Thursday, 25 May 2000: 11:30 AM
As a result of several observational, radar and numerical studies some processes leading to the formation of tornadoes associated with tropical cyclones have become better understood. It has been established that the convection responsible for hurricane tornadoes is relatively shallow, sometimes reaching only about 3 km above ground level(AGL).
Convective Available Potential Energy (CAPE) can be much smaller than in the environments of non-tropical tornadoes. Following the trends of midwestern tornado studies, storm relative helicity (SRH) was given prominence as a supercell predictor. The WSR-88D studies of hurricane tornadoes have shown that although the associated mesocyclones are relatively small-- sometimes about 2km across-- their detection is possible in the form of presistently intense radar reflectivity patterns and small horizontal shear couplets. Because of the shallowness of convection, only those cells in close proximity to a radar (within roughly 100 km) stand a good chance for detection. Despite our improved understanding of hurricane tornadoes, some still occur outside warnings, watches or outlooks. To increase forecast skill for these events, further knowldege of environmental shear, storm-scale characteristics and WSR-88D radar imagery is essential.
We have collected conventional observations, eta-model and satellite data relating to the tornadoes for Tropical Cyclone Frances (1998)in Louisiana, Hurricane Earl (1998) in Florida and the Carolinas, and Floyd (1999) in North Carolina. The WSR-88D from the relevant stations has been identified also. Preliminary examination of Frances yielded high SRH (on the order of 400-500 m2 s-2) and widely varying instabilities (CAPE ranging from 30 J kg-1 to nearly 1500 J kg-1). Three F1 tornadoes and nine of F0 rating occurred in Louisiana. As Hurricane Floyd (1999) crossed into North Carolina, CAPE approached 1800 J kg-1 with SRH approaching 400-500 m2 s-2during a period when up to ten tornadoes were reported. Environmental shear and instability characteristics will be discussed in more detail, with implications for operational forecasting of these events.
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