Self-organising maps for rain event classification in Mumbai City, India

Abstract

ABSTRACT The detailed analysis of individual rain event characteristics is an important step for improving our understanding of variations in precipitation over different topographies. In this study, the homogeneity among rain gauges was investigated using the concept of ‘rain event properties’. Thirty-one properties of 23,176 rain events recorded at 47 meteorological stations in Mumbai, India, were analysed utilising seasonal (June–September) rainfall records over 2006–2016. The random forest model was used to evaluate the importance of rain event variables, thus leading to an optimum subset of variables. As a result, 12 signature variables portraying various aspects of rain event behaviour at each station were obtained. The high similarities among the variables indicated similarities among the rain gauges. Furthermore, similar rain gauges were distinguished, investigated, and characterised by cluster analysis using self-organising maps. The cluster analysis results show six clusters of similarly behaving rain gauges, where each cluster addresses one isolated class of variables for the rain gauge. Additionally, the clusters confirm the spatial variation in rainfall caused by the complex topography of Mumbai, comprising the flatland near the Arabian Sea, high-rise buildings (urban areas), and mountain and hill areas (Sanjay Gandhi National Park located in the northern part of Mumbai).