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Journal Article

Citation

Varotsos CA, Krapivin VF, Soldatov VY. Int. J. Disaster Risk Reduct. 2019; 36: e101088.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2019.101088

PMID

unavailable

Abstract

Tropical cyclones are natural meteorological phenomena that are sometimes beneficial and sometimes dangerous. Beneficial because they can carry rain in the dry areas and transfer heat from the tropical regions to the higher latitudes. Dangerous because they can cause many disasters, such as heavy rain, strong winds, heavy shore storm waves and tornadoes. Of course, the extent of these disasters, which are very dangerous to people's life, depends largely on the intensity, size and location of this phenomenon. For these reasons, the development of reliable models for timely forecasting and monitoring of these phenomena is vital, especially as climate change is thought to increase both their frequency and intensity. This paper proposes an information-modeling tracker (IMT) of tropical cyclones based on the cluster algorithm to assess the instability of the atmosphere-ocean system. To this end, an instability indicator of the atmosphere-ocean system (IIAOS) is developed to form the basis for IMT synthesis and to be used as a precursor for the onset of tropical cyclones. Harmonization of IIAOS with the well-established Saffir-Simpson scale is carried out allowing the assessment of tropical cyclones characteristics, including their strength, and providing the basis for real-time atmosphere-ocean diagnostics. Finally, the IMT results obtained for a set of tropical cyclones (e.g., Franklin, Harvey, Irma and Katia) are presented and can be characterized as encouraging. Therefore, the functional IMT structure synthesized in this study can be used reliably as part of the global ocean monitoring system to reduce the risk from tropical cyclones.


Language: en

Keywords

Cyclone forecasting; Franklin; Harvey; Information theory; Irma and Katia tropical cyclones; Tropical cyclones disasters

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