The world's most accurate historical irradiance and weather data. 20+ weather parameters tailored to solar energy applications, from 2007 to 7 days ago. Available in JSON via synchronous API, or instant CSV web download.
Source: Solcast API, Solar Assets from Global Solar Power Tracker, Global Energy Monitor, Bankability Site Data from DNV
*Private site locations are approximated to another location in the same region and climate zone
You're in good company
CLOUD AND IRRADIANCE TRACKING
Tracking the world's clouds in the finest detail
Designed for Solar, from the ground up. Never rely on generic weather model data again. Solcast's real time and forecast data tracks and forecasts real clouds at a resolution of 1-2km and 5 minutes. Our irradiance data and PV power data is updated every 5 to 15 minutes, downscaled to 90 metre resolution. Aerosol and albedo effects are explicitly treated.
WEATHER DATA
Full suite of high resolution weather data
Other weather data from leading reanalysis datasets completes the full suite of 20+ parameters available at 5, 10, 15, 30 and 60 minute resolutions. Coverage from 2007 to 7 days ago.
Validation
We provide upfront and clear accuracy and validation information
Be confident that our data is fit for purpose.
Explore up to date, independent validation statistics at locations similar to your area of interest.
Data Access
Get data via synchronous API or instant CSV download
Synchronous API returns JSON data in 1-5 seconds per request, and requests can be submitted in parrallel up to your account rate limit.
Web downloads for up to 20 locations at at time. Choose from multiple file types including CSV, ready to use in your favourite simulation software.
Historical Time Series Data Specifications
Geographic coverage | Global (note: far ocean and polar regions are coarser resolution) |
Temporal coverage | January 2007 to 7 days ago (for past 7 days to present time and forecasts, use our Live and Forecast data) |
Temporal resolution | 5, 10, 15, 30 & 60 minutes (period-mean values) |
Spatial resolution | 90 meters (irradiance, PV power, snow soiling, cloud parameters, and other parameters across all regions) |
Data parameters | The following data parameters are available.
^ Clear-sky scenarios also available for these parameters |
Data access | API or Web download |
Download wait time | API: synchronous requests. Web download: seconds. |
File formats | CSV, JSON, PVsyst, SAM, TMY3 |
Data formats | Solcast standard, PVsyst (60 minute only) |
Time zone | UTC, longitudinal, or user-specified fixed offset. |
Historic Data Products
Time Series
The complete suite of irradiance and weather data required for effective monitoring, operation, and forecasting at your large-scale solar farm.
Typical Meteorological Year (TMY)
The complete suite of irradiance and weather data required for effective monitoring, operation, and forecasting at your large-scale solar farm
Commonly Asked Questions about Historical Irradiance Data
Historical solar irradiance data is the recorded measurements of solar energy received per unit area over a period of time. Solcast’s historical data covers from 2007 to 7 days ago. Historical irradiance data will include several irradiance parameters, including Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), Diffuse Horizontal Irradiance (DHI), and Global Tilted Irradiance (GTI). It is essential for analyzing long-term solar energy trends and planning future solar projects’ feasibility and performance.
Solcast's historical time series data is generated through a combination of satellite observations and weather models. These inputs are then calibrated using advanced modeling algorithms to create high-resolution solar data that presents accuracy over time. Learn more about Solcast’s irradiance methodology here.
Average daily solar irradiance is the mean value of solar radiation received per unit area each day, measured in kWh/m²/day. This is typically averaged over a longer period such as a month or year. This metric is useful for daily performance analysis, energy production estimates, and optimising solar panel settings.
Historical time series is crucial for forecasting because it provides a baseline of past patterns and trends, including seasonal variations, deviations, and anomalies. By using Solcast's bankable historical data, you can develop predictive models that accurately estimate solar irradiance which is beneficial for grid management, energy trading, and asset operational planning.
