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Real-time prediction of movement, intensity and storm surge of very severe cyclonic storm Hudhud over Bay of Bengal using high-resolution dynamical model.

Authors :
Nadimpalli, Raghu
Osuri, Krishna
Pattanayak, Sujata
Mohanty, U.
Nageswararao, M.
Kiran Prasad, S.
Source :
Natural Hazards; Apr2016, Vol. 81 Issue 3, p1771-1795, 25p
Publication Year :
2016

Abstract

Tropical cyclone (TC) 'Hudhud' (October 2014) over the Bay of Bengal was the first TC to strike the Port city, Vishakhapatnam, with intensity of 100 knots (180 km h) since 1891. The advanced research weather research and forecasting (ARW) model with 9-km grid spacing is coupled offline with dynamical storm surge model and is used for real-time prediction of Hudhud. In the current study, the successful story of prediction of Hudhud is substantiated. The ARW model was able to predict the genesis in advance of 3 days with reasonable accuracy in position and strength. The mean initial vortex position and intensity errors are 46 km and 6 knots, respectively. The model predictions showed that Hudhud would intensify to a very severe cyclonic storm (max. sustained wind speed ~97 knots from all the experiments) in advance of ~4 days which is consistent with the observation. The mean absolute intensity forecast error is significantly less (18 knots) up to 96-h forecast. The model could reproduce the upper-level warming of ~7.5 °C at ~50 km radial distance similar to that of satellite observation. The ARW model showed appreciable performance in track prediction (with errors ≤150 km up to 96-h forecast). On the landfall day, the rainfall patterns are realistic and consistent with IMD rainfall observation. The dynamical storm surge model, forced with the outputs of the ARW model, was able to predict realistic surge ranging between 1.4-2.2 m in 24- to 96-h forecast lengths. This study highlights the importance and need of high-resolution numerical models for operational TC and associated surge forecast over the region. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0921030X
Volume :
81
Issue :
3
Database :
Complementary Index
Journal :
Natural Hazards
Publication Type :
Academic Journal
Accession number :
113610899
Full Text :
https://doi.org/10.1007/s11069-016-2155-x