Articles | Volume 31, issue 1
https://doi.org/10.5194/npg-31-115-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-31-115-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Feb 2024
Research article |
| 27 Feb 2024
| 27 Feb 2024
A comparison of two causal methods in the context of climate analyses
Meteorological and Climatological Information Service, Royal Meteorological Institute of Belgium, Brussels, Belgium
Giorgia Di Capua
Department of Water, Environment, Construction and Safety, Magdeburg-Stendal University of Applied Sciences, Magdeburg, Germany
Research Department I – Earth System Analysis, Potsdam Institute for Climate Impact Research – Member of the Leibniz Association, Potsdam, Germany
Reik V. Donner
Department of Water, Environment, Construction and Safety, Magdeburg-Stendal University of Applied Sciences, Magdeburg, Germany
Research Department I – Earth System Analysis, Potsdam Institute for Climate Impact Research – Member of the Leibniz Association, Potsdam, Germany
Carlos A. L. Pires
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal
Amélie Simon
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal
Department of Mathematical and Electrical Engineering, IMT Atlantique, Lab-STICC, UMR CNRS 6285, Brest, France
Stéphane Vannitsem
Meteorological and Climatological Information Service, Royal Meteorological Institute of Belgium, Brussels, Belgium
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23 citations as recorded by crossref.
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- Nonlinear causal dependencies as a signature of the complexity of the climate dynamics S. Vannitsem et al. https://doi.org/10.5194/esd-16-703-2025
- Drivers of summer Antarctic sea-ice extent at interannual time scale in CMIP6 large ensembles based on information flow D. Docquier et al. https://doi.org/10.1007/s00382-025-07878-3
- Synergistic-unique-redundant decomposition of the causal influences of four large-scale climate oscillations on meteorological drought in the Yangtze River Basin K. Ren et al. https://doi.org/10.1007/s00477-026-03255-6
- Drivers of summer Arctic sea-ice extent at interannual time scale in CMIP6 large ensembles revealed by information flow D. Docquier et al. https://doi.org/10.1038/s41598-024-76056-y
- Historical changes in the Causal Effect Networks of compound hot and dry extremes in central Europe Y. Tian et al. https://doi.org/10.1038/s43247-024-01934-2
- Causal mechanisms of subpolar gyre variability in CMIP6 models S. Falkena et al. https://doi.org/10.5194/esd-16-1833-2025
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- Kalman phase transfer entropy (KTE-TP): a novel measure for information transfer measurement to enhance brain-computer decoding J. Zhang et al. https://doi.org/10.1088/1741-2552/ae60d1
- Major fires in Indonesian Borneo are possible under all ENSO phases T. Lam et al. https://doi.org/10.1038/s44304-026-00209-4
- Quantifying the causal effects of large-scale climate indices on basin-scale meteorological drought using transfer entropy: a case study of the yellow river basin K. Ren & T. Ming https://doi.org/10.1007/s00477-025-03030-z
- Deepening mechanisms of cut-off lows in the Southern Hemisphere and the role of jet streams: insights from eddy kinetic energy analysis H. Pinheiro et al. https://doi.org/10.5194/wcd-5-881-2024
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- A Causal Inference Framework for Climate Change Attribution in Ecology J. Dudney et al. https://doi.org/10.1111/ele.70192
- Assessment of the atmospheric drivers of flash drought in India through complex causal pathways A. Pachore et al. https://doi.org/10.1007/s00704-026-06054-9
- Deficient ocean–atmosphere feedbacks constrain seasonal NAO prediction E. Kolstad https://doi.org/10.5194/wcd-7-507-2026
- Integrated causal and information-theoretic analysis of teleconnection–dust relationships in Iran: identifying linear pathways and nonlinear dependencies Y. Ghavidel et al. https://doi.org/10.1007/s00477-026-03288-x
- The Many Shades of the Vegetation–Climate Causality: A Multimodel Causal Appreciation Y. Shao et al. https://doi.org/10.3390/f15081430
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- Spatiotemporal variation and driving effects of evapotranspiration in China during 2001–2022 H. Tang et al. https://doi.org/10.1016/j.ejrh.2025.102853
- Prominent impacts of snow–hydrological processes on near-surface temperature variability over Western Siberia N. Ganeshi et al. https://doi.org/10.1016/j.jhydrol.2025.133187
- Rapid changes in warm and cold extremes in recent decades and their future projections for India R. Kumar et al. https://doi.org/10.1016/j.jenvman.2025.125832
23 citations as recorded by crossref.
- The three causal pathways of ENSO teleconnections to High Mountain Asia winter precipitation P. Borah et al. https://doi.org/10.1007/s00382-026-08198-w
- Nonlinear causal dependencies as a signature of the complexity of the climate dynamics S. Vannitsem et al. https://doi.org/10.5194/esd-16-703-2025
- Drivers of summer Antarctic sea-ice extent at interannual time scale in CMIP6 large ensembles based on information flow D. Docquier et al. https://doi.org/10.1007/s00382-025-07878-3
- Synergistic-unique-redundant decomposition of the causal influences of four large-scale climate oscillations on meteorological drought in the Yangtze River Basin K. Ren et al. https://doi.org/10.1007/s00477-026-03255-6
- Drivers of summer Arctic sea-ice extent at interannual time scale in CMIP6 large ensembles revealed by information flow D. Docquier et al. https://doi.org/10.1038/s41598-024-76056-y
- Historical changes in the Causal Effect Networks of compound hot and dry extremes in central Europe Y. Tian et al. https://doi.org/10.1038/s43247-024-01934-2
- Causal mechanisms of subpolar gyre variability in CMIP6 models S. Falkena et al. https://doi.org/10.5194/esd-16-1833-2025
- Summer Greenland Blocking in reanalysis and in SEAS5.1 seasonal forecasts: robust trend or natural variability? J. Beckmann et al. https://doi.org/10.5194/wcd-6-1875-2025
- Kalman phase transfer entropy (KTE-TP): a novel measure for information transfer measurement to enhance brain-computer decoding J. Zhang et al. https://doi.org/10.1088/1741-2552/ae60d1
- Major fires in Indonesian Borneo are possible under all ENSO phases T. Lam et al. https://doi.org/10.1038/s44304-026-00209-4
- Quantifying the causal effects of large-scale climate indices on basin-scale meteorological drought using transfer entropy: a case study of the yellow river basin K. Ren & T. Ming https://doi.org/10.1007/s00477-025-03030-z
- Deepening mechanisms of cut-off lows in the Southern Hemisphere and the role of jet streams: insights from eddy kinetic energy analysis H. Pinheiro et al. https://doi.org/10.5194/wcd-5-881-2024
- Inferring causal associations in hydrological systems: a comparison of methods H. Liang et al. https://doi.org/10.1007/s00477-025-02977-3
- A Causal Inference Framework for Climate Change Attribution in Ecology J. Dudney et al. https://doi.org/10.1111/ele.70192
- Assessment of the atmospheric drivers of flash drought in India through complex causal pathways A. Pachore et al. https://doi.org/10.1007/s00704-026-06054-9
- Deficient ocean–atmosphere feedbacks constrain seasonal NAO prediction E. Kolstad https://doi.org/10.5194/wcd-7-507-2026
- Integrated causal and information-theoretic analysis of teleconnection–dust relationships in Iran: identifying linear pathways and nonlinear dependencies Y. Ghavidel et al. https://doi.org/10.1007/s00477-026-03288-x
- The Many Shades of the Vegetation–Climate Causality: A Multimodel Causal Appreciation Y. Shao et al. https://doi.org/10.3390/f15081430
- Quantitative comparison of causal inference methods for climate tipping points N. Lohmann et al. https://doi.org/10.5194/npg-33-313-2026
- Causal dependencies and Shannon entropy budget: Analysis of a reduced‐order atmospheric model S. Vannitsem et al. https://doi.org/10.1002/qj.4805
- Spatiotemporal variation and driving effects of evapotranspiration in China during 2001–2022 H. Tang et al. https://doi.org/10.1016/j.ejrh.2025.102853
- Prominent impacts of snow–hydrological processes on near-surface temperature variability over Western Siberia N. Ganeshi et al. https://doi.org/10.1016/j.jhydrol.2025.133187
- Rapid changes in warm and cold extremes in recent decades and their future projections for India R. Kumar et al. https://doi.org/10.1016/j.jenvman.2025.125832
Saved (final revised paper)
Latest update: 30 Jul 2026
Short summary
Identifying causes of specific processes is crucial in order to better understand our climate system. Traditionally, correlation analyses have been used to identify cause–effect relationships in climate studies. However, correlation does not imply causation, which justifies the need to use causal methods. We compare two independent causal methods and show that these are superior to classical correlation analyses. We also find some interesting differences between the two methods.
Identifying causes of specific processes is crucial in order to better understand our climate...
