A comparison of two identification and tracking methods for polar lows
In this study, we compare two different cyclone-tracking algorithms to detect North Atlantic polar lows, which are very intense mesoscale cyclones. Both approaches include spatial filtering, detection, tracking and constraints specific to polar lows. The first method uses digital bandpass-filtered m...
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ftdoajarticles:oai:doaj.org/article:65effa7e88f9491da03d0088c01357d3 2023-05-15T17:31:04+02:00 A comparison of two identification and tracking methods for polar lows Hans Von Storch Frauke Feser Kevin I. Hodges Matthias Zahn Lan Xia 2012-02-01T00:00:00Z https://doi.org/10.3402/tellusa.v64i0.17196 https://doaj.org/article/65effa7e88f9491da03d0088c01357d3 EN eng Stockholm University Press http://www.tellusa.net/index.php/tellusa/article/view/17196/pdf_1 https://doaj.org/toc/0280-6495 https://doaj.org/toc/1600-0870 doi:10.3402/tellusa.v64i0.17196 0280-6495 1600-0870 https://doaj.org/article/65effa7e88f9491da03d0088c01357d3 Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 64, Iss 0, Pp 1-11 (2012) cyclone tracking algorithm polar lows spatial filter North Atlantic Oceanography GC1-1581 Meteorology. Climatology QC851-999 article 2012 ftdoajarticles https://doi.org/10.3402/tellusa.v64i0.17196 2022-12-30T23:53:30Z In this study, we compare two different cyclone-tracking algorithms to detect North Atlantic polar lows, which are very intense mesoscale cyclones. Both approaches include spatial filtering, detection, tracking and constraints specific to polar lows. The first method uses digital bandpass-filtered mean sea level pressure (MSLP) fields in the spatial range of 200–600 km and is especially designed for polar lows. The second method also uses a bandpass filter but is based on the discrete cosine transforms (DCT) and can be applied to MSLP and vorticity fields. The latter was originally designed for cyclones in general and has been adapted to polar lows for this study. Both algorithms are applied to the same regional climate model output fields from October 1993 to September 1995 produced from dynamical downscaling of the NCEP/NCAR reanalysis data. Comparisons between these two methods show that different filters lead to different numbers and locations of tracks. The DCT is more precise in scale separation than the digital filter and the results of this study suggest that it is more suited for the bandpass filtering of MSLP fields. The detection and tracking parts also influence the numbers of tracks although less critically. After a selection process that applies criteria to identify tracks of potential polar lows, differences between both methods are still visible though the major systems are identified in both. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Tellus A: Dynamic Meteorology and Oceanography 64 1 17196 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
cyclone tracking algorithm polar lows spatial filter North Atlantic Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
spellingShingle |
cyclone tracking algorithm polar lows spatial filter North Atlantic Oceanography GC1-1581 Meteorology. Climatology QC851-999 Hans Von Storch Frauke Feser Kevin I. Hodges Matthias Zahn Lan Xia A comparison of two identification and tracking methods for polar lows |
topic_facet |
cyclone tracking algorithm polar lows spatial filter North Atlantic Oceanography GC1-1581 Meteorology. Climatology QC851-999 |
description |
In this study, we compare two different cyclone-tracking algorithms to detect North Atlantic polar lows, which are very intense mesoscale cyclones. Both approaches include spatial filtering, detection, tracking and constraints specific to polar lows. The first method uses digital bandpass-filtered mean sea level pressure (MSLP) fields in the spatial range of 200–600 km and is especially designed for polar lows. The second method also uses a bandpass filter but is based on the discrete cosine transforms (DCT) and can be applied to MSLP and vorticity fields. The latter was originally designed for cyclones in general and has been adapted to polar lows for this study. Both algorithms are applied to the same regional climate model output fields from October 1993 to September 1995 produced from dynamical downscaling of the NCEP/NCAR reanalysis data. Comparisons between these two methods show that different filters lead to different numbers and locations of tracks. The DCT is more precise in scale separation than the digital filter and the results of this study suggest that it is more suited for the bandpass filtering of MSLP fields. The detection and tracking parts also influence the numbers of tracks although less critically. After a selection process that applies criteria to identify tracks of potential polar lows, differences between both methods are still visible though the major systems are identified in both. |
format |
Article in Journal/Newspaper |
author |
Hans Von Storch Frauke Feser Kevin I. Hodges Matthias Zahn Lan Xia |
author_facet |
Hans Von Storch Frauke Feser Kevin I. Hodges Matthias Zahn Lan Xia |
author_sort |
Hans Von Storch |
title |
A comparison of two identification and tracking methods for polar lows |
title_short |
A comparison of two identification and tracking methods for polar lows |
title_full |
A comparison of two identification and tracking methods for polar lows |
title_fullStr |
A comparison of two identification and tracking methods for polar lows |
title_full_unstemmed |
A comparison of two identification and tracking methods for polar lows |
title_sort |
comparison of two identification and tracking methods for polar lows |
publisher |
Stockholm University Press |
publishDate |
2012 |
url |
https://doi.org/10.3402/tellusa.v64i0.17196 https://doaj.org/article/65effa7e88f9491da03d0088c01357d3 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Tellus: Series A, Dynamic Meteorology and Oceanography, Vol 64, Iss 0, Pp 1-11 (2012) |
op_relation |
http://www.tellusa.net/index.php/tellusa/article/view/17196/pdf_1 https://doaj.org/toc/0280-6495 https://doaj.org/toc/1600-0870 doi:10.3402/tellusa.v64i0.17196 0280-6495 1600-0870 https://doaj.org/article/65effa7e88f9491da03d0088c01357d3 |
op_doi |
https://doi.org/10.3402/tellusa.v64i0.17196 |
container_title |
Tellus A: Dynamic Meteorology and Oceanography |
container_volume |
64 |
container_issue |
1 |
container_start_page |
17196 |
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1766128380541927424 |