Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-25T05:51:32.425Z Has data issue: false hasContentIssue false
  • English
  • Français

The practice of climate simulation and its social and political context

Published online by Cambridge University Press:  01 April 2016

A.C. Petersen
A.C. Petersen*
Affiliation:
Netherlands Environmental Assessment Agency, P.O. Box 303, 3720 AH Bilthoven, the Netherlands. Email:[email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The practice of climate simulation takes place in a polarized social and political context. In this paper some methodological aspects of the practice of climate simulation are addressed and the potential value-ladenness of modelling assumptions is discussed. I claim that there is clearly a plurality of values guiding climate simulation efforts with climate scientists themselves also commonly holding different political views on the climate-change problem. There exist climate models of varying levels of concreteness and with different basic assumptions, and the modelling approaches behind these models are valued differently by different groups of climate scientists. The social and political context in which the climate modelling is done plays a role in these value judgements. In order to prevent one particular group of models from dominating the field for social and/or political reasons, the climate-modelling community should acknowledge the vital and necessary role of plurality in the practice of climate science and should stimulate reflection within this practice. Finally, while the IPCC partly addresses the issue by presenting model ensembles, the uncertainties in climate simulation should be better communicated to policy makers and politicians.

Keywords

climate changecomputer simulationscientific practicesocial and political valuesuncertaintyvalue-ladenness
Type
Research Article
Information
Netherlands Journal of Geosciences , Volume 87 , Issue 3 , September 2008 , pp. 219 - 229
Copyright
Copyright © Stichting Netherlands Journal of Geosciences 2008

References

Bray, D. & Von Storch, H., 1999. Climate science: an empirical example of postnormal science. Bulletin of the American Meteorological Society 80: 440–455.Google Scholar
Bray, D. & Von Storch, H., 2007. Climate Scientists’ Perceptions of Climate Change Science, GKSS Report 2007/11. Institute for Coastal Research, GKSS Forschungszentrum (Geesthacht) Germany: 124 pp. Available at: http://dvsun3.gkss.de/BERICHTE/GKSS_Berichte_2007/GKSS_2007_ll.pdf.Google Scholar
Claussen, M., Mysak, L.A., Weaver, A.J., Crucifix, M., Fichefet, T., Loutre, M.-F., Weber, S.L., Alcamo, J., Alexeev, V.A., Berger, A., Calov, R., Ganopolski, A., Goosse, H., Lohmann, G., Lunkeit, F., Lunkeit, F., Mokhov, I.I., Petoukhov, V., Stone, P. & Wang, Z., 2002. Earth system models of intermediate complexity: closing the gap in the spectrum of climate system models. Climate Dynamics 18: 579–586.Google Scholar
Edwards, P.N., 1999. Global climate science, uncertainty and politics: data-laden models, model-filtered data. Science as Culture 8: 437–472.Google Scholar
Funtowicz, S.O. & Ravetz, J.R., 1993. Science for the post-normal age. Futures 25: 739–755.Google Scholar
Harvey, L.D.D. & co-authors, 1997. An Introduction to Simple Climate Models Used in the IPCC Second Assessment Report, IPCC Technical Paper 2. Intergovernmental Panel on Climate Change (Geneva): 50 pp. Available at: http://www.ipcc.ch/pdf/technical-papers/paper-II-en.pdf.Google Scholar
Held, I.M., 2005. The gap between simulation and understanding in climate modeling. Bulletin of the American Meteorological Society 86: 1609–1614.Google Scholar
Hisschemoller, M., Hoppe, R., Groenewegen, P. & Midden, C.J.H., 2001. Knowledge use and political choice in Dutch environmental policy: a problem-structuring perspective on real life experiments in extended peer review. In: Hisschemoller, M., Hoppe, R., Dunn, W.N. & Ravetz, J.R. (eds): Knowledge, Power, and Participation in Environmental Policy Analysis. Transaction Publishers (New Brunswick) USA: 437–470.Google Scholar
IPCC, 2001. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell, K. & Johnson, C.A. (eds)). Cambridge University Press (Cambridge) United Kingdom & (New York) NY, USA: 881 pp.Google Scholar
IPCC, 2007a. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Solomon, S., Qin, D., Manning, M., Chen, I., Marquis, M., Averyt, K.B., Tignor, M. & Miller, H.L. (eds)). Cambridge University Press (Cambridge) United Kingdom & (New York) NY, USA: 996 pp.Google Scholar
IPCC, 2007b. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Parry, M.L., Canziani, O.F., Palutikof, J.P., Van der Linden, P.J. & Hanson, C.E. (eds)). Cambridge University Press (Cambridge) United Kingdom & (New York) NY, USA: 976pp.Google Scholar
IPCC, 2007c. Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Metz, B., Davidson, O.R., Bosch, P.R., Dave, R. & Meyer, L.A. (eds)). Cambridge University Press (Cambridge) United Kingdom & (New York) NY, USA: 851 pp.Google Scholar
Kloprogge, P., Van der Sluijs, J.P. & Petersen, A.C., submitted. A method for the analysis of assumptions in model-based environmental assessments.Google Scholar
Lahsen, M., 2008. Experiences of modernity in the greenhouse: a cultural analysis of a physicist ‘trio’ supporting the backlash against global warming. Global Environmental Change 18: 204–219.Google Scholar
Laudan, L., 1984. Science and Values: The Aims of Science and Their Role in Scientific Debate. University of California Press (Berkeley) CA, USA: 149 pp.Google Scholar
Leggett, J., 1999. The Carbon War: Global Warming at the End of the Oil Era. Penguin Books (London) UK: 342 pp.Google Scholar
McGuffie, K. & Henderson-Sellers, A., 1997. A Climate Modelling Primer, 2nd edition. John Wiley & Sons (New York): 268 pp.Google Scholar
Müller, P. & Von Storch, H., 2004. Computer Modelling in Atmospheric and Oceanic Sciences: Building Knowledge. Springer (Berlin, Heidelberg & New York): 304 pp.Google Scholar
National Research Council, 1998. The Capacity of U.S. Climate Modeling to Support Climate Change Assessment Activities. National Academy Press (Washington DC) USA: 78 pp.Google Scholar
Parker, W.S., 2006. Understanding pluralism in climate modelling. Foundations of Science 11: 349–368.Google Scholar
Petersen, A.C., 2000. Models as technological artefacts. Social Studies of Science 30: 793–799.Google Scholar
Petersen, A.C., 2006a. Simulation uncertainty and the challenge of postnormal science, in: Lenhard, J., Küppers, G. & Shinn, T. (eds): Simulation: Pragmatic Constructions of Reality - Sociology of the Sciences, vol. 25. Springer (Dordrecht) the Netherlands: 173–185.Google Scholar
Petersen, A.C., 2006b. Simulating Nature: A Philosophical Study of Computer-Simulation Uncertainties and Their Role in Climate Science and Policy Advice. Het Spinhuis Publishers (Apeldoorn) the Netherlands & (Antwerp) Belgium: 210 pp. Available at: http://hdl.handle.net/1871/11385.Google Scholar
Pielke, R.A., 2007. The Honest Broker: Making Sense of Science in Policy and Politics. Cambridge University Press (Cambridge) UK: 188 pp.Google Scholar
Popper, K.R., (1934) 1959. The Logic of Scientific Discovery. Routledge (London) UK: 480 pp.Google Scholar
Randall, D.A. & Wielicki, B.A., 1997. Measurements, models, and hypotheses in the atmospheric sciences. Bulletin of the American Meteorological Society 78: 399–406.Google Scholar
Rind, D., 1999. Complexity and climate. Science 284: 105–107.Google Scholar
Shackley, S., 2001. Epistemic lifestyles in climate change modeling. In: Miller, C.A. & Edwards, P.N. (eds): Changing the Atmosphere: Expert Knowledge and Environmental Governance. MIT Press (Cambridge) Ma, USA: 107–133.Google Scholar
Shackley, S., Young, P., Parkinson, S. & Wynne, B., 1998. Uncertainty, complexity and concepts of good science in climate change modeling: are GCMs the best tools? Climatic Change 38: 155–201.Google Scholar
Shackley, S., Risbey, J., Stone, P. & Wynne, B., 1999. Adjusting to policy expectations in climate change modeling: an interdisciplinary study of flux adjustments in coupled atmosphere-ocean general circulation models. Climatic Change 43: 413–454.Google Scholar
Swart, R., Bernstein, L., Ha-Duong, M. & Petersen, A., 2008. Agreeing to disagree: uncertainty management in assessing climate change, impacts and responses by the IPCC. Climatic Change, in press, doi:10.1007/s10584-008-9444-7: 29 pp.Google Scholar
Tennekes, H., 1994. The limits of science. In: Zweers, W. & Boersema, J.J. (eds.): Ecology, Technology and Culture. The White Horse Press (Cambridge) UK: 72–88.Google Scholar
Van Asselt, H., Berghuis, J., Biermann, F., Cornelisse, C., Haug, C., Gupta, J. & Massey, E., 2008. Exploring the Socio-Political Dimensions of Climate Change Mitigation, IVM Report W-08/18. Institute for Environmental Studies, Vrije Universiteit (Amsterdam): 104 pp. Available at: http://www.ivm.vu.nl/images_upload/4BC45814-D58C-1894-9C415605D27FB5Bl.pdf.Google Scholar
Van der Sluijs, J.P., Petersen, A.C., Janssen, P.H.M., Risbey, J.S. & Ravetz, J.R., 2008. Exploring the quality of evidence for complex and contested policy decisions. Environmental Research Letters 3: 024008: 9 pp.Google Scholar
Wardekker, J.A., Van der Sluijs, J.P., Janssen, P.H.M., Kloprogge, P. & Petersen, A.C., 2008. Uncertainty communication in environmental assessments: views from the Dutch science-policy interface. Environmental Science & Policy 11: 627–641.Google Scholar
Werner, B.T., 1999. Complexity in natural landform patterns. Science 284: 102–104.Google Scholar