Hourly and daily-integrated solar radiation data are available for download for U.S. Virgin Islands, Puerto Rico, Dominican Republic, Haiti, Jamaica and Cuba by clicking here. Examples of the daily integrated solar radiation data are given below.
YESTERDAY’S SOLAR RADIATION DATA FOR PUERTO RICO
Characteristics of the Solar Radiation Data
Puerto Rico, Culebra, Vieques and U.S. Virgin Islands 1-km
Puerto Rico, Dominican Republic, Haiti, Jamaica and Cuba 2-km
Range of data for 1-km dataset: March 2009 through present. The data set is not entirely complete. Technical problem prevented data from being collected between mid January through mid March 2011.
Range of data for 2-km dataset: Early March 2010 through present. The data set is not entirely complete. Technical problem prevented data from being collected between mid January through mid March 2011.
Format of data files: The name of the data file indicates where the data is from. RICO signifies Puerto Rico, Culebra, Vieques and U.S. Virgin Islands. CARIB signifies Puerto Rico, Dominican Republic, Haiti, Jamaica and Cuba. Also given in the file name is the julian day and year. For example, 2010079, indicated the year 2010, julian day 79. The extension on the file is .gz, which can be unzipped with any compression software such as WinZip or or 7-Zip and can be downloaded at the following site http://www.filehippo.com .
The unzipped file is a text file. If the file is imported into an Excel spreadsheet, you will see three columns of data: column 1 is solar radiation in units of megajoules per square meter per day x 100, column 2 is latitude north and column 3 is longitude west. To obtain the solar radiation in megajoules per square meter per day, simply divide the value by 100.
Archived Daily Solar Radiation Images for Puerto Rico
Archived Monthly Average Solar Radiation Images for Puerto Rico
Archived Annual Average Solar Radiation Images for Puerto Rico (2009 through 2015)
Remote Sensing Calibration: Harmsen et al. (2014) conducted a calibration and validation of the satellite remote sensing product. The study resulted in the following conclusions (direct quotation):
“In this study, pyranometers at Fortuna and UPRM were re-calibrated. Using the re-calibrated pyranometers, solar radiation data from a GDM satellite remote sensing method was calibrated. For the daily-integrated analysis, R2 values for the linear equations, for Fortuna and UPRM were 0.88 and 0.83, respectively. The R2 value for the combined data equation was 0.87. A validation was conducted for a 283-day period for Fortuna and a 226-day period for UPRM. The site-specific equations [equations (5) and (6)] performed well, however, when using the combined data equation [equation (9)], solar radiation was underestimated consistently by 1 or 2 MJ/m2/day on average for Fortuna. On the other hand, the same equation performed well for Mayaguez (MBE = –0.11 MJ/m2day, RMSE = 1.79 MJ/m2day and % error = –0.56). The uncorrected data produced reasonably accurate results at both locations with a maximum % error of 6.22%, which is comparable with estimates obtained in the literature. Therefore, the uncorrected remotely sensed solar radiation data are recommended for use throughout Puerto Rico. This study did not consider areas of the island defined as humid-mountainous, and therefore, future calibration/validation efforts should focus on this environment. This research should be considered preliminary, as ongoing efforts are underway to further improve the accuracy of the remote sensing product in Puerto Rico.”
Harmsen, E.W., P. Tosado and J. Mecikalski, 2014. Calibration of Selected Pyranometers and Satellite Derived Solar Radiation in Puerto Rico. Int. J. Renewable Energy Technology, 5(1):43-54.
Definitions of terms in the above paragraph: Fortuna is located at the University of Puerto Rico Agricultural Experiment Station near Juana Diaz, PR. UPRM is the University of Puerto Rico-Mayaguez Campus. GDM stands for Gautier, Diak, and Masse, the original developers of the solar radiation estimation procedure. R2 stands for R squared or the coefficient of determination. MBE is mean bias error, and RMSE is the root mean squared error.
DISCLAIMER: The information is provided “as is”. The authors and publishers of this information disclaim any loss or liability, either directly or indirectly as a consequence of applying the information provided herein, or in regard to the use and application of said information. No guarantee is given, either expressed or implied, in regard to the accuracy, or acceptability of the information.
Acknowledgement: I would like to thank Dr. John Mecikalski for extending the GDM GOES-based solar radiation model to include Puerto Rico, Hispaniola, Jamaica and Cuba. Dr. Mecikalski is an Associate Professor in the Department of Atmospheric Sciences, University of Alabama in Huntsville (UAH). He also conducts research for the National Space Science and Technology Center (NSSTC). Email: firstname.lastname@example.org
Some Applications of Remotely Sensed Solar Radiation
Otkin, A. J., M. C. Anerso, J. R. Mecikalski and G. R. Diak, 2005. Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network. J. of Hydrometeorology, Vol. 6, August:460-475.
Harmsen, E. W., J. Mecikalski, A. Mercado and P. Tosado Cruz, 2010. Estimating evapotranspiration in the Caribbean Region using satellite remote sensing. Proceedings of the AWRA Summer Specialty Conference, Tropical Hydrology and Sustainable Water Resources in a Changing Climate. San Juan, Puerto Rico. August 30-September 1, 2010.
Harmsen E. W., J. Mecikalski, P. Tosado Cruz and Ariel Mercado Vargas, 2010. Estimating Evapotranspiration using Satellite Remote Sensing in Puerto Rico, Haiti and the Dominican Republic. PowerPoint Presention given at the 46th Annual Meeting of the Caribbean Food Crops Society, July 12, 2010, Boca Chica, Dominican Republic
Harmsen, E. W., J. Mecikalski, M. J. Cardona-Soto, A. Rojas Gonzalez and R. Vasquez, 2009. Estimating daily evapotranspiration in Puerto Rico using satellite remote sensing. WSEAS Transactions on Environment and Development. Vol. 6(5):456-465.
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