11A.3 Tornado Forecasting with High Resolution Climate Models

Wednesday, 9 January 2013: 4:30 PM
Ballroom B (Austin Convention Center)
Abraham Solomon, COLA, Calverton, MD; and J. Lu, B. Cash, and J. Kinter

Record setting weather related damage over the past three years has occurred in conjunction with some of the hottest global mean temperatures in the instrumental record. This fact has lead many to believe that climate change is driving an increase in extreme weather. A number of papers have been published confirming a link between climate change and increased risk from severe thunderstorms and tornadoes [Trapp 2007, Diffenbaugh 2009]. These investigations rely on the relationships between severe weather events and the larger atmospheric environment that produces them, because the models used for studying global climate (GCMs) do not directly simulate convection at the scale of individual storms. It has been demonstrated that the spatial distribution and seasonal cycle of tornado frequency can be reasonably reproduced by defining indices for severe weather days based on environmental parameters predicted by models [Brooks 2003, Timbal 2009, Tippett 2012]. Such indices define a severe weather day based on some function of low-level buoyancy and vertical shear exceeding an empirical threshold. This approach is limited both by the accuracy with which these simple relations can reproduce the actual tornado risk and the accuracy with which the environmental parameters themselves can be predicted. This study investigates one such index to evaluate the skill with which it reproduces the observed tornado risk within the continental U.S. and how projections of future risk may depend on the model's horizontal resolution.

A method for determining a severe weather index based on the observed seasonal cycle of tornados is introduced and applied to the North American Regional Reanalysis. This index based on convective precipitation and vertical shear, exhibits skill at reproducing the spatial distribution of tornado risk and the interannual variability of the tornado season from 1979-2001. The index is then applied to a pair of high-resolution climate simulations (T159 and T1279) in order to examine their ability to reproduce the observations of the 20th century and to compare their projections for the 21st century. The results show that the higher resolution model better reproduces the spatial distribution and interannual variability of tornado risk. Both simulations indicate an increased risk of tornados in a warmer world, consistent with previous studies. The lower resolution model projects dire changes, exceeding 25%, over much of the eastern U.S. However, the higher resolution model shows more moderate changes and its greater skill at reproducing the observations may suggest that these climate change projections are more credible. This difference is due to larger changes in the mean atmospheric circulation projected by the lower resolution model. A poleward shift of the mid-latitude westerly winds is a common feature of climate change simulations, but the implication for the distributions of tornados has not been previously noted. This study underscores the fact that the magnitude and seasonality of such a change in circulation will have consequences for our weather patterns. If regional projections of climate change are going to be useful for policy makers, the fidelity of these subtle tendencies must be examined closely.

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