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...
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ftdatacite:10.7916/d8n01h5r 2023-05-15T17:28:53+02:00 Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models Gaffney, Scott J. Robertson, Andrew W. Smyth, Padhraic Camargo, Suzana J. Ghil, Michael 2007 https://dx.doi.org/10.7916/d8n01h5r https://academiccommons.columbia.edu/doi/10.7916/D8N01H5R unknown Columbia University https://dx.doi.org/10.1007/s00382-007-0235-z Cyclone tracks North Atlantic oscillation Meteorology Text Articles article-journal ScholarlyArticle 2007 ftdatacite https://doi.org/10.7916/d8n01h5r https://doi.org/10.1007/s00382-007-0235-z 2021-11-05T12:55:41Z 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 phase of the NAO is associated with the SW–NE oriented cluster, whose tracks are relatively straight and smooth (with cyclones that are typically faster, more intense, and of longer duration). The negative NAO phase is associated with more-erratic W–E tracks, with typically weaker and slower-moving cyclones. The S–N cluster is accompanied by a more transient geopotential trough over the western North Atlantic. No clear associations are found in the case of the GCM composites. The GCM is able to capture cyclone tracks of quite realistic orientation, as well as subtle associated features of cyclone intensity, speed and lifetimes. The clustering clearly highlights, though, the presence of serious systematic errors in the GCM’s simulation of ETC behavior. Text North Atlantic North Atlantic oscillation DataCite Metadata Store (German National Library of Science and Technology) |
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Cyclone tracks North Atlantic oscillation Meteorology |
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Cyclone tracks North Atlantic oscillation Meteorology Gaffney, Scott J. Robertson, Andrew W. Smyth, Padhraic Camargo, Suzana J. Ghil, Michael Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
topic_facet |
Cyclone tracks North Atlantic oscillation Meteorology |
description |
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 phase of the NAO is associated with the SW–NE oriented cluster, whose tracks are relatively straight and smooth (with cyclones that are typically faster, more intense, and of longer duration). The negative NAO phase is associated with more-erratic W–E tracks, with typically weaker and slower-moving cyclones. The S–N cluster is accompanied by a more transient geopotential trough over the western North Atlantic. No clear associations are found in the case of the GCM composites. The GCM is able to capture cyclone tracks of quite realistic orientation, as well as subtle associated features of cyclone intensity, speed and lifetimes. The clustering clearly highlights, though, the presence of serious systematic errors in the GCM’s simulation of ETC behavior. |
format |
Text |
author |
Gaffney, Scott J. Robertson, Andrew W. Smyth, Padhraic Camargo, Suzana J. Ghil, Michael |
author_facet |
Gaffney, Scott J. Robertson, Andrew W. Smyth, Padhraic Camargo, Suzana J. Ghil, Michael |
author_sort |
Gaffney, Scott J. |
title |
Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
title_short |
Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
title_full |
Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
title_fullStr |
Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
title_full_unstemmed |
Probabilistic Clustering of Extratropical Cyclones Using Regression Mixture Models |
title_sort |
probabilistic clustering of extratropical cyclones using regression mixture models |
publisher |
Columbia University |
publishDate |
2007 |
url |
https://dx.doi.org/10.7916/d8n01h5r https://academiccommons.columbia.edu/doi/10.7916/D8N01H5R |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
https://dx.doi.org/10.1007/s00382-007-0235-z |
op_doi |
https://doi.org/10.7916/d8n01h5r https://doi.org/10.1007/s00382-007-0235-z |
_version_ |
1766122018050146304 |