image plotting of backscatter signal in log scale
February 17, 2026 · View on GitHub
Python library for reading and processing ALC (Automated Lidars and Ceilometers) measurements. A-Profiles supports E-PROFILE ceilometer data. This library is used by V-Profiles.
📗 Documentation
The official documentation is available here.
✨ Installation
via pip
aprofiles is directly available on pip. This will install the latest released version of aprofiles and its depencencies.
- with pip
pip install aprofiles
- with pipx
pipx install aprofiles
from source
-
clone this repository
git clone https://github.com/AugustinMortier/A-Profiles.git -
installation
-
with pip (>21.3)
pip install . -
with pipx
pipx install . -
with uv
uv pip install .
-
In order to install directly the package from source with pip, you can also use the combined command
pip install "git+ssh://git@github.com/AugustinMortier/A-Profiles.git"
🚀 Get started
Reading Data
# import library
import aprofiles as apro
# read local NetCDF L2 data
path = "examples/data/E-PROFILE/L2_0-20000-006735_A20210908.nc"
profiles = apro.reader.ReadProfiles(path).read()
Basic corrections and Image plotting
# extrapolate lowest layers for removing outliers
profiles.extrapolate_below(z=150, inplace=True)
# image plotting of backscatter signal in log scale
profiles.plot(zref='agl', vmin=1e-2, vmax=1e1, log=True)
Profiles Analysis
# fog/condensation detection
profiles.foc(zmin_cloud=200)
# clouds detection
profiles.clouds()
# planetary boundary layer
profiles.pbl(zmin=200, zmax=3000, under_clouds=True)
Visualization
Image
# image plotting with additional retrievals
profiles.plot(show_fog=True, show_clouds=True, show_pbl=True, vmin=1e-2, vmax=1e1, log=True)
Single Profile
# plot single profile at 21:20
datetime = np.datetime64('2021-09-09T21:20:00')
profiles.plot(datetime=datetime, vmin=-1, vmax=10, zmax=12000, show_clouds=True, show_pbl=True)
⚖️ License
🎓 Support
A-Profiles is developed by MET Norway and supported by EUMETNET.