Establishing causation in climate litigation: admissibility and reliability

Abstract

Climate litigation has attracted renewed interest as a governance tool. A key challenge in climate litigation is to assess the factual basis of causation. Extreme weather attribution, specifically the Fraction of Attributable Risk (FAR), has been proposed as a way to tackle this challenge. What remains unclear is how attribution science interacts with the legal admissibility of evidence based on climate models. While evidence has to be legally admissible in order to be considered in a trial, it has to be reliable in order for the court to arrive at a legally correct conclusion. Since parties to the trial have incentives to produce evidence favorable to their case, admissibility requirements and the reliability of the evidence brought forward are linked. We provide a specific proposal for how to accommodate FAR estimates in admissibility standards by modifying an existing set of admissibility criteria, the Daubert criteria. We argue that two of the five Daubert criteria are unsuitable for dealing with such evidence and that replacing those criteria with ones directly addressing the reliability of FAR estimates is adequate. Lastly, we highlight the dependence of courts on both the existence and accessibility of a framework to determine the reliability of FAR estimates in executing such criteria.

This is a preview of subscription content, log in to check access.

Fig. 1

Notes

  1. 1.

    Solar Geoengineering is a novel, untested, but potentially effective form of intervention in the global climate system with the purpose of counteracting global warming. Deployment, however, will entail the risk of undesirable side effects (Schäfer et al. 2015, Ocean Studies Board and National Research Council (2015), Niemeier and Tilmes 2017).

  2. 2.

    By the “attribution community,” we mean the scientists regularly publishing work related to the attribution of extreme events. When we state that this community “does” something, we contend that this “doing” reflects the big picture of the relevant literature.

  3. 3.

    For example, in common law States, the standard of preponderance of the evidence, usually taken to mean “more likely than not”, is most common in civil law.

  4. 4.

    FAR has its origin in epidemiology. However, there are clear limitations in the comparability of its application in attribution science and in epidemiology (Shepherd 2016).

  5. 5.

    This a simplification of the legal reality in that the two steps are not formally separated in all jurisdictions. However, for the purposes of this paper, the simplification is innocuous (see Online Resource).

  6. 6.

    We use the terms reliable and reliability in a strictly epistemological sense. In legal contexts, “evidentiary reliability” of evidence is sometimes used as a criterion for admissibility. In social sciences other than law, “reliability” is usually employed as a prerequisite of “validity” and has the meaning of consistency or repeatability (Carmines and Zeller 1979). In order to avoid terminological confusion, we emphasize that we exclusively refer to the epistemological definition provided below. For a more detailed discussion of these terms and definitions, see Haack (2008).

  7. 7.

    For example, arbitrary requirements like “the modeling choices must have appeared in the IPCC reports” may well decrease the reliability of the FAR estimates produced.

  8. 8.

    Event attribution exclusively based on observations is not capable of discerning the purely anthropogenic influence on extreme events.

  9. 9.

    Note that the US Supreme Court explicitly refers to Popper in its judgment in which it developed the Daubert criteria, and it explicitly equates testability and falsifiability.

  10. 10.

    While a “magnitude” approach is not suitable for answering questions of probabilistic causation, it may well be the right approach for answering other questions pertaining to other stages of a trial, e.g., damage determination.

References

  1. Allen M (2003) Liability for climate change. Nature 421(6926):891

    Article  Google Scholar 

  2. Allen M et al (2007) Scientific challenges in the attribution of harm to human influence on climate. Univ Pa Law Rev:1353–1400

  3. Angélil O et al (2017) An independent assessment of anthropogenic attribution statements for recent extreme temperature and rainfall events, Journal of Climate. 30.1:5–16

  4. Berger MA (2005) What has a decade of Daubert wrought? Am J Public Health 95(S1):S59–S65

    Article  Google Scholar 

  5. Carmines, Edward G., and Richard A. Zeller (1979) Reliability and validity assessment. Vol. 17. Sage publications

  6. Carrier M (2011) Underdetermination as an epistemological test tube: expounding hidden values of the scientific community. Synthese 180(2):189–204

    Article  Google Scholar 

  7. Christidis N et al (2013) A new HadGEM3-A-based system for attribution of weather-and climate-related extreme events. Journal of Climate 26(9):2756–2783

    Article  Google Scholar 

  8. Coumou D, Rahmstorf S (2012) A decade of weather extremes. Nat Clim Chang 2(7):491

    Article  Google Scholar 

  9. Diffenbaugh NS, Swain DL, Touma D (2015) Anthropogenic warming has increased drought risk in California. Proceedings of the National Academy of Sciences112 13:3931–3936

  10. Diffenbaugh NS et al (2017) Quantifying the influence of global warming on unprecedented extreme climate events. Proc Natl Acad Sci 114(19):4881–4886

    Article  Google Scholar 

  11. Dole R et al (2011) Was there a basis for anticipating the 2010 Russian heat wave? Geophysical Research Letters38:6

  12. Goldman AI (1986) Epistemology and cognition. Harvard University Press

  13. Haack S (2008) What's wrong with litigation-driven science-an essay in legal epistemology. Seton Hall L Rev 38:1053

    Google Scholar 

  14. Haack S (2010) Federal philosophy of science: a deconstruction-and a reconstruction. NYUJL & Liberty 5:394

    Google Scholar 

  15. Hannart A et al (2016) Causal counterfactual theory for the attribution of weather and climate-related events. Bulletin of the American Meteorological Society 97(1):99–110

    Article  Google Scholar 

  16. Hauser, Mathias, et al. (2017) "Methods and model dependency of extreme event attribution: the 2015 European drought." Earth's Future 5(10): 1034–1043

  17. Heinzerling L (2006) Doubting Daubert. JL & Pol'y 14:65

    Google Scholar 

  18. Herring SC et al (2016) Explaining extreme events of 2015 from a climate perspective. Bull Am Meteorol Soc 97(12):1–145

    Google Scholar 

  19. Herring SC et al (2018) Explaining extreme events of 2016 from a climate perspective. Bull Am Meteorol Soc 99(1):1–157

    Google Scholar 

  20. Horton JB, Parker A, Keith D (2014) Liability for solar geoengineering: historical precedents, contemporary innovations, and governance possibilities. NYU Envtl LJ 22:225

    Google Scholar 

  21. Jasanoff S (2005) Law’s knowledge: science for justice in legal settings. Am J Public Health 95(S1):S49–S58

    Article  Google Scholar 

  22. Kravitz B et al (2011) The geoengineering model intercomparison project (GeoMIP). Atmos Sci Lett 12(2):162–167

    Article  Google Scholar 

  23. Lott FC, Stott PA (2016) Evaluating simulated fraction of attributable risk using climate observations. J Clim 29(12):4565–4575

    Article  Google Scholar 

  24. Lusk G (2017) The social utility of event attribution: liability, adaptation, and justice-based loss and damage. Clim Chang 143(1–2):201–212

    Article  Google Scholar 

  25. Mann ME, Lloyd EA, Oreskes N (2017) Assessing climate change impacts on extreme weather events: the case for an alternative (Bayesian) approach. Clim Chang 144(2):131–142

    Article  Google Scholar 

  26. Marjanac S, Patton L, Thornton J (2017) Acts of God, human influence and litigation. Nat Geosci 10(9):616–619

    Article  Google Scholar 

  27. Marjanac S, Patton L (2018) Extreme weather event attribution science and climate change litigation: an essential step in the causal chain? J Energy Nat Resour Law:1–34

  28. McAvaney, Bryant J., et al. Model evaluation. Climate change 2001: the scientific basis. Contribution of WG1 to the Third Assessment Report of the IPCC (TAR). Cambridge University Press, 2001. 471–523

  29. McCormick S et al (2017) Science in litigation, the third branch of US climate policy. Science 357(6355):979–980

    Article  Google Scholar 

  30. McGarity TO (2004) Our science is sound science and their science is junk science: science-based strategies for avoiding accountability and responsibility for risk-producing products and activities. U Kan L Rev 52:897

    Google Scholar 

  31. National Academies of Sciences, Engineering, and Medicine. Attribution of extreme weather events in the context of climate change. National Academies Press, 2016

  32. Niemeier U, Tilmes S (2017) Sulfur injections for a cooler planet. Science 357(6348):246–248

    Article  Google Scholar 

  33. Ocean Studies Board and National Research Council (2015) Climate intervention: reflecting sunlight to cool earth. National Academies Press

  34. Otto FEL et al (2012) Reconciling two approaches to attribution of the 2010 Russian heat wave. Geophys Res Lett 39:4

    Article  Google Scholar 

  35. Otto, Friederike EL (2012) Modelling the earth’s climate-an epistemic perspective. Diss. Freie Universität Berlin

  36. Otto FEL et al (2017) Assigning historic responsibility for extreme weather events. Nature Climate Change 7(11):757

    Article  Google Scholar 

  37. Palmer TN et al (2008) Toward seamless prediction: calibration of climate change projections using seasonal forecasts. Bull Am Meteorol Soc 89(4):459–470

    Article  Google Scholar 

  38. Parker, Wendy S. (2009) "II—confirmation and adequacy-for-purpose in climate modelling." Aristotelian Society Supplementary Volume. Vol. 83. No. 1. Oxford, UK: Blackwell Publishing Ltd

  39. Petersen, Arthur C (2012) Simulating nature: a philosophical study of computer-simulation uncertainties and their role in climate science and policy advice. CRC Press

  40. Popper KR (1959) The logic of scientific discovery. Routledge

  41. Rahmstorf S, Coumou D (2011) Increase of extreme events in a warming world. Proc Natl Acad Sci 108(44):17905–17909

    Article  Google Scholar 

  42. Reynolds JL (2015) An economic analysis of liability and compensation for harm from large-scale field research in solar climate engineering. Climate Law 5(2–4):182–209

    Article  Google Scholar 

  43. Saxler B, Siegfried J, Proelss A (2015) International liability for transboundary damage arising from stratospheric aerosol injections. Law Innov Technol 7(1):112–147

    Article  Google Scholar 

  44. Schäfer S et al (2015) The European transdisciplinary assessment of climate engineering (EuTRACE): removing greenhouse gases from the atmosphere and reflecting sunlight away from. Earth

  45. Seager R, et al. (2015) "Causes of the 2011–14 California drought." J Clim 28.18: 6997–7024

  46. Shepherd TG (2014) Atmospheric circulation as a source of uncertainty in climate change projections. Nat Geosci 7(10):703

    Article  Google Scholar 

  47. Shepherd TG (2016) A common framework for approaches to extreme event attribution. Curr Clim Chang Rep 2(1):28–38

    Article  Google Scholar 

  48. Shiogama H et al (2013) An event attribution of the 2010 drought in the South Amazon region using the MIROC5 model. Atmos Sci Lett 14(3):170–175

    Article  Google Scholar 

  49. Sillmann J et al (2013) Climate extremes indices in the CMIP5 multimodel ensemble: part 1. Model evaluation in the present climate. J Geophys Res: Atmospheres 118(4):1716–1733

    Google Scholar 

  50. Stott, Peter A., et al. "Attribution of extreme weather and climate-related events." Wiley Interdisciplinary Reviews: Climate Change 7.1 (2016): 23–41

  51. Stott PA, Karoly DJ, Zwiers FW (2017) Is the choice of statistical paradigm critical in extreme event attribution studies? Clim Chang 144(2):143–150

    Article  Google Scholar 

  52. Stott PA et al (2018) Future challenges in event attribution methodologies. Bull Am Meteorol Soc 99(1):S155–S157

    Article  Google Scholar 

  53. Swinehart MW (2007) Remedying Daubert’s inadequacy in evaluating the admissibility of scientific models used in environmental-tort litigation. Tex L Rev 86:1281

    Google Scholar 

  54. Thornton J, Covington H (2016) Climate change before the court. Nat Geosci 9(1):3

    Article  Google Scholar 

  55. Trenberth KE, Fasullo JT, Shepherd TG (2015) Attribution of climate extreme events. Nat Clim Chang 5(8):725

    Article  Google Scholar 

  56. Wagner W (2005) The perils of relying on interested parties to evaluate scientific quality. Am J Public Health 95(S1):S99–S106

    Article  Google Scholar 

  57. Weisheimer A, Palmer TN (2014) On the reliability of seasonal climate forecasts. J Royal Soc Interface 11(96):20131162

    Article  Google Scholar 

  58. Wilhite DA, Glantz MH (1985) Understanding: the drought phenomenon: the role of definitions. Water Int 10(3):111–120

    Article  Google Scholar 

  59. Williams AP et al (2015) Contribution of anthropogenic warming to California drought during 2012–2014. Geophys Res Lett 42(16):6819–6828

    Article  Google Scholar 

Download references

Funding

The authors gratefully acknowledge funding by the German Research Foundation DFG under grant numbers CA120/19-2 (MC, JL), GO1604/3-2 (TG, TP), PR1323/2-2 (AP, HM), and SCHM2158/4-2 (HS, UN).

Author information

Affiliations

Authors

Contributions

TP developed the basic idea and concept underlying the study. All of the authors have contributed to the development of idea and concept of this paper and to the writing. TP, TG, and AP have drafted large parts of the manuscript. TP coordinated the writing process and calculated the FAR estimates. UN has performed the climate model simulations and contributed to their analysis.

Corresponding author

Correspondence to Tobias Pfrommer.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 423 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pfrommer, T., Goeschl, T., Proelss, A. et al. Establishing causation in climate litigation: admissibility and reliability. Climatic Change 152, 67–84 (2019). https://doi.org/10.1007/s10584-018-2362-4

Download citation