Editorial Type:
Article
Article Type:
Research Article

Estimating Maximum Surface Winds from Hurricane Reconnaissance Measurements

Mark D. Powell NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida

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Eric W. Uhlhorn NOAA/Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, Miami, Florida

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Jeffrey D. Kepert Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, Victoria, Australia

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Print Publication:
01 Jun 2009
DOI:
https://doi.org/10.1175/2008WAF2007087.1
Page(s):
868–883
Restricted access

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Abstract

Radial profiles of surface winds measured by the Stepped Frequency Microwave Radiometer (SFMR) are compared to radial profiles of flight-level winds to determine the slant ratio of the maximum surface wind speed to the maximum flight-level wind speed, for flight altitude ranges of 2–4 km. The radius of maximum surface wind is found on average to be 0.875 of the radius of the maximum flight-level wind, and very few cases have a surface wind maximum at greater radius than the flight-level maximum. The mean slant reduction factor is 0.84 with a standard deviation of 0.09 and varies with storm-relative azimuth from a maximum of 0.89 on the left side of the storm to a minimum of 0.79 on the right side. Larger slant reduction factors are found in small storms with large values of inertial stability and small values of relative angular momentum at the flight-level radius of maximum wind, which is consistent with Kepert’s recent boundary layer theories. The global positioning system (GPS) dropwindsonde-based reduction factors that are assessed using this new dataset have a high bias and substantially larger RMS errors than the new technique. A new regression model for the slant reduction factor based upon SFMR data is presented, and used to make retrospective estimates of maximum surface wind speeds for significant Atlantic basin storms, including Hurricanes Allen (1980), Gilbert (1988), Hugo (1989), Andrew (1992), and Mitch (1998).

Corresponding author address: Dr. Mark Powell, FSU-COAPS, 2035 E. Paul Dirac Dr., 200 RM Johnson Bldg., Tallahassee, FL 32306-2840. Email: mark.powell@noaa.gov

A comment reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/full/10.1175/WAF-D-10-05001.1 and http://journals.ametsoc.org/doi/full/10.1175/WAF-D-10-05054.1

Abstract

Radial profiles of surface winds measured by the Stepped Frequency Microwave Radiometer (SFMR) are compared to radial profiles of flight-level winds to determine the slant ratio of the maximum surface wind speed to the maximum flight-level wind speed, for flight altitude ranges of 2–4 km. The radius of maximum surface wind is found on average to be 0.875 of the radius of the maximum flight-level wind, and very few cases have a surface wind maximum at greater radius than the flight-level maximum. The mean slant reduction factor is 0.84 with a standard deviation of 0.09 and varies with storm-relative azimuth from a maximum of 0.89 on the left side of the storm to a minimum of 0.79 on the right side. Larger slant reduction factors are found in small storms with large values of inertial stability and small values of relative angular momentum at the flight-level radius of maximum wind, which is consistent with Kepert’s recent boundary layer theories. The global positioning system (GPS) dropwindsonde-based reduction factors that are assessed using this new dataset have a high bias and substantially larger RMS errors than the new technique. A new regression model for the slant reduction factor based upon SFMR data is presented, and used to make retrospective estimates of maximum surface wind speeds for significant Atlantic basin storms, including Hurricanes Allen (1980), Gilbert (1988), Hugo (1989), Andrew (1992), and Mitch (1998).

Corresponding author address: Dr. Mark Powell, FSU-COAPS, 2035 E. Paul Dirac Dr., 200 RM Johnson Bldg., Tallahassee, FL 32306-2840. Email: mark.powell@noaa.gov

A comment reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/full/10.1175/WAF-D-10-05001.1 and http://journals.ametsoc.org/doi/full/10.1175/WAF-D-10-05054.1

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