The need for research and development of new cost-efficient methods for tracking and analyzing atmospheric cyclones is apparent. Currently storm tracking is performed either manually or using numerical codes. The manual approach is more accurate but it requires considerable time and labor. Numerical schemes [e.g., Murray and Simmonds, 1991] track the cyclones from digital sea level pressure (SLP) data, linking the sequential positions of cyclone centers using different assumptions based on atmospheric dynamics. This approach is very effective computationally but it creates a number of uncertainties and biases, especially in the Northern Hemisphere.