Abstract

ABSTRACT The actions of wind and atmospheric pressure associated with tropical cyclones (e.g. typhoons) are considered the primary factors behind the generation of storm surges, though the fields used in meteorological models can sometimes deviate from observations. To improve these, the direct modification method (DMM) has been previously proposed, though this only modifies the wind field of a typhoon, and further development is necessary for applying it to storm surge hindcasts. The present work describes the development of a semi-empirical gradient wind balance-based method (GWB-M) for modifying both the wind and pressure fields in meteorological models, based on the dynamic relationship between the wind and pressure in typhoons (i.e. gradient wind balance). The applicability of GWB-M was assessed through a storm surge hindcast based on Typhoon Faxai in 2019, which generated powerful waves and a storm surge at Tokyo Bay. GWB-M improved the time series of 10 m wind speed and sea level pressure, with their spatial distributions being more realistic than those in DMM and blending parametric typhoon models (BM), which cannot take into account the influence of the complex topography around Tokyo Bay. Further, the maximum sea level anomalies after the typhoon made landfall were also captured by GWB-M with a higher accuracy than DMM.

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