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

7 Conclusion
The cloud filtering provides a clear improvement when estimating the BLH with the four
applied methods and may easily be implemented in an automated BLH detection algorithm.
As the cloud filtering methods may be chosen according to different cloud conditions or BLH
definitions, they provide flexibility in BLH detection. The amount of usable data may be
increased considerably by filtering clouds. In this analysis, ∼60% of the aerosol backscatter
measurements during the year showed cloud cover, and many would have been discarded
without the filtering methods applied.
Both of the BLH detection algorithms that have been modified in this work may provide
better estimates of the BLH under certain conditions. The variable critical threshold value is
easily implemented in an automated BLH detection algorithm. The larger the range in aerosol
backscatter values for a given study, the larger is the benefit of implementing the modification.
The exponent idealized method shows a notable improvement when aerosol concentrations
are high near the surface. In this study this was often seen when there were strong winds
from the west. As the method is computationally intense with the two additional parameters,
it may therefore be dependent on the specific study whether the benefits of the modification
outweigh the extra computational time.
The ceilometer may be used for analysis of the ABL structure and the daily evolution.
The standard deviation of the 10 s BLH estimates is significantly larger when the aerosol
backscatter signals are weak and generally more robust BLH estimations are performed when
the signals are strong. The backscatter signals are seen to depend on the RH of the atmosphere,
as this influences the aerosol size.
A significant correlation is found between the BLH estimations from the aerosol backscatter
measurements with ceilometer data and BLH estimations based on turbulence measurements
with the wind lidar. As both instruments are dependent on the aerosol content of the atmosphere,
they only produce reliable measurements when aerosol concentration is above a
critical value. This was often not the case when winds were easterly. It would therefore be
interesting to compare the ceilometer-based BLH estimates with other methods than the
minimum TKE, also as this method is not reliable in the presence of clouds. This comparison
would also be relevant for further investigation of the cloud filtering methods, as no clear
consensus on a definition of the CTBL exists.
For the first time frequency distributions of BLH estimates were made with a large data set
with measurements from Høvsøre. It is noteworthy that no matter the method of estimation,
the mean BLH and the shape of the distributions were relatively similar. This tells something
about the robustness of the BLH detection algorithms. The monthly analysis of the marine
BLH estimates often showed bi-modal distributions. It was possible to divide these monthly
distributions into separate distributions by wind direction or air temperature criteria. Division
of the marine BLH estimates into day and night showed similar distributions with the same
mean BLH, as was expected. The monthly frequency distributions of BLH estimates with
easterly winds showed more surprising results, as the distributions were seldom bi-modal. The
division of the BLH estimates into day and night showed no consistent results, sometimes
with a higher mean BLH during nighttime than daytime.
The wave patterns of the vertical backscatter profiles in the ceilometer data, mentioned in
section 5.8 have not been filtered for this work. The patterns are not so dominant in the two
profile fitting methods, but it may still be worthwhile to correct for these patterns in future
analyses.
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