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Hurricane Sea Surface Inflow Angle and an Observation-Based Parametric Model

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  • 1 Rosenstiel School of Marine and Atmospheric Science, University of Miami, and NOAA/AOML/Hurricane Research Division, Miami, Florida
  • | 2 NOAA/AOML/Hurricane Research Division, Miami, Florida
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Abstract

This study presents an analysis of near-surface (10 m) inflow angles using wind vector data from over 1600 quality-controlled global positioning system dropwindsondes deployed by aircraft on 187 flights into 18 hurricanes. The mean inflow angle in hurricanes is found to be −22.6° ± 2.2° (95% confidence). Composite analysis results indicate little dependence of storm-relative axisymmetric inflow angle on local surface wind speed, and a weak but statistically significant dependence on the radial distance from the storm center. A small, but statistically significant dependence of the axisymmetric inflow angle on storm intensity is also found, especially well outside the eyewall. By compositing observations according to radial and azimuthal location relative to storm motion direction, significant inflow angle asymmetries are found to depend on storm motion speed, although a large amount of unexplained variability remains. Generally, the largest storm-relative inflow angles (<−50°) are found in the fastest-moving storms (>8 m s−1) at large radii (>8 times the radius of maximum wind) in the right-front storm quadrant, while the smallest inflow angles (>−10°) are found in the fastest-moving storms in the left-rear quadrant. Based on these observations, a parametric model of low-wavenumber inflow angle variability as a function of radius, azimuth, storm intensity, and motion speed is developed. This model can be applied for purposes of ocean surface remote sensing studies when wind direction is either unknown or ambiguous, for forcing storm surge, surface wave, and ocean circulation models that require a parametric surface wind vector field, and evaluating surface wind field structure in numerical models of tropical cyclones.

Corresponding author address: Dr. Jun Zhang, NOAA/AOML/Hurricane Research Division, Universtiy of Miami/CIMAS, 4301 Rickenbacker Causeway, Miami, FL 33149. E-mail: jun.zhang@noaa.gov

Abstract

This study presents an analysis of near-surface (10 m) inflow angles using wind vector data from over 1600 quality-controlled global positioning system dropwindsondes deployed by aircraft on 187 flights into 18 hurricanes. The mean inflow angle in hurricanes is found to be −22.6° ± 2.2° (95% confidence). Composite analysis results indicate little dependence of storm-relative axisymmetric inflow angle on local surface wind speed, and a weak but statistically significant dependence on the radial distance from the storm center. A small, but statistically significant dependence of the axisymmetric inflow angle on storm intensity is also found, especially well outside the eyewall. By compositing observations according to radial and azimuthal location relative to storm motion direction, significant inflow angle asymmetries are found to depend on storm motion speed, although a large amount of unexplained variability remains. Generally, the largest storm-relative inflow angles (<−50°) are found in the fastest-moving storms (>8 m s−1) at large radii (>8 times the radius of maximum wind) in the right-front storm quadrant, while the smallest inflow angles (>−10°) are found in the fastest-moving storms in the left-rear quadrant. Based on these observations, a parametric model of low-wavenumber inflow angle variability as a function of radius, azimuth, storm intensity, and motion speed is developed. This model can be applied for purposes of ocean surface remote sensing studies when wind direction is either unknown or ambiguous, for forcing storm surge, surface wave, and ocean circulation models that require a parametric surface wind vector field, and evaluating surface wind field structure in numerical models of tropical cyclones.

Corresponding author address: Dr. Jun Zhang, NOAA/AOML/Hurricane Research Division, Universtiy of Miami/CIMAS, 4301 Rickenbacker Causeway, Miami, FL 33149. E-mail: jun.zhang@noaa.gov
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