Solcast vs Vaisala 3TIER
Vaisala 3TIER is a long-running commercial source of global satellite-derived irradiance data, with a regional focus on North America. Compared to Vaisala 3TIER, Solcast is bankable, has lower uncertainty, and offers more data features, at similar price points.
About Vaisala 3TIER
3TIER by Vaisala is a US-based solar data company acquired by Vaisala in 2013, which specialises in wind and solar resource assessment, particularly in North America. The solar dataset was first developed in 2009.
Commercial and Technology
Vaisala and Solcast are both sources of global historical data and TMY, with similar price points. Unlike Vaisala, Solcast data is globally considered to be bankable, has an API with open documentation, and is free to test with instant access.
Data Features and Capabilities
Solcast |
Vaisala |
|
|---|---|---|
| Bankable? | ||
| Free trial with instant access and data download? | ||
| Download wait time | 1-3 seconds | 5 minutes to 24 hours |
| Comprehensive, global, independent validation | ||
| Finest time resolution of satellite-based irradiance | 5 minutes | 10 minutes |
| Real time data available? | ||
| Excludes older, less reliable satellites |
Source: Vaisala 3TIER Services Global Solar Dataset: Methodology and Validation
Inputs and Algorithms
Rather than focusing on the highest performance of a single dataset, Vaisala 3TIER maintains five separate datasets, based on a number of different models and cloud identification techniques. The Vaisala cloud model has a lower resolution than the Solcast model, based around a 3 km grid rather than Solcast’s 1-2km. Solcast has real-time data available, whereas Vaisala ends between 3 months ago and 1 day ago, depending on the product. The Vaisala coverage begins between 1997 and 1999, depending on location. Solcast only uses data from recent generation geostationary meteorological satellites (GMS). We do not use data prior to 2007 due to climate change and satellite data quality issues. This maximises data quality and validity, while still providing 15+ years of data history from which to sample for interannual variability.
Validation and Accuracy
Vaisala and Solcast are both globally validated, Vaisala at 196 sites and Solcast at 207 sites. In the case of Vaisala, there is a lack of independent validations, so we have to trust the results they provide. Also, Vaisala has not included DNI validation data, so we can’t compare that parameter. Solcast is more accurate and has lower uncertainty than Vaisala data. Validations show that Solcast outperforms Vaisala on all GHI measures, by a significant margin, across bias spread and RMSE.
Meta analysis of large global validation studies: GHI results
| Solcast | Vaisala | |||||
|---|---|---|---|---|---|---|
| Data Version | Solcast | V1.0 | V1.1 | V1.2 | V2.0 | V2.1 |
| Performed by | DNV | Vaisala | Vaisala | Vaisala | Vaisala | Vaisala |
| Year published | 2023 | 2019 | ||||
| No. of sites | 207 | 196 | ||||
| Mean Bias | +0.33% | -0.19% | +0.17% | +0.12% | +1.65% | +1.20% |
| Bias Std. Dev. | ±2.47% | ±4.37% | ±4.41% | ±4.43% | ±4.43% | ±4.09% |
| Mean nMAD (nMAE) | 10.33% | 13.63% | 13.62% | 13.61% | 12.96% | 12.79% |
| Mean nRMSD (nRMSE) | 15.99% | 20.78% | 20.78% | 20.77% | 20.15% | 19.94% |
Meta analysis for North America only: GHI results
| Solcast | Vaisala | |||||
|---|---|---|---|---|---|---|
| Data Version | Solcast | V1.0 | V1.1 | V1.2 | V2.0 | V2.1 |
| Performed by | DNV | Vaisala | Vaisala | Vaisala | Vaisala | Vaisala |
| Year published | 2023 | 2019 | ||||
| No. of sites | 38 | 78 | ||||
| Mean Bias | +0.77% | +0.22% | +0.53% | +0.58% | +2.44% | +1.88% |
| Bias Std. Dev. | ±1.40% | ±3.37% | ±3.36% | ±3.35% | ±4.74% | ±4.20% |
| Mean nMAD (nMAE) | 9.38% | 12.19% | 12.17% | 12.27% | 12.20% | 11.97% |
| Mean nRMSD (nRMSE) | 14.75% | 19.42% | 19.40% | 19.50% | 19.45% | 19.14% |
References
Vaisala. (2019). Vaisala Global Solar Dataset 2019 Release.