Tornado outbreak variability follows Taylor's power law of fluctuation scaling and increases dramatically with severity

Nature Communications

Volumn 7, Issue , 2016, Pages

  Tippett, Michael K ^a,b   Cohen, Joel E ^c,d  

^a Department of Earth and Environmental Sciences   (United States)

^b KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

^c ROCKEFELLER UNIVERSITY   (United States)

^d NONE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAUSE OF DEATH; DAMAGE; DATA ASSIMILATION; EXTREME EVENT; NUMERICAL METHOD; POWER LAW; RISK ASSESSMENT; TORNADO; WIND VELOCITY;

SAMPLING; TORNADO;

UNITED STATES;

EID: 84959378664     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms10668     Document Type: Article

References (32)

1. Data from Summary of U.S. Natural Hazard Statistics 2005-2014 compiled by the National Weather Service Office of Climate, Water and Weather Services and the National Climatic Data Center. http://www.nws.noaa.gov/om/hazstats.shtml.
2. Fuhrmann, C. M. et al. Ranking of tornado outbreaks across the United States and their climatological characteristics. Wea. Forecasting 29, 684-701 (2014).
3. Smith, A. & Matthews, J. Quantifying uncertainty and variable sensitivity within the US billion-dollar weather and climate disaster cost estimates. Nat. Hazards 77, 1829-1851 (2015).
4. Diffenbaugh, N. S., Scherer, M. & Trapp, R. J. Robust increases in severe thunderstorm environments in response to greenhouse forcing. Proc. Natl Acad. Sci. USA 110, 16361-16366 (2013).
5. Gensini, V. & Mote, T. Downscaled estimates of late 21st century severe weather from CCSM3. Clim. Change 129, 307-321 (2015).
6. Tippett, M. K., Allen, J. T., Gensini, V. A. & Brooks, H. E. Climate and hazardous convective weather. Curr. Clim. Change Rep. 1, 60-73 (2015).
7. Verbout, S. M., Brooks, H. E., Leslie, L. M. & Schultz, D. M. Evolution of the U.S. tornado database: 1954-2003. Wea. Forecasting 21, 86-93 (2006).
8. Brooks, H. E., Carbin, G. W. & Marsh, P. T. Increased variability of tornado occurrence in the United States. Science 346, 349-352 (2014).
9. Elsner, J. B., Elsner, S. C. & Jagger, T. H. The increasing efficiency of tornado days in the United States. Clim. Dyn. 45, 651-659 (2015).
10. Tippett, M. K. Changing volatility of U.S. annual tornado reports. Geophys. Res. Lett. 41, 6956-6961 (2014).
11. Sander, J., Eichner, J. F., Faust, E. & Steuer, M. Rising variability in thunderstorm-related U.S. losses as a reflection of changes in large-scale thunderstorm forcing. Wea. Climate Soc. 5, 317-331 (2013).
12. Long, J. A. & Stoy, P. C. Peak tornado activity is occurring earlier in the heart of 'Tornado Alley'. Geophys. Res. Lett. 41, 6259-6264 (2014).
13. Lu, M., Tippett, M. & Lall, U. Changes in the seasonality of tornado and favorable genesis conditions in the central United States. Geophys. Res. Lett. 42, 4224-4231 (2015).
14. Doswell, III C. A., Edwards, R., Thompson, R. L., Hart, J. A. & Crosbie, K. C. A simple and flexible method for ranking severe weather events. Wea. Forecasting 21, 939-951 (2006).
15. Taylor, L. R. Aggregation, variance and the mean. Nature 189, 732-735 (1961).
16. Eisler, Z., Bartos, I. & Kertész, J. Fluctuation scaling in complex systems: Taylor's law and beyond. Adv. Phys. 57, 89-142 (2008).
17. Cohen, J. E., Xu, M. & Schuster, W. S. F. Stochastic multiplicative population growth predicts and interprets Taylor's power law of fluctuation scaling. Proc. R. Soc. B 280, 20122955 (2013).
18. Malamud, B. D. & Turcotte, D. L. Statistics of severe tornadoes and severe tornado outbreaks. Atmos. Chem. Phys. 12, 8459-8473 (2012).
19. Elsner, J. B., Jagger, T. H., Widen, H. M. & Chavas, D. R. Daily tornado frequency distributions in the United States. Environ. Res. Lett. 9, 024018 (2014).
20. Cohen, J. E. & Xu, M. Random sampling of skewed distributions implies Taylor's power law of fluctuation scaling. Proc. Natl Acad. Sci. USA 112, 7749-7754 (2015).
21. Vitolo, R., Stephenson, D. B., Cook, I. M. & Mitchell-Wallace, K. Serial clustering of intense European storms. Meteor. Z. 18, 411-424 (2009).
22. Karremann, M. K., Pinto, J. G., Reyers, M. & Klawa, M. Return periods of losses associated with European windstorm series in a changing climate. Environ. Res. Lett. 9, 124016 (2014).
23. Agee, E. & Childs, S. Adjustments in tornado counts, F-scale intensity, and path width for assessing significant tornado destruction. J. Appl. Meteor. Climatol. 53, 1494-1505 (2014).
24. Mesinger, F. et al. North American regional reanalysis. Bull. Am. Meteorol. Soc. 87, 343-360 (2006).
25. Davies, J. M. in 17th Conference on Severe Local Storms, 107-111 (Amer. Meteor. Soc., St. Louis, MO, 1993).
26. Rasmussen, E. N. & Blanchard, D. O. A baseline climatology of sounding-derived supercell and tornado forecast parameters. Wea. Forecasting 13, 1148-1164 (1998).
27. Tippett, M. K., Sobel, A. H. & Camargo, S. J. Association of U.S. tornado occurrence with monthly environmental parameters. Geophys. Res. Lett. 39, L02801 (2012).
28. Tippett, M. K., Sobel, A. S., Camargo, S. J. & Allen, J. T. An empirical relation between U.S. tornado activity and monthly environmental parameters. J. Clim. 27, 2983-2999 (2014).
29. Brooks, H. E., Lee, J. W. & Craven, J. P. The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data. Atmos. Res. 67-68, 73-94 (2003).
30. Brooks, H. E. Severe thunderstorms and climate change. Atmos. Res. 123, 129-138 (2013).
31. Gilleland, E., Brown, B. G. & Ammann, C.M. Spatial extreme value analysis to project extremes of large-scale indicators for severe weather. Environmetrics 24, 418-432 (2013).
32. Thompson, R. L., Mead, C. M. & Edwards, R. Effective storm-relative helicity and bulk shear in supercell thunderstorm environments. Wea. Forecasting 22, 102-115 (2007).