The metar library
Python-metar is a python package for interpreting METAR and SPECI coded weather reports.
METAR and SPECI are coded aviation weather reports. The official coding schemes are specified in the World Meteorological Organization (WMO) Manual on Codes, vol I.1, Part A (WMO-306 I.i.A). US conventions for METAR/SPECI reports vary in a number of ways from the international standard, and are described in chapter 12 of the Federal Meteorological Handbook No.1. (FMH-1 1995), issued by the National Oceanic and Atmospheric Administration (NOAA). General information about the use and history of the METAR standard can be found at
This module extracts the data recorded in the main-body groups of reports that follow the WMO spec or the US conventions, except for the runway state and trend groups, which are parsed but ignored. The most useful remark groups defined in the US spec are parsed, as well, such as the cumulative precipitation, min/max temperature, peak wind and sea-level pressure groups. No other regional conventions are formally supported, but a large number of variant formats found in international reports are accepted.
Current METAR reports
Current and historical METAR data can be obtained from various places. The current METAR report for a given airport is available at the URL
where is the four-letter ICAO airport station code. The accompanying script get_report.py will download and decode the current report for any specified station.
The METAR reports for all stations (worldwide) for any "cycle" (i.e., hour) in the last 24 hours are available in a single file at the URL
where is a 2-digit cycle number (e.g., "00", "05" or "23").
The Federal Meteorological Handbook No.1. (FMH-1 1995), which describes the U.S. standards, is available online at
The World Meteorological Organization (WMO) Manual on Codes, vol I.1, Part A (WMO-306 I.i.A) can be downloaded from site I use to distribute this package,
Tom Pollard firstname.lastname@example.org May 2, 2009
If you're using the
anaconda python distribution, you can create a new
enviroment with the following:
conda create --name metar33 python=3.3 matplotlib pandas six pip nose ipython-notebook openpyxl
Then clone this repository, activate the recently created environment, and install via pip:
git clone https://github.com/phobson/python-metar.git cd python-metar source activate metar33 # omit `source` on Windows
The standard pip command to install would be:
pip install .
However, if you're gonna modify the source code (for whatever reason), pass in
-e flag. That way, you can just restart your python interpreter after
altering the source to test your changes.
pip install -e .
There's a small, annoyingly slow test suite that can be run by saying
There are a couple of sample scripts and IPython Notebook, described briefly below.
There's no real documentation to speak of, yet, but feel free to contact me with any questions you might have about how to use this package.
You can always obtain the most recent version of this package using git, via
git clone git://github.com/tomp/python-metar.git
This is a public copy of the code repository I use for development. Thanks to Toby White for making me aware of github.
Contents (way out of date)
README ............. this file parse_metar.py ..... a simple commandline driver for the METAR parser get_report.py ....... a script to download and decode the current reports for one or more stations. sample.py .......... a simple script showing how the decoded data can be accessed. (see metar/*.py sources and the test/test_*.py scripts for more examples.) sample.metar ....... a sample METAR report (longer than most). Try feeding this to the parse_metar.py script... metar/ Metar.py ....... the implementation of the Metar class. This class parses and represents a single METAR report. Datatypes.py ... a support module that defines classes representing different types of meteorological data, including temperature, pressure, speed, distance, direction and position. test/ all_tests.py ... a master test driver, which invokes all of the unit tests test_*.py ...... individual test modules setup.py ........... installation script
See the sample.py script for an annonated demonstration of the use of this code. Just as an appetizer, here's an interactive example...
from metar import Metar obs = Metar.Metar('METAR KEWR 111851Z VRB03G19KT 2SM R04R/3000VP6000FT TSRA BR FEW015 BKN040CB BKN065 OVC200 22/22 A2987 RMK AO2 PK WND 29028/1817 WSHFT 1812 TSB05RAB22 SLP114 FRQ LTGICCCCG TS OHD AND NW -N-E MOV NE P0013 T02270215') print obs.string()
station: KEWR type: routine report, cycle 19 (automatic report) time: Tue Jan 11 18:51:00 2005 temperature: 22.7 C dew point: 21.5 C wind: variable at 3 knots, gusting to 19 knots peak wind: WNW at 28 knots visibility: 2 miles visual range: runway 04R: 3000 meters to greater than 6000 meters feet pressure: 1011.5 mb weather: thunderstorm with rain; mist sky: a few clouds at 1500 feet broken cumulonimbus at 4000 feet broken clouds at 6500 feet overcast at 20000 feet sea-level pressure: 1011.4 mb 1-hour precipitation: 0.13in remarks: - Automated station (type 2) - peak wind 28kt from 290 degrees at 18:17 - wind shift at 18:12 - frequent lightning (intracloud,cloud-to-cloud,cloud-to-ground) - thunderstorm overhead and NW - TSB05RAB22 -N-E MOV NE METAR: METAR KEWR 111851Z VRB03G19KT 2SM R04R/3000VP6000FT TSRA BR FEW015 BKN040CB BKN065 OVC200 22/22 A2987 RMK AO2 PK WND 29028/1817 WSHFT 1812 TSB05RAB22 SLP114 FRQ LTGICCCCG TS OHD AND NW -N-E MOV NE P0013 T02270215
The metar library is
Copyright (c) 2004-2009, Tom Pollard All rights reserved.
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