Km‐Scale Simulations of Mesoscale Convective Systems Over South America—A Feature Tracker Intercomparison
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- National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Univ. of Toulouse (France); Centre National de la Recherche Scientifique (CNRS), Toulouse (France)
- National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Earth Resources Technology (ERT), Inc., Laurel, MD (United States)
- Univ. of Sao Paulo (Brazil)
- Univ. of California, Santa Barbara, CA (United States)
Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth's water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object-based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluate MCSs in kilometer-scale simulations with observational-based MCSs over 3 years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS characteristics is less sensitive to the tracker formulation and all trackers agree that the model can capture MCS characteristics well across different South American climate zones. Dominant sources of uncertainty are the segmentation of cloud systems in space and time and the treatment of how MCSs are linked in time. Our results highlight that comparing MCS analyses that use different tracking algorithms is challenging. We provide general guidelines on how MCS characteristics compare between trackers to facilitate a more robust assessment of MCS statistics in future studies.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); National Aeronautics and Space Administration (NASA)
- Grant/Contract Number:
- AC05-76RL01830; AC02-05CH11231; 1852977; AGS 1937899; 80NSSC24K0012
- OSTI ID:
- 2337593
- Report Number(s):
- PNNL-SA-191681
- Journal Information:
- Journal of Geophysical Research. Atmospheres, Vol. 129, Issue 8; ISSN 2169-897X
- Publisher:
- American Geophysical UnionCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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