Analyzing the rainfall trend and hydroclimatic teleconnections using Hilbert Huang Transform for the coastal smart cities of India
Abstract
The changing climatic patterns associated with intense and erratic rainfall have led to high flooding risk in urban areas. Identifying these hydro-meteorological risks in cities is a matter of concern for decision-makers. The present study investigates long-term rainfall variability and trend analysis in 11 coastal smart cities in India. A relatively new approach involving the Hilbert Huang transform (HHT) method is used to identify long-term trends by investigating time-frequency characterization. The study shows that the rainfall trend with a periodicity of 12.5 15.6 years is significantly increasing for Panaji while decreasing for Thane during the southwest monsoon (SWM), even though both cities are located on the west coast of India and are mainly influenced by SWM. Further, the intensity of northeast monsoon (NEM) decreased in Chennai, while the influence of SWM has increased in recent decades. Thane shows a firm decreasing rainfall trend, which is alarming and potent among the studied cities. Subsequently, a detailed co-relation study investigates a link between the changing rainfall patterns and global climate indices. The results illustrate that the influence of climatic indices is highly dynamic city-wise. The present method is very efficient and effective for analyzing rainfall variability in the context of coastal urban areas
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