For best experience please turn on javascript and use a modern browser!

The climate sciences are riddled with competing models and hardly any options for experimental validation. A broad consortium took on the challenge to see if the field could benefit from applying causality inference techniques and wrote a perspective paper on the subject, which is published in Nature Communications.


A broad consortium of scientists from computational modelling, complexity science, ecology, causality inference, and various climate sciences came together in a workshop “Causality in Complex Systems” in June 27–30, 2017, in Soesterberg, The Netherlands. The workshop was organised by IAS external faculty member Marten Scheffer. A second workshop "Causality in Climate Science" took place at the IAS on October 24, 2018, organised by Dim Coumou.

In a field riddled with competing models and hardly any option for experimental validation, the idea of the workshops was to see if the field could benefit from learning about causality inference techniques of different types, possibly applicable in different situations. The discussions were lively and so fruitful that a large part of the participants agreed on writing a perspective article on the subject, with the goal of improving the visibility of these techniques as well as their important considerations, in the climate sciences. This perspective article, spearheaded by Jakob Runge and Jordi Munoz, has now been published in Nature Communications.

IAS research fellow Rick Quax took part in the writing process and contributed some data sets for the accompanying CauseMe website with sample data sets and inference challenges to help the field forward.