Using Cloud Classification to Model Solar Variability

Imagery from GOES satellites is analyzed to determine how solar variability is related to the NOAA classification of cloud type. Without using a model to convert satellite imagery to average insolation on the ground, this paper investigates using cloud categories to directly model the expected statistical variability of ground irradiance. Hourly cloud classified satellite images are compared to multiple years of ground measured irradiance at two locations to determine if measured irradiance, ramp rates, and variability index are correlated with cloud category. Novel results are presented for ramp rates grouped by the cloud category during the time period. This correlation between satellite cloud classification and solar variability could be used to model the solar variability for a given location and time and could be used to determine the variability of a location based on the prevalence of each cloud category.