Check the Setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
Global point weather forecasts for building location-specific planning tools outside the U.S. National Weather Service footprint.
Report a ProblemFrom Source to Product Signal
Locationforecast returns JSON weather for any latitude and longitude. Start with the compact product for one coordinate. Identify the client in User-Agent or MET Norway returns 403. Forecasts change, and this product is not an official warning service.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
import pandas as pd
import requests
response = requests.get(
"https://api.met.no/weatherapi/locationforecast/2.0/compact",
params={"lat": 59.91, "lon": 10.75},
headers={
"User-Agent": (
"TrilemmaDataCatalogExample/1.0 "
"(https://data.trilemma.foundation)"
)
},
timeout=30,
)
response.raise_for_status()
timeseries = pd.json_normalize(
response.json()["properties"]["timeseries"]
)
print(
timeseries.filter(
regex="time|air_temperature|wind_speed|precipitation_amount"
).head()
)Test a Useful Signal
Test whether Locationforecast can power a bounded local planning card.
Norwegian Meteorological Institute is a government source. Last verified 2026-08-18. Temporal coverage: current forecasts out to about nine days.