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Impact Forecasting to Support Emergency Management of Natural Hazards

Merz, Bruno; Kuhlicke, Christian; Kunz, Michael ORCID iD icon 1; Pittore, Massimiliano; Babeyko, Andrey; Bresch, David N.; Domeisen, Daniela I. V.; Feser, Frauke; Koszalka, Inga; Kreibich, Heidi; Pantillon, Florian 1; Parolai, Stefano; Pinto, Joaquim G. 1; Punge, Heinz Jürgen 1; Rivalta, Eleonora; Schröter, Kai; Strehlow, Karen; Weisse, Ralf; Wurpts, Andreas
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)


Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.

Verlagsausgabe §
DOI: 10.5445/IR/1000123885
Veröffentlicht am 27.03.2021
DOI: 10.1029/2020RG000704
Zitationen: 104
Web of Science
Zitationen: 93
Zitationen: 136
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2020
Sprache Englisch
Identifikator ISSN: 8755-1209, 1944-9208
KITopen-ID: 1000123885
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Reviews of geophysics
Verlag American Geophysical Union (AGU)
Band 58
Heft 4
Seiten e2020RG000704
Vorab online veröffentlicht am 24.08.2020
Nachgewiesen in Dimensions
Web of Science
Globale Ziele für nachhaltige Entwicklung Ziel 11 – Nachhaltige Städte und Gemeinden
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