GitHub

ALCF

Automatic Lidar and Ceilometer
Framework

The 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 Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP). ALCs are vertically pointing atmospheric lidars, measuring cloud and aerosol backscatter. The primary focus of the ALCF are atmospheric studies of cloud using ALC observations and model cloud validation.
Paper  |  Presentation  |  Poster 1, 2  |  Thesis

Features

Multiple instruments and models

The ALCF can process data from multiple ceilometers and lidars: Vaisala CL31, CL51, CL61, 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.

A photo of Lufft CHM 15k ceilometer A photo of Vaisala CL51 ceilometer

Resampling and noise removal

The 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.

A plot of ceilometer backackatter resampled and with noise removed

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 observationsA plot of Lufft CHM 15k backscatter
AMPS model simulated lidarA plot of AMPS model simulated lidar backscatter

Cloud detection

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

A plot of ceilometer backscatter with detected clouds

Cloud occurrence

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

Vaisala CL51 vs. HadGEM3 model
A plot of Vaisala CL51 vs. HadGEM3 model cloud occurrence by height
A plot of NBP1704 CHM 15k cloud occurrence by height
A plot of TAN1802 CHM 15k cloud occurrence by height

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).

A plot of ceilometer backscatter and lidar ratio

Open source

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