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  Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks

Pfleiderer, P., Schleussner, C.-F., Geiger, T., Kretschmer, M. (2020): Robust predictors for seasonal Atlantic hurricane activity identified with causal effect networks. - Weather and Climate Dynamics, 1, 2, 313-324.
https://doi.org/10.5194/wcd-1-313-2020

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Datensatz-Permalink: https://publications.pik-potsdam.de/pubman/item/item_24828 Versions-Permalink: https://publications.pik-potsdam.de/pubman/item/item_24828_3
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 Urheber:
Pfleiderer, Peter1, Autor              
Schleussner, Carl-Friedrich1, Autor              
Geiger, Tobias1, Autor              
Kretschmer, Marlene2, Autor
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Atlantic hurricane activity varies substantially from year to year and so do the associated damages. Longer-term forecasting of hurricane risks is a key element to reduce damages and societal vulnerabilities by enabling targeted disaster preparedness and risk reduction measures. While the immediate synoptic drivers of tropical cyclone formation and intensification are increasingly well understood, precursors of hurricane activity on longer time-horizons are still not well established. Here we use a causal network-based algorithm to identify physically motivated late-spring precursors of seasonal 15Atlantic hurricane activity. Based on these precursors we construct seasonal forecast models with competitive skill compared to operational forecasts. We present a skillful model to forecast July to October cyclone activity at the beginning of April.Earlier seasonal hurricane forecasting provides a multi-month lead time to implement more effective disaster risk reduction measures. Our approach also highlights the potential of applying causal effects network analysis in seasonal forecasting

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Sprache(n): eng - Englisch
 Datum: 2020-03-132020-06-23
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.5194/wcd-1-313-2020
MDB-ID: No data to archive
PIKDOMAIN: RD3 - Transformation Pathways
PIKDOMAIN: RD1 - Earth System Analysis
Organisational keyword: RD3 - Transformation Pathways
Organisational keyword: RD1 - Earth System Analysis
Working Group: Earth System Modes of Operation
Working Group: Ecosystems in Transition
Working Group: Event-based modeling of economic impacts of climate change
 Art des Abschluß: -

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Titel: Weather and Climate Dynamics
Genre der Quelle: Zeitschrift, other, oa
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 1 (2) Artikelnummer: - Start- / Endseite: 313 - 324 Identifikator: Publisher: Copernicus Publications
Publisher: EGU European Geosciences Union
Anderer: 2698-4016
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/weather-and-climate-dynamics
Publisher: Copernicus