the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Mar 2024
TAMS: A Tracking, Classifying, and Variable-Assigning Algorithm for Mesoscale Convective Systems in Simulated and Satellite-Derived Datasets
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 v2.0, 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.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-259', Julia Kukulies, 30 Mar 2024
This paper describes a novel tracking algorithm that was originally developed to track MCSs over Africa,
and has been enhanced to a more general tool to track MCSs in large observational and model datasets.
The manuscript is well-written and the tracking steps are easy to understand based on the figures
presented. Another strength of the paper is that many specific examples are given which help the reader
to set the technical features into a scientific context and better understand the implications of different
tracking options. An outstanding feature of the TAMS algorithm is its capability to work with unstructured
grids, which has become more and more important with the advent of global k-scale models. In addition,
TAMS provides the possibility to combine tracked MCS features with any other variable or dataset, which
is useful to better understand the processes of convective organization from multiple angles. The tracking
tool should therefore be of high interest to the weather and climate research community. I recommend the
publication of this manuscript after addressing some minor issues (see my detailed comments and suggestions in the attached document) -
RC2: 'Comment on egusphere-2024-259', Anonymous Referee #2, 01 May 2024
The manuscript introduces the Python-based version of the Tracking Algorithm for Mesoscale Convective Systems (TAMS), TAMS v2.0. In addition to describing the algorithm, the authors provide some examples to help readers understand it. The topic is within the scope of GMD, and the tool is helpful in the scientific community. However, the manuscript has three significant limitations and cannot be published in its current form.
Major comments
- The algorithm introduction involves too many software functions (e.g., tams.identify, ctt_core_threshold, etc.) but lacks a scientific description. It makes the manuscript look more like a user guide or technical documentation than a scientific paper. I strongly suggest the authors rewrite the algorithm's description in a more general way: tell the readers the principles of the algorithm but not list those built-in functions. For example, for ctt_core_threshold, please tell the readers the relevant physical variable but not this type of acronym used in the tool.
- I don’t find enough updates in TAMS v2.0 compared to TAMS v1.0. However, since TAMS v2.0 is a Python-based and open-source software and TAMS v1.0 has not been published independently, describing TAMS v2.0 in a separate paper is acceptable. I suggest the authors avoid describing TAMS v1.0 too much or remove the version label entirely. The Python-based TAMS can be an independent tool.
- The tool is designed to track MCSs. However, the tracked MCSs contain systems lasting only a few hours. Are they really MCSs? I think the tool tracks all convective systems but not just MCSs. Please clarify the terms throughout the manuscript.
Minor comments
Lines 33: How about “identifies and tracks cloud clusters using IR and a corresponding graph node via the area overlap method”?
Line 67: “However, before discussing the Python-based TAMS, we will review the first version of TAMS (TAMS v1.0), which is written in MATLAB”?
Lines 86-87: I’m afraid I have to disagree that using IMERG is an advantage of TAMS. The precipitation assignment is the last step of TAMS v1.0, which doesn’t affect the tracking algorithm. To my knowledge, FLEXTRKR used Stage IV over the United States, which had a resolution of 4 km, and IMERG for the global MCS dataset.
Line 88: “MCSs in Africa”?
Line 104: Delete “was written in MATLAB, and it”?
Line 113: Delete the first sentence.
Line 156: Correct the citation format and the full name of IFS.
Line 157: Correct the citation format.
Line 168: “from the regridded MPAS data”?
Line 170: What do you mean by current and previous CTTs?
Lines 187-188: What do you mean here?
Figure 5 caption: Correct the description for panels in different rows and columns. Similar to Figure 6. Please add a legend for the color shading in Figure 6.
Lines 208-211: What is the minimum duration that an MCS can have? Can a track be considered an MCS if it lasts only 1 hour? Or do you only consider MCCs and CCCs as MCSs? Please rewrite these confusing sentences.
Line 225: If so, can they still be considered MCSs?
Citation: https://doi.org/10.5194/egusphere-2024-259-RC2 - EC1: 'Reviewer 3 comments', Peter Caldwell, 15 May 2024
- AC1: 'AC Response', Kelly Núñez Ocasio, 10 Jun 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-259', Julia Kukulies, 30 Mar 2024
This paper describes a novel tracking algorithm that was originally developed to track MCSs over Africa,
and has been enhanced to a more general tool to track MCSs in large observational and model datasets.
The manuscript is well-written and the tracking steps are easy to understand based on the figures
presented. Another strength of the paper is that many specific examples are given which help the reader
to set the technical features into a scientific context and better understand the implications of different
tracking options. An outstanding feature of the TAMS algorithm is its capability to work with unstructured
grids, which has become more and more important with the advent of global k-scale models. In addition,
TAMS provides the possibility to combine tracked MCS features with any other variable or dataset, which
is useful to better understand the processes of convective organization from multiple angles. The tracking
tool should therefore be of high interest to the weather and climate research community. I recommend the
publication of this manuscript after addressing some minor issues (see my detailed comments and suggestions in the attached document) -
RC2: 'Comment on egusphere-2024-259', Anonymous Referee #2, 01 May 2024
The manuscript introduces the Python-based version of the Tracking Algorithm for Mesoscale Convective Systems (TAMS), TAMS v2.0. In addition to describing the algorithm, the authors provide some examples to help readers understand it. The topic is within the scope of GMD, and the tool is helpful in the scientific community. However, the manuscript has three significant limitations and cannot be published in its current form.
Major comments
- The algorithm introduction involves too many software functions (e.g., tams.identify, ctt_core_threshold, etc.) but lacks a scientific description. It makes the manuscript look more like a user guide or technical documentation than a scientific paper. I strongly suggest the authors rewrite the algorithm's description in a more general way: tell the readers the principles of the algorithm but not list those built-in functions. For example, for ctt_core_threshold, please tell the readers the relevant physical variable but not this type of acronym used in the tool.
- I don’t find enough updates in TAMS v2.0 compared to TAMS v1.0. However, since TAMS v2.0 is a Python-based and open-source software and TAMS v1.0 has not been published independently, describing TAMS v2.0 in a separate paper is acceptable. I suggest the authors avoid describing TAMS v1.0 too much or remove the version label entirely. The Python-based TAMS can be an independent tool.
- The tool is designed to track MCSs. However, the tracked MCSs contain systems lasting only a few hours. Are they really MCSs? I think the tool tracks all convective systems but not just MCSs. Please clarify the terms throughout the manuscript.
Minor comments
Lines 33: How about “identifies and tracks cloud clusters using IR and a corresponding graph node via the area overlap method”?
Line 67: “However, before discussing the Python-based TAMS, we will review the first version of TAMS (TAMS v1.0), which is written in MATLAB”?
Lines 86-87: I’m afraid I have to disagree that using IMERG is an advantage of TAMS. The precipitation assignment is the last step of TAMS v1.0, which doesn’t affect the tracking algorithm. To my knowledge, FLEXTRKR used Stage IV over the United States, which had a resolution of 4 km, and IMERG for the global MCS dataset.
Line 88: “MCSs in Africa”?
Line 104: Delete “was written in MATLAB, and it”?
Line 113: Delete the first sentence.
Line 156: Correct the citation format and the full name of IFS.
Line 157: Correct the citation format.
Line 168: “from the regridded MPAS data”?
Line 170: What do you mean by current and previous CTTs?
Lines 187-188: What do you mean here?
Figure 5 caption: Correct the description for panels in different rows and columns. Similar to Figure 6. Please add a legend for the color shading in Figure 6.
Lines 208-211: What is the minimum duration that an MCS can have? Can a track be considered an MCS if it lasts only 1 hour? Or do you only consider MCCs and CCCs as MCSs? Please rewrite these confusing sentences.
Line 225: If so, can they still be considered MCSs?
Citation: https://doi.org/10.5194/egusphere-2024-259-RC2 - EC1: 'Reviewer 3 comments', Peter Caldwell, 15 May 2024
- AC1: 'AC Response', Kelly Núñez Ocasio, 10 Jun 2024
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Cited
Kelly M. Núñez Ocasio
Zachary L. Moon
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3544 KB) - Metadata XML