WSR – 88D Observations of Tropical WSR – 88D Observations of Tropical

Cyclone Low-level Wind MaximaCyclone Low-level Wind Maxima

Lubbock Severe Weather ConferenceFebruary, 18 2010

Ian M. Giammanco1, John L. Schroeder2, Mark D. Powell3, Doug A. Smith4

1 PhD Candidate Wind Science and Engineering, Texas Tech University2 Associate Professor, Atmospheric Science Group, Texas Tech University3 Research Meteorologist, NOAA COAPS, Florida State University4 Associate Professor, Department of Civil Engineering, Texas Tech University

Texas Tech UniversityWind Science and Engineering

OVERVIEW

• Literature review Literature review

•VAD Processing VAD Processing techniquetechnique

•Composite profilesComposite profiles

•Identified featuresIdentified features

VAD wind profile example, KMLB Hurricane Frances (2004)

Literature Review

•Kepert (2001) and Kepert and Kepert (2001) and Kepert and Wang (2001) provided Wang (2001) provided mechanisms in which “super-mechanisms in which “super-gradient” flow could develop gradient” flow could develop in the hurricane boundary layerin the hurricane boundary layer

•Powell et al. (2003) and Powell et al. (2003) and Franklin et al. (2003) showed a Franklin et al. (2003) showed a broad “jet-like” feature near broad “jet-like” feature near 500 m in GPS dropwindsonde 500 m in GPS dropwindsonde composite profilescomposite profiles

From Powell et al. (2003)

•Kepert (2001) and Kepert and Wang Kepert (2001) and Kepert and Wang (2001) found that the radial (2001) found that the radial advection of momentum and vertical advection of momentum and vertical advection of the radial wind advection of the radial wind contributed to the development of contributed to the development of super-gradient flowsuper-gradient flow

•Validated model results from Validated model results from snapshots of individual hurricanes snapshots of individual hurricanes using GPS dropwindsonde datausing GPS dropwindsonde data

•Linear model was able to replicate Linear model was able to replicate some of the mean structure observed some of the mean structure observed by GPS dropwindsondesby GPS dropwindsondes

Literature Review

Model results and GPS dropwindsonde observations for Hurricane Georges Kepert (2006a)

GPS Dropwindsonde Profiles

MOTIVATION

•Significant low-level wind speed maxima have Significant low-level wind speed maxima have been commonly observed in GPS been commonly observed in GPS dropwindsonde profiles (11% of all sondes dropwindsonde profiles (11% of all sondes contained a wind maximum below 200 m)contained a wind maximum below 200 m)

•GPS dropwindsonde composite wind profiles GPS dropwindsonde composite wind profiles exhibited structure similar to a low-level jetexhibited structure similar to a low-level jet

•Are features present at landfall? Are features present at landfall?

•Do minimum design standards cover this Do minimum design standards cover this change in wind speed height?change in wind speed height?

•Do the features represent a significant Do the features represent a significant departure from log or power law wind profilesdeparture from log or power law wind profiles

•WSR-88D VAD wind profiles provided WSR-88D VAD wind profiles provided opportunity to examine mean vertical wind opportunity to examine mean vertical wind profiles during hurricane landfallsprofiles during hurricane landfalls

Images courtesy of gulfstream.net

VAD Technique

•Assume variation in radial Assume variation in radial velocity as a function of azimuth velocity as a function of azimuth follows a Fourier series follows a Fourier series (Lhermitte and Atlas 1961; (Lhermitte and Atlas 1961; Browning and Wexler 1968)Browning and Wexler 1968)

•Fit a Fourier series to the radial Fit a Fourier series to the radial velocity versus azimuth datavelocity versus azimuth data

•Fourier coefficients used to Fourier coefficients used to compute wind speed, direction, compute wind speed, direction, deformation, etc…deformation, etc…

•Volumetric and temporal Volumetric and temporal averageaverage

VAD Technique

•For the current study, area For the current study, area of interest is the lowest 1 kmof interest is the lowest 1 km

•VAD processing was VAD processing was conducted for velocity data conducted for velocity data within 3-5 km of radar site, within 3-5 km of radar site, for each tilt anglefor each tilt angle

•Approximate vertical Approximate vertical resolution of 75 m forresolution of 75 m for

VCP 11 (resolution a VCP 11 (resolution a function of VCP)function of VCP)

VAD Technique

•Assumption: Linear wind field (no curvature)Assumption: Linear wind field (no curvature)

•Assumption: Fall velocity of target is Assumption: Fall velocity of target is horizontally uniformhorizontally uniform

•Limitations: Non-homogeneous fall speedsLimitations: Non-homogeneous fall speeds

Variability in the reflectivity Variability in the reflectivity field field

VAD Wind Profiles

•330 VAD Wind profiles 330 VAD Wind profiles over 14 eventsover 14 events

from 1996-2008from 1996-2008

•Error estimated from Error estimated from residuals from the Fourier residuals from the Fourier series fits ~ 3 msseries fits ~ 3 ms-1-1

VAD Wind Profiles

•VAD profiles composited to generate mean VAD profiles composited to generate mean profilesprofiles

•Binned by heightBinned by height

•Stratified by radius, quadrant, and Stratified by radius, quadrant, and Radius/Radius of maximum windsRadius/Radius of maximum winds

•Data normalized by layer mean wind speed Data normalized by layer mean wind speed below 500 m (MBL)below 500 m (MBL)

VAD Wind Profiles

VAD Wind Profiles

VAD Wind Profiles

VAD Wind Profiles – Hurricane Bertha (KLTX)

VAD Wind Profiles – Hurricane Bertha (KLTX)

VAD Wind Profiles – Hurricane Fran (KLTX)

VAD Wind Profiles – Hurricane Fran (KLTX)

VAD Wind Profiles – Hurricane Frances (KMLB)

VAD Wind Profiles – Hurricane Frances (KMLB)

VAD Wind Profiles – Hurricane Frances (KMLB)

VAD Wind Profiles – Hurricane Frances (KMLB)

VAD Wind Profiles – Hurricane Ike (KHGX)

VAD Wind Profiles – Hurricane Ike (KHGX)

VAD Wind Profiles

• VAD wind profile observations binned by height

• Log and Power Law profiles fit to the ~50 -400 m layer. Pushes the limit of similarity theory

• Assumes neutral stability

• Mean R2 for logarithmic least squares fits of 0.93

• Mean R2 for Power law least squares fits of 0.86

VAD Wind Profiles

VAD Wind Profiles

• Low-level wind maxima identified in VAD wind Low-level wind maxima identified in VAD wind profilesprofiles

• Decrease in height of the wind maximum with Decrease in height of the wind maximum with decreasing radiusdecreasing radius

• Lowest maxima found near or slightly within radius Lowest maxima found near or slightly within radius of maximum windsof maximum winds

• Logarithmic wind profile beneath maximumLogarithmic wind profile beneath maximum

• Features also found near rainbandsFeatures also found near rainbands

• Peak wind speed within entire dataset 55.6 msPeak wind speed within entire dataset 55.6 ms-1-1

QUESTIONS? COMMENTS…

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REFERENCES:

Browning, K. A., and R. Wexler, 1968: The determination of kinematic properties of awind field using Doppler radar. J. Appl. Meteor., 7, 105-113.

Franklin, J.L., M.L. Black and K. Valde, 2003: GPS dropwindsonde profiles in hurricanes and their operational implications. Wea. Forecasting, 18, 32-44

Kepert, J.D., 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part I: Linear theory. J. Atmos. Sci. 58, 2469-2483.

Kepert, J.D. and Y. Wang, 2001: The dynamics of boundary layer jets within the tropical cyclone core. Part II: Non-linear enhancement. J. Atmos. Sci. 58, 2469-2483.

Kepert, J.D., 2006: Observed boundary layer wind structure and balance in the hurricane core. Part I: Hurricane Georges. J. Atmos. Sci. 63, 2169-2193.

Lhermitte, R., and D. Atlas, 1961. Precipitation motion by pulse Doppler radar. Proc. Ninth Wea. Radar Conf., Boston, Ma, Am. Meteor. Soc., 218-223.

Powell, M.D., P.J. Vickery, and T.A. Reinhold, 2003: Reduced drag coefficients for high wind speeds in tropical cyclones. Nature, 422, 279-283