Solar Tower and Dish Power Contour Lines, 500-Meter Intervals: United States, 1998-2005
Abstract/Contents
- Abstract
- This line shapefile contains solar tower and dish power resource levels of watt hours per meter squared (Wh/m2) for direct solar irradiance in the contiguous United States using 500-meter interval contour lines. This layer is a part of a collection of GIS data containing renewable and electric energy information for the U.S., including data on transmission lines, power plants and electricity substations.
- Purpose
- This layer can be used for estimates of solar resource potential.
Description
| Type of resource | cartographic, software, multimedia |
|---|---|
| Form | Shapefile |
| Extent | 0.676 |
| Place | San Diego, California, US |
| Publisher | Hart Energy Publishing |
| Date valid | 1998 - 2005 |
| Publication date | 2015 |
| Edition | 1018 update |
| Language | English |
| Digital origin | born digital |
| Map data | Scale not given. ; EPSG::4269 W 124°30ʹ55ʺ--W 67°1ʹ58ʺ/N 49°21ʹ15ʺ--N 25°8ʹ21ʺ, Scale not given ; EPSG::4326 |
Creators/Contributors
| Creator | Hart Energy Publishing |
|---|
Subjects
| Subject | Solar energy |
|---|---|
| Subject | Solar radiation |
| Subject | United States |
| Subject | 1998 > 2005 |
| Subject | Utilities and Communication |
| Genre | Geospatial data |
| Genre | Cartographic dataset |
Bibliographic information
| Supplemental information | This data provides monthly average and annual average daily total solar resource averaged over surface cells of 0.1 degrees in both latitude and longitude, or about 10 km in size. This data was developed using the State University of New York/Albany satellite radiation model. This model was developed by Dr. Richard Perez and collaborators at the National Renewable Energy Laboratory and other universities for the U.S. Department of Energy. Specific information about this model can be found in Perez, et al. (2002). This model uses hourly radiance images from geostationary weather satellites, daily snow cover data, and monthly averages of atmospheric water vapor, trace gases, and the amount of aerosols in the atmosphere to calculate the hourly total insolation (sun and sky) falling on a horizontal surface. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. A modified Bird model is used to calculate clear sky direct normal (DNI). This is then adjusted as a function of the ratio of clear sky global horizontal (GHI) and the model predicted GHI. Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalable at a 10km resolution. As a result, it is believed that the modeled values are accurate to approximately 15% of a true measured value within the grid cell. Due to terrain effects and other microclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain. |
|---|---|
| WGS84 Cartographics | This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection. |
| Location | https://purl.stanford.edu/qc836kz0571 |
Access conditions
- Use and reproduction
- These data are licensed by Stanford Libraries and are available to Stanford University affiliates only. Affiliates are limited to current faculty, staff and students. Non affiliates seeking access should contact the publisher directly. These data may not be reproduced or used for any purpose without permission.
- Copyright
- Copyright ownership resides with the originator.
Preferred citation
- Preferred citation
- Hart Energy Publishing. (2015). Solar Tower and Dish Power Contour Lines, 500-Meter Intervals: United States, 1998-20055. Hart Energy Publishing. Available at: http://purl.stanford.edu/qc836kz0571
Collection
Renewable energy GIS data : United States
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