Satellite-based Cloudiness and Solar Energy Potential in Texas and Surrounding Regions




Xia, Shuang
Mestas-Nuñez, Alberto M.
Xie, Hongjie
Vega, Rolando

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Global horizontal irradiance (i.e., shortwave downward solar radiation received by a horizontal surface on the ground) is an important geophysical variable for climate and energy research. Since solar radiation is attenuated by clouds, its variability is intimately associated with the variability of cloud properties. The spatial distribution of clouds and the daily, monthly, seasonal, and annual solar energy potential (i.e., the solar energy available to be converted into electricity) derived from satellite estimates of global horizontal irradiance are explored over the state of Texas, USA and surrounding regions, including northern Mexico and the western Gulf of Mexico. The maximum (minimum) monthly solar energy potential in the study area is 151–247 kWh/m2 (43–145 kWh/m2) in July (December). The maximum (minimum) seasonal solar energy potential is 457–706 kWh/m2 (167–481 kWh/m2) in summer (winter). The available annual solar energy in 2015 was 1295–2324 kWh/m2. The solar energy potential is significantly higher over the Gulf of Mexico than over land despite the ocean waters having typically more cloudy skies. Cirrus is the dominant cloud type over the Gulf which attenuates less solar irradiance compared to other cloud types. As expected from our previous work, there is good agreement between satellite and ground estimates of solar energy potential in San Antonio, Texas, and we assume this agreement applies to the surrounding larger region discussed in this paper. The study underscores the relevance of geostationary satellites for cloud/solar energy mapping and provides useful estimates on solar energy in Texas and surrounding regions that could potentially be harnessed and incorporated into the electrical grid.



cloud distribution and frequency, surface solar irradiance, global horizontal irradiance, cloud types, solar energy, Texas, Mexico, Gulf of Mexico


Remote Sensing 11 (9): 1130 (2019)


Earth and Planetary Sciences