Objective Algorithm for Detection and Tracking of Extratropical Cyclones in the Southern Hemisphere.

In this study, we propose an easy and robust algorithm to identify and track extratropical cyclone events using 850 hPa relative vorticity data, gaussian filter and connected-component labeling technique, which recognize the cyclone as areas under a threshold. Before selecting the events, the algorithm can include essential characteristics that are good metrics of intensity, like minimum mean sea level pressure and maximum 10-m winds. We implemented the algorithm in the Southern Hemisphere, using a 41-year high resolution dataset. Sensitivity tests were performed to determine the best parameters for detection and tracking, such as degree of smoothing, thresholds of relative vorticity at 850 hPa and the minimum area within the threshold. Two case studies were used to assess the positive and negative points of the methodology. The results showed that it is efficient in obtaining the position of extratropical cyclones in their most intense stage, but it does not always perform well during cyclolysis. We compare the methodology using 1-h temporal resolution to that using a 6-hours temporal resolution, and their reproducibility regarding the literature. The extratropical cyclone climatology in the Southern Hemisphere is provided and discussed. The algorithm developed here can be applied to datasets with good spacial and temporal resolution, providing a better inventory of extratropical cyclones. [ABSTRACT FROM AUTHOR]