A Markov chain model of tornadic activity

Monthly Weather Review

Volumn 131, Issue 12, 2003, Pages 2941-2953

  Drton, Mathias ^a   Marzban, Caren ^a,b   Guttorp, Peter ^a   Schaefer, Joseph T ^c  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF OKLAHOMA   (United States)

^c UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATOLOGY; DATA REDUCTION; MARKOV PROCESSES; MATHEMATICAL MODELS; PARAMETER ESTIMATION; WEATHER FORECASTING;

TORNADIC ACTIVITY;

TORNADOES;

FORECASTING METHOD; MARKOV CHAIN; MODELING; SPRING (SEASON); SUMMER; TORNADO;

NORTH AMERICA; UNITED STATES;

EID: 0346655449     PISSN: 00270644     EISSN: None     Source Type: Journal    
DOI: 10.1175/1520-0493(2003)131<2941:AMCMOT>2.0.CO;2     Document Type: Article

References (30)

1. Anderson, C. J., and C. K. Wikle, 2002: Analysis of tornado counts with hierarchical Bayesian spatio-temporal models. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 459-460.
2. Brooks, H. E., and C. A. Doswell III, 2001: Some aspects of the international climatology of tornadoes by damage classification. Atmos. Res., 56, 191-201.
3. Brook, H. E., C. A. Doswell III, and M. P. Kay, 2003: Climatological estimates of local daily tornado probability for the United States. Wea. Forecasting, 18, 626-640.
4. Brown, C. W., 1933: A study of the time, areal. and type of distribution of tornadoes in the United States. Trans. Amer. Geophys. Union, 14, 100-106.
5. Colquhoun, J. R., and P. A. Riley, 1996: Relationships between tornado intensity and various wind and thermodynamic variables. Wea. Forecasting, 11, 360-371.
6. Efron, B., and R. J. Tibshirani, 1993: An Introduction to the Bootstrap. Chapman and Hall, 436 pp.
7. Fawbush, E. J., R. C. Miller, and L. G. Starrett, 1951: An empirical method of forecasting tornado development. Bull. Amer. Meteor. Soc., 32, 1-9.
8. Gates, P., and H. Tong, 1976: On Markov chain modeling to some weather data. J. Appl. Meteor., 15, 1145-1151.
9. Grazulis, T. P., J. T. Schaefer, and R. F. Abbey Jr., 1993: Advances in tornado climatology, hazards, and risk assessment since Tornado Symposium II. The Tornado: Its Structure, Dynamics, Prediction, and Hazards, Geophys. Monogr., No. 79, Amer. Geophys. Union, 409-426.
10. Guttorp, P., 1995: Stochastic Modeling of Scientific Data. Chapman and Hall, 384 pp.
11. Hamill, T. M., and A. T. Church, 2000: Conditional probabilities of significant tornadoes from RUC-2 forecasts. Wea. Forecasting, 15, 461-475.
12. Hughes, J. P., and P. Guttorp, 1994: Incorporating spatial dependence and atmospheric data in a model of precipitation. J. Appl. Meteor., 33, 1503-1515.
13. Johns, R. H., and R. A. Dorr Jr., 1996: Some meteorological aspects of strong and violent tornado episodes in New England and eastern New York. Nat. Wea. Dig., 20, 2-12.
14. Kao, E. P. C., 1997: An Introduction to Stochastic Processes. Duxbury Press, 438 pp.
15. Katz, R. W., 1974: Computing probabilities associated with the Markov chain model for precipitation. J. Appl. Meteor., 13, 953-954.
16. Kelly, D. L., J. T. Schaefer, R. F. McNulty, C. A. Doswell III, and R. F. Abbey Jr., 1978: An augmented tornado climatology. Mon. Wea. Rev., 106, 1172-1183.
17. Lakshmanan, V., 2001: Lossless coding and compression of radar reflectivity data. Preprints. 30th Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 50-52.
18. Marzban, C., 1998: Scalar measures of performance in rare-event situations. Wea. Forecasting, 13, 753-763.
19. Marzban, C., 2000: A neural network for tornado diagnosis. Neural Comput. Appl., 9, 133-141.
20. Marzban, C., and J. T. Schaefer, 2001: The correlation between U.S. tornados and Pacific sea surface temperature. Mon. Wea. Rev., 129, 884-895.
21. Masters, T., 1993: Practical Neural Network Recipes in C+ +. Academic Press, 493 pp.
22. Murphy, A. H., and R. L. Winkler, 1987: A general framework for forecast verification. Mon. Wea. Rev., 115, 1330-1338.
23. Murphy, A. H., and R. L. Winkler, 1992: Diagnostic verification of probability forecasts. Int. J. Forecasting, 7, 435-455.
24. Ray, P. S., R. Bieringer, X. Niu, and B. Whissel, 2003: An improved estimate of tornado occurrence in the central plains of the United States. Mon. Wea. Rev., 131, 1026-1031.
25. Reap, R. M., and D. S. Foster, 1979: Automated 12-36 hour probability forecasts of thunderstorms and severe local storms. J. Appl. Meteor., 18, 1304-1315.
26. Schaefer, J. T., D. L. Kelly, C. A. Doswell III, J. G. Galway, R. J. Williams. R. P. McNulty, L. R. Lemon, and B. D. Lambert, 1980: Tornadoes, when, where, how often. Weatherwise, 33, 52-59.
27. Spratt, S. M., D. W. Sharp, P. Walsh, A. Samdrik, F. Alsheimer, and C. Paxton, 1997: A WSR-88D assessment of tropical cyclone outer rainband tornadoes. Wea. Forecasting, 12, 479-501.
28. Stern, R. D., 1982: Computing a probability distribution for the start of the rains from a Markov chain model for precipitation. J. Appl. Meteor., 21, 420-422.
29. Valdez, M. P., and K. C. Young, 1985: Number fluxes in equilibrium raindrop populations: A Markov chain analysis. J. Atmos. Sci., 42, 1024-1036.
30. Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences. Academic Press, 467 pp.