Time series data is a historical record of weather data for a specified location. Time series of solar radiation and meteorological variables are used during the simulation of energy production of solar power plants to understand expected year-to-year variability, seasonal or intra-day energy generation profile, and for calculation of energy estimates for P90 or other probabilistic scenarios. Recent time series data can be used to understanding how much solar radiation was reaching a site over previous months, to determine how much energy your solar panels should have generated, or to calibrate equipment, or to update energy models.
Solcast offers two variants of Time Series: Basic (hourly granularity only) and Extended (all time granularities from hourly down to 5 minute). See details on the Solcast pricing page
Time Series Data Specifications
|Time granularity||Basic time series||Extended time series||Available on request|
|60 minute||5, 10, 15, 30 or 60 minute, native satellite||1 minute|
|Coverage||Global, except for ocean and polar regions|
|Spatial resolution of satellite data||1-2 km|
|Timespan of database||January 2007 to 7 days ago (for past 7 days to present time, or forecasts, use our Live and Forecast data)|
|Files provided|| |
|Time zone|| |
|Database update frequency||Daily (Live and Forecast data is also available)|
|Access method||Data can be ordered and downloaded via the Solcast API Toolkit|
|Download wait time||Typically 1 to 9 minutes|
Regarding time granularity, Native satellite times are 6-minute average estimates centered on the time of the satellite scan over the actual location.
Regular period averages (at 5, 10, 15, 30 or 60 minutes) are interpolations and averages derived from the native data. The shorter periods, particularly 5 minutes, may tend to result in estimates that are minimise error, but are smoother compared to corresponding measurements, due to interpolation from the less granular satellite scans. Contact us if you need synthetically generated 1 or 5 minute irradiance data with realistic cloud variability.