Study of Tropical Cyclones in the North Indian Ocean basin using Percolation in Climate Networks

Every point on the Earth’s surface is a dynamical system which behaves in a complex way while interacting with other dynamical systems. Network theory captures this feature of climate to study the collective behaviour of these interacting systems giving new insights into the problem. Recently, climate networks have been a promising approach to the study of climate phenomena such as El Niño, Indian monsoon, etc. These phenomena, however, occur over a long period of time. Weather phenomena such as tropical cyclones (TCs) that are relatively short-lived, destructive events are a major concern to life and property especially for densely populated coastlines such as in the North Indian Ocean (NIO) basin. Here, we study TCs in the NIO basin by constructing climate networks using the ERA5 Sea Surface Temperature and Air temperature at 1000 hPa. We analyze these networks using the percolation framework for the post-monsoon (October-November-December) season which experiences a high frequency of TCs every year. We find significant signatures of TCs in the network structure which appear as abrupt discontinuities in the percolation-based parameters during the period of a TC. This shows the potential of climate networks towards forecasting of tropical cyclones.

 

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.