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inner layer is of the order of 0.1 L, and the perturbation of the top of the hill, the so-called relative speed up, is found as: ∆u u0 ≈ 2 H L Troen & Petersen (1989) have developed the theory into a Fourier form, allowing one to build an arbitrary landscape as a superposition of low hills, which when combined with the roughness changes, becomes the model in the WAsP system Troen & Petersen (1989). If the slope becomes too large, of the order of 20%, flow separation develops on both the upstream and the downstream slope. We next turn towards the situations which are driven by a changing heat flux. Here we start with the diurnal cycle for a horizontally homogeneous area at midlatitude, where the boundary layer show obvious diurnal changes. As we have discussed the changes, they will be smaller if the wind is high, and the atmosphere is cloudy, than when the wind is low and the sky is clear. But it will always be present, and limiting the degree of stationarity one can expect for such a surface. A similar changing rate can be found in frontal passages, which take a time of the order of one day or longer. Figure 25: A heat flux driven diurnal change of the ABL for a homogeneous midlatitude land surface (Stull, 1988). We next turn towards an IBL controlled by the surface heat flux, where the IBL, here denoted TIBL, growths against a stable upstream ABL. Here, we can use the growth of the unstable boundary layer equation in eq. 10, also depicted in fig. 25. Just assuming that the upward heat flux now happens as function of fetch, x, instead of time, inserting t = u/x in eq. 10. A more comprehensive description of these types of models are found in Gryning et al. (1990). The situation can happen for both land and water surfaces, being dependent on differences in surface heat flux and/or surface temperature of the two surfaces involved. However, it is quite easy to imagine, that it is developing at a coast line. Here the surface temperature of the land and the sea is quite often different. Due to the two different surfaces response in the surface energybudget (eq. 17)on a diurnal scale. As the time and space scales for such coastal system increase, the differential heating between two surfaces, will influence the atmospheric dynamics, because air will tend to rise over the relatively warm surface and sink over the colder area. The resulting circulation is called a land-sea breeze system. At night the land cools relatively to the sea, and the flow reverses. The land-sea breeze is the best known one of the breeze systems. However, breeze systems occur also as breeze systems around major cities, because of the “urban heat island” effect. When the spatial scale of a land-breeze system increase to continental scale, one talk about Monsoons, which will typical be seasonal rather than diurnal. However breeze systems of many scales can exist at the same location, and will often interact. A more complex situation appears for a transition from an unstable ABL passing over a colder surface, where the more intensive unstable ABL has to decay before the stable IBL can establish itself. Also, these situations occur quite often in some coastal areas. 44 DTU Wind Energy-E-Report-0029(EN) (22)
Figure 26:Land-seabreeze system,where ahot landresultsin risingair, whileovertherelative cold water air sinks. Especially the transition from relatively warm unstable/neutral land ABL into a stable IBL over the water (Melas, 1998). Several things happens. The air gradually looses heat to the water and reach the water surface temperature at the interface, where a small neutral layer establishes itself. This neutral layer slowly growths up through the stable IBL, until the original temperature gradient between the two air masses is concentrated at the top of a new boundary layer that however can take many hundred kilometers to establish itself. Figure27:Warmneutralairflowingovercoldwater,anddevelopsastableIBL,SIBL,gradually transitioning to a neutral ABL with an inversion on the top. Over the water for off-winds. (Lange et al., 2004). The broken triangular line indicates the possibility for a low level jet at the transition. A low level jet may happen in the transition between land and water, because the surface friction in the boundary layer suddenly disappears, for the air crossing the coastal line. Considering eq. 1, we see that the wind above the boundary layer is unchanged,friction is unimportant here. The velocity within the ABL must accelerate because the friction is reduced, finally the wind has to go to zero at the surface. It is a transitional phenomenon that graduallydisappearsas the full profileand stress profilereasserts themselves downstreamfrom the coast line. These lowlevel jets can appears, wherever the surface stress reduces because of increasing stability or decreasing roughness or both. It is quite well known over the nighttime Plains of US, where they are a result of the growing night time stability. The heat/temperature controlled IBLs may happen also especially over water, when synoptic air masses are advected over relatively cold or warm water. Here especially, the second one, will give rise to a thermally induced convective IBL, which over the water typically will DTU Wind Energy-E-Report-0029(EN) 45
Page 1 and 2: Remote Sensing for Wind Energy DTU
Page 3 and 4: Author: Alfredo Peña, Charlotte B.
Page 5 and 6: 4 Introduction to continuous-wave D
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: u∗2 u∗1 u1(h) = u∗1 k ln h
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
Page 55 and 56: To get the velocity field from the
Page 57 and 58: τ(k) [Arbitrary units] 10 3 10 2 1
Page 59 and 60: (Koopmans, 1974; Bendat and Piersol
Page 61 and 62: anemometer was installed at each en
Page 63 and 64: and fSw(f) u 2 ∗ = 1.05n 1+5.3n 5
Page 65 and 66: and n = 0.468. This spectrum implie
Page 67 and 68: to be calculated. We do that on a m
Page 69 and 70: Notation A Charnock constant neutra
Page 71 and 72: Maxey M. R. (1982) Distortion of tu
Page 73 and 74: 4.2 Basic principles of lidar opera
Page 75 and 76: 4.2.5 Wind profiling in conical sca
Page 77 and 78: 4.3.1 Behaviour of scattering parti
Page 79 and 80: the beam radius at the output lens.
Page 81 and 82: from which the value of VLOS is der
Page 83 and 84: the atmosphere. The SNR 4 for a win
Page 85 and 86: individual line-of-sight wind speed
Page 87 and 88: A general approach to mitigating th
Page 89 and 90: from ±VH sinδ (if the tilt is tow
Page 91 and 92: as a down draught (of the same abso
Page 93 and 94: Table 7: Combined results from 28 Z
Page 95 and 96:
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
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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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