Automatic Lidar and Ceilometer


Below you can find installation instructions for supported operating systems:

You can also build the ALCF from the source code if you want to modify any of its parts.


The instructions below assume that you enter the commands in the terminal.

  1. Install required programs and libraries:

    On Debian-based Linux distributions (Ubuntu, Debian, Devuan, …), install dependencies with:

     sudo apt install gcc make gfortran libhdf5-dev libnetcdf-dev \
         libnetcdff-dev python3 python3-setuptools python3-pip cython

    On Fedora, install dependencies with:

     sudo yum install make gcc gfortran hdf5-devel netcdf-devel \
         netcdf-fortran-devel python3-setuptools python3-pip python3-Cython
  2. Install the ALCF with:

     # To install globally:
     sudo pip3 install alcf --upgrade
     # To install in the user's home directory
     # (make sure "$HOME/.local/bin" is in the PATH environment variable):
     pip3 install alcf --upgrade --user

    Note that depending on the distribution you might have to replace pip3 above with pip.


It is recommended to run ALCF on Linux.

Installation on Windows is possible under the “Windows Subsystem for Linux”.

  1. Install “Ubuntu” from the Microsoft Store. You might have to enable “Windows Subsystem for Linux” under “Windows Features” first.

  2. Open “Ubuntu” from the Start Menu. Update packages with:

     apt update
     apt upgrade

    Follow the instructions above for installation on Linux (Debian-based distributions).

    Note: You can use cd /mnt/c/Users/<user>, where <user> is your Windows user name to change the current directory to your home directory, and ls to list the directory contents.


It is recommended to run ALCF on Linux.

The installation has been tested on macOS Monterey Intel. Installation on Apple M1 may be possible but is untested.

  1. Install Anaconda.

  2. Install MacPorts.

  3. Install required MacPorts packages:

     sudo port install gcc11 hdf5 netcdf netcdf-fortran
     sudo port select --set gcc mp-gcc11
  4. Install the ALCF with:

     pip install alcf

On macOS, the default shell zsh does not work with the command-line syntax of the ALCF. It is highly recommeded to run any alcf commands in the bash shell:

% bash
bash-3.2$ alcf


After completing the installation, you should be able to run the 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.


- `auto`: Peform automatic processing of model or lidar data.
- `calibrate`: Calibrate lidar backscatter.
- `convert`: Convert input instrument or model data to the ALCF standard NetCDF.
- `lidar`: Process lidar data.
- `model`: Extract model data at a point or along a track.
- `plot`: Plot lidar data.
- `simulate`: Simulate lidar measurements from model data using COSP.
- `stats`: Calculate cloud occurrence statistics.


- `--help`: Print help for command.
- `--debug`: Enable debugging information.

How to uninstall ALCF

To uninstall ALCF:

pip3 uninstall alcf

Note that depending on the distribution you might have to replace pip3 above with pip.

Building from the source code

If you want to build the ALCF from the source code, run the following commands in the source code directory:

pip3 install .

Note that depending on the distribution you might have to replace pip3 above with pip.

This will download and unpack ALCF-COSP (a version of COSP with support for ground-based lidars), and compile and install the ALCF. Use this option if you want to customise any parts of the ALCF.

You can also use the following command to continusly change code and have changes immediately applied in the alcf commands:

pip3 install -e .

Note that depending on the distribution you might have to replace python3 above with python.

Preparing a source distribution

To prepare a source distribution:

python3 sdist

The resulting package can be found in dist/alcf-<version>.tar.gz. This is the type of package available on PyPI.


Below is a list of releases of the ALCF. The version numbers follow the Semantic Versioning. Installation instructions have been changing with versions. Please follow the installation instructions in the documentation of the particular version.

1.5.0 (2023-04-22)

Release notes
  • Fixed calculation of time and time bounds in model drivers.
  • Require ds-format 3.6.1, which fixes an issue with readdir.
  • Support for index reading in the AMPS model driver.
  • Less verbose output from the COSP simulator.

1.4.1 (2023-04-21)

Release notes
  • Fixed a missing function argument in model drivers.

1.4.0 (2023-04-21)

Release notes
  • IMPORTANT: Fixed temperature reading in the AMPS driver. Temperature was read as 32 K colder than it should, resulting in a relatively small but potentially significant error in lidar cloud occurrence calculated from AMPS data.
  • Fixed skip option handling.
  • Added support for ARM format of CL51 data.
  • Parallel processing of model input.
  • Partial time limiting support in lidar drivers using the time option.
  • Faster interpolation implemented in Cython.
  • Speed improvements in the ICON driver.
  • Improvements in documentation.

1.3.1 (2023-03-16)

Release notes
  • Fixed issues with a new version of NumPy.
  • Minor improvements in the documentation.

1.3.0 (2023-03-15)

Release notes
  • Support for the ICON model.
  • Minor improvements in the documentation.

1.2.1 (2023-01-30)

Release notes
  • Support for reading Vaisala CL61 data files with zero-dimensional elevation variables.

1.2.0 (2022-11-22)

Release notes
  • Recursive directory processing options in alcf convert, alcf lidar and alcf model.
  • Support for double-dash command line delimiter.
  • cl51: Reading of files with arbitrary time units.
  • alcf simulate NetCDF matadata.
  • Improved documentation.

1.1.4 (2021-12-12)

Release notes
  • Use proleptic Gregorian calendar for time variables.
  • Include required fonts.

1.1.2 (2021-11-30)

Release notes
  • Simplified installation by removing a dependency on CMOR.

1.1.0 (2021-06-29) [documentation] [DOI: 10.5281/zenodo.5153867]

Release notes
  • Support for Vaisala CL61 and NetCDF files produced by BL-VIEW.
  • Improved documentation.

1.0.1 (2021-02-24) [documentation] [DOI: 10.5281/zenodo.5036683]

Release notes
  • Fixed download links to dependencies (udunits archive was removed upstream).

1.0.0 (2021-01-02) [documentation] [DOI: 10.5281/zenodo.4411633]

Release notes
  • First stable release. No change from 1.0.0-beta.3.

1.0.0-beta.3 (2020-10-15) [documentation] [DOI: 10.5281/zenodo.4088217]

Release notes
  • alcf lidar option for coupling of observed data with simulated molecular backscatter.
  • Removal of molecular backscatter in plots (if available).
  • alcf stats filter option now supports "night" and "day" and passing of multiple arguments.
  • New lidar type "default" for re-processing of already processed lidar data.
  • Support for plotting of model cloud liquid water, ice content and cloud fraction.
  • Calculation of lidar ratio changed to effective lidar ratio.
  • Backscatter plots now show effective lidar ratio and cloud mask by default.
  • Changed default vlim for backscatter plots to { 0.1 200 } and default sigma to 5.
  • Output files names are now without colons, which are not compatible with Windows.
  • More accurate plot labels.
  • Improved time sampling: exact profile time bounds are used from weighting.
  • Improved handling of errors and stopping with Ctrl+C.
  • Improved NetCDF metadata.
  • Improved compatibility with newer versions of matplotlib.
  • Fixed clearing of figures in alcf plot backscatter.

1.0.0-beta.2 (2020-05-01) [documentation] [DOI: 10.5281/zenodo.3779518]

Release notes
  • Initial beta release.