Spatio-temporal models for large-scale indicators of extreme weather
Version of Record online: 18 NOV 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Volume 22, Issue 3, pages 294–303, May 2011
How to Cite
Heaton, M. J., Katzfuss, M., Ramachandar, S., Pedings, K., Gilleland, E., Mannshardt-Shamseldin, E. and Smith, R. L. (2011), Spatio-temporal models for large-scale indicators of extreme weather. Environmetrics, 22: 294–303. doi: 10.1002/env.1050
- Issue online: 15 APR 2011
- Version of Record online: 18 NOV 2010
- Manuscript Accepted: 19 APR 2010
- Manuscript Revised: 26 MAR 2010
- Manuscript Received: 1 DEC 2009
- severe storm;
- reanalysis data;
- extreme value;
- point process
Extreme weather events such as thunderstorms and tornadoes are of great concern as these events pose a significant threat to life, property, and economic stability. Because of the difficulty of gathering data on extreme events, this paper proposes modeling the conditions for extreme weather through large-scale indicators. The advantage of using large-scale indicators is that climate models can be used to generate data whereas climate models cannot generate data on extreme events themselves. This paper focuses on comparing spatio-temporal models for reanalysis data of large-scale indicators for extreme weather observed across the continental United States and Mexico. Results indicate that rigorous treatment of spatial and temporal dynamics is necessary. The models find that the intensity of conditions for extreme weather is particularly high for the central United States and the intensity of these conditions is increasing over time but the amount of increase may not be practically significant. Copyright © 2010 John Wiley & Sons, Ltd.