Recent interest in the validation of general circulation models (GCMs)\ud has been devoted to objective methods. A small number of authors\ud have used the direct synoptic identification of phenomena together\ud with a statistical analysis to perform the objective comparison between\ud various datasets. This paper describes a general method for performing\ud the synoptic identification of phenomena that can be used for an\ud objective analysis of atmospheric, or oceanographic, datasets obtained\ud from numerical models and remote sensing. Methods usually associated\ud with image processing have been used to segment the scene and to\ud identify suitable feature points to represent the phenomena of interest.\ud This is performed for each time level. A technique from dynamic scene\ud analysis is then used to link the feature points to form trajectories.\ud The method is fully automatic and should be applicable to a wide\ud range of geophysical fields. An example will be shown of results\ud obtained from this method using data obtained from a run of the Universities\ud Global Atmospheric Modelling Project GCM
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