Decoders of various weather reports.
The decoders are binary applications storing decoded reports in JSON files which are suitable for further machine processing.
Install the decoders by running:
cargo install rweather-decoder
``` [filip@fractal ~]$ decode-metar -h rweather-decoder 0.1.1 CLI decoder of METAR files
USAGE:
decode-metar [FLAGS] [OPTIONS]
FLAGS: -h, --help Prints help information -p, --pretty-print Enable pretty-printing of output JSON file -q, --quiet Quiet -V, --version Prints version information
OPTIONS:
-a, --anchor-time
ARGS:
Check for latest METAR reports at https://tgftp.nws.noaa.gov/data/observations/metar/cycles/.
We will download the file 16Z.TXT (cycle 16Z) and run the decode-metar tool as follows:
decode-metar -p 16Z.TXT 16Z.json
Decoded reports will be saved to the file 16Z.json and the option -p will enable pretty-printing of the output,
so it is more readable for humans (see below). If input reports are repeated, they will be deduplicated.
The output file contains an array of decoded reports. Here is an example for the LFBD airport (Bordeaux–Mérignac Airport):
json
{
"station_id": "LFBD",
"observation_time": {
"value_type": "date_time",
"value": "2023-05-12T16:00:00Z"
},
"is_corrected": false,
"is_automated": true,
"wind_from_direction": {
"value_type": "exact",
"value": 330.0,
"units": "degT"
},
"wind_from_direction_range": {
"value_type": "range",
"value": [
{
"value_type": "exact",
"value": 270.0
},
{
"value_type": "exact",
"value": 40.0
}
],
"units": "degT"
},
"wind_speed": {
"value_type": "exact",
"value": 16.0,
"units": "kt"
},
"wind_gust": {
"value_type": "exact",
"value": 32.0,
"units": "kt"
},
"prevailing_visibility": {
"value_type": "above",
"value": 10000.0,
"units": "m"
},
"minimum_visibility": {
"value_type": "exact",
"value": 600.0,
"units": "m"
},
"directional_visibilites": [],
"runway_visual_ranges": [
{
"runway": "23",
"visual_range": {
"value_type": "exact",
"value": 1100.0,
"units": "m"
},
"trend": "decreasing"
},
{
"runway": "05",
"visual_range": {
"value_type": "above",
"value": 2300.0,
"units": "m"
},
"trend": null
},
{
"runway": "29",
"visual_range": {
"value_type": "exact",
"value": 1800.0,
"units": "m"
},
"trend": "decreasing"
}
],
"present_weather": [
{
"intensity": "heavy",
"is_in_vicinity": false,
"descriptor": "thunderstorm",
"phenomena": [
"rain"
]
},
{
"intensity": "moderate",
"is_in_vicinity": false,
"descriptor": "patches",
"phenomena": [
"fog"
]
}
],
"clouds": [
{
"cover": "few",
"height": {
"value_type": "exact",
"value": 2400.0,
"units": "ft"
},
"cloud_type": null
},
{
"cover": "broken",
"height": {
"value_type": "exact",
"value": 3800.0,
"units": "ft"
},
"cloud_type": null
},
{
"cover": "broken",
"height": {
"value_type": "exact",
"value": 4400.0,
"units": "ft"
},
"cloud_type": null
},
{
"cover": null,
"height": null,
"cloud_type": "cumulonimbus"
}
],
"ceiling": {
"value_type": "exact",
"value": 3800.0,
"units": "ft"
},
"temperature": {
"value_type": "exact",
"value": 15.0,
"units": "degC"
},
"dew_point": {
"value_type": "exact",
"value": 11.0,
"units": "degC"
},
"pressure": {
"value_type": "exact",
"value": 1018.0,
"units": "hPa"
},
"recent_weather": [],
"report": "LFBD 121600Z AUTO 33016G32KT 270V040 9999 0600 R23/1100D R05/P2300 R29/1800D +TSRA BCFG FEW024/// BKN038/// BKN044/// ///CB 15/11 Q1018 TEMPO 3000 SHRA BKN010 SCT020CB BKN030TCU"
},
If you wish to decode reports from an another source, you can use the option -f plain which accepts input files with one METAR report per row.