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spelling ftecoleponts:oai:HAL:hal-04110181v1 2024-06-09T07:48:05+00:00 Probabilistic clustering of extratropical cyclones using regression mixture models Gaffney, Scott J. Robertson, Andrew W. Smyth, Padhraic Camargo, Suzana J. Ghil, Michael Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) 2007 https://hal.science/hal-04110181 https://doi.org/10.1007/s00382-007-0235-z en eng HAL CCSD Springer Verlag info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-007-0235-z hal-04110181 https://hal.science/hal-04110181 BIBCODE: 2007ClDy.29.423G doi:10.1007/s00382-007-0235-z ISSN: 0930-7575 EISSN: 1432-0894 Climate Dynamics https://hal.science/hal-04110181 Climate Dynamics, 2007, 29, pp.423-440. ⟨10.1007/s00382-007-0235-z⟩ [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2007 ftecoleponts https://doi.org/10.1007/s00382-007-0235-z 2024-05-16T12:32:04Z International audience 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. Article in Journal/Newspaper North Atlantic North Atlantic oscillation École des Ponts ParisTech: HAL Climate Dynamics 29 4 423 440
institution Open Polar
collection École des Ponts ParisTech: HAL
op_collection_id ftecoleponts
language English
topic [SDU]Sciences of the Universe [physics]
spellingShingle [SDU]Sciences of the Universe [physics]
Gaffney, Scott J.
Robertson, Andrew W.
Smyth, Padhraic
Camargo, Suzana J.
Ghil, Michael
Probabilistic clustering of extratropical cyclones using regression mixture models
topic_facet [SDU]Sciences of the Universe [physics]
description International audience 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.
author2 Laboratoire de Météorologie Dynamique (UMR 8539) (LMD)
Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris
École normale supérieure - Paris (ENS-PSL)
Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL)
Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)
format Article in Journal/Newspaper
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 HAL CCSD
publishDate 2007
url https://hal.science/hal-04110181
https://doi.org/10.1007/s00382-007-0235-z
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_source ISSN: 0930-7575
EISSN: 1432-0894
Climate Dynamics
https://hal.science/hal-04110181
Climate Dynamics, 2007, 29, pp.423-440. ⟨10.1007/s00382-007-0235-z⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-007-0235-z
hal-04110181
https://hal.science/hal-04110181
BIBCODE: 2007ClDy.29.423G
doi:10.1007/s00382-007-0235-z
op_doi https://doi.org/10.1007/s00382-007-0235-z
container_title Climate Dynamics
container_volume 29
container_issue 4
container_start_page 423
op_container_end_page 440
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