ALCF is an open source command line tool for processing of automatic lidar and ceilometer (ALC) data and intercomparison with atmospheric models such as general circulation models (GCMs), numerical weather prediction (NWP) models and reanalyses utilising a lidar simulator of the COSP instrument simulator framework. ALCs are vertically pointing atmospheric lidars, measuring cloud and aerosol backscatter. The primary focus of ALCF are atmospheric studies of cloud using ALC observations and model cloud validation.
Multiple instruments and models
ALCF can process data from multiple ceilometers and lidars: Vaisala CL31, CL51, Lufft CHM 15k, Sigma Space MiniMPL. Multiple models and reanalyses are supported by the lidar simulator: MERRA-2, AMPS, NZCSM.
Resampling and noise removal
ALCF resamples lidar backscatter to chosen temporal and vertical sampling to increase signal-to-noise ratio, calculates noise standard deviation from the highest level and removes noise.
Embedded lidar simulator based on COSP can be applied on model data to produce virtual backscatter measurements comparable with ALC observations for the purpose of model evaluation.
Cloud detection is done by applying a threshold on the denoised absolute backscatter. More sophisticated algorithms may be added in the future.
Cloud occurrence histogram as a function of height can be calculated and plotted from observations and model simulated backscatter.
Lidar ratio can calculated and plotted along the backscatter for absolute calibration of lidar backscatter using fully-opaque stratocumulus scenes (O’Connor et al., 2004).
ALCF is available under the terms of the MIT license, which allows free use, copying, modification and redistribution.