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. A regression mixture model is used to describe the longitude-time and latitude-time propagation of the ETCs. Tracks are obtained from a simple tracking algor...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
| Published: |
2005
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| Subjects: | |
| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.59.8843 http://www.atmos.ucla.edu/tcd/PREPRINTS/GaffneyEtAl_MWRsubm_Jun05.pdf |
| Summary: | A probabilistic clustering technique is developed for classification of wintertime extratropical cyclone (ETC) tracks over the North Atlantic. A regression mixture model is used to describe the longitude-time and latitude-time propagation of the ETCs. Tracks are obtained from a simple tracking algorithm applied to 6-hourly mean sea-level pressure fields from either a general circulation model (GCM) or an observed data set. Three clusters of ETC behavior are identified in both cases; they are characterized by predominantly south-to-north (S-N), west-to-east (W-E), and southwest-to-northeast (SW-NE) tracking cyclones. Quadratic curves are found to provide the best description of the data. The results |
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