Skip to main content

Visualizing METAR data on a Raspberry Pi with LEDs.

Project description


Inspired by some DIY projects, this script allows you to quickly discern weather conditions by changing the colors of LEDs to reflect the current METAR information. You will need a Raspberry Pi, some WS281X LEDs, and the four letter designators of the airports you are interested in.

This code assumes you’ve connected to GPIO 18 (PWM0) and have added blacklist snd_bcm2835 to the /etc/modprobe.d/snd-blacklist.conf file.

Don’t want to DIY it? This is the code that powers the Aviation Weather Maps products. Enjoy a premade product, or continue reading and happy tinkering!


sudo su
apt install python3-venv python3-dev
python3 -m venv /opt/rpi_metar
source /opt/rpi_metar/bin/activate
pip install wheel
pip install rpi_metar


You need to tell rpi_metar which LEDs correspond to which airports. You may do this by creating the /etc/rpi_metar.conf file. There must be an [airports] section where the airport codes are assigned to LEDs. For example:

KDEN = 0
KBOS = 1

The LED indexes can be skipped and do not need to be continuous. If you don’t have an LED associated with an airport, it does not need to be entered.

The behavior of the program can be tweaked by including a settings section in the configuration file. These configuration values can be set:

Option Default Description
brightness 128 An integer (from 0 to 255) controlling the intensity of the LEDs appear. In a well lit room, 75 or 85 are recommended. In a bright room, try 128.
disable_gamma False A boolean that will allow you to disable the gamma correction. You may need this if using LEDs from different manufacturers / batches in a single run.
do_fade True A boolean controlling whether or not stations will fade into their new color during a transition. If False, they will just abruptly change colors.
lightning True A boolean that controls if thunderstorm conditions should be visually indicated. They will appear as short blinks of white before going back to the station’s original color.
lightning_dura tion 1.0 A float controlling how long a station blinks white before returning to its original color.
max_wind 30 An integer that sets the threshold for max wind speed in knots. Any steady or gusting winds above this value will result in yellow blinking lights.
metar_refresh_rate 300 An integer that controls how frequently (in seconds) the METAR information is polled.
sources NOAA,NO AABacku p,SkyVe ctor The data sources to be used. A comma separated list of class names from the file. BOM is another source for Australian stations.
wind True A boolean that controls if high wind speeds should be visually indicated. They will appear as short blinks of yellow before going back to the station’s original color.
wind_duration 1.0 A float controlling how long a station blinks yellow before returning to its original color.
unknown_off True A boolean that controls whether or not stations that are not reporting data will just turn off. If set to False, after three attempts (during which time they appear as yellow), they will instead turn to orange.

For example, to reduce the brightness of the LEDs:

brightness = 85

Another feature includes setting up a legend. These are a series of lights that will always display their assigned static color. Similar to setting up the airports by LED index, you can assign flight categories to LED indexes:

VFR = 10
IFR = 11
LIFR = 12
MVFR = 13
WIND = 14


Create the /etc/systemd/system/rpi_metar.service file with the following contents:

Description=METAR Display



Make systemd aware of the changes:

systemctl daemon-reload

Make sure it’s set to run at boot:

systemctl enable rpi_metar

Start the service:

systemctl start rpi_metar

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for rpi-metar, version 0.4.1
Filename, size File type Python version Upload date Hashes
Filename, size rpi_metar-0.4.1.tar.gz (357.2 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page