JAYALAKSHMI JANAPATI

Dr. JAYALAKSHMI JANAPATI

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Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 August 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
BSBalaji kumar Seela
Balaji kumar Seela
JJJAYALAKSHMI JANAPATI
JAYALAKSHMI JANAPATI
UCUnnikrishnan C.K.
Unnikrishnan C.K.
Pay-Liam LinPay-Liam Lin
Pay-Liam Lin
Jui Le LohJui Le Loh
Jui Le Loh
MRMannem Venkatrami Reddy
Mannem Venkatrami Reddy
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.

19 January 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
BSBalaji kumar Seela
Balaji kumar Seela
JJJAYALAKSHMI JANAPATI
JAYALAKSHMI JANAPATI
Pay-Liam LinPay-Liam Lin
Pay-Liam Lin
CLChen-Hau Lan
Chen-Hau Lan
RSRyuichi Shirooka
Ryuichi Shirooka
KRK. Krishna Reddy
K. Krishna Reddy
Due to the severe threat of tropical cyclones to human life, recent years have witnessed an increase in the investigations on raindrop size distributions of tropical cyclones to improve their quantitative precipitation estimation algorithms and modeling simulations. So far, the raindrop size distributions of tropical cyclones using disdrometer measurements have been conducted at coastal and inland stations, but such studies are still missing for oceanic locations. To the authors’ knowledge, the current study examines—for the first time—the raindrop size distributions of fourteen tropical cyclones observed (during 2003–2007) at an oceanic station, Aimeliik, located in the Palau islands in the Western Pacific. The raindrop size distributions of Western Pacific tropical cyclones measured in the Palau islands showed unlike characteristics between stratiform and convective clusters, with a larger mass-weighted mean diameter and smaller normalized intercept parameter in the convective type. The contribution of the drop diameters to the total number concentration showed a gradual decrease with the increase in drop diameter size. Raindrop size distributions of Western Pacific tropical cyclones measured in the Palau islands differed slightly from Taiwan and Japan. The helpfulness of empirical relations in raindrop size distribution in rainfall estimation algorithms of ground-based (Z–R, μ–Λ, Dm–R, and Nw–R) and remote-sensing (σm–Dm, μo–Dm, Dm–Zku, and Dm–Zka) radars are evaluated. Furthermore, the present study also related the rainfall kinetic energy of fourteen tropical cyclones with rainfall rate and mass-weighted mean diameter (KEtime–R, KEmm–R, and KEmm–Dm). The raindrop size distribution empirical relations appraised in this study offer a chance to: (1) enhance the rain retrieval algorithms of ground-based, remote sensing radars; and (2) improve rainfall kinetic energy estimations using disdrometers and GPM DPR in rainfall erosivity studies.