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

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120 100 80 Threshold Westerly winds 120 T>9 ° C T9 ° C T9 ° C T9 ° C T9 ◦ C and T
140 120 Threshold night day Easterly winds 140 120 Ideal profile night day 100 100 counts 80 60 counts 80 60 40 40 20 20 0 0 500 1000 1500 2000 BLH 0 0 500 1000 1500 2000 BLH 140 120 Exponent−ideal profile night day 140 120 Vertical gradient night day 100 100 counts 80 60 counts 80 60 40 40 20 20 0 0 500 1000 1500 2000 BLH 0 0 500 1000 1500 2000 BLH Figure 49: Frequency distribution of all BLH estimates during October 2010, easterly wind direction, divided in day and night. wind directions are shown in table 10. The mean BLH is much higher when winds are north westerly according to all methods. The explanation of the higher BLHs when winds are from NW is given above for April 2010, but here the difference is more noticeable and the mean BLHs significantly higher, as the sea surface temperature is higher in October than in April. The detections of the critical threshold method show the highest mean BLH both with south westerly and north westerly winds compared with the other methods. The vertical gradient method results in the lowest mean BLH for both wind direction criteria. Method SW mean BLH [m] NW mean BLH [m] Critical threshold 633 884 Idealized profile 577 859 Exp. ideal. profile 602 870 Vertical gradient 558 826 Table 10: Mean BLH October 2010 north westerly- and south westerly winds. February 2011 In Figure 51 the frequency distributions of the BLH estimates are shown for easterly wind directions, divided into day and night for February 2011. The BLH estimates are found between 0 and 1800 m. The four different BLH detection methods show similar distributions and generally higher BLHs during night than during daytime. The mean BLHs are seen in Table 11 and it is seen that the nighttime BLHs are not much higher, only ∼60 m higher than the daytime BLHs. The lowest mean BLH estimates are made with the idealized profile, both day 60 DTU Wind Energy Master Thesis M-0039
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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 and 32: 1600 Zero filter 23/07/2010 22:00 N
Page 33 and 34: 5.2 Continuous and average data The
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: Threshold Westerly winds Ideal prof
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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