, including for instance the implementation of accurate impact‐based DEWS (Göber et al, 2023). Improvements in the accuracy in drought IbF can specifically be achieved through the recent evolution of the ML field and increased availability of impact datasets to train the data‐driven models (Torelló‐Sentelles & Franzke, 2021).…”

Section: Implications and Actions To Improve Ibf Dewsmentioning

confidence: 99%

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Shyrokaya,

Pappenberger,

Pechlivanidis

et al. 2023

WIREs Water

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Advances in impact modeling and numerical weather forecasting have allowed accurate drought monitoring and skilful forecasts that can drive decisions at the regional scale. State‐of‐the‐art drought early‐warning systems are currently based on statistical drought indicators, which do not account for dynamic regional vulnerabilities, and hence neglect the socio‐economic impact for initiating actions. The transition from conventional physical forecasts of droughts toward impact‐based forecasting (IbF) is a recent paradigm shift in early warning services, to ultimately bridge the gap between science and action. The demand to generate predictions of “what the weather will do” underpins the rising interest in drought IbF across all weather‐sensitive sectors. Despite the large expected socio‐economic benefits, migrating to this new paradigm presents myriad challenges. In this article, we provide a comprehensive overview of drought IbF, outlining the progress made in the field. Additionally, we present a road map highlighting current challenges and limitations in the science and practice of drought IbF and possible ways forward. We identify seven scientific and practical challenges/limitations: the contextual challenge (inadequate accounting for the spatio‐sectoral dynamics of vulnerability and exposure), the human‐water feedbacks challenge (neglecting how human activities influence the propagation of drought), the typology challenge (oversimplifying drought typology to meteorological), the model challenge (reliance on mainstream machine learning models), and the data challenge (mainly textual) with the linked sectoral and geographical limitations. Our vision is to facilitate the progress of drought IbF and its use in making informed and timely decisions on mitigation measures, thus minimizing the drought impacts globally.This article is categorized under: Science of Water > Water Extremes Science of Water > Methods Science of Water > Water and Environmental Change

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“…As exposure and vulnerabilities are anticipated to rise, socio-economic impacts are consequently expected to increase in space and time, including intensified detrimental consequences from compound and cascading effects affecting various sectors simultaneously (Br as et al, 2021;de Brito, 2021;Schumacher et al, 2022). This highlights the urgency for targeted adaptation actions that can lead to drought mitigation, including for instance the implementation of accurate impact-based DEWS (Göber et al, 2023). Improvements in the accuracy in drought IbF can specifically be achieved through the recent evolution of the ML field and increased availability of impact datasets to train the datadriven models .…”

Section: Implications and Actions To Improve Ibf Dewsmentioning

confidence: 99%

Advances and gaps in the science and practice of impact-based forecasting of droughts

Shyrokaya

Pappenberger

Pechlivanidis

et al. 2023

Preprint

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Advances in impact modelling and numerical weather forecasting have allowed accurate drought monitoring and skillful forecasts that can drive decisions at the regional scale. State-of-the-art drought early warning systems are currently based on statistical drought indicators, which do not account for regional vulnerabilities, and hence neglect the socio-economic impact for initiating actions. The transition from conventional physical forecasts of droughts towards impact-based forecasting (IbF) is a recent paradigm shift in early warning services, to ultimately bridge the gap between science and action. The demand to generate predictions of “what the weather will do” underpins the rising interest in drought IbF across all weather-sensitive sectors. Despite the socio-economic benefits are expected to be high, migrating to this new paradigm presents myriad challenges. In this paper, we outline the progress in IbF of drought, and present a road map highlighting current challenges and corresponding needs for advancing this emerging field. More specifically, we identify the main disconnects and biases of the science and practice of IbF of drought, namely contextual bias (inadequate accounting for the spatio-sectoral dynamics of vulnerability and exposure), data bias (mainly textual and lacking collection protocols for all sectors), model bias (mostly reliant on machine learning models), sectoral bias (mainly agriculture in the science), and geography (mainly Europe for the science, and developing regions in the practice). Our vision is to facilitate the IbF progress and its use in making informed and timely decisions on mitigation measures, thus minimizing the impacts of droughts globally.           

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Enhancing the Value of Weather and Climate Services in Society: Identified Gaps and Needs as Outcomes of the First WMO WWRP/SERA Weather and Society Conference

Abstract: Enhancing the value of weather and climate services in society -identified gaps and needs as outcomes of the 1st WMO WWRP/SERA "Weather and Society" Conference

Cited by 8 publications

References 0 publications

Hydrological regimes explain the seasonal predictability of streamflow extremes

Hydrological regimes explain the seasonal predictability of streamflow extremes

Advances and gaps in the science and practice of impact‐based forecasting of droughts

Advances and gaps in the science and practice of impact-based forecasting of droughts

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