Forcing ocean model with atmospheric model outputs to simulate storm surge in the Bangladesh coast

Mamnun, Nabir; Bricheno, Lucy M. ORCID:; Rashed-Un-Nabi, Md. 2020 Forcing ocean model with atmospheric model outputs to simulate storm surge in the Bangladesh coast. Tropical Cyclone Research and Review, 9 (2). 117-134.

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Tropical cyclones are devastating hazards and have been a major problem for the coastal population of Bangladesh. Among the advancements in atmospheric and oceanic prediction, accurate forecasting of storm surges is of specific interest due to their great potential to inflict loss of life and property. For decades, the numerical model based storm surge prediction systems have been an important tool to reduce the loss of human lives and property damage. In order to improve the accuracy in predicting storm surge and coastal inundation, recent model development efforts tended to include more modeling components, such as meteorology model and surface wave model in storm surge modeling. In this study, we used the outputs of an atmospheric model to force the ocean model for simulating storm surges in the Bay of Bengal with particular focus on the Bangladesh coast. The ability of the modeling system was investigated simulating water levels in the Bangladesh coast of two tropical cyclones Sidr (2007) and Aila (2009). The effectiveness of the model was verified through comparing the obtained computational outputs against tide gauge data. The cyclone tracks and intensities reproduced by the atmospheric model were reasonable, though the model had a tendency to overestimate the cyclone intensity during peaks and also close to coast. The water levels are reproduced fairly well by the ocean model, although errors still exist. The root mean square errors in water level at different gauges range from 0.277 to 0.419 m with coefficient of correlation (R2) between 0.64 to 0.97 in case of Sidr and 0.209 to 0.581 m with R2 0.62 to 0.98 for Aila. The overall coupled modeling system is found to be useful with reasonable accuracy and precision, though there are spaces for improvement. Higher-resolution modeling approaches are recommended to gain more skills.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 22256032
Date made live: 14 May 2020 08:29 +0 (UTC)

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