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The Interannual Variability of Tropical Cyclones

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  • 1 Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania
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Abstract

This paper examines the interannual variability of tropical cyclones in each of the earth’s cyclone basins using data from 1985 to 2003. The data are first analyzed using a Monte Carlo technique to investigate the long-standing myth that the global number of tropical cyclones is less variable than would be expected from examination of the variability in each basin. This belief is found to be false. Variations in the global number of all tropical cyclones are indistinguishable from those that would be expected if each basin was examined independently of the others. Furthermore, the global number of the most intense storms (Saffir–Simpson categories 4–5) is actually more variable than would be expected because of an observed tendency for storm activity to be correlated between basins, and this raises important questions as to how and why these correlations arise. Interbasin correlations and factor analysis of patterns of tropical cyclone activity reveal that there are several significant modes of variability. The largest three factors together explain about 70% of the variance, and each of these factors shows significant correlation with ENSO, the North Atlantic Oscillation (NAO), or both, with ENSO producing the largest effects. The results suggest that patterns of tropical cyclone variability are strongly affected by large-scale modes of interannual variability. The temporal and spatial variations in storm activity are quite different for weaker tropical cyclones (tropical storm through category 2 strength) than for stronger storms (categories 3–5). The stronger storms tend to show stronger interbasin correlations and stronger relationships to ENSO and the NAO than do the weaker storms. This suggests that the factors that control tropical cyclone formation differ in important ways from those that ultimately determine storm intensity.

Corresponding author address: William M. Frank, Department of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802. Email: frank@ems.psu.edu

Abstract

This paper examines the interannual variability of tropical cyclones in each of the earth’s cyclone basins using data from 1985 to 2003. The data are first analyzed using a Monte Carlo technique to investigate the long-standing myth that the global number of tropical cyclones is less variable than would be expected from examination of the variability in each basin. This belief is found to be false. Variations in the global number of all tropical cyclones are indistinguishable from those that would be expected if each basin was examined independently of the others. Furthermore, the global number of the most intense storms (Saffir–Simpson categories 4–5) is actually more variable than would be expected because of an observed tendency for storm activity to be correlated between basins, and this raises important questions as to how and why these correlations arise. Interbasin correlations and factor analysis of patterns of tropical cyclone activity reveal that there are several significant modes of variability. The largest three factors together explain about 70% of the variance, and each of these factors shows significant correlation with ENSO, the North Atlantic Oscillation (NAO), or both, with ENSO producing the largest effects. The results suggest that patterns of tropical cyclone variability are strongly affected by large-scale modes of interannual variability. The temporal and spatial variations in storm activity are quite different for weaker tropical cyclones (tropical storm through category 2 strength) than for stronger storms (categories 3–5). The stronger storms tend to show stronger interbasin correlations and stronger relationships to ENSO and the NAO than do the weaker storms. This suggests that the factors that control tropical cyclone formation differ in important ways from those that ultimately determine storm intensity.

Corresponding author address: William M. Frank, Department of Meteorology, The Pennsylvania State University, 503 Walker Building, University Park, PA 16802. Email: frank@ems.psu.edu

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