Boundary-layer height detection with a ceilometer at a coastal ... - Orbit

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1600 BLH, critical threshold, different cloud filtering 400 1400 350 1200 300 Height [m] 1000 800 600 250 200 150 β [1/(10 8 ⋅srad⋅m)] 400 100 200 50 06:00 09:00 12:00 15:00 18:00 21:00 Time of day 0 Figure 20: The backscatter coefficient measured with the ceilometer on August 19 2010. The coloured shading indicates the intensity of the backscattered light, blue shading indicates minimal scattering and white indicates negative backscatter values. All BLH estimates are made with the critical threshold method and three different cloud filtering methods are applied. The black circles indicate zero filter, green triangles indicate nearest neighbour interpolation and pink stars indicate the cloud base filter. DTU Wind Energy Master Thesis M-0039 33
5.2 Continuous and average data The ceilometer at Høvsøre provides measurements of the aerosol backscatter every ten seconds (henceforth, 10 s data). These data are not readily available on the Høvsøre database, but remain stored at the Risø met data server. The ten minute means (henceforth, 10 min data) of these high resolution data are as mentioned in section 3 available on the database. To compare the BLH estimates of 10 min data with those of the 10 s data, BLH estimates are made for every 10 s data during a ten minute interval for a single whole day. The mean of these 60 estimates is calculated (henceforth, 10 s mean BLH) and compared to the 10 min data BLH estimates. 600 Exponent idealized profile 400 550 500 450 350 300 Height [m] 400 350 300 250 250 200 150 β [1/(10 8 *srad*m)] 200 150 100 100 50 50 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 Time of day 0 Figure 21: The diurnal evolution of the ABL on June 21 2010. The BLH estimates are found by fitting the exponent idealized profile. Black stars indicate the BLH estimates from the 10 min data and magenta stars the BLH estimates from the 10 s mean BLH. The error bars represent the standard deviation of the 10 s estimates within 10 minutes. In Figure 21 the BLH estimates from the different data types, 10 s and 10 min, are illustrated for an entire day, starting at midnight. These BLH estimates have all been performed by fitting the exponent idealized profile described in Section 4.4. It should be noted that the error bars shown are not exact errors, but the BLH variability, found by computing the standard deviation, σ of all 10 s BLH estimates within 10 minutes. It is seen that the variability is generally larger during daytime, from around 7:00 to 16:00, than during nighttime, from 00:00 to 07:00. The standard deviation of the BLH estimates is largest in the late evening from 20:00 to 22:00, where the backscatter signal is relatively weak. The cloud visible from around 23:00 has been removed with the cloud base filter described in Section 4.5. The BLH estimates from the two data sets agree very well, though with a tendency in the 10 min data estimates to be a little higher, especially during daytime. This is common for all four methods of BLH detection, and may be seen in appendix B where plots similar to Figure 21 are made for the remaining three detection methods. Figure 22 shows a scatter plot of the 10 min BLH estimates and those 10 min means derived from the 10 s estimates from the four different BLH detection methods. As in Figure 21 the 34 DTU Wind Energy Master Thesis M-0039
Page 1 and 2: DTU Wind Energy Master Thesis M-003
Page 3 and 4: Contents 1 Introduction 5 1.1 Thesi
Page 5 and 6: 1.1 Thesis contents The content of
Page 7 and 8: and Batchvarova, 1994; Stull, 1988)
Page 9 and 10: ∂ē ∂t = g w ′ θ v ′ − u
Page 11 and 12: 2.7 Boundary-layer clouds The prese
Page 13 and 14: the square root of the variance. Ro
Page 15 and 16: 3 Site and measurements In this sec
Page 17 and 18: occasionally use the term “radial
Page 19 and 20: Ultrasonic Wind Sensor uSonic-3 Sci
Page 21 and 22: 4 Boundary-layer height detection T
Page 23 and 24: 90/(10 8 m srad), respectively). Fo
Page 25 and 26: 1400 β profile 16/04/2010 11:40 14
Page 27 and 28: 24/04/2010 06:20 1000 σ w 1000 ē
Page 29 and 30: Decoupled Clouds Clouds that are no
Page 31: 1600 Zero filter 23/07/2010 22:00 N
Page 35 and 36: of the error bars during the day. T
Page 37 and 38: also be explained by the shape of t
Page 39 and 40: increases from 19:00-20:00. A resid
Page 41 and 42: 1400 1200 BLH estimations 01/05/201
Page 43 and 44: 5.4 Cold front passage On April 8 2
Page 45 and 46: Wind vectors at 10m height. Metmast
Page 47 and 48: 0.3 The inverse Obukhov length 1/L
Page 49 and 50: Wind vectors at 10m height. Metmast
Page 51 and 52: 0.1 The inverse Obukhov length 1/L
Page 53 and 54: 1400 BLH from minimum TKE 16 June 2
Page 55 and 56: 70 60 Threshold night day Easterly
Page 57 and 58: Threshold Westerly winds Ideal prof
Page 59 and 60: 140 120 Threshold night day Easterl
Page 61 and 62: Threshold Easterly winds Ideal prof
Page 63 and 64: 400 300 Threshold night day Easterl
Page 65 and 66: 5.9 Intra-annual variation The BLH
Page 67 and 68: wind lidar (Sathe et al., 2011). Ho
Page 69 and 70: distributions. It is clear that the
Page 71 and 72: A Appendix Abbreviations ABL Atmosp
Page 73 and 74: References Batchvarova, E., X. Cai,
Page 75: Sinclair, V. A., S. Niemelä, and M

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