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.
Data product · Listing updated 11 Nov 2026
Worldwide, no country restrictions stated.
Forecasts updated hourly; median API response about 120 ms
40+ variables for any point on Earth, up to a 15-day horizon
Startups, Small and medium businesses, Mid-market, Enterprises
National weather service models, reanalysis datasets and quality-controlled surface stations
Hourly multi-model blend with machine-learning post-processing calibrated on station observations
A single API for past, present and future weather anywhere on Earth, designed for developers and data teams.
Forecasts blend several global and regional numerical weather prediction models from national meteorological services, then apply machine-learning post-processing trained on about 60,000 quality-controlled surface stations. Effective resolution ranges from about 1 km in Europe and North America to 9 km elsewhere. Historical data combine ERA5 reanalysis with station corrections and are flagged where station density is low. Forecast skill by region and lead time is published in our documentation; day-one temperature error averages about 1.2 °C across European stations. A 14-day free trial includes all variables.
13 fields as documented by Alpenglow Weather Systems.
| Field | Type | Description | Example |
|---|---|---|---|
| latitude | number | Query latitude, WGS 84 | — |
| longitude | number | Query longitude, WGS 84 | — |
| timestamp_utc | datetime | Valid time, UTC | — |
| temperature_2m_c | number | Air temperature at 2 m, °C | — |
| precipitation_mm | number | Precipitation in the hour, mm | — |
| snowfall_cm | number | Snowfall in the hour, cm | — |
| wind_speed_10m_ms | number | Wind speed at 10 m, m/s | — |
| wind_gust_ms | number | Maximum gust in the hour, m/s | — |
| relative_humidity_pct | number | Relative humidity at 2 m | — |
| cloud_cover_pct | number | Total cloud cover | — |
| shortwave_radiation_wm2 | number | Global horizontal irradiance, W/m² | — |
| weather_code | integer | WMO weather interpretation code | — |
| model_run | datetime | Issue time of the forecast | — |
Real rows from the provider's sample file. Personal data is masked before anything is shown.
| latitudestring | longitudestring | timestamp_utcstring | temperature_2m_cstring | precipitation_mmstring | wind_speed_10m_msstring | cloud_cover_pctstring | model_runstring |
|---|---|---|---|---|---|---|---|
| 47.3769 | 8.5417 | 2026-11-11T06:00:00Z | 3.4 | 0.0 | 2.1 | 88 | 2026-11-11T03:00:00Z |
| 47.3769 | 8.5417 | 2026-11-11T07:00:00Z | 3.9 | 0.2 | 2.6 | 93 | 2026-11-11T03:00:00Z |
| 40.7128 | -74.0060 | 2026-11-11T12:00:00Z | 9.8 | 0.0 | 5.4 | 35 | 2026-11-11T09:00:00Z |
Prices in USD, as published by Alpenglow Weather Systems
Starter: 100,000 API calls a month
Business: 1 million calls a month, history included
Pro: 10 million calls a month, bulk history and SLA
Converted amounts use DataStoa display rates and are approximate. Alpenglow Weather Systems quotes the final price, taxes and terms.
Request detailed pricingWorldwide coverage.
Time coverage: 1950 to present.
Provider-reported
Latency: Forecasts updated hourly; median API response about 120 ms
DataStoa has not audited these figures. Ask the provider how they are measured, or test them on a sample.
The licence is agreed directly between you and Alpenglow Weather Systems. This summary is provider-reported; the linked terms prevail.
Not listed: AI / ML model training, redistribution allowed, marketing and outreach, research use. Ask Alpenglow Weather Systems if you need any of these.
Weather, climate risk and air quality data for any location on Earth
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.
Also available on: Snowflake Marketplace, AWS Data Exchange, Databricks Marketplace, Microsoft Azure
What buyers say about Alpenglow Weather Systems. Reviews cover the provider, not only this listing.
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