Boundary-layer height detection with a ceilometer at a coastal ... - Orbit
Boundary-layer height detection with a ceilometer at a coastal ... - Orbit
Boundary-layer height detection with a ceilometer at a coastal ... - Orbit
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3000<br />
Threshold<br />
3000<br />
Ideal profile<br />
2500<br />
2500<br />
2000<br />
2000<br />
counts<br />
1500<br />
counts<br />
1500<br />
1000<br />
1000<br />
500<br />
500<br />
0<br />
0 500 1000 1500<br />
BLH<br />
0<br />
0 500 1000 1500<br />
BLH<br />
3000<br />
Exponent−ideal profile<br />
3000<br />
Vertical gradient<br />
2500<br />
2500<br />
2000<br />
2000<br />
counts<br />
1500<br />
counts<br />
1500<br />
1000<br />
1000<br />
500<br />
500<br />
0<br />
0 500 1000 1500<br />
BLH<br />
0<br />
0 500 1000 1500<br />
BLH<br />
Figure 52: Histogram of all BLH estim<strong>at</strong>es between April 2010–March 2011. The bars show<br />
the histograms and the solid black line shows a fit using a Gamma distribution.<br />
Method α s αs<br />
√ αs<br />
Critical threshold 3.59 144 516 273<br />
Idealized profile 2.36 201 475 309<br />
Exp. ideal. profile 3.07 162 498 284<br />
Vertical gradient 2.80 169 473 283<br />
Table 12: The shape parameter (α), scale parameter (s), mean (αs) and devi<strong>at</strong>ions ( √ αs)<br />
found by a Gamma fit of all BLH estim<strong>at</strong>es during April 2010– March 2011.<br />
in the vertical backsc<strong>at</strong>ter profiles. The wave p<strong>at</strong>tern is visible in the density plots as weak<br />
horizontal ’bands’ e.g. in Figures 27(a) and 36, where the backsc<strong>at</strong>ter intensities are rel<strong>at</strong>ively<br />
weak. The BLH estim<strong>at</strong>es tend to converge to the regions where the backsc<strong>at</strong>ter signals are<br />
weaker due to the wave p<strong>at</strong>tern. According to Schäfer et al. (2004) this wave p<strong>at</strong>tern is<br />
caused by a small disturbance in the receiver electronics. They worked <strong>with</strong> a Vaisala CT25K<br />
<strong>ceilometer</strong> and removed the wave p<strong>at</strong>tern <strong>with</strong> an algorithm th<strong>at</strong> subtracts the p<strong>at</strong>tern from<br />
every backsc<strong>at</strong>ter profile.<br />
Figure 53 shows the frequency distribution of BLH estim<strong>at</strong>es in the period April 2010 –<br />
March 2011, easterly winds only and further divided into day and night. The BLH estim<strong>at</strong>es<br />
are found between 0–2500 m. The figure shows the interval 0–1500 m, as estim<strong>at</strong>es above<br />
1500 m make ∼1% of the total. The bin size is 20 m. The figure also shows a Gamma distribution<br />
fitted to each frequency distribution. The shape parameter, scale parameter, the mean<br />
and devi<strong>at</strong>ion of a Gamma distributions are seen in Table 13. The mean BLHs estim<strong>at</strong>ed in<br />
daytime are generally slightly higher than the nighttime BLH estim<strong>at</strong>es, except for the critical<br />
threshold method which shows the same mean BLHs day and night.<br />
The frequency distributions do not follow the Gamma distribution as well as in the case<br />
DTU Wind Energy Master Thesis M-0039 63