Articles | Volume 13, issue 11
Atmos. Meas. Tech., 13, 6237–6254, 2020
https://doi.org/10.5194/amt-13-6237-2020
Atmos. Meas. Tech., 13, 6237–6254, 2020
https://doi.org/10.5194/amt-13-6237-2020

Research article 20 Nov 2020

Research article | 20 Nov 2020

Filtering of pulsed lidar data using spatial information and a clustering algorithm

Leonardo Alcayaga

Data sets

Østerild Balconies Experiment (Phase 2) E. Simon and N. Vasiljevic https://doi.org/10.11583/DTU.7306802.v1

Model code and software

Lidar data filtering algorithms L. Alcayaga https://doi.org/10.5281/zenodo.4014151

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Short summary
Wind lidars present advantages over meteorological masts, including simultaneous multipoint observations, flexibility in measuring geometry, and reduced installation cost. But wind lidars come with the cost of increased complexity in terms of data quality and analysis. The common carrier-to-noise ratio and median filters are compared to the DBSCAN clustering algorithm to find improved data quality and recovery rate.