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  Fingerprint of volcanic forcing on the ENSO–Indian monsoon coupling

Singh, M., Krishnan, R., Goswami, B., Choudhury, A. D., Swapna, P., Vellore, R., Prajeesh, A. G., Sandeep, N., Venkataraman, C., Donner, R. V., Marwan, N., Kurths, J. (2020): Fingerprint of volcanic forcing on the ENSO–Indian monsoon coupling. - Science Advances, 6, 38, eaba8164.
https://doi.org/10.1126/sciadv.aba8164

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Singh, M.1, Autor
Krishnan, R.1, Autor
Goswami, Bedartha2, Autor              
Choudhury, A. D.1, Autor
Swapna, P.1, Autor
Vellore, R.1, Autor
Prajeesh, A. G.1, Autor
Sandeep, N.1, Autor
Venkataraman, C.1, Autor
Donner, Reik V.2, Autor              
Marwan, Norbert2, Autor              
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Coupling of the El Niño–Southern Oscillation (ENSO) and Indian monsoon (IM) is central to seasonal summer monsoon rainfall predictions over the Indian subcontinent, although a nonstationary relationship between the two nonlinear phenomena can limit seasonal predictability. Radiative effects of volcanic aerosols injected into the stratosphere during large volcanic eruptions (LVEs) tend to alter ENSO evolution; however, their impact on ENSO-IM coupling remains unclear. Here, we investigate how LVEs influence the nonlinear behavior of the ENSO and IM dynamical systems using historical data, 25 paleoclimate reconstructions, last-millennium climate simulations, large-ensemble targeted climate sensitivity experiments, and advanced analysis techniques. Our findings show that LVEs promote a significantly enhanced phase-synchronization of the ENSO and IM oscillations, due to an increase in the angular frequency of ENSO. The results also shed innovative insights into the physical mechanism underlying the LVE-induced enhancement of ENSO-IM coupling and strengthen the prospects for improved seasonal monsoon predictions.

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 Datum: 2020-08-012020
 Publikationsstatus: Final veröffentlicht
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
DOI: 10.1126/sciadv.aba8164
MDB-ID: No data to archive
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Monsoon
Working Group: Development of advanced time series analysis techniques
Working Group: Network- and machine-learning-based prediction of extreme events
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Titel: Science Advances
Genre der Quelle: Zeitschrift, SCI, Scopus, p3, oa
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Seiten: - Band / Heft: 6 (38) Artikelnummer: eaba8164 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/161027
Publisher: American Association for the Advancement of Science (AAAS)