Weather, climate risk and air quality data for any location on Earth
4.4(3)4 published listings.
Hourly forecasts to 15 days and history back to 1950 for any latitude and longitude via REST API: temperature, precipitation, wind, humidity, solar radiation and more.
Asset-level flood, extreme heat, wildfire, windstorm and drought scores for any address or coordinate, today and under SSP1-2.6, SSP2-4.5 and SSP5-8.5 to 2100.
Hourly pollutant concentrations and air quality indices on a 1 km European grid plus 3,000 station series, with four-day forecasts and history from 2015.
Daily heating and cooling degree days, weather anomalies and ready-made demand features by store, postcode or region, for retailers, utilities and gas traders.
Alpenglow Weather Systems runs a global weather API, physical climate risk models and a European air-quality service from Zurich. Its forecasts blend national weather service models with machine-learning post-processing, and every historical series is backed by station observations and reanalysis.
What the provider licenses its data for, and what it does not allow.
Energy and retail demand forecasting, logistics planning, insurance underwriting, climate risk disclosure and agriculture.
Replacing official national weather warnings for life-safety decisions.
DataStoa's acceptable use policy applies on top: no re-identification, discrimination, surveillance or sanctioned uses.
Provider-reported. Ask for certificates or a data processing agreement before you sign.
Other places you can receive this provider's data, useful if your team already buys through a cloud marketplace.
Buyers rate four things: data quality, volume and coverage, value for money and service.
from 3 reviews
Adding degree days and the weather-driven demand features to our model noticeably reduced forecast error for heat-sensitive products. Setup took a day since site coordinates were all they needed.
Lukas W., Demand planning manager, Beverage distributor
Each hazard score came with the underlying model resolution, the scenario and the time horizon, which let our actuaries decide where to rely on it. Subsidence scores are less granular than flood. Their scientists joined two calls to explain the method.
Isabel T., Catastrophe modeller, Specialty insurer
We started on the Starter tier and moved to Business when we launched. Response times are consistently fast, the history endpoint uses the same schema as forecasts, and the docs have examples in three languages.
Noah F., CTO, Agritech start-up