The Epistemology of Climate Change
Project
Philosophy of science perspectives on the climate challenge
Understanding and modelling climate systems---in particular local ones---in an appropriate way is an extremely difficult task, but science actually quite often faces extremely difficult tasks. The specificity and the importance of climate science is that it is expected to provide scientific and empirical grounds for decision- and policy-making in the face of the climate challenge. This research project aims to carefully investigate and clarify the methodological and epistemic foundations of climate science and climate modelling using the tools of philosophy of science in order to provide the best possible support for addressing the climate challenge, with particular attention to local, regional climate modelling and decision-making at the national level (Switzerland will be taken as a study case). Indeed, mitigation and above all adaptation requires appropriate policy-making at the national level. Moreover, appropriate understanding of the climate-related issues at the local level may enhance public support and adherence to climate policy.
While there is a large consensus about model projections for global trends such as increasing global mean surface temperature under various emissions scenarios, the reliability of more local (and long term) projections is far weaker. But impact assessment and policy-making at the national level typically rely on local, high-resolution climate projections. In many ways, climate modelling and climate decision-making are now at a turning point, facing the tension between, on the one hand, the current focus on more detailed, complex climate models and on increasing computational resources and, on the other hand, possible fundamental epistemic constraints (such as structural instabilities) and uncertainties linked to high-resolution (local, long term) projections.
The project is divided in four strongly interconnected parts. The first part provides a detailed and critical landscape of the main current epistemic issues in contemporary climate science and climate modelling, with a focus on the degree of expert consensus. The second part aims to evaluate to what extent certain structural epistemic features of climate models (such as structural model error) point towards some fundamental epistemic limitation for climate modelling and may require some kind of ‘paradigm’ shift in the epistemology of climate science, where expert judgement may explicitly play a more important role in complement to complex climate model outputs. The third part investigates the nature and the role of scientific understanding and explanation (central to expert judgement) in climate science and climate modelling. The goal is to bring a new perspective on and develop a clear conceptual framework for the explanatory schemes and the relationships between the various (local and global) levels at work in climate science and climate modelling. The fourth part takes regional climate modelling in the Swiss context as a study case.
Funding
The Project is funded by Swiss National Science Foundation, SNSF professorships
Teaching
Seminar autumn 2020
Philosophy of science perspectives on the climate challenge
Julie Jebeile, Vincent Lam & Mason Majszak
Venue
14:15-16:00 Room F-113, Unitobler, 36 Lerchenweg.
Some of the sessions will be held online, contact Julie Jebeile for access information.
Background readings
- Frigg, R., Thompson, E. & Werndl, C. (2015). Philosophy of Climate Science Part I: Observing Climate Change. Philosophy Compass 10/12, 953–964. Full text
- Frigg, R., Thompson, E. & Werndl, C. (2015). Philosophy of Climate Science Part II: Modelling Climate Change. Philosophy Compass 10/12, 965–977. Full text
- Bradley R. & Steele K. (2015). Philosophy of Climate Science Part III: Making Climate Decisions. Philosophy Compass, 10/11, 799–810. Full text
- Parker, W. (2018). Climate Science. The Stanford Encyclopedia of Philosophy, Summer 2018 Edition. Full text
- Winsberg, E. (2018), Philosophy and Climate Science. Cambridge University Press. Full text
24.09.2020 Introduction & overview
- Parker, W. (2018). Climate Science. The Stanford Encyclopedia of Philosophy, Summer 2018 Edition. Full text
01.10.2020 Definition of climate
- Werndl, C. (2016). On Defining Climate and Climate Change. The British Journal for the Philosophy of Science 67 (2), 337-364. Full text
- Katzav, J. and Parker, W. (2018). Issues in the theoretical foundations of climate science. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 63, 141-149. Full text
08.10.2020 (online) Confirmation of models
- Carrier, M. and Lenhard, J. (2019). Climate Models: How to Assess Their Reliability. International Studies in the Philosophy of Science, 32(2), 81-100. Full text
- Parker, Wendy S. (2020). Model Evaluation: An Adequacy-for- Purpose View. Philosophy of Science, 87(3), 457-477. Full text
15.10.2020 Ethics of climate change
Invited speaker: Michel Bourban, University of Warwick.
- Bourban, M. (2020) Promoting Justice in Global Climate Policies. In book: Routledge Handbook on the Political Economy of the Environment. Publisher: Routledge.
22.10.2020 (online) Values in climate services
Invited speaker: Greg Lusk, Michigan State University
- Lusk, G. (2020). Political Legitimacy in the Democratic View: The Case of Climate Services. Philosophy of Science. Full text
- Parker, W. and Lusk, G. (2019). Incorporating User Values into Climate Services. Bulletin of the American Meteorological Society, 100(9), 1643-1650. Full text
29.10.2020 (online) History of climate change
Invited speaker: Dania Achermann, Bergische Universität Wuppertal.
- Heymann, M. and Achermann, D. (2018). From Climatology to Climate Science in the 20th Century. In Sam White, Christian Pfister, and Franz Mauelshagen (eds.). Palgrave Handbook of Climate History, Palgrave MacMillan UK. Full text
05.11.2020 (online) Holism in models
Invited speaker: Johannes Lenhard, Technische Universität Kaiserlautern.
- Lenhard, J. (2018). Holism, or the Erosion of Modularity: A Methodological Challenge for Validation. Philosophy of Science, 85(5), 832-844. Full text
12.11.2020 (online) Machine learning in climate science
Invited speaker: Suzanne Kawamleh, Indiana University.
- Kawamleh, S. (2020). Can machines learn clouds? The Epistemic Implications of Machine Learning Methods in Climate Science. Philosophy of Science.
19.11.2020 (online) Climate tipping points
- Curcifix, M. and Annan, J. (2020). Is the concept of ’tipping point’ helpful for describing and communicating possible climate futures? In M. Hulme (ed.), Contemporary Climate Change Debates, London: Routledge, pp. 23–35. Full text
- Lenton, T. M. (2020). Tipping positive change. Philosophical Transactions of the Royal Society B, 375: 20190123. Full text
26.11.2020 (online) Structural uncertainty
Invited speaker: Marina Baldissera Pacchetti, University of Leeds.
- Baldissera Pacchetti, M. (2020). Structural uncertainty through the lens of model building. Synthese. Full text
03.12.2020 (online) Robustness analysis
Invited speaker: Martin Vezér, Pennsylvania State University.
- Vezér, M. A., (2016). Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-Of-Evidence Inferences and Robustness Analysis, Studies in History and Philosophy of Science: Part A, 56: 95–102. Full text
10.12.2020 (online) Decisions with model ensembles
Invited speaker: Joe Roussos, Institute for Futures Studies, Stockholm.
- Roussos, J. and Bradley, R. and Frigg, R. (2020) Making confident decisions with model ensembles. Philosophy of science. Full text
17.12.2020 (online) Discussion and conclusion
Spring semester 2020
Seminar Philosophical Issues in Modeling Climate Change
Julie Jebeile, Ralf Hand, Vincent Lam & Jakob Zscheischler.
Location and time: Uni Mittelstrasse 43, Seminarraum 324, 14:15-16:00. Except on the 24.04: Seminarraum 124.
- 21.02.2020: Introduction & overview of climate modelling.
- Müller, P. 2010. Constructing Climate Knowledge With Computer Models. WIREs Climate Change 1, 565–580.
- 06.03.2020: Uncertainty in climate change projections.
- Stainforth, D. et al. 2007. Confidence, Uncertainty and Decision-Support Relevance in Climate Predictions. Philosophical Transactions of the Royal Society A 365: 2145-61.
- Parker, W. 2010. Whose Probabilities? Predicting Climate Change with Ensembles of Models. Philosophy of Science, 77: 985–999.
- 13.03.2020: Climate model evaluation.
- Baumberger, C., Knutti, R. and Hirsch Hadron, G. (2017). Building confidence in climate model projections: an analysis from fit. WIREs Climate Change, e454.
- Lloyd, E. A: (2009). Varieties of Support and Confirmation of Climate Models. Proceedings of the Aristotelian Society Supplementary Volume, 83: 213-232.
- Parker, W. S. (2009). Confirmation and Adequacy-For-Purpose in Climate Modelling. Proceedings of the Aristotelian Society Supplementary Volume, 83: 233-249.
- 20.03.2020: Values in climate science.
- Parker, W. S. & Winsberg, E. (2018) Values and evidence: how models make a difference. European Journal for Philosophy of Science 8(1): 125-142.
- Intemann, K. (2015) Distinguishing between legitimate and illegitimate values in climate modeling. European Journal for Philosophy of Science, 5, 217–232.
- 03.04.2020: Attribution of climate change and climate extremes.
- Lloyd, E. A. and Oreskes, N. (2018). Climate Change Attribution: When Is It Appropriate to Accept New Methods? Earth’s Future, 6: 311-325.
- Stott, P. A., Stone, D. A., and Allen, M. R. (2004). Human contribution to the European heatwave of 2003. Nature. 432: 610-614.
- Winsberg, E., Oreskes, N. and Lloyd, E. A. (2019). Severe Weather Attribution: Why values won’t go away.
- 24.04.2020 (Seminarraum 124): Climate change and ethical issues.
- Caney, S. 2009. Climate Change and the Future: Discounting for Time, Wealth and Risk. Journal of Social Philosophy 40, 163–186.
- Broome, J. 2008. The Ethics of Climate Change. Scientific American, June 69–73.
- Caney, S. 2016. The Struggle for Climate Justice in a Non-ideal World. Midwest Studies in Philosophy XL:1 “Ethics and Global Climate Change”, 9–26.
- 15.05.2020: Adaptation and regional climate modeling.
- Oreskes, N., Stainforth, D. A. and Smith, L. A. (2010). Adaptation to Global Warming: Do Climate Models Tell Us What We Need to Know? Philosophy of Science, 77: 1012-1028.
- Hall, A. (2014). Projecting regional change. Science, 346: 1461-1462.
- Maraun, D. and Widmann, M. (2018). Statistical Downscaling and Bias Correction for Climate Research. Cambridge: Cambridge University Press, chapter 17.
Background readings for the whole course:
- Frigg, R., Thompson, E. & Werndl, C. 2015. Philosophy of Climate Science Part I: Observing Climate Change. Philosophy Compass 10/12, 953–964.
- Frigg, R., Thompson, E. & Werndl, C. 2015. Philosophy of Climate Science Part II: Modelling Climate Change. Philosophy Compass 10/12, 965–977.
- Bradley R. & Steele K. 2015. Philosophy of Climate Science Part III: Making Climate Decisions. Philosophy Compass 10/11, 799–810.
- Parker, W. 2018. Climate Science. The Stanford Encyclopedia of Philosophy (Summer 2018 Edition).
- Winsberg, E. 2018, Philosophy and Climate Science. Cambridge: Cambridge University Press.
Fall semester 2019
Seminar Philosophy of science perspectives on the climate challenge
Vincent Lam
Interdisciplinary meetings devoted to the foundational and conceptual issues in climate science and climate modelling (and more generally linked the climate challenge).
- 04.10.19, 10:15-12:00, Unitobler F004: Introduction
- 11.10.19, 10:15-12:00, Unitobler F004: Discussion of the papers
- Frigg, R. et al. (2014), Laplace’s Demon and the Adventures of His Apprentices, Philosophy of Science 81: 31-59
- Nabergall et al. (2019), An antidote for hawkmoths: on the prevalence of structural chaos in non-linear modeling, European Journal for Philosophy of Science 9:21
- Smith, L. A. (2002), What might we learn from climate forecasts, Proceedings of the National Academy of Sciences 4: 2487-92
- McWilliams, J. C. (2007), Irreducible imprecision in atmospheric and oceanic simulations, Proceedings of the National Academy of Sciences 21: 8709-13.
- 17.10.19, 10:15-12:00, Unitobler F001: Talk by Roman Frigg (London School of Economics) We will discuss an unpublished draft, please contact us to get the document.
- 18.10.19, 10:15-12:00, Unitobler F004: Discussion of the papers
- Reichstein et al. (2019), Deep learning and process understanding for data-driven Earth system science, Nature 566, 195-204.
- Knüsel et al. (2019), Applying big data beyond small problems in climate research, Nature Climate Change 9, 196-202.
- Unpublished draft. Please contact us to get the document.
- 15.11.19, 9:15-12:00, Unitobler F011: Workshop ‘Big data, machine learning, climate modelling & understanding’ with Benedikt Knüsel (ETHZ), Lionel Moret (MeteoSwiss) and Tim Räz (UNIBE).
- 22.11.19, 10:15-12:00, Unitobler F004. Talk by Juan Avella (UNIBE) & discussion of the paper :
- Weaver et al. (2013), Improving the contribution of climate model information to decision making, WIREs: Clim Change 4:39-60.
- 29.11.19, 10:15-12:00, Unitobler F004: Talk by Mathias Frisch (Leibniz Universität Hannover)
- 05.12.19, 11:15-13:00, Unitobler F114: Talk by Stefan Brönnimann (UNIBE)
- 13.12.19, 10:15-12:00, Unitobler F004: Talk by Emmanuele Russo (UNIBE) & discussion of the paper:
- Samartin et al. (2017). Warm Mediterranean mid-Holocene summers inferred from fossil midge assemblages. Nature Geosci 10:207–212.
Colloquium: Philosophy of science
Claus Beisbart & Vincent Lam
- Every friday, 14:15-16:00, Unitobler F001.
Spring semester 2019
Seminar Philosophical Issues in Modeling Climate Change
Claus Beisbart, Vincent Lam & Stefan Brönnimann
People
Principal investigator
- Name / Titel
- Prof. Dr. Vincent Lam
- Funktion
- SNF Professor
- vincent.lam@philo.unibe.ch
- Phone
- 031 631 34 55
Team members
- Dr. Julie Jebeile, postdoctoral researcher (UniBE, personal website).
- Mason Majszak, PhD student.
- Daniel C. Bünzli, technical staff.