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IIT -M, German scientists explore interaction between two cyclones
Indicators derived from this methodology were found to clearly distinguish the different stages of mutual interaction between two cyclones and provide an early indication of a cyclone merger.
Professor RI. Sujith, department of aerospace engineering at the Indian Institute of Technology / Madras/ Image IIT- Madras
A team of researchers from the Indian Institute of Technology Madras (IIT Madras), IIT Hyderabad and Potsdam Institute of Climate Impact Research (PIK), Germany have tackled the problem of merging tropical cyclones by using a novel, data-driven approach based on the interdisciplinary methodology of complex networks in an article titled ‘Study of Interaction and Complete Merging of Binary Cyclones Using Complex Networks’ published in Chaos.
“Analysing cyclone interactions using the novel framework pioneered in this study has the potential to improve the accuracy of the early warning signals provided by meteorological organizations to the government so that they can take pre-emptive and early action to reduce the impact of such disasters,” said professor RI. Sujith, department of aerospace engineering at the Indian Institute of Technology Madras.
Dr Somnath De, the lead author of this study, said, “We believe that this network-based approach can be used to study binary cyclone interactions from observational or model-based relative vorticity data to obtain better insights on the possibility of cyclone merger. It paves the path to analyze such highly unusual/rare events in which sudden alteration of cyclone tracks or re-strengthening occurs, on a case-by-case basis, and facilitate improved prediction of cyclone tracks and the fate of such interactions”.
Dr Vishnu R. Unni from IIT Hyderabad further mentioned that data-driven methods for the prediction of extreme weather events have a unique advantage since they allow one to identify critical patterns in the evolution of such weather events that are elusive to traditional methods.
A complex network encodes the pattern of interaction of a complex system and can be directly applied to study the Fujiwhara interaction between two cyclonic vortices. Indicators derived from this methodology were found to clearly distinguish the different stages of mutual interaction between two cyclones and provide an early indication of cyclone merger, often better than conventionally used indicators such as the separation distance between two cyclones, said the release by IIT Madras.
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