• search hit 3 of 3
Back to Result List

An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures

  • Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events withDroughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.show moreshow less

Download full text files

  • pmnr1207.pdfeng
    (3434KB)

    SHA-512a906b9191a0fdb5d9ca6ea2a3644cffb2976b437d4cd10740bb71b9cca5c992e3797a3df210fbb6f0c49dcf59051e25fc0e283ca746dd067275fe0c6231dd09d

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Catrin CiemerORCiDGND, Lars Rehm, Jürgen KurthsORCiDGND, Reik Volker DonnerORCiDGND, Hilke Ricarda WinkelmannORCiDGND, Niklas BoersORCiDGND
URN:urn:nbn:de:kobv:517-opus4-525863
DOI:https://doi.org/10.25932/publishup-52586
ISSN:1866-8372
Title of parent work (German):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1207)
Publication type:Postprint
Language:English
Date of first publication:2019/12/14
Publication year:2020
Publishing institution:Universität Potsdam
Release date:2021/11/17
Tag:Amazon rainforest; complex networks; droughts; prediction
Issue:9
Article number:094087
Number of pages:12
Source:Catrin Ciemer et al 2020 Environ. Res. Lett. 15 094087
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
DDC classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Green Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
External remark:Bibliographieeintrag der Originalveröffentlichung/Quelle
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.