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There is growing interest in the study of causal methods in the Earth sciences.
Deterministic nonperiodic flow
Edward N. Lorenz · 1963
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Scavenging of aerosol particles by precipitation
Lawrence F. Radke, Peter V. Hobbs, and Mark W. Eltgroth · 1980
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Detecting strange attractors in turbulence
Floris Takens · 1981
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d-separation: From theorems to algorithms
Dan Geiger, Thomas Verma, and Judea Pearl · 1990
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A probabilistic calculus of actions
Judea Pearl · 1994
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Causal diagrams for empirical research
Judea Pearl · 1995
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Predictability: A problem partly solved
Edward N Lorenz · 1996
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Investigating soil moisture feedbacks on precipitation with tests of granger causality
Guido D Salvucci, Jennifer A Saleem, and Robert Kaufmann · 2002
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A general identification condition for causal effects
Jin Tian and Judea Pearl · 2002
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Breaking the cloud parameterization deadlock
David Randall, Marat Khairoutdinov, Akio Arakawa, and Wojciech Grabowski · 2003
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Pattern recognition and machine learning
Christopher M Bishop · 2006
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Identifiability in causal bayesian networks: A sound and complete algorithm
Yimin Huang and Marco Valtorta · 2006
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Identification of conditional interventional distributions
Ilya Shpitser and Judea Pearl · 2006
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Atmospheric science: an introductory survey , volume 92
John M Wallace and Peter V Hobbs · 2006
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Atmospheric deposition of organic and black carbon to the global oceans
Elena Jurado, Jordi Dachs, Carlos M. Duarte, and Rafel Simó · 2008
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Transportability of causal effects: Completeness results
Elias Bareinboim and Judea Pearl · 2012
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Causal discovery for climate research using graphical models
Imme Ebert-Uphoff and Yi Deng · 2012
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Challenges in climate science and contemporary applied mathematics
Andrew J. Majda · 2012
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No, we should not just ‘at least do the research’
Clive Hamilton · 2013
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Advanced data analysis from an elementary point of view, 2013
Cosma Shalizi · 2013
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Recovering from selection bias in causal and statistical inference
Elias Bareinboim, Jin Tian, and Judea Pearl · 2014
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Atmospheric Aerosols , pages 9–24
Olivier Boucher · 2015
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Could machine learning break the convection parameterization deadlock?
P. Gentine, M. Pritchard, S. Rasp, G. Reinaudi, and G. Yacalis · 2018
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Causal network reconstruction from time series: From theoretical assumptions to practical estimation
J. Runge · 2018
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Systematic Errors in Weather and Climate Models: Nature, Origins, and Ways Forward
Ayrton Zadra, Keith Williams, Ariane Frassoni, Michel Rixen, Ángel F. Adames, Judith Berner, François Bouyssel, Barbara Casati, Hannah Christensen, Michael B. Ek, Greg Flato, Yi Huang, Falko Judt, Hai Lin, Eric Maloney, William Merryfield, Annelize Van Niekerk, Thomas Rackow, Kazuo Saito, Nils Wedi, and Priyanka Yadav · 2018
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Tropospheric and stratospheric causal pathways between the mjo and nao
Elizabeth A. Barnes, Savini M. Samarasinghe, Imme Ebert-Uphoff, and Jason C. Furtado · 2019
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Constraining the aerosol influence on cloud liquid water path
E. Gryspeerdt, T. Goren, O. Sourdeval, J. Quaas, J. Mülmenstädt, S. Dipu, C. Unglaub, A. Gettelman, and M. Christensen · 2019
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Dennis L Hartmann · 2015
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Causal inference and the data-fusion problem
Elias Bareinboim and Judea Pearl · 2016
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Causal counterfactual theory for the attribution of weather and climate-related events
A. Hannart, J. Pearl, F. E. L. Otto, P. Naveau, and M. Ghil · 2016
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Using causal effect networks to analyze different arctic drivers of midlatitude winter circulation
Marlene Kretschmer, Dim Coumou, Jonathan F. Donges, and Jakob Runge · 2016
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Regionally strong feedbacks between the atmosphere and terrestrial biosphere
Julia K. Green, Alexandra G. Konings, Seyed Hamed Alemohammad, Joseph Berry, Dara Entekhabi, Jana Kolassa, Jung-Eun Lee, and Pierre Gentine · 2017
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The chilean coastal orographic precipitation experiment: Observing the influence of microphysical rain regimes on coastal orographic precipitation
Adam K. Massmann, Justin R. Minder, René D. Garreaud, David E. Kingsmill, Raul A. Valenzuela, Aldo Montecinos, Sara Lynn Fults, and Jefferson R. Snider · 2017
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General identifiability with arbitrary surrogate experiments
Sanghack Lee, Juan D Correa, and Elias Bareinboim · 2019
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When does vapor pressure deficit drive or reduce evapotranspiration?
Adam Massmann, Pierre Gentine, and Changjie Lin · 2019
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Inferring causation from time series in earth system sciences
Jakob Runge, Sebastian Bathiany, Erik Bollt, Gustau Camps-Valls, Dim Coumou, Ethan Deyle, Clark Glymour, Marlene Kretschmer, Miguel D Mahecha, Jordi Muñoz-Marí, et al · 2019
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Adapting neural networks for the estimation of treatment effects
Claudia Shi, David M Blei, and Victor Veitch · 2019
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The blessings of multiple causes
Yixin Wang and David M. Blei · 2019
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Emulation of bin microphysical processes with machine learning
David John Gagne, Chih-Chieh Chen, and Andrew Gettelman · 2020
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Debates—does information theory provide a new paradigm for earth science? causality, interaction, and feedback
Allison E. Goodwell, Peishi Jiang, Benjamin L. Ruddell, and Praveen Kumar · 2020
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Plant responses to rising vapor pressure deficit
Charlotte Grossiord, Thomas N. Buckley, Lucas A. Cernusak, Kimberly A. Novick, Benjamin Poulter, Rolf T. W. Siegwolf, John S. Sperry, and Nate G. McDowell · 2020
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Generative interventions for causal learning
Chengzhi Mao, Amogh Gupta, Augustine Cha, Hao Wang, Junfeng Yang, and Carl Vondrick · 2020
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A causality-based view of the interaction between synoptic- and planetary-scale atmospheric disturbances
Savini M. Samarasinghe, Yi Deng, and Imme Ebert-Uphoff · 2020
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On efficient adjustment in causal graphs
Janine Witte, Leonard Henckel, Marloes H Maathuis, and Vanessa Didelez · 2020
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