Automatic Lidar and Ceilometer


ALCF is written in Python and Fortran. Installation on Linux is recommended. Installation on other operating systems may be possible and planned in the future, but is not described here at the moment.


The installation has been tested on Debian GNU/Linux 10, Devuan GNU/Linux 2.1, Ubuntu Desktop 19.10 and Fedora 31 Workstation.

Install the following required software:

Download and unpack the latest ALCF version, and run commands below in the unpacked directory.

Before compiling the dependencies, you might need to install the following packages: gfortran, libexpat-dev, m4, libcurl4-openssl-dev and zlib1g-dev, python3-setuptools, python3-pip and eccodes. Install with:

# Debian, Devuan, Ubuntu:
apt-get install gfortran libexpat-dev m4 libcurl4-openssl-dev zlib1g-dev python3-setuptools python3-pip libeccodes-tools
# Fedora:
yum install make patch g++ gfortran expat-devel m4 libcurl-devel zlib-devel python3-setuptools python3-pip eccodes

To download and build dependencies (UDUNITS, NetCDF, NetCDF-Fortran, OSSP uuid, HDF5, CMOR, COSP):


download_dep will automatically download required libraries and build_dep will compile the libraries (it might take up to 5 minutes to finish).

Note: ALCF uses the Python libraries ds-python, aquarius-time and pst, which are installed with the commands below.

To install in system directories:

pip3 install \ \
python3 install

To install in user directories (make sure ~/.local/bin is in the environmental variable PATH):

pip3 install --user \ \
python3 install --user

You should now be able to run ALCF in the terminal:


should output:

alcf - Tool for processing of automatic lidar and ceilometer (ALC) data
and intercomparison with atmospheric models.


    alcf <cmd> [<options>]
    alcf <cmd> --help


- `cmd`: see Commands below
- `options`: command options


`--help`: print help for command


- `convert`: convert input instrument or model data to ALCF standard NetCDF
- `model`: extract model data at a point or along a track
- `cosp`: simulate lidar measurements from model data using COSP
- `lidar`: process lidar data
- `stats`: calculate cloud occurrence statistics
- `plot`: plot lidar data
- `plot_stats`: plot lidar statistics