Abstract
We propose a high speed non-empirical method to detect centers of tropical cyclones, which is useful to identify tropical cyclones in huge climatology data. In this method, centers of tropical cyclones are detected automatically by iteration of streamline in down-stream direction from some initial positions. We also bend the path of streamline successively to converge on the center of tropical cyclone rapidly. Since this method is free from empirical conditions used in the conventional method, the accuracy is independent of these conditions. Moreover, because the proposed method does not need to check these at all grid points, computational cost is significantly reduced. We compare the accuracy and effectiveness of the method with those of the conventional one for tropical cyclone identification task in observational data. Our method could find almost all tropical cyclones, some of which were not identified by the conventional method. This method will be useful for future huge climatology data, since computational cost does not depend on the number of grid points.
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Acknowledgments
This work was supported by Grant-in-Aids for the 21st Century COE “Frontier of Computational Science” and the Global Environment Research Fund (RF-070) of the Ministry of the Environment, Japan. The numerical analysis was performed by Fujitsu HPC2500 super computer system at the Information Technology Center, Nagoya University.
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Sugimoto, N., Pham, M., Tachibana, K., Yoshikawa, T., Furuhashi, T. (2009). A Fast Non-Empirical Tropical Cyclone Identification Method. In: Elsner, J., Jagger, T. (eds) Hurricanes and Climate Change. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09410-6_14
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DOI: https://doi.org/10.1007/978-0-387-09410-6_14
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