Upper Air Wind Measurements by Weather Radar Iwan Holleman, Henk Benschop, and Jitze vd Meulen Contents:  Introduction to Doppler Radar  Velocity Azimuth Display (VAD) 

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Transcript Upper Air Wind Measurements by Weather Radar Iwan Holleman, Henk Benschop, and Jitze vd Meulen Contents:  Introduction to Doppler Radar  Velocity Azimuth Display (VAD) 

Upper Air Wind Measurements by Weather Radar

Iwan Holleman, Henk Benschop, and Jitze vd

Meulen

Contents:  Introduction to Doppler Radar  Velocity Azimuth Display (VAD)  Volume Velocity Processing (VVP)  Implementation and quality control  Verification against radiosonde and Hirlam  Conclusions

KNMI Weather Radar

    Only in presence of scatterers Measures radial velocity as function of range, azimuth, and elevation Unambiguous velocity is limited  outliers due to dealiasing technique (dual-PRF) Assumption: wind speed = observed velocity

Weather Radar Wind Profiles    Volume scan of radial velocity Algorithm for analysis Wind profile above radar site

Velocity Azimuth Display (VAD) ff=20.4 m/s dd=217 deg

Doppler Radar Volume Scan Height layer   10 Elevations between 0.5 and 25 degrees Multiple VADs per height layer

Retrieval Techniques    VAD1-2: Fourier expansion of radial velocity as a function of azimuth : V rad (  ) = a0/2 + b1  sin  + a1 b2  sin2   cos  + + a2  cos2  + ...

VVP1-3: Use all available volume scan data for a given height layer at once Assumption of linear wind model at radar site:    U(x,y,z) = u V(x,y,z) = v 0 0 W(x,y,z) = w 0 + + x  u/  x + y  u/  y x  v/  x + y  v/  y + + (z-z 0 )  u/  z (z-z 0 )  v/  z + (z-z 0 )  w/  z

Weather Radar Wind Profiles   8 January 2005 Doppler Radar and Hirlam analyses

Implementation and Quality Control        Volume scan data are input to retrieval techniques Application of minimum and maximum range Removal of radial velocities close to zero Binning of scan data in 8 azimuth sectors: neighboring empty sectors are not allowed Linear fit using Singular Value Decomposition (SVD) VAD: parameters per height layer are determined using weighted average Removal of radial velocity outliers and re-run of wind model fit

Verification of Wind Profiles     Verification of Weather Radar Wind Profiles against radiosonde and Hirlam 9 Months of volume scan data, radiosonde and Hirlam profiles Comparison of different wind profile retrieval algorithms   Availability Quality Impact of quality control procedures

Availability of VVP profiles 40% 28% std.dev. 2 m/s 19%

Conclusions     Weather radar provides wind profiles VVP algorithm performs better than VAD Availability of wind profiles is reasonable Weather radar winds are at least as good as radiosonde winds More info: I. Holleman, JAOT 2005, in press