English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

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

Ciemer, C., Rehm, L., Kurths, J., Donner, R. V., Winkelmann, R., Boers, N. (2020): An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures. - Environmental Research Letters, 15, 9, 094087.
https://doi.org/10.1088/1748-9326/ab9cff

Item is

Files

show Files
hide Files
:
Ciemer_2020_Environ._Res._Lett._15_094087.pdf (Publisher version), 2MB
Name:
Ciemer_2020_Environ._Res._Lett._15_094087.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Ciemer, Catrin1, Author              
Rehm, Lars2, Author
Kurths, Jürgen1, Author              
Donner, Reik V.1, Author              
Winkelmann, Ricarda1, Author              
Boers, Niklas1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: 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 with lead-times up to 18 months.

Details

show
hide
Language(s):
 Dates: 2020-09-072020
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1748-9326/ab9cff
MDB-ID: Entry suspended
PIKDOMAIN: RD4 - Complexity Science
PIKDOMAIN: RD1 - Earth System Analysis
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Weather
Regional keyword: South America
Research topic keyword: Oceans
Model / method: Nonlinear Data Analysis
Organisational keyword: RD4 - Complexity Science
Organisational keyword: RD1 - Earth System Analysis
Working Group: Network- and machine-learning-based prediction of extreme events
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Environmental Research Letters
Source Genre: Journal, SCI, Scopus, p3, oa
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 15 (9) Sequence Number: 094087 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/150326
Publisher: IOP Publishing