Analysis of Geostationary Satellite Imagery Using a Temporal-Differencing Technique

Abstract

A new and innovative cloud analysis technique has been developed that exploits the temporal information content of geostationary satellite imagery. The algorithm is designed to identify new cloud development and moving cloud systems by comparing the relative change in visible bidirectional reflectance and infrared brightness temperature of collocated pixels taken from consecutive image pairs. First, pixels whose temporal changes exceed predicted values for the cloud-free background are identified as cloudy. Then, based on this information, dynamic visible and infrared cloud thresholds are specified for local analysis regions within the image. Algorithm attributes include minimal reliance on supporting databases such as expected clear-scene bidirectional reflectances and land surface skin temperatures, applicability to all current geostationary environmental satellites [the algorithm processes data from the Geostationary Meteorological Satellite (GMS), Meteosat, and Geostationary Operational Environmental Satellites (GOES)], and a reliable tendency not to overanalyze cloud. Since 1 April 2002, temporal differencing has been running in checkout mode, alongside the U.S. Air Force (USAF) Real-Time Nephanalysis (RTNEPH), as the geostationary algorithm segment of the next-generation Cloud Depiction and Forecast System (CDFS) model. Initial experiences with the model to date (through June 2002) are outlined and discussed. By the end of summer 2002, CDFS will replace RTNEPH as the USAF's real-time operational global cloud model, the only of its kind in the world.