Hindcast Insights from Storm Surge Forecasting of Super Typhoon Saola (2309) in Hong Kong with the SLOSH Model

Lau, Dick-Shum and Chan, Wai-Soen and Wong, Yat-Chun and Lam, Ching-Chi and Chan, Pak-Wai (2024) Hindcast Insights from Storm Surge Forecasting of Super Typhoon Saola (2309) in Hong Kong with the SLOSH Model. In: Research Advances in Environment, Geography and Earth Science Vol. 5. B P International, pp. 161-194. ISBN 978-81-974388-2-0

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Abstract

This study highlights the techniques in storm surge forecasting and the challenges in the risk assessment of inundation. The combined effect of storm surges, rainfall and overtopping waves has been a major threat causing inundation in a city like Hong Kong as shown in various studies. Super Typhoon Saola (2309) skirted past south-southeast of Hong Kong within about 40 km on the night of 1 September 2023, posing a significant storm surge threat to Hong Kong. Given the close proximity of Saola with a peak intensity of about 210 km/h within 300 km of Hong Kong, a close call of the “super typhoon direct-hit” scenario, this case provides valuable insights from a hindcast review of storm surge forecast and warning operations. The Hong Kong Observatory (HKO) has adopted the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model as its operational storm surge model. This paper also examined the performance of the HKO's Probabilistic Inundation Map Evaluation System (PRIMES) using model ensemble and statistical techniques. Saola was a challenging case for operational forecasting of a compact tropical cyclone (TC) structure with changes in storm size and intensity when it came close to Hong Kong. With major observations of storm structure using weather radar and dense automatic weather station, tide gauge and water level gauge networks, the high sensitivity of storm surge forecasts to the storm size parameter and the distance of closest approach was clearly revealed in the case of Saola. Even with a circularly symmetric TC parametric model like SLOSH, the hindcast review results illustrated that the model outputs were reasonably accurate during the closest approach of Saola given an accurate storm size and distance of closest approach were input, and using a highly computationally efficient storm surge model made it possible for the nowcasting of storm surges to handle compact and intense TC direct-hit cases in operational TC forecasting. To enhance the storm surge alert/warning service for disaster prevention and mitigation, the efficient dissemination of forecast updates and effective communication with decision makers to facilitate their emergency preparedness and response are also critical factors for success. By utilising a nowcasting approach, one can enhance the accuracy of storm tide forecasts and create a more robust warning strategy for emergency response actions. This is achieved by rapidly updating the analysis and prediction of TC parameters including storm size, intensity, and position in real-time, say on an hourly basis, when TCs come within a certain range of the shore, taking into account the lead time required for taking emergency preparedness and response actions. This article offered a nowcasting procedure for storm surge operation. This rapid-update nowcasting approach is also considered very useful when TCs undergo rapid intensification nearshore which pose serious storm surge threats to densely populated coastal cities like Hong Kong. With the use of real-time surface observations and remote-sensing data to analyse the latest TC structure, and the use of a computationally efficient storm surge model to update predictions accordingly, a rapid-update nowcasting approach is operationally viable to tackle the challenge of regional storm surge predictions in cases of direct hits or close calls of compact and intense TCs, especially when those TCs are already nearshore while undergoing rapid changes in storm size or having erratic motion that could affect the distance of closest approach.

Item Type: Book Section
Subjects: Impact Archive > Geological Science
Depositing User: Managing Editor
Date Deposited: 15 Jun 2024 08:19
Last Modified: 15 Jun 2024 08:19
URI: http://research.sdpublishers.net/id/eprint/4140

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