BIBLIOS

Document type
Journal articles

Document subtype
Full paper

Title
A comparison of two causal methods in the context of climate analyses

Participants in the publication
David Docquier (Author)
Giorgia Di Capua (Author)
Reik V. Donner (Author)
Carlos A. L. Pires (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
Amélie Simon (Author)
Stéphane Vannitsem (Author)

Summary
Correlation does not necessarily imply causation, and this is why causal methods have been developed to try to disentangle true causal links from spurious relationships. In our study, we use two causal methods,\nnamely, the Liang–Kleeman information flow (LKIF) and the Peter and Clark momentary conditional independence (PCMCI) algorithm, and we apply them to four different artificial models of increasing complexity and one\nreal-world case study based on climate indices in the Atlantic and Pacific regions. We show that both methods\nare superior to the classical correlation analysis, especially in removing spurious links. LKIF and PCMCI display some strengths and weaknesses for the three simplest models, with LKIF performing better with a smaller\nnumber of variables and with PCMCI being best with a larger number of variables. Detecting causal links from\nthe fourth model is more challenging as the system is nonlinear and chaotic. For the real-world case study with\nclimate indices, both methods present some similarities and differences at monthly timescale. One of the key\ndifferences is that LKIF identifies the Arctic Oscillation (AO) as the largest driver, while the El Niño–Southern\nOscillation (ENSO) is the main influencing variable for PCMCI. More research is needed to confirm these links,\nin particular including nonlinear causal methods.


Institution
Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749–016, Lisboa, Portugal

Where published
Nonlinear Processes in Geophysics

Publication Identifiers
ISSN - 1607-7946

Publisher
Copernicus GmbH



Document Identifiers
DOI - https://doi.org/10.5194/npg-31-115-2024
URL - http://dx.doi.org/10.5194/npg-31-115-2024