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  Detection and attribution of trends of meteorological extremes in Central America

Hidalgo, H. G., Chou-Chen, S. W., McKinnon, K. A., Pascale, S., Quesada Chacón, D., Alfaro, E. J., Bautista-Solís, P., Pérez-Briceño, P. M., Diaz, H. F., Maldonado, T., Rivera, E. R., Nakaegawa, T. (2025): Detection and attribution of trends of meteorological extremes in Central America. - Climatic Change, 178, 95.
https://doi.org/10.1007/s10584-025-03940-5

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Hidalgo, H. G.1, Autor
Chou-Chen, S. W.1, Autor
McKinnon, K. A.1, Autor
Pascale, S.1, Autor
Quesada Chacón, Dánnell2, Autor                 
Alfaro, E. J.1, Autor
Bautista-Solís, P.1, Autor
Pérez-Briceño, P. M.1, Autor
Diaz, H. F.1, Autor
Maldonado, T.1, Autor
Rivera, E. R.1, Autor
Nakaegawa, T.1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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 Zusammenfassung: We present an analysis to determine whether historical trends in extreme precipitation and temperature indices, as well as in yearly averages of several climate variables can be associated in part with anthropogenic climate change or explained solely by natural causes. To achieve this, we use three methodologies: a) a climate model-based approach, b) a hybrid method that combines models and observations (1979–2019), and c) a climate observations-based method (1983–2016). For each methodology, we compare the climate change signal, represented by the historical trends, to the noise generated by simulated climate datasets (using models or statistical methods) that do not include human influence. Overall, the model-based method suggests possible detection of the human influence in most temperature extreme indices and in precipitation-related indices in the northern countries. The hybrid method detects human influence in significantly fewer variables, but in many cases, consistently with those of the model-based approach. Both the hybrid and observation-based methods exhibit similar noise variability to the model-based method. Notably, due to limitations in data availability, our analysis excludes the most recent five years, during which substantial warming and an increase of extreme events have been observed globally.

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Sprache(n): eng - English
 Datum: 2024-09-052025-04-192025-04-302025-04-30
 Publikationsstatus: Final veröffentlicht
 Seiten: 21
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1007/s10584-025-03940-5
Organisational keyword: RD3 - Transformation Pathways
PIKDOMAIN: RD3 - Transformation Pathways
Regional keyword: South America
Research topic keyword: Climate impacts
Research topic keyword: Extremes
Research topic keyword: Attribution
MDB-ID: No data to archive
OATYPE: Hybrid Open Access
 Art des Abschluß: -

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Titel: Climatic Change
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Seiten: - Band / Heft: 178 Artikelnummer: 95 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals80
Publisher: Springer