Frequently Asked Questions
Using SolarAnywhere® Data
What is included with a SolarAnywhere historical download?
SolarAnywhere historical time-series downloads include a file containing data at the spatial and temporal resolutions included in your license, as well as a license file. All possible resolutions can be seen on the Data Resolutions page.
SolarAnywhere typical-year downloads come with a typical GHI year and a typical DNI year file, as well as a license file. Typical GHI or DNI year files contain hourly data for a combination of the twelve months in which summed GHI or DNI insolation is the closest to the average for that month from 1998 through the last complete year.
What is the difference between Standard, Enhanced and High resolution data?
Standard SolarAnywhere spatial resolution is approximately one-tenth of a degree, which equates to an area that is approximately 10 by 10 km. Standard resolution data is available with a 60-minute time resolution.
Enhanced resolution data is one-hundredth of a degree, which equates to an area that is approximately 1 by 1 km. Enhanced resolution data is available with 60, 30 or 15 -minute time resolutions.
High resolution data is one-hundredth of a degree, which equates to an area that is approximately 1 by 1 km. High resolution data is available with 10, 5 or 1-minute time resolutions.
More information about SolarAnywhere data resolutions can be found on the resolution page.
How do I use SolarAnywhere data with PVsyst?
Follow the steps in this video to learn how to successfully import your SolarAnywhere data downloads into PVsyst.
If you’re planning to use the relative humidity field in your PVsyst projects, download and import your SolarAnywhere data in the native SolarAnywhere format. While you can include relative humidity data in TMY3 format downloads, PVsyst cannot read this field when you import the data in this format.
How do I use SolarAnywhere data with the NREL System Advisor Model (SAM)?
SolarAnywhere data can be easily imported into SAM by following a few simple steps:
- Convert the file to samcsv format
- Download either typical-year or time series data from SolarAnywhere in either TMY3 or SolarAnywhere output format, selecting the 60-minute time resolution.
- Create a project in SAM.
- In the bottom left corner, select Macros.
- Select Solar Resource File Converter from the list, then select SolarAnywhere from the Weather file format drop down in the top right corner.
- Select Run macro and choose your SolarAnywhere file.
- The converted file will appear in the same location as the original.
- Import the file into SAM
- Select Location and Resource from the menu on the far left.
- Select Add/remove weather file folders…
- Choose your converted SolarAnywhere file. It will then be available for use in the Solar Resource Library.
What do the column headers in the first row of SolarAnywhere time-series output files mean?
The first row in SolarAnywhere time-series data files contains standard TMY3 format header information, plus a summary comment. From left to right, the columns correspond to:
- Site identifier code – Because SolarAnywhere data covers areas where no TMY3 site exists, we report all site identifier codes as ‘0.’
- Site name – This is the site name specified in the Site Name column on the SolarAnywhere Data Sites page or as the tile name under Tiles in the SolarAnywhere Data Typical Year page. You can edit the site name by clicking the pencil icon that appears beside it when you mouse-over the current name.
- Station state – Always listed as “NA” or Not Applicable, since our data locations may include areas of multiple states.
- Site time zone – Listed in hours offset from UTC; time zones west of Greenwich are negative (e.g. PST is 8 hours behind UTC, therefore PST is listed as -8).
- Site latitude – In decimal degrees.
- Site longitude – In decimal degrees.
- Site elevation – In meters.
- Summary comment:
- Data version – The SolarAnywhere data version.
- File type – The file will be either the typical typical-year or time time-series file type.
- Latitude/Longitude resolution – Spatial resolution of the selected tile in decimal degrees.
- Time resolution – Period between data points.
- Averaging method – Middle-of-period or end-of-period.
- Copyright information
What averaging method is used in the data website output files?
SolarAnywhere data uses standard top-of-hour, end-of-period integration. Cloud cover at times when satellite images are collected are projected to top-of-hour, end-of-period using techniques to normalize irradiation against the time period. Hourly data with time stamps of 0:00 will represent the normalized irradiation from the proceeding hour (i.e. 11:00 represents 10:00 to 11:00).
How SolarAnywhere Data compares with other data sources
Is the Perez model used to generate SolarAnywhere Data new or different from the one used by the NREL NSRDB?
SolarAnywhere Data is generated using a more recent version of the Perez model than that used to generate the NSRDB 2005 and 2010 updated datasets. SolarAnywhere also provides more recent data through the last hour, forecasts and other features that are not available from the NSRDB.
How does SolarAnywhere Data compare with NREL TMY data?
Typical Meteorological Year irradiance data available from NREL is synthesized from historical sources to represent a “typical” year for a fixed number of sites in the U.S. SolarAnywhere represents actual hourly estimates of irradiance for each specific location based on satellite imagery and atmospheric conditions at the site.
How do satellite-derived irradiation sources compare with output from ground-based measurement instruments?
If properly calibrated and maintained, ground-based instruments can be very accurate for the immediate area around the equipment. As the area of interest is located further from the unit, the accuracy declines, increasing the usefulness of satellite-based observations. The cost of equipment, inaccuracies from calibration and long setup times can favor satellite over ground-based measurements. Satellite irradiance is also often used in conjunction with ground-based instruments, and is particularly useful for detecting ground device calibration drift and for filling in missing data.
What data sources are used when generating SolarAnywhere Data?
Cloud, albedo, elevation, temperature and wind speed data is used in conjunction with satellite imagery collected from geosynchronous satellite networks.
How often is new SolarAnywhere Data made available?
SolarAnywhere Data is collected, processed and available for use within approximately one hour. When the forecast option is licensed, a continuous dataset extending from January 1, 1998 through the present, and up to 168 hours into the future is available.
Why are different models used when forecasting days-ahead and hours-ahead data periods?
Short-term SolarAnywhere forecasts utilize a vector based cloud model. Longer-term forecasts rely on numerical analysis. The bifurcated approach utilizes the method expected to give the best results for the time interval requested.
What happens when the SolarAnywhere model changes?
SolarAnywhere algorithms are occasionally updated to improve accuracy. See the release notes for more information. After a model update, historical data is often reprocessed to take advantage of the new model’s improved accuracy.
To provide continuity for users of older SolarAnywhere datasets, prior versions may be provided upon user request. Presently, only support back to SolarAnywhere version 2.2 is available via data.solaranywhere.com. Contact us for information on prior datasets.
There are periods of missing measurements in my SolarAnywhere file. Why?
Missing data occur in the SolarAnywhere irradiance database due to missing satellite images. Missing images are normal and occur due to rare unplanned outages and regular maintenance performed by the National Oceanic and Atmospheric Administration (NOAA). Missing data also occur in the ancillary surface air temperature and wind speed data due to periods of missing measurement from ground-based sensor networks.
How does SolarAnywhere handle missing data?
SolarAnywhere strives to generate uninterrupted solar irradiance on an hourly basis; however, occasionally it is not possible, usually due to satellite image interruptions.
Neighboring values may be used to generate estimates in place of the missing values. When this occurs, the observationType column will contain a suffix of “E” indicating that a value was generated from the surrounding observations.
If too many samples are missing, the ObservationType column will contain a suffix of “M,” indicating that no data is available for that hour. Note that a prefix value of “M” in the ObservationType column is different from a suffix value of “M.” A prefix value of “M” indicates that the values in the row were generated for the current month.
Are there options to fill periods of missing data in SolarAnywhere?
- Average Values – This option replaces data gaps with the climatological average for the specific day of the year. For instance, if April 22nd, 2012 presents a data gap, the software will replace that day with the average measurements from all other intact April 22nd days in the database (i.e., 1998, 1999, 2000…). This option is the preselected, default value and is available in TMY3 and SolarAnywhere file formats.
- Blanks – This option returns data gaps with blank cells. This option is available in TMY3 and SolarAnywhere file formats.
- -999 – This option replaces all data gaps with the integer -999. This option is often preferred when looking to sift for data gap measurement periods. This option is only available in SolarAnywhere file format.
- NaN – This option replaces all data gaps with the text string NaN. Also preferred for sifting periods with data gaps, this option gives additional compatibility with database software used to further manipulate SolarAnywhere Data (i.e., Microsoft Excel). This option is only available in SolarAnywhere file format.
What is the difference between TGY and P50 data?
We’re sometimes asked whether a TGY is a P50. In short, no! The typical year is constructed of closest-to-average months. In practice the annual total of a typical year is very similar the average of the annual totals of the timeseries. P50, on the other hand, represents the median year of the distribution. Half of future years are expected to fall above the value, and half are expected to fall below.
TGY and P50 are often similar but diverge for asymmetrical distributions. Click here to learn more about SolarAnywhere PXX Data.
What is SolarAnywhere v3.0 and what are IR images?
SolarAnywhere v3.0 differs from previous models in that it incorporates infrared (IR) image processing into the measurement of cloud location and resulting irradiance. Under previous models, only visible wavelength light images were used to determine cloud location; however, regions with heavy snow cover often confounded the model by detecting snow not cloud cover. The use of IR image channels allows SolarAnywhere to differentiate between snow and cloud, and improve model accuracy when snow cover exists.
IR images are similar to visible images in that they are captured by the same geostationary satellite networks. They are different, though, because they capture images at infrared (3.8 – 13.3 microns) wavelengths. For more information, see the release notes.
SolarAnywhere Licensing Options
How are geographic areas defined when licensing data?
The basic geographic unit is a satellite visible “tile.” Tile areas directly correspond to satellite image resolution. SolarAnywhere offers data in 10 km nominal (0.1 x 0.1 degree) resolution in all available regions, and up 1 km nominal (0.01 x 0.01 degree) resolution in select regions. For information on licensing, see purchase options or contact us.
Why aren’t you offering 10 km time-series data licenses anymore?
Since we started offering 1 km resolution data seven years ago, demand for 1 km enhanced resolution data has increased steadily.
The most common use case for our historical time series data is as an input to bankable resource assessments for commercial and utility scale PV project financing. In these cases, reducing resource risk significantly improves project returns. Since 1 km data offers better accuracy in complex terrain and coastal areas, and an overall reduction in the annual GHI Mean Bias Error (MBE), it just makes sense to make 1 km data the time-series standard.
It’s still possible to obtain 10 km time-series data with a 1 km resolution license.
I only need data for a specific region, can I purchase a more limited license for a lower price?
Yes. For Typical Year Data, the Professional license offers an accessible price for 25 sites per year, which is ideal for regional developers.
In addition, historical time series data can be purchased on a per site basis for customers that only need data for one or a few sites per year. You can see all licensing options here.
If I need more Typical Year sites in a year than my license allows, can I upgrade?
Yes, you can upgrade to the unlimited license. The other option is to purchase a fresh Professional license valid for 1 year. You can see all the licensing options here.
Can I access SolarAnywhere Data to support my research free-of-charge?
Yes, researchers have limited access to SolarAnywhere Typical Year and Time Series data for North America with an Academic license. The Academic license offers the same data that was formerly available via NREL’s Solar Prospector tool. Commercial use of SolarAnywhere data obtained through an Academic license is not supported. You can see all the licensing options here.