tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of dat...
| প্রধান লেখক: | , , , , , , , , , , , , , , , , |
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| বিন্যাস: | Journal article |
| ভাষা: | English |
| প্রকাশিত: |
European Geosciences Union
2024
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| _version_ | 1826317070278590464 |
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| author | Sokolowsky, GA Freeman, SW Jones, WK Kukulies, J Senf, F Marinescu, PJ Heikenfeld, M Brunner, KN Bruning, EC Collis, SM Jackson, RC Leung, GR Pfeifer, N Raut, BA Saleeby, SM Stier, P van den Heever, SC |
| author_facet | Sokolowsky, GA Freeman, SW Jones, WK Kukulies, J Senf, F Marinescu, PJ Heikenfeld, M Brunner, KN Bruning, EC Collis, SM Jackson, RC Leung, GR Pfeifer, N Raut, BA Saleeby, SM Stier, P van den Heever, SC |
| author_sort | Sokolowsky, GA |
| collection | OXFORD |
| description | There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed. |
| first_indexed | 2025-02-19T04:32:43Z |
| format | Journal article |
| id | oxford-uuid:25e5b2d1-c3ed-4bf7-a353-664d13abdb1b |
| institution | University of Oxford |
| language | English |
| last_indexed | 2025-02-19T04:32:43Z |
| publishDate | 2024 |
| publisher | European Geosciences Union |
| record_format | dspace |
| spelling | oxford-uuid:25e5b2d1-c3ed-4bf7-a353-664d13abdb1b2025-01-17T16:30:25Ztobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomenaJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:25e5b2d1-c3ed-4bf7-a353-664d13abdb1bEnglishSymplectic ElementsEuropean Geosciences Union2024Sokolowsky, GAFreeman, SWJones, WKKukulies, JSenf, FMarinescu, PJHeikenfeld, MBrunner, KNBruning, ECCollis, SMJackson, RCLeung, GRPfeifer, NRaut, BASaleeby, SMStier, Pvan den Heever, SCThere is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed. |
| spellingShingle | Sokolowsky, GA Freeman, SW Jones, WK Kukulies, J Senf, F Marinescu, PJ Heikenfeld, M Brunner, KN Bruning, EC Collis, SM Jackson, RC Leung, GR Pfeifer, N Raut, BA Saleeby, SM Stier, P van den Heever, SC tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title | tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title_full | tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title_fullStr | tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title_full_unstemmed | tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title_short | tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena |
| title_sort | tobac v1 5 introducing fast 3d tracking splits and mergers and other enhancements for identifying and analysing meteorological phenomena |
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