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
Summary
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.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
