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LMO Monin-Obukhov length lp half length of the ideally rectangular light pulse leaving the Windcube rb beam radius Rij Covariance tensor RMSPE root mean square percent errors s distance along the beam from the focus or center of the range gate T absolute temperature u Component of the velocity field in the mean wind direction u∗ friction velocity uqq Component of the velocity field in the mean wind direction measured by the ZephIR uWC Component of the velocity field in the mean wind direction measured by the Windcube v Component of the velocity field perpendicular to the mean wind direction in a horizontal plane vqq Component of the velocity field perpendicular to the mean wind direction in a horizontal plane measured by the ZephIR vr radial velocity/line of sight velocity vWC Component of the velocity field perpendicular to the mean wind direction in a horizontal plane measured by the Windcube w Component of the velocity field perpendicular to the mean wind direction in a vertical plane wqq Component of the velocity field perpendicular to the mean wind direction in a vertical plane measured by the ZephIR wWC Component of the velocity field perpendicular to the mean wind direction in a vertical plane measured by the Windcube References Banakh V. A., Smalikho I. N., Köpp F., and Werner C. (1995) Representativeness of wind measurements with a CW Doppler lidar in the atmospheric boundary layer. Appl. Opt., 34:2055–2067 Banta R. M., Newsom R. J., Lundquist J. K., Pichugina Y. L., Coulter R. L., and Mahrt L. (2002) Nocturnal low-level jet characteristics over Kansas during CASES-99. Bound.-Layer Meteorol., 105:221–252 Browning K. A. and Wexler R. (1968) The determination of kinematic properties of a wind field using a Doppler radar. J. Appl. Meteorol., 7:105–113 Citriniti J. H. and George W. K. (1997) The reduction of spatial aliasing by long hot-wire anemometer probes. Exp. Fluids, 23:217–224. Eberhard W. L., Cupp R. E., and Healy K. R. (1989) Doppler lidar measurements of profiles of turbulence and momentum flux. J. Atmos. Oceanic Technol., 6:809–819 Emeis S., Harris M., and Banta R. M.. (2007) Boundary-layer anemometry by optical remote sensing for wind energy applications. Meteorol. Z., 16:337–347 Engelbart D. A. M., Kallistratova M., and Kouznetsov R. (2007) Determination of the turbulent fluxes of heat and momentum in the ABL by ground-based remote-sensing techniques (a review). Meteorol. Z., 16:325–335 Gal-Chen T., Xu M., and Eberhard W. L. (1992) Estimation of atmospheric boundary layer fluxes and other turbulence parameters from Doppler lidar data. J. Geophys. Res., 97:409–423 Genz A. C. and Malik A. A. (1980) An adaptive algorithm for numerical integration over an n-dimensional rectangular region. J. Comput. Appl. Math., 6:295–302 Gryning S.-E., Batchvarova E., Brümmer B., Jørgensen H., and Larsen S. (2007) On the extension of the wind profile over homogeneous terrain beyond the surface layer. Bound.-Layer Meteorol. 124:251–268 Kaimal J. C. and Finnigan J. J. (1994) Atmospheric Boundary Layer Flows, 255–257. Oxford University Press, New York Kaimal J. C., Wyngaard J. C., Izumi Y., and Coté O. R. (1972) Spectral characteristics of surface-layer turbulence. Q. J. Royal Meteorol. Soc., 98:563–589 Kindler D., Oldroyd A., MacAskill A., and Finch D. (2007) An eight month test campaign of the QinetiQ ZephIR system: Preliminary results. Meteorol. Z. 16:479–489 Kropfli R. A.. (1986) Single Doppler radar measurement of turbulence profiles in the convective boundary layer. J. Atmos. Oceanic Technol., 3:305–314 Lenschow D. H., Mann J., and Kristensen L. (1994) How long is long enough when measuring fluxes and other turbulence statistics? J. Atmos. Oceanic Technol., 11:661–673 258 DTU Wind Energy-E-Report-0029(EN)
Lindelöw P. (2007) Fibre Based Coherent Lidars for Remote Wind Sensing. PhD thesis, Technical University Denmark Mann J. (1994) The spatial structure of neutral atmospheric surface-layer turbulence. J. Fluid Mech., 273: 141–168 Mann J., Cariou J., Courtney M., Parmentier R., Mikkelsen T., Wagner R., Lindelow P., Sjöholm M., and Enevoldsen K. (2009) Comparison of 3D turbulence measurements using three staring wind lidars and a sonic anemometer. Meteorol. Z., 18:135–140 Mann J, Peña A., Bingöl F., Wagner R., and Courtney M. S. (2010) Lidar scanning of momentum flux in and above the surface layer. J. Atmos. Oceanic Technol., 27:792–806 Monin A. S. and Yaglom A. M. (1975) Statistical Fluid Mechanics, volume 2. MIT Press, Motta M. and Barthelmie R. J. (2005) The influence of non-logarithmic wind speed profiles on potential power output at Danish offshore sites. Wind Energy, 219–236 Peña A., Hasager C. B., Gryning S.-E., Courtney M., Antoniou I., Mikkelsen T. (2009) Offshore wind profiling using light detection and ranging measurements. Wind Energy 12:105–124 Peña A., Gryning S.-E., and Hasager C. B. (2010a) Comparing mixing-length models of the diabatic wind profile over homogeneous terrain. Theor. Appl. Climatol. 100:325–335 Peña A., Gryning S.-E, and Mann J. (2010) On the length scale of the wind profile. Q. J. Royal Meteorol. Soc., 136: 2119–2131 Pichugina Y. L., Banta R. M., Kelly N. D., Jonkman B. J., S C. Tucker S. C., R K. Newsom B. J., and Brewer W. A. (2008) Horizontal-velocity and variance measurements in the stable boundary layer using Doppler lidar: Sensitivity to averaging procedures. J. Atmos. Oceanic Technol., 25:1307–1327 Sathe A., Mann J., Gottschall J., and Courtney M. (2011) Can wind lidars measure turbulence? Accepted for publication in the J Atmos. Oceanic Technol. Sjöholm M., Mikkelsen T., Mann J., Enevoldsen K., and Courtney M. (2009) Spatial averaging-effects on turbulence measured by a continuous-wave coherent lidar. Meteorol. Z., 18:281–287 Smalikho I., Kopp F., and Rahm S. (2005) Measurement of atmospheric turbulence by 2-µm Doppler lidar. J Atmos. Oceanic Technol., 22:1733–1747 Smith D. A., Harris M., Coffey A. S., Mikkelsen T., Jørgensen H. E., Mann J., and Danielian R. (2006) Wind lidar evaluation at the Danish wind test site in Høvsøre. Wind Energy 9:87–93 Sonnenschein C.M.andHorriganF.A.(1971) Signal-to-noise relationships forcoaxialsystems thatheterodyne backscatter from atmosphere. Appl. Opt., 10: 1600 Wagner R.,Mikkelsen T.,and Courtney M.(2009) Investigation ofturbulence measurements with acontinuous wave, conically scanning lidar. Technical Report Risø-R-1682(EN), Risø DTU, 2009 Wilson D. A. (1970) Doppler radar studies of boundary layer wind profiles and turbulence in snow conditions. In Proc. 14 th Conf. on Radar Meteorology, 191–196, Wyngaard J. C. (1968) Measurement of small-scale turbulence structure with hot wires. J. Sci. Instrum., 1:1105–1108 DTU Wind Energy-E-Report-0029(EN) 259
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Remote Sensing for Wind Energy DTU
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Author: Alfredo Peña, Charlotte B.
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4 Introduction to continuous-wave D
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8 Nacelle-based lidar systems 157 8
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12 Complex terrain and lidars 231 1
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1 Remote sensing of wind Torben Mik
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Figure 2: Calibration, laboratory w
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Figure 3: Example of scatter plots
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1.2.3 Summary of sodars Most of tod
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1.3.3 Wind lidars Measuring wind wi
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Figure 6: CW wind lidars (ZephIRs)
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Further developments Furthermore, n
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2 The atmospheric boundary layer S
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Figure 9: Large spatial scale varia
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Du3 Dt Du1 Dt Du2 Dt The three mome
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Figure 13: Consensus relations betw
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ψ z L ∼ − 5 L . For unstable c
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Figure 15: Behavior of the turbulen
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Figure 17: Newly developed models t
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The value of q0 at the surface is d
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the spray is the source of icing on
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u∗2 u∗1 u1(h) = u∗1 k ln h
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Figure 26:Land-seabreeze system,whe
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Figure28:Three dimensionalpicture o
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sufficient information. Finally, we
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Mann, J. (1998) Wind field simulati
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(2010) and comparison under differe
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To get the velocity field from the
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τ(k) [Arbitrary units] 10 3 10 2 1
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(Koopmans, 1974; Bendat and Piersol
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anemometer was installed at each en
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and fSw(f) u 2 ∗ = 1.05n 1+5.3n 5
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and n = 0.468. This spectrum implie
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to be calculated. We do that on a m
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Notation A Charnock constant neutra
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Maxey M. R. (1982) Distortion of tu
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4.2 Basic principles of lidar opera
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4.2.5 Wind profiling in conical sca
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4.3.1 Behaviour of scattering parti
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the beam radius at the output lens.
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from which the value of VLOS is der
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the atmosphere. The SNR 4 for a win
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individual line-of-sight wind speed
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A general approach to mitigating th
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from ±VH sinδ (if the tilt is tow
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as a down draught (of the same abso
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Table 7: Combined results from 28 Z
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in Eastern Jutland between January
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Figure 56: Normalized power curves
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the concept. Developments include i
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References x horizontal position in
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Wagner R., Mikkelsen T., and Courtn
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5.2 End-to-end description of pulse
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Scanner Coherent lidar measure the
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Figure 62: Radial wind velocity ret
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transform in order to use data obta
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This wavelength is also the most fa
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Eq.(132)isadaptedforcollimatedsyste
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5.3.6 Existing systems and actual p
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(Gottshall et al., 2010; Albers et
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References Albers A., Janssen A. W.
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derived from fluctuations of the wi
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Acoustic received echo (ARE) method
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Figure 71: Sample time-height cross
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A gradient minimum is characterized
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Figure73:Bragg-relatedacoustic(belo
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stability (inversion strength) can
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Figure 76: Combined soundingwith a
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Figure 79: Favorite regions (shaded
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Direct detection of MLH from acoust
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Engelbart D.A.M.and Bange J. (2002)
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7 What can remote sensing contribut
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uyms 9.0 8.5 8.0 7.5 7.0 120 140 16
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Bottom of rotor Φ rotation r w u
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Height Height Hub 1.6 1.4 1.2 1.0 0
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PP rated PP rated 1.0 0.8 0.6 0.4 0
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KEprofileKEhub 1.2 1.1 1.0 0.9 0.8
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PP rated WS Lidarms 1.0 0.8 0.6 0.4
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8 Nacelle-based lidar systems Andre
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• Flexibletrajectories.Dependingo
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Figure 104: Sketch of simultaneous
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The normal wind direction vector nw
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Figure 109: Test site at DTU Wind E
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Figure 112: Power curve met mast an
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Notation C number of sent photons C
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9 Lidars and wind turbine control -
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for three unknowns, it is impossibl
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model of the blade pitch actuator,
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|GRL| [-] 1 0.8 0.6 0.4 0.2 10 k [r
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PSD(Ωg) [(rpm) 2 /Hz] PSD(Ωg) [
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0.04 0.03 ˆk [ rad m ] 0.02 0.63 0
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[%] 10 0 −10 −20 −30 MyT Moop
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PSD(θ1) [rad 2 /Hz] PSD(Moop1) [Nm
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Pel/Pel,max [-] 1 0.98 0.96 0.94 0.
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fL weighting function GRL transfer
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E. Hau, Windkraftanlagen, 4th ed. S
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¨¦¦§©¡§ ¥§¨¦¦§£ ¡¥
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vertical (m) 150 100 50 R d 0
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With feedback only, on the other ha
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Figure 136: Estimated preview requi
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Normalized C r = C r P Q 2 W (r) b
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Normalized C r = C r P Q 2 W (r) b
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Coherence 1 0.8 0.6 0.4 0.2 0 10
Page 207 and 208: Coherence 1 0.8 0.6 0.4 0.2 0 10
Page 209 and 210: Magnitude Squared 10 8 10 7 10 6 10
Page 211 and 212: Figure 148: During simulation, FAST
Page 213 and 214: Figure 149: Collective flap respons
Page 215 and 216: Magnitude (abs) blade pitch gen spe
Page 217 and 218: • Measurement coherence, which ca
Page 219 and 220: Jonkman, B. (2009) TurbSim user’s
Page 221 and 222: 11 Lidars and wind profiles Alfredo
Page 223 and 224: z [m] 160 100 80 60 40 20 10 15 20
Page 225 and 226: z [−] zo 1 κ ln 40 38 36 34 32 3
Page 227 and 228: z [m] z [m] 1000 900 800 700 600 50
Page 229 and 230: the growth of the length scale, agr
Page 231 and 232: 12 Complex terrain and lidars Ferha
Page 233 and 234: Figure 158: The ZephIR models which
Page 235 and 236: Uconst wΑx l h Φ h.tanΦ Figure 1
Page 237 and 238: Figure 162: Lavrio: The scatter plo
Page 239 and 240: Figure 163: Panahaiko: The scatter
Page 241 and 242: References Albers A. and Janssen A.
Page 243 and 244: Wexler (1968), where the limitation
Page 245 and 246: 13.2.1 Systematic turbulence errors
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Page 249 and 250: The theoretical systematic errors a
Page 251 and 252: Height (m) 160 140 120 100 80 60 40
Page 253 and 254: Height (m) Height (m) 160 140 120 1
Page 255 and 256: RMSPE (%) 70 60 50 40 30 20 10 0 vu
Page 257: involves interaction of all compone
Page 261 and 262: plications, including meteorologica
Page 263 and 264: Figure 173: Rayleigh-Jeans’ appro
Page 265 and 266: Figure 176: Brightness temperature
Page 267 and 268: with rain are shown in Fig. 179. A
Page 269 and 270: This method gives a good accuracy (
Page 271 and 272: Figure 183: A recent maintenance in
Page 273 and 274: Figure 185: Temperature profiles in
Page 275 and 276: References s point in space Sν(s)
Page 277 and 278: Also the Doppler Centroid anomaly c
Page 279 and 280: Christiansen et al., 2006). The res
Page 281 and 282: educe speckle noise, a random noise
Page 283 and 284: Figure 188: Envisat ASAR wind field
Page 285 and 286: Figure 190: Envisat ASAR wind field
Page 287 and 288: Satellites in sun-synchronous polar
Page 289 and 290: 500 overlapping scenes for wind res
Page 291 and 292: (with the fewest samples). The unce
Page 293 and 294: Badger M., Hasager C. B., Thompson
Page 295 and 296: Ren Y. Z., Lehner S., Brusch S., Li
Page 297 and 298: tracking, climate studies, air-sea
Page 299 and 300: The modified logarithmic wind profi
Page 301 and 302: sea ice mask was applied and σ0 me
Page 303 and 304: QuikSCAT 25 20 15 10 5 Horns Rev Fi
Page 305 and 306: Figure 203:Example of an ASCAT coas
Page 307 and 308: References Bourassa M.A., Legler D.
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