  Application of Dynamic Mode Decomposition to clear-sky index forecasting of
shadowing effects of convective fair-weather cumulus clouds is presented. Cloud
dynamics are captured by sequences of visible-light photographic video frames.
This method can be more easily applied to the modeling of cloud evolution than
traditional fluid-based methods, and can enhance existing frozen-cloud
advection methods. Its use is demonstrated for an actual fair-weather cumulus
cloud image sequence and compared to an advection-only forecast. It is
concluded that the method shows promise for very short-term clear-sky index
forecasting for up to seven minute horizons.

Computational Engineering, Finance, and Science