The primary objective of this effort is to create a meteorological database of synoptic climatologies which can be applied to many of the future expert systems efforts related to forecasting. The complexity of the meteorological domain can be reduced to limited set of parameters and possible decisions. One method of modeling this domain is with objects which can represent meteorological features/phenomena and the three-dimensional structures of the atmosphere. To facilitate expert systems development and create a common framework, this effort specifically focuses on representing synoptic features in a classroom hierarchy. Phase i is a 2-step process: 1) broad classification of all basic synoptic phenomena related to general climatology, and 2) regional climatologies built upon the broad classification from the first step and modified by regional differences. A prototype demonstration will indicate how the resulting climatological object base should provide a standard reference for both commercial and government interests. A seperate optional task will identify issues related to the practical application of the system. Climatologies identified and defined in phase i will be formalized into a complete objectbase in phase ii.
Keywords: training regional synoptic climatology artificial intelligence battlefield weather support
