Changing volatility of U.S. annual tornado reports

Geophysical Research Letters

Volumn 41, Issue 19, 2014, Pages 6956-6961

  Tippett, Michael K ^a,b  

^a Department of Applied Physics and Applied Mathematics Columbia University ^*  (United States)

^b KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

Author keywords

tornadoes

Indexed keywords

ACTIVITY RESULTS; ATMOSPHERIC CONDITIONS; ENVIRONMENT INDEX; INTENSITY LEVELS; NON-STATIONARY BEHAVIORS; PHYSICAL ENVIRONMENTS; PROPERTY DAMAGE; STANDARD DEVIATION;

TORNADOES;

ANNUAL VARIATION; CLIMATE MODELING; ENVIRONMENTAL MODELING; STATISTICAL ANALYSIS; TORNADO;

UNITED STATES;

EID: 84911072515     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2014GL061347     Document Type: Article

References (14)

1. Banerjee, A., J. J. Dolado, J. W. Galbraith, and, D. F. Hendry, (1993), Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data, Oxford Univ. Press, Oxford, U. K.
2. Brooks, H. E., (2013), Severe thunderstorms and climate change, Atmos. Res., 123, 129-138, doi: 10.1016/j.atmosres.2012.04.002.
3. Diffenbaugh, N. S., M. Scherer, and, R. J. Trapp, (2013), Robust increases in severe thunderstorm environments in response to greenhouse forcing, Proc. Natl. Acad. Sci. U.S.A., 110 (41), 16,361-16,366, doi: 10.1073/pnas.1307758110.
4. Doswell, C. A., III, H. E. Brooks, and, N. Dotzek, (2009), On the implementation of the enhanced Fujita scale in the USA, Atmos. Res., 93, 554-563.
5. Elsner, J. B., S. C. Elsner, and, T. H. Jagger, (2014), The increasing efficiency of tornado days in the United States, Clim. Dyn., 1-9, doi: 10.1007/s00382-014-2277-3.
6. Killick, R., and, I. A. Eckley, (2014), Changepoint: An R package for changepoint analysis, J. Stat. Software, 58, 1-19.[Available at http://www.jstatsoft.org/v58/i03.]
7. McCarthy, D., and, J. Schaefer, (2004), Tornado trends over the past thirty years, paper presented at 14th Conference on Applied Meteorology, Am. Meteorol. Soc., Seattle, Wash.
8. Sander, J., J. F. Eichner, E. Faust, and, M. Steuer, (2013), Rising variability in thunderstorm-related U.S.losses as a reflection of changes in large-scale thunderstorm forcing, Weather Clim. Soc., 317-331, doi: 10.1175/WCAS-D-12-00023.1.
9. Schaefer, J. T., and, R. Edwards, (1999), The SPC tornado/severe thunderstorm database, paper presented at 11th Conference on Applied Climatology, Amer. Meteor. Soc., Dallas, Tex.
10. Scott, A. J., and, M. Knott, (1974), A cluster analysis method for grouping means in the analysis of variance, Biometrics, 30, 507-512.
11. Tippett, M. K., A. H. Sobel, and, S. J. Camargo, (2012), Association of U.S. tornado occurrence with monthly environmental parameters, Geophys. Res. Lett., 39, L02801, doi: 10.1029/2011GL050368.
12. Tippett, M. K., A. H. Sobel, S. J. Camargo, and, J. T. Allen, (2014), An empirical relation between U.S. tornado activity and monthly environmental parameters, J. Clim., 27, 2983-2999, doi: 10.1175/JCLI-D-13-00345.1.
13. Trapp, R. J., N. S. Diffenbaugh, and, A. Gluhovsky, (2009), Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations, Geophys. Res. Lett., 36, L01703, doi: 10.1029/2008GL036203.
14. Verbout, S. M., H. E. Brooks, L. M. Leslie, and, D. M. Schultz, (2006), Evolution of the U.S. tornado database: 1954-2003, Weather Forecasting, 21, 86-93.