NREL-nsrdb 4.0.2

National Solar Radiation Database (NSRDB) Software

The National Solar Radiation Database (NSRDB) software includes all the methods for the irradiance data processing pipeline. To get started, check out the NSRDB command line interface (CLI). Refer to the NREL website and the original journal article for more information on the NSRDB. For details on NSRDB variable units, datatypes, and attributes, see the NSRDB variable meta data.

The PXS All-Sky Irradiance Model

The PXS All-Sky Irradiance Model is the main physics package that calculates surface irradiance variables.

The NSRDB Data Model

The NSRDB Data Model is the data aggregation framework that sources, processes, and prepares data for input to All-Sky.

Installation

1. Use conda (anaconda or miniconda with python 3.9) to create an nsrdb environment: conda create --name nsrdb python=3.9

2. Activate your new conda env: conda activate nsrdb

3. Follow the steps used in the pytest actions.

   1. These actions refer to the required repositories needed to run all tests and the commands which should be run from the local location of those repositories

   2. If you plan to run without MLClouds the step associated with this repository can be skipped.

4. Test your installation:

   1. Start ipython and test the following import: from nsrdb.data_model import DataModel

   2. Navigate to the tests/ directory and run the command: pytest

5. If you are a developer, also run pre-commit install in the directory containing .pre-commit-config.yaml.

NSRDB Versions

NSRDB Verions History

Version	Effective Date	Data Years*	Notes
1.0.0	2015	2005-2012	Initial release of PSM v1 (no FARMS) Satellite Algorithm for Shortwave Radiation Budget (SASRAB) model MMAC model for clear sky condition The DNI for cloud scenes is then computed using the DISC model
2.0.0	2016	1998-2015	Initial release of PSM v2 (use of FARMS, downscaling of ancillary data introduced to account for elevation, NSRDB website distribution developed) Clear sky: REST2, Cloudy sky: NREL FARMS model and DISC model Climate Forecast System Reanalysis (CFSR) is used for ancillary data Monthly 0.5º aerosol optical depth (AOD) for 1998-2014 using satellite and ground-based measurements. Monthly results interpolated to daily 4-km AOD data. Daily data calibrated using ground measurements to develop accurate AOD product.
3.0.0	2018	1998-2017	Initial release of PSM v3 Hourly AOD (1998-2016) from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2). Snow-free Surface Albedo from MODIS (2001-2015), (MCD43GF CMG Gap-Filled Snow-Free Products from University of Massachusetts, Boston). Snow cover from Integrated Multi-Sensor Snow and Ice Mapping System (IMS) daily snow cover product (National Snow and Ice Data Center). GOES-East time-shift applied to cloud properties instead of solar radiation. Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is used for ancillary data (pressure, humidity, wind speed etc.)
3.0.1	2018	2017+	Moved from timeshift of radiation to timeshift of cloud properties.
3.0.2	2/25/2019	1998-2017	Air temperature data recomputed from MERRA2 with elevation correction
3.0.3	2/25/2019	1998-2017	Wind data recomputed to fix corrupted data in western extent
3.0.4	3/29/2019	1998-2017	Aerosol optical depth patched with physical range from 0 to 3.2
3.0.5	4/8/2019	1998-2017	Cloud pressure attributes and scale/offset fixed for 2016 and 2017
3.0.6	4/23/2019	1998-2017	Missing data for all cloud properties gap filled using heuristics method
3.1.0	9/23/2019	2018+	Complete refactor of NSRDB processing code for NSRDB 2018
3.1.1	12/5/2019	2018+, TMY/TDY/TGY-2018	Complete refactor of TMY processing code.
3.1.2	6/8/2020	2020	Added feature to adjust cloud coordinates based on solar position and shading geometry.
3.2.0	3/17/2021	2020	Enabled cloud solar shading coordinate adjustment by default, enabled MLClouds machine learning gap fill method for missing cloud properties (cloud fill flag #7)
3.2.1	1/12/2021	2021	Implemented an algorithm to re-map the parallax and shading corrected cloud coordinates to the nominal GOES coordinate system. This fixes the issue of PC cloud coordinates conflicting with clearsky coordinates. This also fixes the strange pattern that was found in the long term means generated from PC data.
3.2.2	2/25/2022	1998-2021	Implemented a model for snowy albedo as a function of temperature from MERRA2 based on the paper “A comparison of simulated and observed fluctuations in summertime Arctic surface albedo” by Becky Ross and John E. Walsh
3.2.3	4/13/23	None	Fixed MERRA interpolation issue #51 and deprecated python 3.7/3.8. Added changes to accommodate pandas v2.0.0.
4.0.0	5/1/23	2022	Integrated new FARMS-DNI model.

Recommended Citation

Update with current version and DOI:

Grant Buster, Brandon Benton, Mike Bannister, Yu Xie, Aron Habte, Galen Maclaurin, Manajit Sengupta. National Solar Radiation Database (NSRDB). https://github.com/NREL/nsrdb (version v4.0.0), 2023. DOI: 10.5281/zenodo.10471523

Acknowledgments

This work (SWR-23-77) was authored by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the DOE Grid Deployment Office (GDO), the DOE Advanced Scientific Computing Research (ASCR) program, the DOE Solar Energy Technologies Office (SETO), the DOE Wind Energy Technologies Office (WETO), the United States Agency for International Development (USAID), and the Laboratory Directed Research and Development (LDRD) program at the National Renewable Energy Laboratory. The research was performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

*Note: The “Data Years” column shows which years of NSRDB data were updated at the time of version release. However, each NSRDB file should be checked for the version attribute, which should be a more accurate record of the actual data version.