2019
DOI: 10.1016/j.atmosres.2019.03.014
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Impact of vortex size and Initialization on prediction of landfalling tropical cyclones over Bay of Bengal

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Cited by 14 publications
(7 citation statements)
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“…The TC samples from the current dataset are clustered into slow movers (TS ≤ 3 m⋅s −1 ), normal movers (4 ≤ TS ≤ 7 m⋅s −1 ) and fast movers (TS > 7 m⋅s −1 ) following Chan and Gray (), for rainfall distribution over the NIO region (Figure ). Initial analyses and recent studies indicate that slow and normal moving TCs are stronger as compared to the fast movers (Mei et al ., ; Busireddy et al ., ; ). The mean intensity of the slow, normal and fast‐moving TCs are 34, 31, and 29 knots, respectively (figure 5b of Busireddy et al ., ; ).…”
Section: Resultsmentioning
confidence: 99%
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“…The TC samples from the current dataset are clustered into slow movers (TS ≤ 3 m⋅s −1 ), normal movers (4 ≤ TS ≤ 7 m⋅s −1 ) and fast movers (TS > 7 m⋅s −1 ) following Chan and Gray (), for rainfall distribution over the NIO region (Figure ). Initial analyses and recent studies indicate that slow and normal moving TCs are stronger as compared to the fast movers (Mei et al ., ; Busireddy et al ., ; ). The mean intensity of the slow, normal and fast‐moving TCs are 34, 31, and 29 knots, respectively (figure 5b of Busireddy et al ., ; ).…”
Section: Resultsmentioning
confidence: 99%
“…Initial analyses and recent studies indicate that slow and normal moving TCs are stronger as compared to the fast movers (Mei et al ., ; Busireddy et al ., ; ). The mean intensity of the slow, normal and fast‐moving TCs are 34, 31, and 29 knots, respectively (figure 5b of Busireddy et al ., ; ). The peak rain rates are higher for the BoB as that of AS TCs for any translation speed.…”
Section: Resultsmentioning
confidence: 99%
“…With the advancements in the dense observational network such as in-situ, satellite, radar, and other remote sensed platforms, the TC movement's prediction accuracy has been improved from the last few decades [12]. Significant improvements have been achieved in the prediction of the track of TC since the previous few years due to the advancements in numerical weather prediction models and data assimilation techniques over the NIO basin [6,7,18,20,21,23], 2015, 2017, [14][15][16], Mohanty et al, 2015Mohanty et al, ,2019, [2]. However, the intensity prediction is still a challenging task for the operational and research community due to their intensity changes such as rapid intensification (RI) 1 and rapid decay (RD) 2 over the basin [11,26], [27].…”
Section: Introductionmentioning
confidence: 99%
“…Recent studies have addressed the improving prediction of intensity changes through various methods such as the use of high-resolution modeling systems [1,3,6,22], vortex in Bhalachandran itialization [2], data assimilation [16,19]. However, these studies are mostly limited to the individual TCs or very few cases.…”
Section: Introductionmentioning
confidence: 99%
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