Vaisala / 3TIER

Compare Solcast historical and TMY products to Vaisala 3TIER

Solcast’s historical solar irradiance database was released in 2019, with a mission to provide highly accurate, validated data to the solar development community.

Using a proprietary cloud detection and identification model, utilising the new fleet of third-generation geostationary satellites and refined over a four-year period, we’ve been able to produce the best performing solar database available. We’ve always thought developers should focus on planning and assessment, not wrestling with data, waiting days to sign up and receive pricing, and paying through the teeth for it. You shouldn’t have to work for your data, it should work for you.

The Vaisala / 3Tier database has been a widely-used meteo data source since its launch in 2009. The Vaisala is generally perceived to have higher errors than Solargis, and similar costs. Compared to the Vaisala dataset, you can expect to find Solcast data more accurate, easier to obtain and trial, and a similar or cheaper price.

Summary

  Solcast Vaisala
Free trial with instant access and data download?
Price point $$ $$
Download wait time 1-9 minutes Up to 24 hours
Mean Bias Error (GHI) 0.0% 3.1%
Bias Deviation (GHI) ± 2.0% ± 4.9%
90% of sites have bias (GHI) smaller than ± 2.5% Not published
Mean RMSE (GHI) 16.5% 18.5%
Comprehensive, global, independent validation
Validation Sites 46 196
Satellite based estimation
Global Coverage
Resolution of satellite data used 1-2 km 3 km
10+ years of satellite data at full temporal resolution
Ignores older, less reliable satellites

Source: Vaisala 3TIER Services Global Solar Dataset: Methodology and Validation

Accuracy & Validation

Both Solcast & Vaisala’s models have been independently validated using multiple locations globally. Solcast’s model has been compared with BSRN ground station measurements, available in the public domain. You can request a copy of our validation data, see accuracy and validation.

Vaisala offers 5 different algorithms for producing their data, based on a number of different clear sky models and cloud identification techniques. To be fair to Vaisala, we’ve used their most recent model, Vaisala 2.1, to compare accuracy with Solcast hourly mean values. A summary of Solcast’s and Vaisala’s hour GHI validation results are given below.

  Solcast Vaisala
Mean Bias Error 0.0% 3.1%
Bias Error Standard Deviation ± 2.0% ± 4.9%
90% of sites have bias smaller than ± 2.5% Not published
Mean RMSE 16.5% 18.5%

Understanding bias helps to understand a possible error of the long-term estimate. Bias variability and RMSE are important for estimating the accuracy of energy simulations and operational calculations. It is clear that the Solcast model decisively outperforms the Vaisala database in all metrics.

The Solcast model is symmetrically centred with an average bias error of zero, while the Vaisala model has a mean positive bias of 3.1%. The Solcast dataset shows significantly less variability, with a bias deviation less than half of Vaisala’s. RMSE, a measure of the differences between the values predicted by the Solcast model and the values actually observed, shows stronger model performance. With much less variability in the dataset, developers can trust the accuracy of their energy simulations and operational calculations.

Solcast v Vaisala Bias Distribution

Vaisala_bias_artv3.PNG

You can find more details on the Solcast dataset on the accuracy and validation page.

The Solcast model, having only recently been released, has not been as extensively validated as the Vaisala data. If you do your own validation, we’d love it if you can send us your results.

  Solcast Vaisala
Comprehensive, global, independent validation
Validation sites 50 196

Model Inputs

The Solcast methodology is semi-empirical and satellite-derived. We begin using validated, published models that offer excellent performance to build clear sky models. We combine this with the ‘secret sauce’, our in-house methods for detecting and tracking clouds. This lets us model the amount and type of solar radiation reaching any particular 1-2 km2 grid cell. For more details see inputs and algorithms.

The Vaisala methodology is similar. It is semi-empirical and satellite-derived, relying on validated, published models to build a clear sky model, and uses a proprietary cloud detection model. The Vaisala cloud model has a lower resolution than the Solcast model, based around a 3 km2 grid.

Solcast only uses data from recent generation geostationary meteorological satellites (GMS). For this reason, we do not use data prior to 2007. Prior to this time, we find that too many of the GMS satellites have significant data quality problems including geolocation, poor temporal sampling frequency, and unreliable, bad or drifting data signatures. This ensures our entire database is based on data of the highest possible resolution, whilst still containing 12+ years of data history from which to understand the interannual variability. Users can be sure our accuracy and validation statistics apply to all our data, not just the most recent half of it.

We don’t believe in using data from older satellites. With longer refresh rates and larger spatial resolutions, it’s just not possible to produce bankable solar radiation assessments with the certainty demanded by the solar community. We’re firm of the opinion that bad data in, bad data out.

Vaisala has an extensive database, compiled using high-resolution new satellites, and lower-resolution, pre-21st century satellites.

  Solcast Vaisala
Resolution of satellite data 1-2 km 3 km
Use of 10+ years of satellite data at full temporal resolution
Ignores older, less reliable satellites

Data Availability

Solcast and Vaisala both offer near-global coverage (latitudes higher than 60-70 degrees are not effectively covered by geostationary satellite images). Solcast offers data from as recent as last week. Data parameters available are shown below.

  Solcast Vaisala
Most recent data available 7 days ago Last Month
Global Horizontal Irradiance (GHI)
Direct Normal Irradiance (DNI)
Diffuse Horizontal Irradiance (DHI)
Air Temperature (TEMP)
Wind Speed (WS)
Wind Direction (WD)
Atmospheric Pressure (AP)
Precipitable Water (PWAT)
Relative Humidity (RH)
Dewpoint (DWPT)
Snow Depth (SWDE)
Cloud Opacity

Solcast strives to make our data easy to use, immediately. Our data is usually available within 1 to 9 minutes of ordering. Our data is available in the following ready-to-import formats.

  Solcast Vaisala
Download Wait Time 1-9 minutes Up to 24 hours
CSV
TMY3
TMY2
PVsyst (CSV)
SAM (CSV)

Pricing

Solcast offers the best value for money and much lower risk for developers, operators and investors into solar power plants. Solcast is cheaper than Vaisala for evaluating just a single site and similar in price if your company conducts scores of assessments a year. We also offer the ability to purchase specific years of a time series, so you don’t have to pay for what you don’t need. See details on the historic & TMY data pricing page.

TMY Time Series TMY & Time Series
Solcast Vaisala / 3TIER Solcast Vaisala / 3TIER Solcast Vaisala / 3TIER
Single site $400 N/A $400 (full record), or $100 per year N/A $800 $1000
25 sites $120 $100 $120 (full record), or $30 per year $100 $240 $200
100 sites $96 $50 $96 (full record), or $24 per year $50 $192 $100

In addition to commercial pricing, Solcast offers free access to data for researchers. Solcast also provides every account registered with some initial credit, so users can get the feel of how our system works, and get your hands on some data quickly - Try it now.

  Solcast Vaisala
Free data to researchers
Free credit to every new account

Test now, free

Get free historical data credits when you sign up, so you can try our data for yourself. You can download data automatically within around 1 to 9 minutes of submitting your request.