TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets

The Tracking Algorithm for Mesoscale Convective Systems (TAMS) is a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems (MCSs). TAMS was initially developed to analyze MCSs over Africa and their relation to African easterly waves using satellite-derived datasets....

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Published inGeoscientific Model Development Vol. 17; no. 15; pp. 6035 - 6049
Main Authors Núñez Ocasio, Kelly M., Moon, Zachary L.
Format Journal Article
LanguageEnglish
Published Katlenburg-Lindau Copernicus GmbH 15.08.2024
Copernicus Publications
Subjects
African easterly waves
Algorithms
Analysis
Automation
Classification
Cyclones
Datasets
Dynamic meteorology
Easterly waves
Mesoscale convective complexes
Mesoscale convective systems
Mesoscale phenomena
Precipitation
Propagation
Rain
Satellite tracking
Satellites
Storms
Tracking
Unstructured grids (mathematics)
Africa
Online AccessGet full text
ISSN1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
DOI10.5194/gmd-17-6035-2024

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Abstract The Tracking Algorithm for Mesoscale Convective Systems (TAMS) is a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems (MCSs). TAMS was initially developed to analyze MCSs over Africa and their relation to African easterly waves using satellite-derived datasets. This paper describes TAMS, an open-source MCS tracking and classifying Python-based package that can be used to study both observed and simulated MCSs. Each step of the algorithm is described with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this MCS tracker is its support for unstructured grids in the MCS identification stage and grid-independent tracking of MCSs, enabling application across various native modeling grids and satellite-derived products. A description of the available settings and helper functions is also provided. Finally, we share some of the current development goals for TAMS.
AbstractList The Tracking Algorithm for Mesoscale Convective Systems (TAMS) is a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems (MCSs). TAMS was initially developed to analyze MCSs over Africa and their relation to African easterly waves using satellite-derived datasets. This paper describes TAMS, an open-source MCS tracking and classifying Python-based package that can be used to study both observed and simulated MCSs. Each step of the algorithm is described with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this MCS tracker is its support for unstructured grids in the MCS identification stage and grid-independent tracking of MCSs, enabling application across various native modeling grids and satellite-derived products. A description of the available settings and helper functions is also provided. Finally, we share some of the current development goals for TAMS.
Audience Academic
Author Núñez Ocasio, Kelly M.
Moon, Zachary L.
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Snippet The Tracking Algorithm for Mesoscale Convective Systems (TAMS) is a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems...
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StartPage 6035
SubjectTerms African easterly waves
Algorithms
Analysis
Automation
Classification
Cyclones
Datasets
Dynamic meteorology
Easterly waves
Mesoscale convective complexes
Mesoscale convective systems
Mesoscale phenomena
Precipitation
Propagation
Rain
Satellite tracking
Satellites
Storms
Tracking
Unstructured grids (mathematics)
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Title TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
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https://doi.org/10.5194/gmd-17-6035-2024
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