Inferring causation from time series in Earth system sciences

Inferring causation from time series in Earth system sciences

Questions of causality are ubiquitous in Earth system sciences and beyond, yet correlation techniques still prevail. This Perspective provides an overview of causal inference methods, identifies promising applications and methodological challenges, and initiates a causality benchmark platform.

Saved in:
Bibliographic Details
Main Authors: Jakob Runge, Sebastian Bathiany, Erik Bollt, Gustau Camps-Valls, Dim Coumou, Ethan Deyle, Clark Glymour, Marlene Kretschmer, Miguel D. Mahecha, Jordi Muñoz-Marí, Egbert H. van Nes, Jonas Peters, Rick Quax, Markus Reichstein, Marten Scheffer, Bernhard Schölkopf, Peter Spirtes, George Sugihara, Jie Sun, Kun Zhang, Jakob Zscheischler
Format: article
Language:EN
Published: Nature Portfolio 2019
Subjects:
Science
Q
Online Access:https://doaj.org/article/c9cb78b8c1d74e3fbd7d14afb1c5eee7
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Questions of causality are ubiquitous in Earth system sciences and beyond, yet correlation techniques still prevail. This Perspective provides an overview of causal inference methods, identifies promising applications and methodological challenges, and initiates a causality benchmark platform.

Similar Items