MET Norway Weather Forecast Scraper - Global Hourly Data avatar

MET Norway Weather Forecast Scraper - Global Hourly Data

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from $0.04 / 1,000 results

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MET Norway Weather Forecast Scraper - Global Hourly Data

MET Norway Weather Forecast Scraper - Global Hourly Data

$0.04/1K πŸ”₯ MET Norway weather scraper! Hourly global forecasts β€” temperature, wind, rain & pressure. No key. JSON, CSV, Excel or API in seconds. Build weather apps & logistics planning ⚑

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from $0.04 / 1,000 results

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ninhothedev

ninhothedev

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5 days ago

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MET Norway Weather Forecast Scraper 🌦️

Scrape free hourly weather forecasts for anywhere on Earth from the MET Norway (Yr / Norwegian Meteorological Institute) public API β€” no API key, no account, no rate-limit dashboard. Feed in latitude/longitude pairs and get up to ~10 days of hourly rows with temperature, wind speed and direction, precipitation, air pressure, humidity, cloud cover and weather symbols, exportable as JSON, CSV, Excel or via API.

Why this actor

  • No API key. MET Norway's locationforecast/2.0 is fully open. Zero signup friction.
  • Global coverage. Any coordinate on the planet, land or sea.
  • ~90 hourly rows per location, one dataset item per forecast step β€” instantly chartable.
  • Clean flat schema. No nested JSON to unpack; every field is a plain column.
  • Cheap. Roughly $0.5 per 1,000 rows in Apify platform usage.
  • Compliant User-Agent. The actor sends the descriptive, contact-carrying User-Agent MET Norway requires (see below).

What you get

FieldDescription
location_nameYour label, or "lat,lon" when you didn't supply one
latitude, longitude, altitudeResolved coordinates and station altitude in metres
timeForecast timestamp, ISO-8601 UTC
air_temperatureTemperature in Β°C
air_pressure_hpaAir pressure at sea level in hPa
relative_humidityRelative humidity in %
wind_speed_msWind speed in m/s
wind_direction_degWind origin direction in degrees
cloud_cover_pctCloud area fraction in %
symbol_1h / symbol_6hWeather symbol codes (e.g. cloudy, fair_day, rain)
precipitation_1h_mm / precipitation_6h_mmPrecipitation in mm
updated_atWhen MET Norway last refreshed the model run
source, scraped_atProvenance metadata

Input

{
"mode": "forecast",
"locations": ["52.52,13.405,Berlin", "59.91,10.75,Oslo"],
"maxItems": 200
}
  • mode β€” currently forecast (hourly rows per location).
  • locations β€” "lat,lon" or "lat,lon,Label". The label lands in location_name.
  • maxItems β€” cap on total rows (default 200, max 2000). One location β‰ˆ 90 rows.

Sample output

{
"location_name": "Berlin",
"latitude": 52.52,
"longitude": 13.405,
"altitude": 37.0,
"time": "2026-07-28T11:00:00Z",
"air_temperature": 21.3,
"air_pressure_hpa": 1021.6,
"relative_humidity": 45.3,
"wind_speed_ms": 4.8,
"wind_direction_deg": 277.3,
"cloud_cover_pct": 96.9,
"symbol_1h": "cloudy",
"precipitation_1h_mm": 0.0,
"symbol_6h": "partlycloudy_day",
"precipitation_6h_mm": 0.1,
"updated_at": "2026-07-28T11:18:37Z",
"source": "met.no",
"scraped_at": "2026-07-28T11:52:04Z"
}

Use cases

  • Weather apps & dashboards β€” a free, key-less backend for hourly forecast widgets and charts.
  • Logistics & fleet routing β€” wind, ice and rain risk along delivery corridors before dispatch.
  • Agriculture & irrigation β€” hourly precipitation and humidity for spraying, harvesting and watering windows.
  • Event planning β€” rain probability and wind for outdoor venues, festivals and construction schedules.
  • Energy & renewables β€” wind speed profiles for turbine yield estimates, cloud cover for solar output.
  • Research & backtesting β€” build a longitudinal forecast archive by scheduling daily runs.

The required User-Agent (important)

MET Norway's terms of service require every client to send a descriptive User-Agent header containing contact information. Requests with a generic or missing UA are answered with HTTP 403. This actor sends a compliant identifying UA on both its transports (curl_cffi with a Chrome TLS fingerprint, and a stdlib urllib fallback), so you never have to think about it. Please keep runs reasonable β€” MET Norway funds this service publicly.

Data is licensed under CC BY 4.0 / NLOD by the Norwegian Meteorological Institute; credit MET Norway when you republish it.

Tips

  • Schedule a daily run to build your own forecast-accuracy archive.
  • Raise maxItems when scraping more than two locations β€” the cap is shared across all of them.
  • Use the overview dataset view for a quick location / time / temperature / symbol table.
  • Symbol codes map 1:1 to Yr's public weather icon set, so you can render them directly.

Disclaimer

This actor collects public, non-personal meteorological data only. It is not affiliated with or endorsed by the Norwegian Meteorological Institute. Respect MET Norway's terms of service when using the data.