Welcome to pytroll!¶

This is the home of the pytroll project. The pytroll project started out in 2009 as a collaboration on weather satellite data processing between DMI and SMHI. Pytroll now has a growing international user base and is used operationally at several National Met Services.

The objective is to provide different free and open source python modules for the reading, interpretation, and writing of weather satellite data. The provided python packages are designed to be used both in R&D environments and in 24/7 operational production.

For a quick and easy overview of what Pytroll can possibly offer for you have a look at the Pytroll tutorial which was shown at the 2016 Eumetsat conference in Darmstadt Wednesday September 28

If you want to contact us, you can use the following mailing list: https://groups.google.com/group/pytroll or chat with us on the pytroll slack: https://pytrollslackin.herokuapp.com/ or on the pytroll IRC channel on freenode: irc://irc.freenode.net/pytroll


RSHU, Saint Petersburg, Russia, March 2017

A pytroll developers workshop was held at the Russian State Hydrometeorological University (RSHU) in Saint Petersburg, Russia, between March 27th and 31st, 2017. We were around 20 participants from various National Meteorological Institutes, universities and companies.

The available pytroll python packages at the moment are:

  • pyresample for resampling satellite data
  • mipp for reading (mostly HRIT/LRIT formated) weather satellite data
  • mpop for reading and processing weather satellite data
  • pycoast for putting coastlines, borders and rivers on an image
  • pyorbital for computing satellite orbital parameters and reading TLE’s
  • posttroll a higher-level messaging library for pytroll
  • pykdtree for really fast nearest neighbour search
  • python-geotiepoints for interpolating (and extrapolation) geographic tiepoints
  • trollimage the new image packagse for pytroll (replaces and enhances the image.py module in mpop)
  • trollsift for the formatting, parsing and filtering of satellite granule file names
  • pyspectral to read and manipulate satellite sensor spectral responses and solar irradiance spectra
  • pydecorate to simplify the drawing of logos, text labels, color scales and legends onto images
  • trollduction a framework for satellite batch processing
  • pytroll-schedule to generate optimized satellite schedules for polar reception stations
  • trollcast for realtime sharing of weather satellite data
  • pygac to read NOAA AVHRR Global Area Coverage (GAC) data and apply state of the art calibration and navigation

Some more packages are in the process of being developed (you’re very welcome to have a look and give us a hand):

  • satpy A refactored mpop (for reading and processing weather satellite data)
  • pygranules for validating, fetching and scheduling satellite data granules
  • trollbufr for reading BUFR files

Satellites supported (imager instruments) at the moment by the reader/processor modules include:

  • Meteosat series (tested with 7, 8, 9, 10)
  • GOES series, in HRIT/LRIT format (tested with 11, 12, 13, 15)
  • MTSAT series, in HRIT/LRIT format (tested with 1R, 2)
  • Himawari 8, in HRIT/LRIT format
  • Himawari 8, standard format (satpy only)
  • Electro L, in HRIT/LRIT format (tested with N1)
  • NOAA series, in AAPP, GAC and LAC format (tested with 15, 16, 17, 18, 19)
  • Metop-A/B, in EPS 1a and 1b format
  • Aqua and Terra, in hdf-eos format
  • Suomi NPP, in SDR hdf5 format
  • TerraSAR-X
  • Radarsat-2 SAR
  • COSMO-SkyMed SAR
  • Sentinel-1 SAR
  • Sentinel-2 MSI
  • FY-3 viir


Contact us: https://groups.google.com/group/pytroll