Solcast is independently validated as the lowest uncertainty solar resource dataset.
Compared with SolarAnywhere, Solcast has lower uncertainty, is faster to access, and is cheaper and easier to use.
Solcast’s mission is to bring you bankable data of top quality, faster, cheaper, and easier, and we think our database does just that. You’ll find Solcast data to have very low uncertainty, very easy to obtain and trial, global coverage, and a much lower price than SolarAnywhere.
|Satellite based estimation||✔||✔|
|Ignores older, less reliable satellites||✔||✘|
|Free trial with instant access and data download||✔||✘|
|Mean bias error (GHI)||-0.20||-0.34|
|Bias standard deviation (GHI)||0.99||1.64|
Source: SolarAnywhere Data Validation. Error statistics for Solcast are from North and South America only, and vary from Solcast global dataset validaiton
Accuracy & Validation
Both Solcast’s & SolarAnywhere’s models have been independently validated using multiple locations. Solcast’s model has been validated against the high-quality, well-maintained measurements from BSRN ground stations, available in the public domain. (You can request a copy of our validation data, see accuracy and validation). SolarAnywhere has validated against the same BSRN sites where the dataset has coverage.
An objective, like-for-like comparison can be made between the two datasets using validation results derived from the same BSRN ground station measurements. A summary of Solcast’s and SolarAnywhere’s hourly mean GHI validation results for the Americas region is given below. Note SolarAnywhere statistics cover a 20 year period, while Solcast covers a 13 year period.
|Mean Bias Error (%)||Mean Average Error (%)||RMSE (%)|
|Site Name||BSRN code||Country||Solcast||SolarAnywhere||Solcast||SolarAnywhere||Solcast||SolarAnywhere|
|São Martinho da Serra||SMS||Brazil||-0.88||-1.1||8.82||18.1||14.57||28.8|
|Rock Springs/Penn State||PSU||USA||0.02||0.3||13.20||14.3||20.40||21.7|
|Summary statistics of BSRN sample||Solcast||SolarAnywhere|
|Sample mean bias error||-0.20||-0.34|
|Sample bias deviation||0.99||1.64|
|Sample mean average error||10.73||14.10|
|Sample mean RMSE||17.23||22.08|
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. In this sample, both models show an average of biases of near zero. Both models are symmetrically centered.
The Solcast data shows significantly less variability than SolarAnywhere. A lower mean bias deviation of ±0.99% v ±1.64% means Solcast data is represented by a narrower probability distribution. This means, on average, Solcast data is more likely to be closer to the ground truth than SolarAnywhere. For yield analysis, energy simulations, PPAs, project planning and development, technical due diligence, and financing, selecting a dataset with the lowest long term uncertainty and variability is key.
RMSE, a measure of the differences between the values predicted by the model and the values actually observed, shows the Solcast model performs better than SolarAnywhere. With a lower RMSE of 17.23 compared to 22.08, the Solcast dataset captures the impacts of individual clouds in finer detail with fewer outlier errors. For asset monitoring and control, model training, and performance analysis, selecting a dataset with the lowest RMSE is a primary concern.
You can find more details on the validation of the Solcast dataset on the accuracy and validation page.
The Solcast methodology is semi-empirical and satellite-derived. We begin using validated, published models that offer excellent performance to build clear sky models, with proprietary improvements from industry-leading radiation modelling expert and Solcast co-founder Dr. Nick Engerer. 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 on how we built the lowest uncertainty solar resource dataset ever, see inputs and algorithms.
The SolarAnywhere 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 SolarAnywhere cloud model has the same resolution as the Solcast model.
Use of old satellites
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 13+ 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.
SolarAnywhere has an extensive database, compiled using high-resolution new satellites, and lower-resolution, pre-21st century satellites.
|Resolution of satellite data||1-2 km||1-2 km|
|Use of 10+ years of satellite data at full temporal resolution||✔||✔|
|Ignores older, less reliable satellites||✔||✘|
Solcast offers near-global coverage (latitudes higher than 60-70 degrees are not effectively covered by geostationary satellite images). SolarAnywhere is limited to the Americas and India.
Data parameters available
|Global Horizontal Irradiance (GHI)||✔||✔|
|Direct Normal Irradiance (DNI)||✔||✔|
|Diffuse Horizontal Irradiance (DHI)||✔||✔|
|Air Temperature (TEMP)||✔||✔|
|Wind Speed (WS)||✔||✔|
|Wind Direction (WD)||✔||✔|
|Relative Humidity (RH)||✔||✔|
|Atmospheric Pressure (AP)||✔||✔|
|Precipitable Water (PWAT)||✔||✔|
|Snow Depth (SWDE)||✔||✔|
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.
Data files available
Solcast offers the best value for money and much lower risk for developers, operators and investors into solar power plants. Whether you are evaluating just a single site, or your company conducts scores of assessments a year, Solcast is consistently cheaper than SolarAnywhere. We also offer users the ability to purchase TMY and Time Series data separately, so you don’t have to pay for what you don’t need. See details on the Solcast Pricing Page. Pricing below compares Solcast Extended TMY + Time Series data with SolarAnywhere’s Sites product. Solcast Basic TMY + Time Series products have the same spatial resolution as Extended products, but fewer temporal resolutions download options/Pxx senarios.
|TMY||Time Series||TMY & Time Series|
|Single site||$800||N/A||$600 (full record), or $150 per year||N/A||$1,400||$3,000|
|50 sites||$192||N/A||$144 (full record), or $36 per year||N/A||$336||$1,200|
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.
|Free data from current model to researchers||✔||✘|
|Free credit to every new account||✔||✘|