| Autor: |
Prein, Andreas F.1 (AUTHOR) prein@ucar.edu, Feng, Zhe2 (AUTHOR), Fiolleau, Thomas3 (AUTHOR), Moon, Zachary L.1,4 (AUTHOR), Núñez Ocasio, Kelly M.1 (AUTHOR), Kukulies, Julia1 (AUTHOR), Roca, Rémy3 (AUTHOR), Varble, Adam C.2 (AUTHOR), Rehbein, Amanda5 (AUTHOR), Liu, Changhai1 (AUTHOR), Ikeda, Kyoko1 (AUTHOR), Mu, Ye6 (AUTHOR), Rasmussen, Roy M.1 (AUTHOR) |
| Předmět: |
|
| Zdroj: |
Journal of Geophysical Research. Atmospheres. Apr2024, Vol. 129 Issue 8, p1-25. 25p. |
| Abstrakt: |
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. Plain Language Summary: Large clusters of thunderstorms, called mesoscale convective systems (MCSs), are important in Earth's water and energy cycle including extreme weather events like large hail, strong winds, and heavy rainfall. To better understand MCSs, researchers have developed computer programs called MCS trackers that can identify and track MCSs throughout their lifespan. Different MCS tracking algorithms have been created and used for various purposes, but little is known about how sensitive the results are to the specific algorithm used. This study aims to address this knowledge gap by comparing six different MCS tracking algorithms and assessing their impact on the characteristics of MCSs in South America. We also analyze how sensitive high‐resolution climate simulation evaluations are to the used tracking algorithm. The results show that the choice of tracking algorithm has a large influence on various characteristics of MCSs, such as their frequency, size, duration, and importance to the regional water cycle. However, when it comes to evaluating simulated MCS characteristics, the choice of tracker has less impact. Importantly, all trackers agree that the high‐resolution climate model accurately represents MCS characteristics across different climate zones in South America. Key Points: Mesoscale convective system (MCS) tracker formulation has a profound impact on MCS characteristics such as their frequencies, size, duration, and precipitation volumeTracker formulation uncertainties are smaller for evaluating modeled MCS characteristics but larger for MCS frequency statisticsMCS tracking studies have to be compared cautiously, particularly when different tracking algorithms and MCS classifications are used [ABSTRACT FROM AUTHOR] |
| Databáze: |
GreenFILE |
| Externí odkaz: |
|
Plný text