Satellite Derived Irradiance Estimates

Source: ResearchGate

Step 1: Detecting Cloud Cover with Albedo

The technology used for detecting clouds from space involves satellites in geostationary orbits, which capture full-disk scans of the Earth every 10-15 minutes. By analyzing visible and infrared wavelengths, cloud cover can be detected. Albedo calculations are then used to distinguish between clouds and other surface features like snow or sand.

Step 2: Characterizing Cloud Cover via Cloud Opacity

Cloud opacity, which represents the thickness of cloud cover, is estimated by comparing raw satellite imagery with albedo calculations. This helps in understanding how clouds affect solar radiance. The opacity values are calibrated using ground-based solar measurements to ensure accuracy.

Step 3: Estimating Solar Radiance with a Clear-Sky Model

Models are used to estimate the solar radiance that would reach the Earth’s surface under clear-sky conditions. Factors like solar geometry, Earth/Sun distance, and aerosols/turbidity are considered in these models. This step helps in determining the sunlight that would be available in the absence of clouds.

Step 4: Satellite Derived Solar Radiance

By combining the clear-sky radiance estimates with cloud opacity values, a spatially continuous estimate of solar radiance is generated for different locations covered by satellite imagery. This final calculation provides an understanding of the availability of solar radiance across the region captured by the satellites.

Overall, the use of geostationary weather satellites and advanced algorithms has enabled the estimation of solar radiance over large areas, even where ground-based measurements are limited. This technology plays a crucial role in understanding solar energy potential and forecasting solar resource availability for various applications.

Source: MDPI