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Contents Page 1 Remote sensing of wind 11 1.1 Ground-based remote sensing for today’s wind energy research . . . . . . . . 11 1.1.1 Wind remote sensing (RS) methodologies . . . . . . . . . . . . . . . 11 1.2 Part I: Remote sensing of wind by sound (sodars) . . . . . . . . . . . . . . . 11 1.2.1 RS applications within Wind Energy . . . . . . . . . . . . . . . . . . 13 1.2.2 Recent developments . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.2.3 Summary of sodars . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.3 Part II: RS of wind by light (lidars) . . . . . . . . . . . . . . . . . . . . . . . 17 1.3.1 Introduction to lidars . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.3.2 Wind RS methodologies . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.3.3 Wind lidars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 1.3.4 Wind profiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.3.5 Lidar accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.3.6 Wind lidar applications for wind energy . . . . . . . . . . . . . . . . 22 1.3.7 Summary of lidar . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2 The atmospheric boundary layer 25 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.2 ABL Flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.3 The ideal ABL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.4 Surface Characteristics of real ABLs . . . . . . . . . . . . . . . . . . . . . . 37 2.5 Homogeneous Land ABL . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.6 Homogeneous Marine ABL . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.7 Inhomogenous and instationary ABL . . . . . . . . . . . . . . . . . . . . . . 42 2.8 Complex terrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 2.9 Boundary Layer Climatology for Wind energy . . . . . . . . . . . . . . . . . 47 2.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3 Atmospheric turbulence 52 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.2 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.3 Rapid distortion theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.3.1 RDT and surface layer turbulence . . . . . . . . . . . . . . . . . . . 56 3.3.2 Eddy lifetimes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.3.3 The uniform shear model . . . . . . . . . . . . . . . . . . . . . . . . 58 3.4 Fitting spectra to observations . . . . . . . . . . . . . . . . . . . . . . . . . 58 3.4.1 Uncertainties on spectra . . . . . . . . . . . . . . . . . . . . . . . . 58 3.4.2 Spectral fitting and prediction of coherences . . . . . . . . . . . . . . 59 3.5 Model spectra over the ocean and flat land . . . . . . . . . . . . . . . . . . 61 3.5.1 Code and textbook spectra . . . . . . . . . . . . . . . . . . . . . . . 62 3.6 Comparison with the spectral tensor model . . . . . . . . . . . . . . . . . . . 65 3.7 Wind field simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4 <strong>DTU</strong> Wind Energy-E-Report-0029(EN)
4 Introduction to continuous-wave Doppler lidar 72 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.2 Basic principles of lidar operation and system description . . . . . . . . . . . 73 4.2.1 Brief survey of lidar types . . . . . . . . . . . . . . . . . . . . . . . . 73 4.2.2 Principles underlying anemometry by coherent laser radar (CLR) . . . 73 4.2.3 Role of local oscillator and range selection by focus . . . . . . . . . . 73 4.2.4 Doppler frequency analysis and signal processing . . . . . . . . . . . 74 4.2.5 Wind profiling in conical scan mode . . . . . . . . . . . . . . . . . . 75 4.2.6 Pioneering a revolution: ZephIR lidar . . . . . . . . . . . . . . . . . . 75 4.3 Lidar measurement process: Assumptions . . . . . . . . . . . . . . . . . . . . 76 4.3.1 Behaviour of scattering particles . . . . . . . . . . . . . . . . . . . . 77 4.3.2 Uniformity of flow and backscatter . . . . . . . . . . . . . . . . . . . 77 4.3.3 Beam positional accuracy . . . . . . . . . . . . . . . . . . . . . . . . 77 4.3.4 Optical and electrical interference sources . . . . . . . . . . . . . . . 77 4.3.5 Time-of-flight considerations . . . . . . . . . . . . . . . . . . . . . . 78 4.4 End-to-end measurement process for CW Doppler lidar . . . . . . . . . . . . 78 4.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 4.4.2 Transmitter optics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 4.4.3 Light scattering by aerosols . . . . . . . . . . . . . . . . . . . . . . . 79 4.4.4 Receiver optics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.4.5 Light beating . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.4.6 Photodetection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.4.7 Fourier analysis and lidar sensitivity . . . . . . . . . . . . . . . . . . 81 4.4.8 Velocity estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.5 Ground based, vertical scan configuration wind field parameter determination 84 4.5.1 Least-squares fitting routine . . . . . . . . . . . . . . . . . . . . . . 84 4.5.2 Parameter extraction . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.5.3 Data averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.6 Uncertainty analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.6.1 Rain/snow/cloud, solid objects . . . . . . . . . . . . . . . . . . . . . 85 4.6.2 Cloud effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 4.6.3 System positioning accuracy . . . . . . . . . . . . . . . . . . . . . . 88 4.6.4 Probe volume effects and operation at greater heights . . . . . . . . 89 4.6.5 Flow uniformity and complex terrain . . . . . . . . . . . . . . . . . . 89 4.6.6 Dependence on backscatter level . . . . . . . . . . . . . . . . . . . . 90 4.6.7 Beam obscuration and attenuation . . . . . . . . . . . . . . . . . . . 90 4.6.8 Wind direction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 4.7 Calibration, validation and traceability . . . . . . . . . . . . . . . . . . . . . 91 4.8 Turbine mounted continuous wave lidar . . . . . . . . . . . . . . . . . . . . 92 4.8.1 Least-squaresfittingroutine forhorizontalscanning(turbine mounted) operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 4.8.2 Turbine mounted CW lidar for wind turbine power curve measurement 94 4.9 Summary, state of the art, and future developments . . . . . . . . . . . . . . 96 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 5 Pulsed lidars 104 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 5.2 End-to-end description of pulsed lidar measurement process . . . . . . . . . . 105 5.2.1 Architecture of pulsed lidars . . . . . . . . . . . . . . . . . . . . . . 105 5.2.2 Differences between pulsed vs. continuous wave lidars . . . . . . . . . 107 5.2.3 Signal processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 <strong>DTU</strong> Wind Energy-E-Report-0029(EN) 5
Page 1 and 2: Remote Sensing for Wind Energy DTU
Page 3: Author: Alfredo Peña, Charlotte B.
Page 7 and 8: 8 Nacelle-based lidar systems 157 8
Page 9 and 10: 12 Complex terrain and lidars 231 1
Page 11 and 12: 1 Remote sensing of wind Torben Mik
Page 13 and 14: Figure 2: Calibration, laboratory w
Page 15 and 16: Figure 3: Example of scatter plots
Page 17 and 18: 1.2.3 Summary of sodars Most of tod
Page 19 and 20: 1.3.3 Wind lidars Measuring wind wi
Page 21 and 22: Figure 6: CW wind lidars (ZephIRs)
Page 23 and 24: Further developments Furthermore, n
Page 25 and 26: 2 The atmospheric boundary layer S
Page 27 and 28: Figure 9: Large spatial scale varia
Page 29 and 30: Du3 Dt Du1 Dt Du2 Dt The three mome
Page 31 and 32: Figure 13: Consensus relations betw
Page 33 and 34: ψ z L ∼ − 5 L . For unstable c
Page 35 and 36: Figure 15: Behavior of the turbulen
Page 37 and 38: Figure 17: Newly developed models t
Page 39 and 40: The value of q0 at the surface is d
Page 41 and 42: the spray is the source of icing on
Page 43 and 44: u∗2 u∗1 u1(h) = u∗1 k ln h
Page 45 and 46: Figure 26:Land-seabreeze system,whe
Page 47 and 48: Figure28:Three dimensionalpicture o
Page 49 and 50: sufficient information. Finally, we
Page 51 and 52: Mann, J. (1998) Wind field simulati
Page 53 and 54: (2010) and comparison under differe
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To get the velocity field from the
Page 57 and 58:
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
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Coherence 1 0.8 0.6 0.4 0.2 0 10
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Magnitude Squared 10 8 10 7 10 6 10
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Figure 148: During simulation, FAST
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Figure 149: Collective flap respons
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Magnitude (abs) blade pitch gen spe
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• Measurement coherence, which ca
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Jonkman, B. (2009) TurbSim user’s
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11 Lidars and wind profiles Alfredo
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z [m] 160 100 80 60 40 20 10 15 20
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z [−] zo 1 κ ln 40 38 36 34 32 3
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z [m] z [m] 1000 900 800 700 600 50
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the growth of the length scale, agr
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12 Complex terrain and lidars Ferha
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Figure 158: The ZephIR models which
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Uconst wΑx l h Φ h.tanΦ Figure 1
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Figure 162: Lavrio: The scatter plo
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Figure 163: Panahaiko: The scatter
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References Albers A. and Janssen A.
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Wexler (1968), where the limitation
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13.2.1 Systematic turbulence errors
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where x is the center of the scanni
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The theoretical systematic errors a
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Height (m) 160 140 120 100 80 60 40
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Height (m) Height (m) 160 140 120 1
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RMSPE (%) 70 60 50 40 30 20 10 0 vu
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involves interaction of all compone
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Lindelöw P. (2007) Fibre Based Coh
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plications, including meteorologica
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Figure 173: Rayleigh-Jeans’ appro
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Figure 176: Brightness temperature
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with rain are shown in Fig. 179. A
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This method gives a good accuracy (
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Figure 183: A recent maintenance in
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Figure 185: Temperature profiles in
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References s point in space Sν(s)
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Also the Doppler Centroid anomaly c
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Christiansen et al., 2006). The res
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educe speckle noise, a random noise
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Figure 188: Envisat ASAR wind field
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Figure 190: Envisat ASAR wind field
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Satellites in sun-synchronous polar
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500 overlapping scenes for wind res
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(with the fewest samples). The unce
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Badger M., Hasager C. B., Thompson
Page 295 and 296:
Ren Y. Z., Lehner S., Brusch S., Li
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tracking, climate studies, air-sea
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The modified logarithmic wind profi
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sea ice mask was applied and σ0 me
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QuikSCAT 25 20 15 10 5 Horns Rev Fi
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Figure 203:Example of an ASCAT coas
Page 307 and 308:
References Bourassa M.A., Legler D.
Page 309:
DTU Wind Energy Technical Universit
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