P5.20
Spatial and temporal variability of North Atlantic hurricane tracks
Tingzhuang Yan, Dept. of Marine. Earth and Atmospheric Sciences, NC State University, Raleigh, NC; and L. Xie, L. J. Pietrafesa, and T. R. Karl
Spatial and temporal variability of North Atlantic
hurricane tracks
Abstract
The spatial and temporal variability of North Atlantic
hurricane tracks and its association with the annual
hurricane landfall frequency along the United States East
Coast are studied using Principle Component Analysis (PCA)
of Hurricane Track Density Function (HTDF). Results show
that the North Atlantic HTDF is strongly modulated by,
among other climate factors, the dipole mode (DM) of
tropical Atlantic sea surface temperature (SST) as well as
North Atlantic Oscillation (NAO) and Arctic Oscillation
(AO). Specifically, we found that the first three dominant
EOF modes of HTDF are associated with the overall, the
zonal and the north-south gradients of the Atlantic
hurricane track density, respectively. Tropical Atlantic
SST DM is the only index that significantly correlates
with those EOF modes. ENSO and tropical Atlantic VWS are
negatively correlated with the overall hurricane track
density over the North Atlantic, positively correlated
with the third EOF of HTDF, but have no significant
correlation with the second EOF of North Atlantic HTDF.
The zonal gradient of the HTDF is associated with the
Atlantic SST DM, and extra-tropical processes including
NAO and AO. Since the preferred track patterns in a
hurricane season, together with the overall basin-wide
hurricane activity collectively determine the hurricane
landfall frequency along the U.S. East Coast, results
presented here provide a foundation for the construction
of a statistical model that projects the annual number of
hurricane landfall along the U.S. East Coast.
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Keywords: Tropical cyclone, climate variability, Arctic
Oscillation, North Atlantic Oscillation, El Niņo, tropical
Atlantic SST dipole mode, Hurricane Track Density Function
Poster Session 5, Tropical Cyclone Modeling and Prediction
Tuesday, 25 April 2006, 1:30 PM-5:00 PM, Monterey Grand Ballroom
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