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Typical Meteorological Year
Download a statistically representative “typical year” file built from 15 + years of satellite data for long-term yield modelling.
solcast vs PVGIS Comparison
Solcast is independently validated as the lowest uncertainty solar resource dataset
Solcast vs PVGIS
PVGIS (Photovoltaic Geographical Information System) is a widely used platform for solar resource data and PV performance simulations. However, PVGIS relies on multiple datasets for irradiance and weather data, which vary by region and quality. This page explains PVGIS’s data sources, their limitations, and how Solcast compares as a global, bankable alternative.
PVGIS data sources
PVGIS does not use a single global dataset. Instead, it combines several sources:
- SARAH-3 (Surface Solar Radiation Data Set – Heliosat)
- Produced by CMSAF/EUMETSAT/DWD
- Coverage: Europe, Africa, Middle East
- Resolution: ~5 km
- Time range: 1983–2020 (historical only)
- Produced by NREL
- Coverage: Americas
- Resolution: ~4 km
- Historical dataset (1998 onward)
- Learn more: [Visit our NSRDB comparison page]
- Produced by ECMWF (Copernicus Climate Change Service)
- Coverage: Asia and other regions
- Resolution: ~30 km
- Historical weather dataset (not high-resolution irradiance)
Data Features and Capabilities
Solcast | PVGIS | |
|---|---|---|
Free trial with instant access and data download? | | |
Real time data available? | | |
Comprehensive, global, independent validation | | |
Satellite based estimation | | |
Coverage | Global | SARAH-3: Europe, Africa, Middle East |
Resolution of satellite data used | 1-2 km | 4-30 km |
15+ years of satellite data at full temporal resolution | | |
| |
Source: PVGIS data sources & calculation methods - The Joint Research Centre: EU Science Hub
Inputs and Algorithms
The PVGIS SARAH and Solcast methodology is relatively similar. Both are semi-empirical and are satellite-derived. Both rely on validated, published models to build a clear sky model, and use proprietary cloud detection. The PVGIS-SARAH cloud model has a lower resolution, based around a 5 km grid, compared to Solcast's upres 90 metre resolution. The cloud detection algorithm only processes one image per hour, instead of the native satellite time step. This large time step between satellite images can provide misleading information on cloud formation, tracking, and opacity. Solcast has real-time data available, whereas PVGIS SARAH ends in 2020.
Validation and Accuracy
Meta analysis of Europe and Africa validation results: GHI results
Solcast | PVGIS (SARAH 2.1) | PVGIS (SARAH 2.1) | |
|---|---|---|---|
Performed by | DNV | IEA PVPS | Yang & Bright 2020 |
Year published | 2023 | 2023 | 2020 |
No. of sites | 73 | 54 | 20 |
Mean Bias | +0.26% | +0.45% | +0.76% |
Bias Std. Dev. | ±2.17% | ±6.60% | ±12.44% |
Mean nMAD (nMAE) | 10.92% | 11.04% | Not Published |
Mean nRMSD (nRMSE) | 16.97% | 16.88% | 28.24% |
Meta analysis of Europe and Africa validation results: DNI results
Solcast | PVGIS (SARAH 2.1) | |
|---|---|---|
Performed by | DNV | IEA PVPS |
Year published | 2023 | 2023 |
No. of sites | 48 | 54 |
Mean Bias | +0.10% | +1.77% |
Bias Std. Dev. | ±5.33% | ±13.19% |
Mean nMAD (nMAE) | 18.71% | 24.96% |
Mean nRMSD (nRMSE) | 29.48% | 35.23% |
References
EU Science Hub (2023). PVGIS data sources & calculation methods: Validation of the satellite-based solar radiation data
Yang, D., 2018. A correct validation of the national solar radiation data base (NSRDB). Renewable and Sustainable Energy Reviews, 97, pp.152-155.
Yang, D. and Bright, J.M., 2020. Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years. Solar Energy, 210, pp.3-19.
Forstinger, A., et al. (2023). Worldwide benchmark of modelled solar irradiance data (2023 PVPS Task 16): Solar resource for high penetration and large-scale applications. ResearchGate.
Cuevas-Agulló, E., et al. (2023). A new global high-resolution solar resource dataset. Zenodo.
