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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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doi:10.5194/amt-2016-327
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
11 Nov 2016
Review status
A revision of this discussion paper was accepted for the journal Atmospheric Measurement Techniques (AMT) and is expected to appear here in due course.
Pathfinder: Applying graph theory for consistent tracking of daytime mixed layer height with backscatter lidar
Marco de Bruine1,2, Arnoud Apituley1, Dave Donovan1, Henk Klein Baltink1, and Marijn de Haij1 1Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, the Netherlands
2Institute for Marine and Atmospheric Research (IMAU), Utrecht University, Utrecht, the Netherlands
Abstract. 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 MLHL, which is feasible because the main sources of aerosols are situated at the surface and vertical gradients are expected going 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, MLHL retrievals may jump between different atmospheric layers, rather than reliably track true MLH development over time. This hampers the usefulness of MLHL time series for e.g. process studies, model validation/verification and climatology. Here, we introduce a new method "Pathfinder", which applies graph theory to simultaneously evaluate timeframes 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 presence of clouds and residual layers. Applied to backscatter lidar data from Cabauw, excellent agreement is found with windprofiler retrievals for a 12-day period in 2008 (R2 = 0.90) and visual judgment of lidar data during a full year in 2010 (R2 = 0.96). These values compare favourably against other MLHL methods applied to the same lidar data set and corroborate more consistent MLH tracking by Pathfinder.

Citation: de Bruine, M., Apituley, A., Donovan, D., Klein Baltink, H., and de Haij, M.: Pathfinder: Applying graph theory for consistent tracking of daytime mixed layer height with backscatter lidar, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-327, in review, 2016.
Marco de Bruine et al.
Marco de Bruine et al.

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Short summary
The height atmospheric layers are important to understand how air pollution moves away from their sources. With a laser instrument that detects particles of air pollution we can measure the height of these layers, because the sources of pollution are close to the ground and the air is cleaner higher above the ground. As the height of the layer changes it is difficult to automatically follow the correct layer. "Pathfinder", that works like route planners that find the shortest way, improves this.
The height atmospheric layers are important to understand how air pollution moves away from...
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