# MET Norway Weather Forecast Scraper - Global Hourly Data (`ninhothedev/metno-weather-scraper`) Actor

$0.04/1K 🔥 MET Norway weather scraper! Hourly global forecasts — temperature, wind, rain & pressure. No key. JSON, CSV, Excel or API in seconds. Build weather apps & logistics planning ⚡

- **URL**: https://apify.com/ninhothedev/metno-weather-scraper.md
- **Developed by:** [ninhothedev](https://apify.com/ninhothedev) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.04 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## MET Norway Weather Forecast Scraper 🌦️

Scrape **free hourly weather forecasts for anywhere on Earth** from the MET Norway (Yr / Norwegian Meteorological Institute) public API — **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 — 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

| Field | Description |
|---|---|
| `location_name` | Your label, or `"lat,lon"` when you didn't supply one |
| `latitude`, `longitude`, `altitude` | Resolved coordinates and station altitude in metres |
| `time` | Forecast timestamp, ISO-8601 UTC |
| `air_temperature` | Temperature in °C |
| `air_pressure_hpa` | Air pressure at sea level in hPa |
| `relative_humidity` | Relative humidity in % |
| `wind_speed_ms` | Wind speed in m/s |
| `wind_direction_deg` | Wind origin direction in degrees |
| `cloud_cover_pct` | Cloud area fraction in % |
| `symbol_1h` / `symbol_6h` | Weather symbol codes (e.g. `cloudy`, `fair_day`, `rain`) |
| `precipitation_1h_mm` / `precipitation_6h_mm` | Precipitation in mm |
| `updated_at` | When MET Norway last refreshed the model run |
| `source`, `scraped_at` | Provenance metadata |

### Input

```json
{
  "mode": "forecast",
  "locations": ["52.52,13.405,Berlin", "59.91,10.75,Oslo"],
  "maxItems": 200
}
```

- **mode** — currently `forecast` (hourly rows per location).
- **locations** — `"lat,lon"` or `"lat,lon,Label"`. The label lands in `location_name`.
- **maxItems** — cap on total rows (default 200, max 2000). One location ≈ 90 rows.

### Sample output

```json
{
  "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** — a free, key-less backend for hourly forecast widgets and charts.
- **Logistics & fleet routing** — wind, ice and rain risk along delivery corridors before dispatch.
- **Agriculture & irrigation** — hourly precipitation and humidity for spraying, harvesting and watering windows.
- **Event planning** — rain probability and wind for outdoor venues, festivals and construction schedules.
- **Energy & renewables** — wind speed profiles for turbine yield estimates, cloud cover for solar output.
- **Research & backtesting** — 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 — 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 — 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.

### Related actors

- [Weather Scraper](https://apify.com/ninhothedev/weather-scraper)
- [NOAA Weather Alerts Scraper](https://apify.com/ninhothedev/noaa-weather-alerts-scraper)
- [Air Quality Scraper](https://apify.com/ninhothedev/air-quality-scraper)
- [OpenSky Flights Scraper](https://apify.com/ninhothedev/opensky-flights-scraper)

### 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](https://api.met.no/doc/TermsOfService) when using the data.

# Actor input Schema

## `mode` (type: `string`):

What to scrape. 'forecast' takes your lat/lon pairs and returns one row per hourly forecast step (up to ~10 days ahead) from the MET Norway locationforecast API.

## `locations` (type: `array`):

One entry per location. Use "lat,lon" (e.g. 52.52,13.405) or add your own label with "lat,lon,Label" (e.g. 52.52,13.405,Berlin). The label is written to the location\_name field; without one, "lat,lon" is used. Latitude must be between -90 and 90, longitude between -180 and 180. Coverage is global.

## `maxItems` (type: `integer`):

Hard cap on the number of forecast rows pushed to the dataset across all locations. One location returns roughly 90 hourly rows, so 200 covers about two locations in full. Increase it when scraping many locations.

## Actor input object example

```json
{
  "mode": "forecast",
  "locations": [
    "52.52,13.405",
    "59.91,10.75"
  ],
  "maxItems": 200
}
```

# Actor output Schema

## `results` (type: `string`):

Open the dataset preview for this run.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "locations": [
        "52.52,13.405",
        "59.91,10.75"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("ninhothedev/metno-weather-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "locations": [
        "52.52,13.405",
        "59.91,10.75",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("ninhothedev/metno-weather-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "locations": [
    "52.52,13.405",
    "59.91,10.75"
  ]
}' |
apify call ninhothedev/metno-weather-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,ninhothedev/metno-weather-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/5JDj0YXhkUshG1JIZ/builds/TEKDk2tGgIwGmSZB3/openapi.json