UC San Diego

Solar variability corresponds to strong variations of the solar irradiance, caused mainly by the presence of clouds. Practical uses of solar resource data, such as the design of photovoltaic solar plants, usually employ several years of hourly data, neglecting subhourly features. The effect of clouds on short-time variability can differ by cloud type, suggesting that some cloud effects could be ignored when working with hourly data. In this work, we compare statistics of solar variability calculated at different time intervals and separate the analysis by cloud categories. We use 1 min solar data and cloud radar products from the Atmospheric Radiation Measurement (ARM) cloud, aerosol, and complex terrain interactions campaign in Córdoba, Argentina, where a wide variety of clouds exist. We classify the clouds based on their vertical position and observe solar variability using the mean and standard deviation of the clear sky index for varying time intervals of 5, 15, 30, and 60 min. Time intervals affect the mean and standard deviation of the clear sky index differently for each cloud type: longer time intervals neglect small variability and overestimate the mean clear sky index of low and mid-clouds, while high clouds do not change as much. The effect is also palpable when measuring ramps: the percentile 95 of the ramps obtained for 1 min is 21 times greater compared to 1 h. This ratio varies per cloud type with the strongest differences occurring for mid-clouds, having ramps that are 73 times stronger.