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

Author:

Shyrokaya Anastasiya12ORCID,Pappenberger Florian3,Pechlivanidis Ilias4ORCID,Messori Gabriele1256,Khatami Sina127ORCID,Mazzoleni Maurizio28ORCID,Di Baldassarre Giuliano12

Affiliation:

1. Department of Earth Sciences Uppsala University Uppsala Sweden

2. Centre of Natural Hazards and Disaster Science (CNDS) Uppsala Sweden

3. European Centre for Medium‐Range Weather Forecasts (ECMWF) Reading UK

4. Swedish Meteorological and Hydrological Institute (SMHI) Norrköping Sweden

5. Department of Meteorology Stockholm University Stockholm Sweden

6. Bolin Centre for Climate Research Stockholm University Stockholm Sweden

7. Department of Infrastructure Engineering University of Melbourne Parkville Victoria Australia

8. Institute for Environmental Studies, Vrije Universiteit Amsterdam Amsterdam the Netherlands

Abstract

AbstractAdvances 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

Funder

European Research Council

Publisher

Wiley

Subject

Management, Monitoring, Policy and Law,Ocean Engineering,Water Science and Technology,Aquatic Science,Ecology,Oceanography

Reference123 articles.

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2. Niger (WFP: REAP Project)REAP: Forecast‐based financing (FbF) system for drought.https://www.anticipation-hub.org/Documents/Case_Studies/REAP_Case_Study-Niger-FINAL.pdf

3. Zimbabwe and Ethiopia (Red Cross Netherlands)IBF: Drought impact‐based trigger warning model.https://www.510.global/ibf-drought-trigger-warning-model/

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