Compare Solcast historical and TMY products to Solargis

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

The first version of Solargis was released in 2010. The database is generally regarded to be of good accuracy for most parts of the world, but expensive.

Solcast’s mission is to bring you 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, and a much lower price than Solargis.

If you need PV simulation tools and features, you may be better with Solargis. Solcast is a data provider rather than a tools provider, and we are solar-development focused so we don’t focus on steep mountain areas.


  Solcast Solargis
Free trial with instant access and data download?
Price point $$ $$$$
Download wait time 1-9 minutes 5 minutes to 48 hours
Mean Bias Error (GHI) 0.0% 0.0%
Bias Deviation (GHI) ± 2.0% ± 2.9%
90% of sites have bias (GHI) smaller than ± 2.5% ± 4.6%
Mean RMSE (GHI) 16.5% 18.0%
Comprehensive, global, independent validation
Validation Sites 50 220
Satellite based estimation as primary method
Global Coverage
Resolution of satellite data used 1-2 km 3-4 km
10+ years of satellite data at full temporal resolution
Ignores older, less reliable satellites
Provides PV modeling tools

Source: Solargis Solar Resource Database: Description and Accuracy

Accuracy & Validation

Both Solcast’s & Solargis’ 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. A summary of Solcast’s and Solargis’ hourly mean GHI validation results is given below.

  Solcast Solargis
Mean Bias Error 0.0% 0.0%
Bias Error Standard Deviation ±2.0% ±2.9%
80% of sites have bias smaller than ± 1.93% ± 3.1%
90% of sites have bias smaller than ± 2.50% ± 4.6%
95% of sites have bias smaller than ± 3.64% ± 7.1%
Mean RMSE 16.5% 18.0%

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. Both models show an average of biases of zero. Both models are symmetrically centered.

The Solcast data shows significantly less variability than Solargis. A lower mean bias deviation of ±2.0% v ±2.9% means Solcast data is represented by a narrower probability distribution.

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 Solargis. With much less variability in the dataset, developers can trust the accuracy of their energy simulations and operational calculations.

Solcast v Solargis GHI Bias Distribution


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 Solargis data. If you do your own validation, we’d love it if you can send us your results.

  Solcast Solargis
Comprehensive, global, independent validation
Validation Sites 46 220


Below we present validation statistics for all sites where both Solcast and Solargis have published results. An objective comparison can be made at these sites when both datasets are assessed against the same BSRN ground measurements.

Bias Error (%)RMSE (%)
Site NameBSRN codeCountrySolcastSolargisSolcastSolargis
BrasiliaBRBBrazil-1.334.220.98 21.3
CabauwCABThe Netherlands-0.45 1.017.618.9
De AarDAASouth Africa0.381.8 7.3111.5
FukuokaFUAJapan1.12 0.2 17.5624.0
IshigakijimaISHJapan-3.64-1.3 17.7824.2
LauderLAUNew Zealand-0.04-4.0 21.5631.1
LindenbergLINGermany-1.93-3.0 18.92N/A
MomoteMANPapua New Guinea1.54 -2.921.0425.9
São Martinho da SerraSMSBrazil-0.88 2.814.5718.3
SapporoSAPJapan-0.9-1.4 20.5729.1
Tateno TATJapan1.09-0.1 15.9720.4
XiangheXIAChina0.62-1.0 14.7719.9
Fork PeckFPEUSA1.380.0 16.5920.8
Sioux FallsSXFUSA-1.52-0.4 19.4318.6
Rock Springs/Penn StatePSUUSA0.021.0 20.420.2
BoulderBOUUSA0.51.5 17.8124.7
Boulder (closed)BOSUSA-0.55 20.02
BondvilleBONUSA-1.370.5 17.7317.4
Desert RockDRAUSA0.180.6 9.5112.5
Goodwin CreekDRAUSA0.450.6 13.8515.5
Summary statistics of BSRN sites Solcast Solargis
Sample Mean Bias Error -0.27 0.15
Sample Standard Deviation 1.28 2.15
Sample Mean RMSE 17.20 20.79

Model Inputs

Satellite Resolution

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 Solargis 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 Solargis cloud model has a lower resolution than the Solcast model, based around a 4 km2 grid.

Elevation and altitude

Solcast maps altitude and elevation with a grid size of 150m2, compared with a 250m2 grid used by Solargis. In regions of extreme local topography, Solcast is able to map small elevation changes at a finer level than Solargis.

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 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.

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

  Solcast Solargis
Resolution of satellite data 1-2 km 3-4 km
Use of 10+ years of satellite data at full temporal resolution
Ignores older, less reliable satellites

PV Simulation Software

Solargis has supporting simulation software (pvPlanner, Prospect, and iMaps) that assists users in prospecting and pre-feasibility PV modeling.

Solcast has focused its efforts on producing solar resource data with the understanding that common PV simulation software have advanced capabilities for system design and energy modeling. We make our solar resource data available in multiple file formats, ready-to-import to the most popular software used by the community.

Data Availability

Solcast and Solargis 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.

Data parameters available

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

Data files available

  Solcast Solargis
Download Wait Time 1-9 minutes Up to 48 hours
PVsyst (CSV)


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 Solargis. 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

TMY Time Series TMY & Time Series
Solcast Solargis Solcast Solargis Solcast Solargis
Single site $400 N/A $400 (full record), or $100 per year €1000 (full record), or €500 per year $800 €1250
25 sites $120 N/A $120 (full record), or $30 per year N/A $240 €400
100 sites $96 €100 $96 (full record), or $24 per year N/A $192 €300

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 Solargis
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.