Detecting Climate Teleconnections With Granger Causality

Author(s)

Silva, Filipi N. ^[1] ; Vega-Oliveros, Didier A. ^{[2, 3]} ; Yan, Xiaoran ^[4] ; Flammini, Alessandro ^[3] ; Menczer, Filippo ^{[1, 3]} ; Radicchi, Filippo ^[3] ; Kravitz, Ben ^{[5, 6]} ; Fortunato, Santo ^{[1, 3]}

Affiliation

^[1] Indiana Univ, Network Sci Inst IUNI, Bloomington, IN 47401 - USA

^[2] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil

^[3] Indiana Univ, Luddy Sch Informat Comp & Engn, Ctr Complex Networks & Syst Res, Bloomington, IN 47401 - USA

^[4] Zhejiang Lab, Artificial Intelligence Res Inst, Hangzhou, Zhejiang - Peoples R China

^[5] Pacific Northwest Natl Lab, Atmospher Sci & Global Change Div, Richland, WA 99352 - USA

^[6] Indiana Univ, Dept Earth & Atmospher Sci, Bloomington, IN 47401 - USA

• Document type: Journal article
• Source: Geophysical Research Letters; v. 48, n. 18 SEP 28 2021.
• Web of Science Citations: 0

Abstract

Climate system teleconnections are crucial for improving climate predictability, but difficult to quantify. Standard approaches to identify teleconnections are often based on correlations between time series. Here we present a novel method leveraging Granger causality, which can infer/detect relationships between any two fields. We compare teleconnections identified by correlation and Granger causality at different timescales. We find that both Granger causality and correlation consistently recover known seasonal precipitation responses to the sea surface temperature pattern associated with the El Nino Southern Oscillation. Such findings are robust across multiple time resolutions. In addition, we identify candidates for unexplored teleconnection responses. (AU)

• FAPESP's process: 18/24260-5 - Spatiotemporal Data Analytics based on Complex Networks
• Grantee: Didier Augusto Vega Oliveros
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: Francisco Louzada Neto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
• FAPESP's process: 19/26283-5 - Learning visual clues of the passage of time
• Grantee: Didier Augusto Vega Oliveros
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 16/23698-1 - Dynamical Processes in Complex Network based on Machine Learning
• Grantee: Didier Augusto Vega Oliveros
• Support Opportunities: Scholarships in Brazil - Post-Doctoral