A non-homogeneous hidden Markov model for precipitation occurrence

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 48, Issue 1, 1999, Pages 15-30

  Hughes, James P ^a   Guttorp, Peter ^a   Charles, Stephen P ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b CSIRO   (Australia)

Author keywords

Climate change; EM algorithm; Hidden Markov model; Monte Carlo maximum likelihood; Precipitation model

Indexed keywords

EID: 0033480863     PISSN: 00359254     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9876.00136     Document Type: Article

References (29)

1. Bardossy, A. and Plate, E. J. (1992) Space-time models for daily rainfall using atmospheric circulation patterns. Wat. Resour. Res., 28, 1247-1259.
2. Baum, L. E., Petrie, T., Soules, G. and Weiss, N. (1970) A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann. Math. Statist., 41, 164-171.
3. Besag, J. (1975) Statistical analysis of non-lattice data. Statistician, 24, 179-195.
4. Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J. (1984) Classification and Regression Trees. Belmont: Wadsworth.
5. Charles, S. P., Hughes, J. P., Bates, B. C. and Lyons, T. J. (1996) Assessing downscaling models for atmospheric circulation - local precipitation linkage. In Proc. Int. Conf. Water Resources and Environmental Research: Towards the 21st Century, Kyoto, vol. 1, pp. 269-276. Kyoto: Kyoto University.
6. Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977) Maximum likelihood from incomplete data via the EM algorithm (with discussion). J. R. Statist. Soc. B, 39, 1-38.
7. Gabriel, K. R. and Neumann, J. (1962) A Markov chain model for daily rainfall occurrences at Tel-Aviv. Q. J. R. Meteorol. Soc., 88, 85-90.
8. Gelfand, A. E. and Smith, A. F. M (1990) Sampling-based approaches to calculating marginal densities. J. Am. Statist. Ass., 85, 398-409.
9. Gentilli, J. (1972) Australian Climate Patterns. Melbourne: Nelson.
10. Geyer, C. J. and Thompson, E. A. (1992) Constrained Monte Carlo maximum likelihood for dependent data (with discussion). J. R. Statist. Soc. B, 54, 657-699.
11. Giorgi, F. and Mearns, L. O. (1991) Approaches to the simulation of regional climate change: a review. Rev. Geophys., 29, 191-216.
12. Hay, L., McCabe, G. J., Wolock, D. M. and Ayers, M. A. (1991) Simulation of precipitation by weather type analysis. Wat. Resour. Res., 27, 493-501.
13. Hughes, J. P. (1997) Computing the observed information in the hidden Markov model using the EM algorithm. Probab. Statist. Lett., 32, 107-114.
14. Hughes, J. P. and Guttorp, P. (1994) A class of stochastic models for relating synoptic atmospheric patterns to regional hydrologic phenomena. Wat. Resour. Res., 30, 1535-1546.
15. Hughes, J. P., Guttorp, P. and Charles, S. P. (1996) A nonhomogeneous hidden Markov model for precipitation. Technical Report 316. Department of Statistics, University of Washington, Seattle.
16. Intergovernmental Panel on Climate Change (1995) Climate Change 1995, the Science of Climate Change (eds J. T. Houghton, L. G. Meira Filho, B. A. Callander, N. Harris, A. Kattenberg and K. Maskell). Cambridge: Cambridge University Press.
17. Juang, B. H. and Rabiner, L. R. (1991) Hidden Markov models for speech recognition. Technometrics, 33, 251-272.
18. Kass, R. E. and Raftery, A. E. (1995) Bayes factors. J. Am. Statist. Ass., 90, 773-795.
19. Kavvas, M. L. and Delleur, J. W. (1981) A stochastic cluster model for daily rainfall sequences. Wat. Resour. Res., 17, 1151-1160.
20. Kidson, J. W. (1994) The relation of New Zealand daily and monthly weather patterns to synoptic weather types. Int. J. Climatol., 14, 723-737.
21. LeCam, L. (1961) A stochastic theory of precipitation. In Proc. 4th Berkeley Symp. Mathematical Statistics and Probability. Berkeley: University of California Press.
22. Rai, S. N. and Matthews, D. E. (1993) Improving the EM algorithm. Biometrics, 49, 587-591.
23. Southern, R. L. (1979) The atmosphere. In Environment and Science (ed. B. J. O'Brien), pp. 183-226. Nedlands: University of Western Australia Press.
24. Stern, R. D. and Coe, R. (1984) A model fitting analysis of daily rainfall data (with discussion). J. R. Statist. Soc. A, 147, 1-34.
25. Sturman, A. and Tapper, N. (1996) The Weather and Climate of Australia and New Zealand. Oxford: Oxford University Press.
26. Titterington, D. M. (1990) Some recent research in the analysis of mixture distributions. Statistics, 21, 619-641.
27. Waymire, E. and Gupta, V. K. (1981) The mathematical structure of rainfall representations: 2, A review of the theory of point processes. Wat. Resour. Res., 17, 1273-1285.
28. Wilby, R. L., Greenfield, B. and Glenny, C. (1994) A coupled synoptic-hydrological model for climate change impact assessment. J. Hydrol., 153, 265-290.
29. Yarnal, B. (1993) Synoptic climatology in environmental analysis. London: Blehaven.