An assessment of the foundational assumptions in high-resolution climate projections: the case of UKCP09
- 410 Downloads
The United Kingdom Climate Impacts Programme’s UKCP09 project makes high-resolution projections of the climate out to 2100 by post-processing the outputs of a large-scale global climate model. The aim of this paper is to describe and analyse the methodology used and then urge some caution. Given the acknowledged systematic, shared errors of all current climate models, treating model outputs as decision-relevant projections can be significantly misleading. In extrapolatory situations, such as projections of future climate change, there is little reason to expect that post-processing of model outputs can correct for the consequences of such errors. This casts doubt on our ability, today, to make trustworthy probabilistic projections at high resolution out to the end of the century.
KeywordsClimate change Prediction Projection Simulation Model Probability Reliability Emulation Systematic error Decision-making Structural model error
Work for this paper has been supported by the LSE’s Grantham Research Institute on Climate Change and the Environment and the Centre for Climate Change Economics and Policy funded by the Economics and Social Science Research Council and Munich Re. Frigg further acknowledges financial support from the AHRC-funded ‘Managing Severe Uncertainty’ Project and Grant FFI2012-37354 of the Spanish Ministry of Science and Innovation (MICINN). Smith would like to acknowledge continuing support from Pembroke College, Oxford, from the Blue-Green Cities Research Consortium funded by EPSRC (Grant EP/K013661/1), and from RDCEP via NSF grant No. 0951576. We would like to thank Wendy Parker, Erica Thompson, and Charlotte Werndl for comments on earlier drafts and/or helpful discussions.
- Jenkins, G., Murphy, J., Sexton, D., Lowe, J., & Jones, P. (2009). UK climate projections: briefing report, DEFRA. Met Office Hadley Centre, Exeter.Google Scholar
- Judd, K., & Smith, L. A. (2004). Indistinguishable states II: The imperfect model scenario. Physica D, 196, 224–242.Google Scholar
- Lorenz, E. (1968). Climate determinism. Meteorological Monographs, 8(30), 1–3.Google Scholar
- Murphy, J., Sexton, D., Jenkins, G., Boorman, P., Booth, B., Brown, K., et al. (2010). UK climate projections science report: Climate change projections. Version 3, updated December 2010. http://www.ukclimateprojections.defra.gov.uk/22544. Met Office Hadley Centre, Exeter.
- Oreskes, N. (2007). The scientific consensus on climate change: How do we know we’re not wrong? In J. F. C. DiMento & P. Doughman (Eds.), Climate change: What it means for us, our children, and our grandchildren (pp. 65–99). Boston: MIT Press.Google Scholar
- Parker, W. (2013). Ensemble modeling, uncertainty and robust predictions. Wiley Interdisciplinary Reviews: Climate Change, 4(3), 213–223.Google Scholar
- Salmon, M., Earman, J., Glymour, C., Lennox, J. G., Machamer, P., McGuire, J. E., et al. (1992). Introduction to the philosophy of science. Indianapolis and Cambridge: Hackett.Google Scholar
- Smith, L. A. (2000). Disentangling uncertainty and error: on the predictability of nonlinear systems. In A. I. Mees (Ed.), Nonlinear Dynamics and Statistics (pp. 31–64). Boston: Birkhauser.Google Scholar
- Smith, L. A., Du, H., Suckling, E. B., & Niehörster, F. (2014). Probabilistic skill in ensemble seasonal forecasts. Quarterly Journal of the Royal Meteorological Society. doi: 10.1002/qj.2403.
- Smith, L. A., & Stern, N. (2011). Uncertainty in science and its role in climate policy. Philosophical Transactions of the Royal Society A, 369, 1–24.Google Scholar
- Solomon, S., Qin, D., & Manning, M. (Eds.). (2007). Contribution of Working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.Google Scholar
- Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. M. B., Allen, S. K., Boschung, J., et al. (Eds.). (2013). Climate change 2013. The physical science basis. Working group I contribution to the fifth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.Google Scholar
- Tang, S., & Dessai, S. (2012). Usable science? The UK climate projections 2009 and decision support for adaptation planning. forthcoming in weather, climate, and society.Google Scholar
- Thompson, E. L. (2013). Modelling North Atlantic storms in a changing climate. Ph.D. Thesis. Imperial College, London.Google Scholar
- Winsberg, E., & Biddle, J. (2010). Value judgements and the estimation of uncertainty in climate modeling. In P. D. Magnus & J. B. Busch (Eds.), New waves in philosophy of science (pp. 172–197). London: Palgrave Macmillan.Google Scholar