Abstract

The current study summarizes the raindrop size distributions (RSDs) characteristic of the North Indian Ocean (NIO) tropical cyclones (TCs) measured with ground-based disdrometers installed at the coastal (Thiruvananthapuram, 8.5335°N, 76.9047°E) and inland (Kadapa, 14.4742°N, 78.7098°E) stations in south India. The NIO TCs observed at the coastal station showed more mid- and large-size drops (>1 mm) than the inland station. On the other hand, for both inland and coastal stations, small and mid-size drops (<3 mm) primarily contributed to the total number concentration and rainfall rate. The RSDs of the NIO TCs segregated into precipitation types (stratiform and convective) demonstrated the presence of more mid- and large-size drops at the coastal station. The RSD relations of the NIO TCs, which are used in rain retrieval algorithms of remote sensing (global precipitation measurement) radars, exhibited contrasts between the coastal and inland station. Further, the NIO TCs’ rainfall kinetic energy relations, which are crucial in rainfall erosivity studies, estimated for the coastal station revealed dissimilar characteristics to that of the inland station. The conceivable thermo-dynamical and microphysical processes that are accountable for the disparities in the NIO TCs RSDs measured at the coastal and inland stations are also elucidated in this work.

Highlights

  • Raindrop size distribution (RSD) information from the ground-based disdrometers has profound applications in meteorology, hydrology, and rain attenuation studies

  • The concentration of the raindrops above 1 mm diameter is greater for the coastal station than the inland station

  • Examination of the coast and inland stations’ RSDs for different tropical cyclones (TCs) intensities showed raindrops above 1 mm diameter are more at the coastal station than the inland station

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Summary

Introduction

Raindrop size distribution (RSD) information from the ground-based disdrometers has profound applications in meteorology, hydrology, and rain attenuation studies. 2021, 13, 3178 instance, knowledge about the RSD is useful in offering accurate RSD models for satelliteborne remote-sensing radar and ground-based weather radar rain-retrieval algorithms [1,2]. The substantial vulnerabilities caused by the TCs require us to understand their microphysical attributes, especially the RSDs, which can affect TCs’ rainfall estimation algorithms and cloud modeling [16,17]. In terms of understanding the microphysical features of TCs, globally, there has been increasing interest in TC RSD studies.

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