Structural variation in genesis and landfall locations of North Atlantic tropical cyclones related to SST
Jonas Rumpf, Helga Weindl, Eberhard Faust, Volker Schmidt
Abstract
Jonas Rumpf, Helga Weindl, Eberhard Faust, Volker Schmidt
Abstract
The influence of sea surface temperature on the locations of the genesis and of landfall of tropical cyclones in the North Atlantic is analyzed.For that purpose, these locations are calculated from HURDAT and split into two disjoint subsets according to whether sea surface temperature in the North Atlantic was above or below average in the year the corresponding storms occurred.Landfalls are investigated separately for the groups of cyclones categorized as tropical storms, minor hurricanes, or major hurricanes at the moment of landfall.The locations are considered realizations of inhomogeneous Poisson point processes, and the corresponding density functions are estimated with kernel estimation methods.In this way, any spatial structure inherent in the data is taken into account.These density functions are then compared with Monte Carlo methods from spatial statistics, which allows the detection of areas of statistically significant differences in the two sets with high and low SST, respectively.Results show many such areas, which is of relevance for the insurance industry and mathematical modelling of cyclones, as well as for decision support during the preparation for natural disasters.
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The influence of sea surface temperature on the locations of the genesis and of landfall of tropical cyclones in the North Atlantic is analyzed.For that purpose, these locations are calculated from HURDAT and split into two disjoint subsets according to whether sea surface temperature in the North Atlantic was above or below average in the year the corresponding storms occurred.Landfalls are investigated separately for the groups of cyclones categorized as tropical storms, minor hurricanes, or major hurricanes at the moment of landfall.The locations are considered realizations of inhomogeneous Poisson point processes, and the corresponding density functions are estimated with kernel estimation methods.In this way, any spatial structure inherent in the data is taken into account.These density functions are then compared with Monte Carlo methods from spatial statistics, which allows the detection of areas of statistically significant differences in the two sets with high and low SST, respectively.Results show many such areas, which is of relevance for the insurance industry and mathematical modelling of cyclones, as well as for decision support during the preparation for natural disasters.
Key concepts: Tropical cyclone, Climatology, Landfall, Atlantic hurricane, Tropical Atlantic, Variation (astronomy), African easterly jet, Tropical cyclone scales