National Solar Radiation Database (NSRDB)
The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2017. The NSRDB provides foundational information to support U.S. Department of Energy programs, research, and the general public.
The NSRDB provides time-series data at 30 minute resolution of resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms developed by the University of Wisconsin. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate solar irradiance (GHI, DNI, and DHI). The Global Horizontal Irradiance (GHI) is computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, FARMS is used to compute GHI. The Direct Normal Irradiance (DNI) for cloud scenes is then computed using the DISC model. The PATMOS-X model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites. Ancillary variables needed to run REST2 and FARMS (e.g., aerosol optical depth, precipitable water vapor, and albedo) are derived from the the Modern Era-Retrospective Analysis (MERRA-2) dataset. Temperature and wind speed data are also derived from MERRA-2 and provided for use in SAM to compute PV generation.
The following variables are provided by the NSRDB:
Global Horizontal (ghi)
Direct Normal (dni)
Solar Zenith Angle
Angstrom wavelength exponent (alpha)
Aerosol optical depth (aod)
Aerosol asymmetry parameter (asymmetry)
Cloud optical depth (cld_opd_dcomp)
Cloud effective radius (cld_ref_dcomp)
Reduced ozone vertical pathlength (ozone)
Aerosol single-scatter albedo (ssa)
The data is provided in high density data file (.h5) separated by year. The
variables mentioned above are provided in 2 dimensional time-series arrays
(called “datasets” in h5 files) with dimensions (time x location). The temporal
axis is defined by the
time_index dataset, while the positional axis is
defined by the
meta dataset. We typically refer to a single site in the
data with a
gid, which is just the index of the site in the meta data
(zero-indexed). For storage efficiency each variable has been scaled and stored
as an integer. The scale_factor is provided in the
attribute. The units for the variable data is also provided as an attribute
More recent years of NSRDB data have added “scale_factor” and “units” in addition to “psm_scale_factor” and “psm_units” in order to be consistent with the other NREL datasets.
Data Access Examples
The easiest way to access and extract WTK and NSRDB data is by using the Resource eXtraction tool rex.
Example scripts to extract wave resource data using the command line or python are provided below.
If you are on the NREL Eagle supercomputer, you can use the example below, but
change the filepath to the appropriate WTK or NSRDB file location on
/datasets/ and set
hsds=False. See the basic rex Resource handler
for similar use examples.
You can use
rex to access WTK and NSRDB data from your local computer using
order to do so, you need to setup HSDS and h5pyd. See the rex-HSDS
instructions for more
details on how to do this.
Please note that the NREL-hosted HSDS API is for demonstration purposes only, if you would like to use HSDS for production runs of reV please setup your own service with the instructions here: https://nrel.github.io/rex/misc/examples.hsds.html
The NSRDBX command line utility provides the following options and commands:
NSRDBX --help Usage: NSRDBX [OPTIONS] COMMAND [ARGS]... NSRDBX Command Line Interface Options: -h5, --solar_h5 PATH Path to Resource .h5 file [required] -o, --out_dir PATH Directory to dump output files [required] -v, --verbose Flag to turn on debug logging. Default is not verbose. --help Show this message and exit. Commands: dataset Extract a single dataset multi-site Extract multiple sites given in '--sites' .csv or .json as... sam-file Extract all datasets needed for SAM for the nearest pixel to...
NSRDBX python class
from rex import NSRDBX nsrdb_file = '/nrel/nsrdb/v3/nsrdb_2018.h5' with NSRDBX(nsrdb_file, hsds=True) as f: meta = f.meta time_index = f.time_index dni = f['dni', :, ::1000]
NSRDBX also allows easy extraction of the nearest site to a desired
(lat, lon) location:
from rex import NSRDBX nsrdb_file = '/nrel/nsrdb/v3/nsrdb_2018.h5' nrel = (39.741931, -105.169891) with NSRDBX(nsrdb_file, hsds=True) as f: nrel_dni = f.get_lat_lon_df('dni', nrel)
or to extract all sites in a given region:
from rex import NSRDBX nsrdb_file = '/nrel/nsrdb/v3/nsrdb_2018.h5' state='Colorado' with NSRDBX(nsrdb_file, hsds=True) as f: date = '2018-07-04 18:00:00' dni_map = f.get_timestep_map('dni', date, region=region, region_col='state')
NSRDBX can be used to extract all variables needed to run SAM at a
from rex import NSRDBX nsrdb_file = '/nrel/nsrdb/v3/nsrdb_2018.h5' nrel = (39.741931, -105.169891) with NSRDBX(nsrdb_file, hsds=True) as f: nrel_sam_vars = f.get_SAM_lat_lon(nrel)
For more information about the NSRDB please see the website Users of the NSRDB should please cite: