Articles | Volume 17, issue 15
https://doi.org/10.5194/gmd-17-6035-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6035-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
15 Aug 2024
Methods for assessment of models |
| 15 Aug 2024
| 15 Aug 2024
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Kelly M. Núñez Ocasio
CORRESPONDING AUTHOR
NSF National Center for Atmospheric Research, Boulder, CO, USA
Zachary L. Moon
NSF National Center for Atmospheric Research, Boulder, CO, USA
Earth Resources Technology (ERT), Inc., Laurel, MD, USA
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The Congo Basin has frequent organized thunderstorms producing much of the region’s rainfall, yet their development remains unclear due to limited data. Using a high-resolution global model, it shows the long-lasting storm is supported by vertical wind shear up to 400 km ahead, explaining up to 65 % of its variance, with the mid-level jet stream playing a role in maintaining the shear. The findings highlight the value of such model in data-sparse regions for examining storms and their impacts.
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The Congo Basin has frequent organized thunderstorms producing much of the region’s rainfall, yet their development remains unclear due to limited data. Using a high-resolution global model, it shows the long-lasting storm is supported by vertical wind shear up to 400 km ahead, explaining up to 65 % of its variance, with the mid-level jet stream playing a role in maintaining the shear. The findings highlight the value of such model in data-sparse regions for examining storms and their impacts.
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Forests influence air quality by altering ozone levels, but most air pollution models overlook canopy effects. Our study improves ozone predictions by incorporating forest canopy shading and turbulence into a widely used model. We found that tree cover reduces near-surface ozone by decreasing photolysis rates and diffusion inside canopy, resulting in lower ozone concentrations in densely forested areas. These findings enhance ozone surface prediction accuracy and improve air quality modeling.
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
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Volatile organic compounds (VOCs) fuel the production of air pollutants like ozone and particulate matter. The representation of VOC chemistry remains challenging due to its complexity in speciation and reactions. Here, we develop a chemical mechanism, RACM2B-VCP, that better represents VOC chemistry in urban areas such as Los Angeles. We also discuss the contribution of VOCs emitted from volatile chemical products and other anthropogenic sources to total VOC reactivity and O3.
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Short summary
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective...
