Computational methods for parameter estimation in climate models

Bayesian Analysis

Volumn 3, Issue 4, 2008, Pages 823-850

  Villagran, Alejandro ^a   Huerta, Gabriel ^a   Jackson, Charles S ^b   Sen, Mrinal K ^b  

^a UNIVERSITY OF NEW MEXICO   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Adaptive metropolis; Climate models; Inverse problems; Parametric uncertainties; Simulated annealing

Indexed keywords

EID: 60749087875     PISSN: 19360975     EISSN: 19316690     Source Type: Journal    
DOI: 10.1214/08-BA331     Document Type: Article

References (38)

1. Allen, M. (1999). "Do-it-yourself climate prediction." Nature, 401: 642. 824
2. Annan, J. and Hargreaves, J. (2007). "Efficient estimation and ensemble generation in climate modelling." Philosophical Transactions of the Royal Society A, 365: 2077-2088. 837, 838
3. Barnett, D., Brown, S., Murphy, J., Sexton, D., and Webb, M. (2006). "Quantifyinguncertainty in changes in extreme event frequency in response to doubled CO2 using a large ensemble of GCM simulations." Climate Dynamics, 26: 489-511. 824
4. Collins, M., Booth, B., Harris, G., Murphy, J., Sexton, D., and Webb, M. (2006). "Towards quantifying uncertainty in transient climate change." Climate Dynamics, 127-147. 824
5. Forest, C., Allen, M. R., Sokolov, A. P., and Stone, P. H. (2001). "Constraining climate model properties using optimal fingerprint detection methods." Climate Dynamics, 18: 277-295. 824, 825
6. Forest, C., Allen, M. R., Stone, P. H., and Sokolov, A. P. (2000). "Constraining uncer-tainties in climate models using climate change detection techniques." Geophys. Res. Lett., 27(4): 569-572. 824, 825
7. Forest, C., Stone, P. H., Sokolov, A. P., Allen, M. R., and Webster, M. D. (2002). "Quantifying uncertainties in climate system properties with the use of recent climate observations." Science, 295: 113-117. 824, 825
8. Gates, W. L., Boyle, J. S., Covey, C., Dease, C. G., Doutriaux, C. M., Drach, R. S., Fiorino, M., Gleckler, P. J., Hnilo, J. J., Marlais, S. M., Phillips, T. J., Potter, G. L., Santer, B. D., Sperber, K. R., Taylor, K. E., and Williams, D. N. (1999). "An Overview of the Results of the Atmospheric Model Intercomparison Project (AMIP I)." Bulletin of the American Meteorological Society, 80(1): 29-56. 824
9. Gelfand, A. and Smith, A. (1990). "Sampling-Based Approaches to Calculating Marginal Densities." Journal of the American Statistical Association, 85: 398-409. 829
10. Gelman, A., Roberts, G., and Gilks, W. (1996). "Efficient Metropolis jumping rules." In Bernardo, J., Berger, J., Dawid, A., and Smith, A. (eds.), Bayesian Statistics, volume 5, 599-608. Oxford University Press. 832
11. Geman, S. and Geman, D. (1984). "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images." IEEE Transactions PAMI-6, 721-741. 828
12. Haario, H., Laine, M., Lehtinen, M., Saksman, E., and Tamminen, J. (2004). "Markov Chain Monte Carlo methods for high dimensional inversion in remote sensing." Jour-nal of Royal Statistical Society, 66: 591-607. 830, 837
13. Haario, H., Laine, M., Mira, A., and Saksman, E. (2006). "DRAM: Efficient adaptive MCMC." Statistics and Computing, 16: 339-354. 832
14. Haario, H., Saksman, E., and Tamminen, J. (1999). "Adaptive proposal distribution for random walk Metropolis algorithm." Computational Statistics, 14: 375-395. 830, 837
15. Haario, H. (2001). "An Adaptive Metropolis algorithm." Bernoulli, 7: 223-242. 830, 832, 837
16. Haario, H. (2005). "Componentwise adaptation for high dimensional MCMC." Computational Statistics, 20(2): 265-263. 837
17. Hastings, W. (1970). "Monte Carlo sampling methods using Markov chains and their applications." Biometrika, 57: 97-109. 829
18. Ingber, L. (1989). "Very fast simulated re-annealing." Mathematical Computational Modelling, 12: 967-973. 829
19. Jackson, C. S. and Broccoli, A. (2003). "Orbital forcing of Arctic climate: mechanisms of climate response and implications for continental glaciation." Climate Dynamics, 21: 539-557. 825, 826
20. Jackson, C. S., Sen, M., Huerta, G., Deng, Y., and Bowman, K. (2008). "Error Reduc-tion and Convergence in Climate Prediction." Journal of Climate (in press). 824, 837
21. Jackson, C. S., Sen, M., and Stoffa, P. (2004). "An Efficient Stochastic Bayesian Ap-proach to Optimal Parameter and Uncertainty Estimation for Climate Model Predic-tions." Journal of Climate, 17: 2828-2840. 827, 828, 829, 833
22. Joussaume, S. and Taylor, K. (2000). "The Paleoclimate Modeling Intercomparison Project (PMIP)." In Braconnot, P. (ed.), Proceedings of the third PMIP workshop, Canada, 4-8 October 1999, WCRP-111, WMO/TD-1007, 271. 824
23. Kettleborough, J., Booth, B., Stott, P., and Allen, M. (2007). "Estimates of Uncertainty in Predictions of Global Mean Surface Temperature." Journal of Climate, 20: 843-855. 825
24. Kirkpatrick, S., Gelatt, J., and Vecchi, M. (1983). "Optimization by simulated anneal-ing." Science, 220: 671-680. 829
25. Lopez, A., Tebaldi, C., New, M., Stainforth, D., Allen, M., and Kettleborough, J. (2006). "Two Approaches to Quantifying Uncertainty in Global Temperature Changes." Jour-nal of Climate, 19: 4785-4796. 825, 827
26. McAvaney, B. J., Covey, C., Joussaume, S., Kattsov, V., Kitoh, A., Ogana, W., Pitman, A., Weaver, A., Wood, R., and Zhao, Z. (2001). "Model Evaluation. Climate Change 2001: The Scientific Basis Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change." In Houghton, J., Ding, Y., Griggs, D., Noguer, M., van der Linden, P., Dai, X., Maskell, K., and Johnson, C. (eds.), Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), 881. Cambridge University Press,UK. 824
27. McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D., and White, K. S. (eds.) (2001). Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press, UK. 824
28. Meehl, G., Boer, G., Covey, C., Latif, M., and Stouffer, R. (2000). "The Coupled Model Intercomparison Project (CMIP)." Bulletin of the American Meteorological Society, 81(2): 313-318. 824
29. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A., and Teller, E. (1953). "Equations of State Calculations by Fast Computing Machines." Journal of Chemical Physics, 21: 1087-1091. 829
30. Milankovitch, M. (1941). "Canon of insolation and the ice age problem (Israel Program for Scientific Translations, Jerusalem)." 825
31. Murphy, J., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., and Stainforth, D. A. (2004). "Quantification of modelling uncertainties in a large ensemble of climate change simulations." Nature, 430: 768-772. 824
32. Parry, M., Canziani, O., Palutikof, J., van der Linden, P., and Hanson, C. (eds.) (2007). IPCC, 2007: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contri-bution of Working Group II to the Fourth Assessment Report of Intergovermental panel on Climate Change. Cambridge University Press, UK. 824
33. Sambridge, M. and Mosegaard, K. (2002). "Monte Carlo Methods in Geophysical Inverse Problems." Review of Geophysics, 40: 1-29. 828
34. Sansó, B., Forest, C., and Zantedeschi, D. (2008). "Inferring Climate System Properties Using a Computer Model (with discussion)." Bayesian Analysis, 3(1): 1-62. 835, 837, 838
35. Sen, M. and Stoffa, P. (1996). "Bayesian Inference, Gibbs sampler and uncertainty estimation in geophysical inversion." Geophysical Prospecting, 44: 313-350. 829, 833, 837
36. Stainforth, D., Aina, T., Christensen, C., Collins, M., Faull, N., Frame, D. J., Kettle-borough, J. A., Knight, S., Martin, A., Murphy, J. M., Piani, C., Sexton, D., Smith, L. A., Spicer, R. A., Thorpe, A. J., and Allen, M. R. (2005). "Uncertainty in pre-dictions of the climate response to rising levels of greenhouse gases." Nature, 433: 403-406. 824
37. Tebaldi, C., Smith, R., Nychka, D., and Mearns, L. (2005). "Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles." Journal of Climate, 18: 1524-1540. 824, 827
38. Tierney, L. and Mira, A. (1999). "Some Adaptive Monte Carlo Methods for Bayesian Inference." Statistics in Medicine, 18: 2507-2515. 830