Featured GIS Shapefile Map Layers - for Beginners & Experienced GIS Users Alike. Zip Code Boundaries, School Districts, Indian & Federal Lands, Climate Change, Tornadoes, Dams - Create digital GIS maps in minutes ... more
Reimagination - Reimagining, exploring and celebrating the changes in infrastructure, politics and culture that will help us live in harmony with each other and the earth now and in the future.
Monthly and annual average renewable energy solar resource potential for the state of Hawaii. Provides information on the solar resource potential for the state of Hawaii. The insolation values represent the average solar energy available to a concentrating collector on a 2-axis tracker, such as a dish or a power tower. 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.SUNY Albany and NRELMarch 24, 2007
Lower 48
This data provides monthly average and annual average daily total solar energy 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.
File Formats
The SHP file contains the geospatial data. The SHX file contains the index of the geospatial data. The DBF file contains the attribute data in dBASE® format. The PRJ file contains the coordinate system information (optional). The AVL file contains the legend information (optional). The SBN and SBX files contain the spatial index of the geospatial data (optional). The XML file (*.shp.xml) contains the metadata describing the data set (optional).
This data may come from a variety of U.S. government and self-reporting private sources. While we try to assure the accuracy of this material, we cannot promise that it is absolutely accurate. We do promise that using the map layer will be fun, entertaining or educational. Beyond this, we make no guarantee as to its suitability for any purpose. We assume no liability or responsibility for errors or inaccuracies. Please understand that you use these map layers at your own risk.
MapCruzin.com is an independent firm
specializing in the publication of
educational and research resources.
We created the first U.S. based
interactive toxic chemical facility
maps on the internet in 1996 and we
have been online ever since. Learn more about us and view some of our projects and services.
If you have data, GIS project or custom shapefile needs send me an email.
Didn't find what you are looking for? We've been online since 1996 and have created 1000's of pages. Search below and you may find just what you are looking for.
