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 based on 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.
Paper (submitted to GMD) | Presentation | Poster

### Features

#### Multiple instruments and models

ALCF can process data from multiple ceilometers and lidars: Vaisala CL31, CL51, Lufft CHM 15k and Sigma Space MiniMPL. Multiple models and reanalyses are supported by the lidar simulator: AMPS, ERA5, JRA-55, MERRA-2, NZCSM and UM.

#### 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.

#### Lidar simulator

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.

Luff CHM 15k observations
AMPS model simulated lidar

#### Cloud detection

Cloud detection is done by applying a threshold on the denoised absolute backscatter. More sophisticated algorithms may be added in the future.

#### Cloud occurrence

Cloud occurrence histogram as a function of height can be calculated and plotted from observations and model simulated backscatter.

Vaisala CL 51 vs. HadGEM3 model

#### Calibration

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).

#### Open source

ALCF is available under the terms of the MIT license, which allows free use, copying, modification and redistribution.