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Estimation and Mapping of Hurricane Turbulent Energy Using Airborne Doppler Measurements
Author(s) -
Sylvie Lorsolo,
Jun A. Zhang,
Frank D. Marks,
John F. Gamache
Publication year - 2010
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/2010mwr3183.1
Subject(s) - eye , turbulence kinetic energy , meteorology , wind shear , boundary layer , turbulence , tropical cyclone , geology , storm , dropsonde , environmental science , maximum sustained wind , wind speed , atmospheric sciences , wind gradient , geography , physics , mechanics
Hurricane turbulent kinetic energy (TKE) was computed using airborne Doppler measurements from the NOAA WP-3D tail radars, and TKE data were retrieved for a variety of storms at different stages of their life cycle. The geometry of the radar analysis coupled with the relatively small beam resolution at ranges <8 km allowed for the estimation of subkilometer turbulent processes. Two-dimensional profiles of TKE were constructed and revealed that the strongest turbulence was generally located in convective regions, such as the eyewall, with magnitudes often exceeding 15 m2 s−2 and in the boundary layer with values of 5–10 m2 s−2 in the lowest kilometer. A correlation analysis showed that the strong turbulence was generally associated with strong horizontal shear of vertical and radial wind components in the eyewall and strong vertical shear of horizontal wind in the boundary layer. Mean vertical profiles of TKE decrease sharply above the hurricane boundary layer and level off at low magnitude for all regions outside the radius of maximum wind. The quality of the retrieval method was evaluated and showed very good agreement with TKE values directly calculated from the three-dimensional wind components of in situ measurements. The method presented here provides a unique opportunity to assess hurricane turbulence throughout the storm, especially in high-wind regions, and can be applied on extensive datasets of past and future airborne hurricane penetrations.

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