Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models
A probabilistic clustering technique is developed for classification of wintertime extratropical cyclone (ETC) tracks over the North Atlantic. We use a regression mixture model to describe the longitude-time and latitude–time propagation of the ETCs. A simple tracking algorithm is applied to 6-hourl...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Published: |
2006
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| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.6903 http://www.atmos.ucla.edu/tcd/PREPRINTS/Gaffney-ClimDyn_Rev.pdf |
| Summary: | A probabilistic clustering technique is developed for classification of wintertime extratropical cyclone (ETC) tracks over the North Atlantic. We use a regression mixture model to describe the longitude-time and latitude–time propagation of the ETCs. A simple tracking algorithm is applied to 6-hourly mean sea-level pressure fields to obtain the tracks from either a general circulation model (GCM) or a reanalysis data set. Quadratic curves are found to provide the best description of the data. We select a three-cluster classification for both data sets, based on a mix of objective and subjective criteria. The track orientations in each of the clusters are broadly similar for the GCM and reanalyzed data; they are characterized by predominantly south-to-north (S–N), west-to-east (W–E), and southwest-to-northeast (SW–NE) tracking cyclones, respectively. The reanalysis cyclone tracks, however, are found to be much more tightly clustered geographically than those of the GCM. For the reanalysis data, a link is found between the occurrence of cyclones belonging to different clusters of trajectory-shape, and the phase of the North Atlantic Oscillation (NAO). The positive |
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