4.4 Article

Wavelet Analyses of Turbulence in the Hurricane Surface Layer during Landfalls

期刊

JOURNAL OF THE ATMOSPHERIC SCIENCES
卷 67, 期 12, 页码 3793-3805

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/2010JAS3437.1

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资金

  1. National Science Foundation [AGS-0847332]
  2. NOAA/Florida Hurricane Alliance
  3. Div Atmospheric & Geospace Sciences [0847332] Funding Source: National Science Foundation

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Using wavelet transform (WT), this study analyzes the surface wind data collected by the portable wind towers during the landfalls of six hurricanes and one tropical storm in the 2002-04 seasons. The WT, which decomposes a time series onto the scale-time domain, provides a means to investigate the role of turbulent eddies in the vertical transport in the unsteady, inhomogeneous hurricane surface layer. The normalized WT power spectra (NWPS) show that the hurricane boundary layer roll vortices tend to suppress the eddy circulations immediately adjacent to rolls, but they do not appear to have a substantial effect on eddies smaller than 100 m. For low-wind conditions with surface wind speeds less than 10 m s(-1), the contributions of small eddies (<236 m) to the surface wind stress and turbulent kinetic energy (TKE) decrease with the increase of wind speed. The opposite variation trend is found for eddies greater than 236 m. However, for wind speeds greater than 10 m s(-1), contributions of both small and large eddies tend to level off as wind speeds keep increasing. It is also found that the scale of the peak NWPS of the surface wind stress is nearly constant with a mean value of approximately 86 m, whereas the scale of the peak NWPS of TKE generally increases with the increase of wind speed, suggesting the different roles of eddies in generating fluxes and TKE. This study illustrates the unique characteristics of the surface layer turbulent structures during hurricane landfalls. It is hoped that the findings of this study could enlighten the development and improvement of turbulent mixing schemes so that the vertical transport processes in the hurricane surface layer can be appropriately parameterized in forecasting models.

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