213 8 Applications This book is primarily about the design and operating principles of atmospheric acoustic remote-sensing instruments, so this chapter will simply give a few examples of the use to which this technology can be put. For a more exhaustive insight into applications, there are very good review articles such as Singal (1997), Asimakopou- los (1994), Asimakopoulos and Helmis (1994), Asimakopoulos et al. (1996), Engel- bart (1998), Reitebuch and Emeis (1998), Coulter and Kallistratova (1999), Engelbart et al. (1999), Helmis et al. (2000), Kirtzel et al. (2000), Melas et al. (2000), Ostashev and Wilson (2000), Seibert et al. (2000), Emeis (2001), Engelbart and Steinhagen (2001), Piringer and Baumann (2001), Raabe et al. (2001), Rufeux and Stübi (2001), Neisser et al. (2002), Peters and Fischer (2002), Anderson (2003), and Bradley et al. (2004b). 8.1 REVIEW OF SELECTED APPLICATIONS 8.1.1 E NVIRONMENTAL RESEARCH A major use of SODAR and RASS technology is in monitoring and understanding the atmospheric boundary layer in relation to air pollution and dispersion modeling. Traditionally it has been difcult for these instruments to work effectively in closely built-up urban areas, because of echoes from buildings and because of impact on residents, but this is changing as the acoustic design of the instruments improves. We give here a few results from Salfex, an urban “street canyon” momentum and heat ux study in Salford, Greater Manchester, UK, which was led by Janet Bar- low of Reading University (Barlow et al., 2007). Figure 8.1 shows a site plan of the street canyon study area and the SODAR location. The SODAR was placed on the other side of the River Irwell, with rela- tively open land upwind to the north, but within 30 m of occupied housing to the east. Directly measuring instrumentation included masts extending to just above the dense housing in the study area, and the AeroVironment 4000 SODAR provided data above that height. In this way, wind proles could be obtained at regular intervals, such as the half-hourly proles shown in Figure 8.2. FIGURE 8.1 Site plan for the Salfex cam- paign. The street canyon measurements were at site 1, and the SODAR at site 2. The plot is 1 km on each edge. 3588_C008.indd 213 11/20/07 4:15:05 PM © 2008 by Taylor & Francis Group, LLC 214 Atmospheric Acoustic Remote Sensing Estimates of roughness length in the complex surface of the streets and buildings were readily available, as shown in the example of Figure 8.3. The lowest points, at z–d = 12 m (with d = 8 m) represented the lowest height accessible to the SODAR (because of ringing within the bafe). The roughness length z 0 , friction velocity u * , and drag coefcient (u * /v) 2 all show variation with wind direction. This is not surprising given the clearer sectors, but it would be difcult to quantify these variations with any other instrument than a SODAR. Second-moment data, such as the results for T u,v /T w shown in Figure 8.4, indicate a change in the boundary layer regime at about 80 m. It is the interpretation of this 0 20 40 60 80 100 120 225 230 235 240 245 250 255 260 265 270 Wind Direction (degrees) Height z (m) 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 FIGURE 8.2 :LQGGLUHFWLRQSURÀOHVUHFRUGHGHYHU\KDOIKRXU 2 2.5 3 3.5 4 4.5 5 5791113 Wind Speed V (m s –1 ) 20 40 30 100 70 50 Height z (m) 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 FIGURE 8.3 /RJDULWKPLFZLQGVSHHGSURÀOHVPHDVXUHGHYHU\KDOIKRXU 3588_C008.indd 214 11/20/07 4:15:07 PM © 2008 by Taylor & Francis Group, LLC ln (z-d) (m) Applications 215 type of observed feature which is particularly useful in guiding the development of new models for this challenging area of meteorology. 8.1.2 BOUNDARY LAYER RESEARCH The use of an array of SODARs presents some interesting measurement opportuni- ties. These include being able to investigate advection of non-turbulent structures. The SABLE SODAR array (Bradley et al., 2004b; Bradley and von Hunerbein, 2006) consisted of four vertically pointing speaker-dish units having individual power ampliers and local intelligence. They were interconnected via RS485 operat- u,v w z FIGURE 8.4 Second moment proles. o u /o w (diamonds), T v / T w (squares). Simpson Red Green Blue Yellow 226 m 225 m 389 m 394 m 387 m 224 m + + + + + + + + + FIGURE 8.5 The geometry of the Antarctic SODAR array. 3588_C008.indd 215 11/20/07 4:15:09 PM © 2008 by Taylor & Francis Group, LLC 216 Atmospheric Acoustic Remote Sensing ing at 57.6 kB and exchanged data with a centralized PC. SODAR spacing was about 400 m (Figure 8.5). The SODARs transmitted simultaneously in non-overlapping frequency bands, but with center frequency, pulse characteristics, sampling, and other parameters selectable on a pulse-by-pulse basis. Local control was achieved with microprocessors. The array comprised three SODARs placed at the vertices of an equilateral triangle, and a fourth SODAR at the center. Figure 8.6 shows typical 200 150 100 Height 50 0 678910 Time 11 12 13 14 200 150 100 Height 50 0 678910 Time 11 12 13 14 200 150 100 Height 50 0 678910 Time 11 12 13 14 200 150 100 Height 50 0 678910 Time 11 12 13 14 FIGURE 8.6 6HHFRORULQVHUWIROORZLQJSDJH3ORWVRIWLPHYDULDWLRQVRIWKH C T 2 ÀHOG measured by the four SODARs. 3588_C008.indd 216 11/20/07 4:15:11 PM © 2008 by Taylor & Francis Group, LLC Applications 217 time series of C T 2 proles. Fluctuations in C T 2 occur at each range gate level, and these are often correlated across the four SODARs because of advected coherent structures. Covariances were computed at each height for each pair of SODARs and from these the corresponding time lags were estimated. This resulted in a sys- tem of linear equations to be solved for the advected velocity components (u, v), as follows. ˆ , , , , , , u x x x x x x yr gr gy br by bg $ $ $ $ $ $ § © ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨¨ ¨ ¨ · ¹ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ˆ , , , , v y y y y y yr gr gy br $ $ $ $ $ bby bg yr y r , , , $ $ § © ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ · ¹ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸ 22 2 2 2 / / / / , ,, ,, ,, T T T T yr gr gr gy gy br br b r r r r $ $ $ $ ,, , ,, / / yby bg bg r 2 2 T T$ § © ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨ · ¹ ¸ ¸ ¸ ¸ ¸ ¸ ¸ ¸¸ ¸ ¸ ¸ ¸ , (8.1) where the ∆x and ∆y are the components of the vector ∆r between each pair of SODARs, and the U values are the estimated time lags based on correlations at each range gate of pairs of C T 2 versus time records. Figure 8.7 shows the matrix of covariances versus height, with obvious peaks at each height which can give the U values. This method yields wind proles from non-Doppler SODARs, as shown in Figure 8.8. The technique also allows for estimates of the size of coherent structures, based on the covariance matrix. 8.1.3 WIND POWER AND LOADING We have already presented calibration data from the WISE project in previous chap- ters (Bradley et al., 2004a). The aim of that project was to prove that SODARs have sufcient reliability and accuracy for the rather demanding wind-power industry requirements (better than 1% accuracy at all heights to 150 m with high data avail - ability). Figure 8.9 shows the eld calibration layout. From proles produced by SODARs, it is possible to monitor turbine perfor- mance as a function of wind speed and to do this with considerable accuracy as shown in Figure 8.10 (Antoniou et al., 2004). 8.1.4 COMPLEX TERRAIN SODAR and RASS are relatively portable devices and can operate from a small generator or battery-backed solar cells. This makes them a useful technology for investigations of ows and mixing layer heights in complex terrain. Most of the journal literature relating to acoustic remote sensing in the atmosphere describes such measurements. Here we simply show some of the information which is available. First, Fig- ure 8.11 shows wind proles measured by an AeroVironment 4000 SODAR from prior to dawn through sunrise. Two aspects are very evident: the useful height range is greatly reduced during the night in this example, when turbulence is suppressed 3588_C008.indd 217 11/20/07 4:15:14 PM © 2008 by Taylor & Francis Group, LLC 218 Atmospheric Acoustic Remote Sensing Red Yellow Green Blue Height Time 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 60 40 20 –200 2000 Red Yellow Green Blue FIGURE 8.7 6HHFRORULQVHUWIROORZLQJSDJH0DWUL[RIFRYDULDQFHVEHWZHHQ C T 2 YDO- ues measured by each pair of SODARs at each height. 3588_C008.indd 218 11/20/07 4:15:17 PM © 2008 by Taylor & Francis Group, LLC Applications 219 because of the cool surface; and there are intriguing wind direction changes with height (but not signicant change in wind speed). Both these effects are common in complex terrain, and the SODAR makes boundary layer development easier to visualize, while as well giving a large volume of 3D numerical data. Figures 8.12 and 8.13 show turbulent intensity ( C T 2 ) in complex terrain over a few hours. Figure 8.12 shows an overnight stable boundary layer situation with grav- ity waves in elevated layers. In Figure 8.13, the transition into a convective regime after sunrise is marked. Speed m/s Height (m) 0 10 20 30 40 50 60 70 80 0246810 FIGURE 8.8 :LQGSURÀOHVGHULYHGIURPWKHFRYDULDQFHVVKRZQLQ)LJXUH FIGURE 8.9 7KH ÀHOG OD\RXW IRU WKH :,6( FDOLEUDWLRQ FDPSDLJQ )URP IRUHJURXQG WR EDFNJURXQG6FLQWHF62'$5ZLWKODUJHGLDPHWHUZKLWHEDIÁHV$HUR9LURQPHQW0HWHN 62'$55$66ZLWK5$'$5GLVKDQGDVPDOO0HWHN62'$5 3588_C008.indd 219 11/20/07 4:15:19 PM © 2008 by Taylor & Francis Group, LLC 220 Atmospheric Acoustic Remote Sensing 8.1.5 SOUND SPEED PROFILES Outdoor sound propagation is increasingly important with noise sources such as airports, motorways, industry, and wind turbines increasingly being in close prox- imity to residential areas. In order to predict sound propagation over distances of 1050 –0.2 0 0.2 0.4 0.6 Electrical Power (normalised) Wind Speed (m/s) Electrical Power (normalised) 0.8 1 1.2 15 20 FIGURE 8.10 3RZHUSHUIRUPDQFHYHUVXVZLQGVSHHGIRUPDVWPRXQWHGFXSDQHPRPHWHUV FLUFXODUGRWV62'$5REORQJGRWVDQG=HSK,5/,'$5WULDQJOHV 200 175 150 125 100 Height (m–agl) 75 50 25 06:40 1.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0+ Knots 07:00 07:20 07:40 08:00 Time 08:20 08:40 09:00 09:20 FIGURE 8.11 7KHYHORFLW\SURÀOHVREVHUYHGE\DQ$HUR9LURQPHQW62'$5LQFRP- plex terrain. 3588_C008.indd 220 11/20/07 4:15:22 PM © 2008 by Taylor & Francis Group, LLC Applications 221 a few kilometers, it is necessary to know the atmospheric temperature and wind prole to perhaps 100 m. A SODAR/RASS combination can provide the necessary acoustic refractive index data on a continuous basis over a representative time scale. 02:15 02:30 02:45 03:00 >98 >72 98 96 94 92 90 88 86 84 82 80 78 76 74 02:0001:3001:1501:0000:4500:3000:15 100 200 01:45 dB Scale FIGURE 8.12 Turbulent intensity ( C T 2 ) during an overnight stable boundary layer situa- tion. The vertical scale is height in m. 06.45 07.00 07.15 07.30 08.30 09.3007.45 08.4508.00 09.0008.15 09.15 <98 dB Scale 98 96 94 92 90 88 86 84 82 80 78 76 74 <72 100 200 FIGURE 8.13 The transition from stable boundary layer to convective boundary layer. The vertical scale is height in m. 3588_C008.indd 221 11/20/07 4:15:27 PM © 2008 by Taylor & Francis Group, LLC 222 Atmospheric Acoustic Remote Sensing Figure 8.14 shows sound speed proles reconstructed in this way using a Metek SODAR/RASS (Bradley et al., 2006). In this particular case, the SODAR/RASS has detected the presence of a jet which might not have been included in models based on surface observations and similarity. 8.1.6 HAZARDS Increasingly SODARs and LIDARs are being used routinely at airports to monitor natural coherent wind structures (such as downbursts, gusts, and strong shear), and hazards caused by vortices from the wing tips of planes landing or taking off. By deploying an array of SODARs across the ight path, but outside the runway area, it is possible to obtain a “snapshot” of the entire wind eld above the line of SODARs (Bradley et al., 2007). Figure 8.15 shows the vertical wind velocities recorded by a four-SODAR array during three aircraft landings. The SODARs were 25 m apart in a line on one side of the ight path. Spectral data were collected for single acoustic transmissions, every 2 s, rather than the normal averaging procedure. This meant that the acquired winds were not as accurate, but the fast update rate was required to track the vortices. In order to offset the loss of signal to noise ratio, a simple vortex model was tted to the measured wind eld every snapshot. This tting of the veloc- ity eld was performed independently every 2 s, so smoothness of the estimated vortex movement and development was a strong indication that the method worked. Figure 8.16 shows one example of the estimated development with time of the vortex-pair height and spacing, together with error bars. It can be seen that the method provides a good guide as to the vortex behavior. 336 338 340 342 344 346 348 20 30 40 50 60 70 80 90 100 110 Sound Speed (m/s) Height (m) FIGURE 8.14 6RXQGVSHHGSURÀOHVUHFRQVWUXFWHGIURPWHPSHUDWXUHDQGZLQGYHORFLW\SUR- ÀOHVREWDLQHGIURPD0HWHN62'$55$66 3588_C008.indd 222 11/20/07 4:15:28 PM © 2008 by Taylor & Francis Group, LLC [...]... 80 60 40 20 0 9:02 9:06 9:04 10m/s 9: 08 Time FIGURE 8. 15 (a) Horizontal wind speeds measured at the four-beam SODAR The ori- 80 70 zc, s (m) 60 50 40 30 20 10 0 0 4 8 12 16 Time (s) 20 24 28 30 FIGURE 8. 16 (open circles) in which the spacing increases substantially 8. 2 SUMMARY In this chapter we have given a very brief coverage of some applications of SODAR and RASS These indicate that 1 Acoustic remote. .. mast anemometers (right-hand image) m 1000 0 900 80 0 10 700 600 20 500 400 30 300 200 40 100 9:45 11:45 13:45 15:45 17:45 19:45 21:45 23:45 1:45 3:45 5:45 7:45 9:45 FIGURE A3.2 Typical AQ RASS output FIGURE A3.3 The ARPL mini-SODAR © 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd 243 11/27/07 4: 08: 57 PM 244 Atmospheric Acoustic Remote Sensing FIGURE A3.4 The KPA-1000 phased-array Doppler SODAR (left)... MODOS mobile SODAR © 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd 244 11/27/07 4: 08: 58 PM Appendix 3 245 FIGURE A3.7 Phased-array SODAR DSDPA.9 0-2 4 (left) and phased-array SODAR DSDPA.9 0-6 4+RASS (right) FIGURE A3 .8 The REMTECH PA1 SODAR (left) and PA2 (right) FIGURE A3.9 Scintec SODARs SFAS (left), MFAS (center), and XFAS (right) © 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd 245 11/27/07... remote sensing gives a very good visualisation of temporal development of wind and turbulence fields in the lowest few hundred meters 2 Very good quantitative profiles and profile slopes are obtained even in difficult environments such as urban areas © 20 08 by Taylor & Francis Group, LLC 3 588 _C0 08. indd 223 11/20/07 4:15:32 PM 224 Atmospheric Acoustic Remote Sensing 3 Arrays of acoustic remote sensing. .. availability) 500 80 0 m Maximum measuring height >1000 m >1000 m Recommended frequency 2200–2500 Hz 1500–2500 Hz Signal power Max 80 0 W (elect.) Max 80 0 W (elect.) Antenna gain Typ 20 dB Typ 25 dB Sensitivity of receiver 10–6 N/m2 10–6 N/m2 Beam width 7–12 Typ 5 8 Qualifying standards DIN 3 786 (11), KTA15 08 DIN 3 786 (11), KTA15 08 Power consumption 250 W 250 W © 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd... Diameter 2000 mm Focal length 6 58 mm Source type Circular polarization Height of the shielding fence around each antenna 2050 mm Frequency 915 or 1290 MHz Power 15 W Bandwidth (at ?3 dB) 3 MHz Rejection Better than 60 dB Total gain 39 dB Noise figure 2 dB © 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd 241 11/27/07 4: 08: 53 PM 242 A3 .8 Atmospheric Acoustic Remote Sensing SCINTEC GMBH [TÜBINGEN,... 20 08 by Taylor & Francis Group, LLC 3 588 _A003.indd 237 11/27/07 4: 08: 50 PM 2 38 Atmospheric Acoustic Remote Sensing AQMR90 AQRASS Height 240 cm Height 150 cm Width 180 cm Width 150 cm Temperature range –40 t +60 C Temperature range –40 t +60 C Humidity range 10–100% RH Humidity range 10–100% RH Weight 150 kg Weight 45 kg Antenna beam tilt 0 and 15 Focal length 710 mm Acoustic power . situa- tion. The vertical scale is height in m. 06.45 07.00 07.15 07.30 08. 30 09.3007.45 08. 45 08. 00 09.00 08. 15 09.15 < 98 dB Scale 98 96 94 92 90 88 86 84 82 80 78 76 74 <72 100 200 FIGURE 8. 13. time scale. 02:15 02:30 02:45 03:00 > 98 >72 98 96 94 92 90 88 86 84 82 80 78 76 74 02:0001:3001:1501:0000:4500:3000:15 100 200 01:45 dB Scale FIGURE 8. 12 Turbulent intensity ( C T 2 ) during. Francis Group, LLC 0 10 20 30 40 50 60 70 0 4 8 12 16 20 24 28 30 80 Time (s) z c , s (m) 224 Atmospheric Acoustic Remote Sensing 3. Arrays of acoustic remote sensing instruments can give both vertical