Abstract
There are numerous mathematical models of many environmental phenomena and new ones are continually being constructed. These models, typically depend on a large number of parameters and are often able to reproduce historical trends of the quantities they represent. However, it would also be very useful to have a methodology for assessing the reliability of the models’ forecasts in terms of how fast they propagate errors. This would allow us to compare different models and, perhaps, select the one which magnifies errors at a slow rate. In this paper we deal with a model formulated as a dynamical system but we expect that conceptually similar approaches to the uncertainty analysis may be used in other classes of models.
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References
Braddock, R. D., Filar, J. A. and Zapert R. (1993). System and Control Theory Perspectives of the IMAGE Greenhouse Model, Lecture Notes in Control Theory and Information Sciences, Vol. 184, pp. 53–68. Springer Verlag.
Braddock, R.D., Filar, J.A., den Elzen, M.G., Rotmans J. and Zapert, R. (1994). Mathematical Formulation of the IMAGE Greenhouse Model, Applied Mathematical Modelling, 18, pp. 234–254, 1994.
Cox, D.C. and Baybutt (1981). “Methods for Uncertainty Analysis: A Comparative Study”, Risk Analysis 4, pp. 251–258.
Den Elzen, M. (1993). Uncertainty and Risk Analysis for Global Change: An Integrated Modeling Approach, PhD Thesis, forthcoming, University of Limburg, The Netherlands.
Dilks, D.W., Canale, R.P. and Meier, P.G. (1989). “Analysis of Model Uncertainty Using Bayesian Monte Carlo”, in Malina, F.J. Jr (Ed.), Proceedings of the 1989 A.S.C.E. Conference on Environmental Engineering, pp. 571–577, American Society of Civil Engineering, New York.
Edmonds, J.A., Reilly, J.M., Gardner, R.H. and Brenkert, A. (1986). 2Uncertainty in Future Global Energy Use and Fossil Fuel C02 Emissions 1975 to 2075, TR036, US Dept. of Energy, Carbon Dioxide Research Division, Washington DC.
Hansen, J.E. and Lacis, A.A. (1990). “Sun and Dust Versus Greenhouse Gases: An Assessment of their Relative Roles in Global Climate Change”, Nature 346, pp. 713–719.
Houghton, J.T., Jenkins, G.J. and Ephraums, J.J., (Eds.) (1990). Climate Change. The IPCC Scientific Assessment, Cambridge University Press.
Houghton, J.T., Callander, B.A. and Varney S.K. (1992). Climate Change 1992. The Supplementary Report to the IPCC Scientific Assessment, Cambridge University Press.
Kloeden, P.E. and Platen, E. (1992). Numerical Solutions of Stochastic Differential Equation, Springer Verlag, London.
Nijmeier H. and Van der Schaft A.J., Nonlinear Dynamical Systems, Springer Verlag, Amsterdam, 1991.
O′Neill, R., Gardner, R.H. and Martin, J. (1980). “Analysis of Parameter Error in a Nonlinear Model”, Ecological Modeling 8, pp. 297–311.
Patwardhan, A. and Small, M.J. (1992). “Bayesian Methods for Model Uncertainty Analysis with Application to the Future Sea Level Rise”, Risk Analysis 12/4, pp. 513–523.
Rotmans, J. (1990). IMAGE: An Integrated Model to Assess the Greenhouse Effect, Kluwer, Dordrecht, The Netherlands.
Ruymgaart, P.A. and Soong, T.T. (1988). Mathematics of Kalman-Bucy Filtering, Springer Verlag, New York.
Wigley, T.M., and Raper, C.S.B. (1990). “Natural Variability of the Climate System and Detection of the Greenhouse Effect”, Nature 344, pp. 324–327.
Wigley, T.M. and Raper, C.S.B. (1992). “Implications for Climate and Sea Level of Revised IPCC Emissions Scenarios”, Nature 357.
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© 1996 Kluwer Academic Publishers
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Filar, J.A., Zapert, R. (1996). Uncertainty analysis of a greenhouse effect model. In: Carraro, C., Haurie, A. (eds) Operations Research and Environmental Management. Economics, Energy and Environment, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0129-2_5
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DOI: https://doi.org/10.1007/978-94-009-0129-2_5
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