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

Author:

Zhang Jun A.1,Uhlhorn Eric W.2

Affiliation:

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

Abstract

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.

Publisher

American Meteorological Society

Subject

Atmospheric Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3