Nordic Hourly Weather Forecasts — SMHI

Independent tool; data from official Nordic public meteorological APIs. Not affiliated with SMHI or MET Norway.

Pull hourly weather forecasts for any Nordic coordinate straight from the official keyless meteorological institute API. Temperature, wind and gusts, precipitation, weather symbol, pressure, visibility and thunderstorm probability on every row — flat one-record-per-hour output ready for dashboards, spreadsheets and automation. No API key, no login, no browser; exports to CSV, Excel and JSON.

Source note (updated 2026-09-08): SMHI retired its pmp3g point-forecast API (all opendata-download-metfcst.smhi.se/api/category/pmp3g/... paths return 404 and the category is no longer listed on the SMHI Open Data portal). This actor now uses SMHI's snow1g version 1 point-forecast category as its primary source — despite the "snow" name it is the general point-forecast category, with full hourly series (81 steps: hourly for the first ~2 days, then ~3-hourly out to day 10). If SMHI fails for a point, the actor automatically falls back to MET Norway Locationforecast 2.0 (Yr, keyless with a custom User-Agent required by their terms), mapped onto the same output schema; every row records its origin in the source field.

Why Nordic Weather?

• 🌡️ One row per hour, ready to load — flat name, lat, lon, time, tempC, windMs, windGust, precipMm, symbol, pressure, visibilityKm, thunderstormPct, source records, zero post-processing.
• 🇸🇪 Brand-consistent SMHI data — primary source is SMHI's own open-data forecast API (snow1g v1); MET Norway is only a fallback.
• 🗺️ Any Nordic coordinates — Stockholm, Kiruna, Reykjavík, wherever; pass a list of points in a single run.
• 🔑 No API key — both SMHI Open Data and MET Norway Locationforecast are keyless (MET Norway only requires an identifying User-Agent, which the actor sets).
• 🕐 Hourly when it matters — 81 steps from SMHI: hourly for the first ~2 days, then ~3-hourly out to day 10 (240 rows max per point).
• 💰 Predictable cost — cap the bill with the built-in maxTotalChargeUsd budget; one cheap event per delivered row.

Use cases

Home-assistant and heat-pump automation · energy-price dashboards needing temperature drivers · agriculture and construction scheduling · travel planning across the Nordics · weather-triggered alerting and monitoring.

What data you get?

🏷️ Field	Description
📍 name / lat / lon	Point name (or coordinates if unnamed) and WGS84 position
⏰ time	Forecast valid time, ISO 8601 UTC
🌡️ tempC	Air temperature, °C
💨 windMs / windGust	Wind speed and gust, m/s
🌧️ precipMm	Deterministic mean precipitation amount, mm per step
⛅ symbol	Weather symbol, e.g. partly_cloudy, light_snowfall (WSymb2 text from SMHI; MET symbol code in fallback rows)
🔽 pressure	Air pressure at sea level, hPa
👁️ visibilityKm	Visibility, km (SMHI rows only; null in MET fallback rows)
⚡ thunderstormPct	Thunderstorm probability, % (SMHI rows only)
🛰️ source	smhi-snow1g-v1 or met-locationforecast-2.0

How to use

1. Add the actor to your Apify account and click Run.
2. Paste your points — e.g. {"lat": 59.33, "lon": 18.07, "name": "Stockholm"}.
3. Set hours (1–240) if the default 48 isn't right for you.
4. Export results as JSON, CSV or Excel.

Input

{
  "points": [
    { "lat": 59.33, "lon": 18.07, "name": "Stockholm" },
    { "lat": 67.86, "lon": 20.22, "name": "Kiruna" }
  ],
  "hours": 48
}

Field	Type	Description	Default
points	array	Coordinates to forecast: { lat, lon, name? } (decimal degrees; name defaults to the coordinates)	— (required)
hours	integer	Forecast rows per point, 1–240	48

Output

{
  "name": "Stockholm",
  "lat": 59.33,
  "lon": 18.07,
  "time": "2026-09-08T17:00:00Z",
  "tempC": 17.8,
  "windMs": 3.7,
  "windGust": 6.7,
  "precipMm": 0.0,
  "symbol": "cloudy",
  "pressure": 1001.8,
  "visibilityKm": 20.5,
  "thunderstormPct": 8,
  "source": "smhi-snow1g-v1"
}

Support

Open an issue in the repository or message the actor owner via Apify Console.