Cloud-base height estimates using a combination of meteorological satellite imagery and surface reports

This paper describes how the combination of a satellite-derived cloud class ification with surface observations can improve analysis of cloud-base heig ht. A cloud-base retrieval that combines a cloud classification derived fro m visible and infrared satellite data with surface reports of cloud base is investigated. A method using the satellite classification to interpret the surface data is compared with a more traditional distance-weighted approac h of interpolating the surface data. Cloud-height observations from the U.S. surface synoptic network were merge d with a cloud classification of GOES-8 imager data for 235 test images fro m June 1996. Surface cloud-base height reports were withheld on a revolving basis and used as truth for the cloud-base height predictions from the sat ellite-based method. The comparison was limited to cloud-base heights of le ss than 10 000 feet because of biases in cloud-base height reporting at hig her altitudes. Results indicate that fusion of the satellite cloud classification with sur face cloud-base height reports yields a superior estimate of cloud-base hei ght versus an estimate using only interpolated surface data. This is true e ven though the surface-only method was given the advantage of always being spatially closer to the control site. Performance improvement is more signi ficant for broken and overcast conditions. In addition, the use of a simple textural measure, derived from the satellite cloud classification, causes the satellite-assisted method to outperform the surface-only method by an e ven wider margin.