Oikolab

About Oikolab

Oikolab provides an API for accessing historical, current, and forecast weather and climate data, aggregated from multiple global and regional numerical weather prediction, reanalysis, and ensemble models. Data can be downloaded in JSON, CSV, or NetCDF format, with historical coverage from ERA5 reanalysis data spanning 1940 to present (updated daily with a 5-day delay), alongside higher-resolution land-only data from ERA5-Land.

The service aggregates output from numerous forecast systems, including GFS, GEFS, ICON, GDPS, GEPS, and IFS-Open for global numerical weather prediction and ensemble forecasting, AIFS for AI-based forecasting, and CFS for seasonal and sub-seasonal forecasts, as well as regional datasets covering North America (HRRR, NAM-CONUS, NBM, HRDPS) and Europe (ICON-EU, ICON-D2), plus an air quality dataset (SILAM). Each dataset is accessed through a model parameter in the API.

The product is aimed at data scientists, analysts, climate and data experts across industries, and academic researchers who need processed historical or forecast weather data without performing their own data cleaning and preparation. Oikolab's data has been cited in published research papers covering topics such as geothermal heat systems, wildlife spatial ecology, decarbonized power-gas infrastructure planning, building thermal zoning, heat pump energy potential, cool pavement climate mitigation, electricity demand modeling, and microgrid forecasting.

Key features

• Historical weather and climate data from 1940 to present via ERA5 reanalysis
• High-resolution 9km land surface data via ERA5-Land (1950-present)
• Global NWP and ensemble forecasts (GFS, GEFS, ICON, GDPS, GEPS, IFS-Open) out to 35 days
• AI-based forecasting via ECMWF's AIFS model at 0.25 degree resolution
• Seasonal forecasts up to 9 months ahead via CFS
• Data downloadable in JSON, CSV, or NetCDF format

Frequently asked questions