East Asia meso α and β MCS Tracking Dataset (2001–2023 JJAS): Observational (IMERG, Merged IR) and CPM (WRF) Using PyFLEXTRKR

OverviewThis dataset provides long-term mesoscale convective system (MCS) tracking results over East Asia for the period 2001–2023 (June–September). The dataset includes MCS characteristics tracked at the meso α and β scales using observational datasets (IMERG, Merged IR) and a convection-permitting model (CPM) simulation with the Weather Research and Forecasting (WRF) model. Tracking MethodologyThe MCS tracking and feature extraction were conducted using PyFLEXTRKR (Feng et al., 2023), an open-source Python-based flexible tracking algorithm. Details on PyFLEXTRKR can be found at: https://github.com/FlexTRKR/PyFLEXTRKR Data Contents Tracking Configurations: Configuration files used for MCS tracking. Tracking Statistics: MCS properties and statistics generated from PyFLEXTRKR. Monthly-Averaged Tracking Results: Aggregated MCS statistics for each month. Usage & CitationThis dataset is intended for climate and atmospheric science research, particularly for analyzing long-term MCS variability in East Asia. The dataset is associated with an ongoing research study. If you use this dataset, please cite the following paper describing the dataset and its analysis: Mun, T., Cha, D.-H., Park, H., Park, J., Lee, M.-I., Son, S.-W., & Min, S.-K. (2025). Spatiotemporal Characteristics of Mesoscale Convective Systems over East Asian Monsoon Region Simulated by a Convection-Permitting Model. Journal of Geophysical Research: Atmospheres, 130, e2025JD044820, https://doi.org/10.1029/2025JD044820 Please also acknowledge the tracking methodology: Feng, Z., J. Hardin, H. C. Barnes, J. Li, L. R. Leung, A. Varble, and Z. Zhang, 2023: PyFLEXTRKR: A flexible feature tracking Python software for convective cloud analysis. Geoscientific Model Development, 16, 2753–2776, https://doi.org/10.5194/gmd-16-2753-2023. Contact InformationFor inquiries regarding this dataset, please contact [[e-mail]]