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The semi-diurnal cycle of deep convective systems over Eastern China and its surrounding seas in summer based on an automatic tracking algorithm

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Abstract

Deep convective systems (DCSs) are associated with severe weather events and can affect regional and global climate. To study the semi-diurnal variation of DCSs over Eastern China and its surrounding seas in summer, we modified the Tracking of Organized Convection Algorithm through a 3-D segmentatioN (TOOCAN) by employing Himawari-8 operational cloud property (CLP) products instead of original infrared images, and renamed the algorithm as TOOCAN-CLP. The DCSs detected over land and sea are divided into small-, medium-, and large-sized classes based on the convective core equivalent radius. The small and medium-sized DCSs over land exhibit a maximum occurrence in the afternoon, which is associated with local thermal instability and sea breeze circulation. The occurrence of small DCSs over the tropical sea areas varies analogously to that of small continental DCSs but with a smaller amplitude. However, medium-sized DCSs over the sea, which account for the majority of DCSs over the sea, exhibit weak semi-diurnal variability. Large DCSs over inland China and its surrounding seas tend to initiate at night and decay in the daytime. The generation of large DCSs over inland China at night is mainly due to the enhanced transport of warm and moist air by strong large-scale prevailing southerly or southwesterly winds, while the large offshore DCSs accompanied by heavy rainfall is closely associated with the interaction between local offshore breeze and large-scale monsoon flows, as well as gravity waves.

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Acknowledgements

The work was supported by the National Key R&D Program of China (2019YFC1510103), the National Natural Science Foundation of China (41675003, 41705039). We thank the anonymous reviewers for their constructive comments and Professor Zhaohua Wu for his editorial efforts. We also thank Dr. Fuchang Wang for his help in revising the manuscript. We gratefully acknowledge the P-Tree System, Japan Aerospace Exploration Agency (JAXA) for providing Himawari-8/Advanced Himawari Imager (H-8/AHI) level-2 operational cloud products. The Integrated Multi-satellitE Retrievals for GPM (IMERG) data were provided by the NASA/Goddard Space Flight Center and Precipitation Processing System (PPS), which develop and compute IMERG as a contribution to GPM constellation satellites, and were archived at the NASA Goddard Earth Science Data and Information System Center (GES DISC). We also acknowledge the Japanese 55-year Reanalysis (JRA-55) conducted by the Japan Meteorological Agency (JMA), and the fifth generation ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis (ERA5) produced by ECMWF.

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  1. Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

    Wenwen Li & Yueyue Yu

  2. Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China

    Feng Zhang, Guoyin Wang & Yijun Zhang

  3. Shanghai Qi Zhi Institute, Shanghai, 200232, China

    Feng Zhang

  4. Center for Atmospheric and Oceanic Studies, Graduate School of Science, Tohoku University, Sendai, Japan

    Hironobu Iwabuchi

  5. Shanghai Ecological Forecasting and Remote Sensing Center, Shanghai, China

    Zhongping Shen

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Li, W., Zhang, F., Yu, Y. et al. The semi-diurnal cycle of deep convective systems over Eastern China and its surrounding seas in summer based on an automatic tracking algorithm. Clim Dyn 56, 357–379 (2021). https://doi.org/10.1007/s00382-020-05474-1

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