Temporal Extrapolation of Satellite Imagery for Short-Range Cloud Forecasting

Visidyne proposes to develop an expert, neural net based, system for extrapolating satellite imagery forward in time to provide short-range forecasts of cloud cover. In Phase I Visidyne proposes to investigate the limits of the temporal extrapolation of satellite cloud imagery. For locations in a variety of climate zones, Visidyne will determine how long overlying clouds can be tracked backward in time in satellite images. If these times are sufficiently long, Visidyne will propose a Phase II effort to develop a short-range forecasting system employing an expert, neural net based, system for extrapolating satellite cloud imagery forward in time. The primary benefit of Phase I will be information regarding the utility of developing a short-range cloud forecasting scheme based on the extrapolation of satellite imagery. If the derived time scales are sufficiently long, then experience gained in Phase I will be used to develop a forecasting scheme, which will be proposed in Phase II. Such a forecasting scheme could be adapted for a variety of civilian uses such as in scheduling LANDSAT use or planning cloud seeding activities.