Pathfinder: applying graph theory to consistent tracking of daytime mixed layer height with backscatter lidar
The height of the atmospheric boundary layer or mixing layer is an important parameter for understanding the dynamics of the atmosphere and the dispersion of trace gases and air pollution. The height of the mixing layer (MLH) can be retrieved, among other methods, from lidar or ceilometer backscatte...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-05-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | http://www.atmos-meas-tech.net/10/1893/2017/amt-10-1893-2017.pdf |
| Summary: | The height of the atmospheric boundary layer or mixing layer is an
important parameter for understanding the dynamics of the atmosphere and the
dispersion of trace gases and air pollution. The height of the mixing layer
(MLH) can be retrieved, among other methods, from lidar or ceilometer
backscatter data. These instruments use the vertical backscatter lidar signal
to infer MLH<sub>L</sub>, which is feasible because the main sources of aerosols are
situated at the surface and vertical gradients are expected to go from the
aerosol loaded mixing layer close to the ground to the cleaner free
atmosphere above. Various lidar/ceilometer algorithms are currently applied,
but accounting for MLH temporal development is not always well taken care of.
As a result, MLH<sub>L</sub> retrievals may jump between different atmospheric
layers, rather than reliably track true MLH development over time. This
hampers the usefulness of MLH<sub>L</sub> time series, e.g. for process studies, model
validation/verification and climatology. Here, we introduce a new method
<q>pathfinder</q>, which applies graph theory to simultaneously evaluate
time frames that are consistent with scales of MLH dynamics, leading to coherent
tracking of MLH. Starting from a grid of gradients in the backscatter
profiles, MLH development is followed using Dijkstra's shortest path
algorithm (Dijkstra, 1959). Locations of strong gradients are connected
under the condition that subsequent points on the path are limited to a
restricted vertical range. The search is further guided by rules based on the
presence of clouds and residual layers. After being applied to backscatter lidar data
from Cabauw, excellent agreement is found with wind profiler retrievals for a
12-day period in 2008 (<i>R</i><sup>2</sup> = 0.90) and visual judgment of lidar data during a
full year in 2010 (<i>R</i><sup>2</sup> = 0.96). These values compare favourably to other
MLH<sub>L</sub> methods applied to the same lidar data set and corroborate more
consistent MLH tracking by pathfinder. |
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| ISSN: | 1867-1381 1867-8548 |