DWD Germany Weather Stations Scraper

DWD Germany Weather Stations Scraper

Scrape the complete catalog of DWD Germany weather stations, filtered by name, up to a million per run. Every station comes with its ID, coordinates, altitude, and operational dates. No API key or registration. Export to CSV, JSON, Excel, or XML.

The Deutscher Wetterdienst (DWD) publishes a public directory of its weather stations, but browsing it manually or stitching together API calls is slow. This scraper reads the full station list directly, lets you filter by station name (e.g. BERLIN, MUNICH), and returns each match in one fixed schema.

You get every station's metadata in a flat, analysis-ready dataset.

Who uses it	What they scrape DWD Germany Weather Stations for
Climate researchers	Build a spatial inventory of active and historical measurement points across Germany.
GIS analysts	Geocode DWD station locations for interpolation or mapping projects.
Data journalists	Audit station coverage and identify gaps in weather monitoring infrastructure.
Agritech developers	Find the nearest weather stations to farms for localized forecast models.

What it does

This Actor collects DWD Germany weather stations filtered by an optional name substring and returns each one as a flat row with its ID, name, coordinates, altitude, and operational dates.

• 🔍 Station name filter: supply a substring like BERLIN or MUNICH to collect only matching stations, case-insensitive.
• 📊 Full metadata: every row includes station ID, name, latitude, longitude, altitude, and the date range the station was active.
• ⚙️ Flexible volume: set a maximum from 1 to 1,000,000 stations per run to control dataset size.
• 📁 Multi-format export: download your results as CSV, JSON, Excel, or XML.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with DWD Germany Weather Stations data

🗺️ Map all active stations.

A GIS analyst runs the scraper without a name filter to get every station, then plots them by coordinates to visualize national coverage.

📈 Audit urban monitoring gaps.

A climate researcher filters by BERLIN, collects all stations in the capital region, and checks altitude and operational dates to assess data continuity.

🌾 Locate stations near farmland.

An agritech developer scrapes the full catalog, geocodes farm locations against station coordinates, and selects the three nearest stations for a hyper-local forecast model.

📰 Fact-check weather claims.

A data journalist filters by a specific station name mentioned in a press release, verifies its operational dates, and confirms whether it was active during the cited event.

Why choose this scraper

	What you get
Station ID and name	Unique identifier and human-readable label for every station
Coordinates and altitude	Latitude, longitude, and elevation in meters for spatial analysis
Operational dates	Start and end dates showing when each station was active

How it compares

No other Store actor targets DWD Germany Weather Stations the same way, so the honest comparison is with the alternatives teams actually weigh.

	DWD Germany Weather Stations Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When DWD Germany Weather Stations changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor with an optional station name substring and a maximum item count; the name filter runs as each station is read so only matches reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "maxItems": 10
}

A larger pull:

{
  "maxItems": 200
}

Pricing

Pay-per-result: $0.0085 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.85
1,000 results	$8.50
10,000 results	$85.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the DWD Germany Weather Stations Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to DWD Germany Weather Stations through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/dwd-germany-weather-stations-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Your station name filter may be too specific or contain a typo. Try a shorter substring, like BERLIN instead of BERLIN-TEMPELHOF, or remove the filter entirely to see all stations.

The run finishes but the dataset is empty.

Check that maxItems is set to at least 1. If you used a name filter, verify the spelling. DWD station names use German spellings (e.g. MÜNCHEN, not MUNICH).

I got fewer results than my maxItems setting.

This is expected when the total number of stations matching your filter is smaller than maxItems. Remove the name filter to confirm the full catalog size.

The coordinates look wrong for my station.

DWD coordinates are in decimal degrees (WGS84). Verify you are interpreting them correctly. If a station appears misplaced, check its operational dates; it may have moved and a newer entry exists.

Can I get data for stations outside Germany?

The DWD catalog primarily covers stations within Germany. A few border stations may appear, but this Actor is not designed for global weather station data.

FAQ

Question	Answer
What data does this scraper return?	Each row contains the station ID, station name, latitude, longitude, altitude in meters, and the date range (start and end) when the station was operational.
Can I filter by city or region?	Yes. The station name filter accepts any substring, so BERLIN returns all stations with Berlin in the name. The filter is case-insensitive.
How many stations can I collect in one run?	You set the maximum with the maxItems field, from 1 up to 1,000,000. The full DWD catalog contains several thousand stations.
Do I need a DWD API key?	No. This Actor reads the public station directory directly. No registration, API key, or authentication is required.
Is the data current?	The Actor fetches the live DWD station list on each run, so you always get the latest published catalog.
What export formats are supported?	You can download your dataset as CSV, JSON, Excel, or XML from the Apify dataset tab.
Can I get historical weather measurements?	No. This Actor collects station metadata only (location, altitude, operational dates). It does not return temperature, precipitation, or other measurement values.
How do I find stations near a specific coordinate?	Collect the full catalog, then filter by distance in your own analysis tool using the latitude and longitude fields returned for each station.
What does the operational date range mean?	It shows the period when the station was active. A missing end date typically means the station is still operational.
Can I run this on a schedule?	Yes. Set up an Apify schedule to run the Actor daily or weekly and track changes in the DWD station catalog over time.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Deutscher Wetterdienst. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.