Classifying Urban Rainfall Extremes Using Weather Radar Data: An Application to the Greater New York Area

Abstract

Abstract Extreme rainfall events, specifically in urban areas, have dramatic impacts on society and can lead to loss of life and property. Despite these hazards, little is known about the city-scale variability of heavy rainfall events. In the current study, gridded stage IV radar data from 2002 to 2015 are employed to investigate the clustering and the spatial variability of simultaneous rainfall exceedances in the greater New York area. Multivariate clustering based on partitioning around medoids is applied to the extreme rainfall events’ average intensity and areal extent for the 1- and 24-h accumulated rainfall during winter (December–February) and summer (June–August) seasons. The atmospheric teleconnections of the daily extreme event for winter and summer are investigated using compositing of ERA-Interim. For both 1- and 24-h durations, the winter season extreme rainfall events have larger areal extent than the summer season extreme rainfall events. Winter extreme events are associated with deep and organized circulation patterns that lead to more areal extent, and the summer events are associated with localized frontal systems that lead to smaller areal extents. The average intensities of the 1-h extreme rainfall events in summer are much higher than the average intensities of the 1-h extreme rainfall events in winter. A clear spatial demarcation exists within the five boroughs in New York City for winter extreme events. Resultant georeferenced cluster maps can be extremely useful in risk analysis and green infrastructures planning as well as sewer systems’ management at the city scale.