EMS Annual Meeting Abstracts
Vol. 23, EMS2026-799, 2026, updated on 22 Jun 2026
https://doi.org/10.5194/ems2026-799
EMS Annual Meeting 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 09 Sep, 09:45–10:00 (CEST)| Room Mission 1
Winter Convective Identification and Tracking in the Red Sea: An Algorithm Based on MTG-LI Lightning Observations
Mingyi Xu1,2,5, Martin Fullekrug3, Xiushu Qie4,6, Chenghong Gu3, Li Liang1,2,7, Hao Sun1,7,8, Cen Gao1,7,8, Jia Wang1,7,8, and Shiguang Qin1,7,8
Mingyi Xu et al.
  • 1Meteorological Observation Center, China Meteorological Administration, Beijing, China(104068199@qq.com)
  • 2Key Laboratory of Intelligent Meteorological Observation Technology, China Meteorological Administration, Beijing, China
  • 3University of Bath, Department of Electronic & Electrical Engineering, Bath, United Kingdom of Great Britain and Northern Irelan
  • 4State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
  • 5Shandong Institute of Meteorological Sciences, Jinan, China
  • 6College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, China
  • 7State Key Laboratory of Environment Characteristics and Effects for Near-space, Beijing, China
  • 8Engineering Technology Research Center for Meteorological Observation, China Meteorological Administration, Beijing, China

The deployment of the Lightning Imager (LI) aboard Europe’s Meteosat Third Generation (MTG) satellite has opened new opportunities for monitoring mixed convection over tropical–subtropical transitional maritime zones. The Red Sea experiences localized severe winter convection from November to April annually, characterized by short-duration thunderstorms and strong winds concentrated in its northern and central basins. This winter convection substantially affects maritime safety, coastal infrastructure, and regional climate regulation [1]. Frequent lightning with low precipitation efficiency (including dry thunderstorms) and frequent dust activity typify this region [2]. Focusing on winter convective systems in the Red Sea climatic transition zone (12°N–28°N), this study develops a specialized identification and tracking algorithm integrating MTG-LI lightning observations with cloud parameters from the MTG Flexible Combined Imager (FCI).

 

Key convective parameters are examined: Convective Available Potential Energy (CAPE), cloud-top temperature (CTT), cloud-top height, lightning frequency, and cloud-top cooling rate (CTC)—the latter quantifying CTT change over 10–30-minute intervals to capture convective development dynamics. For storm tracking, we establish nonlinear response thresholds for the lightning frequency–CTC relationship specific to the Red Sea transition zone, constructing a multi-threshold collaborative model. Convective storms are identified when CAPE > 1000 J kg⁻¹, CTT < −50°C, and lightning frequency exceeds 10 flashes per 10 minutes. We then integrate optical flow with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for dynamic storm cell tracking. Optical flow computes displacement vectors of cloud-top features between consecutive time steps to derive storm motion vectors, while DBSCAN clusters spatially dense lightning regions to pinpoint storm core locations and extents.

 

This study establishes a winter convective identification algorithm for the Red Sea, advancing methodologies for tropical–subtropical transition zones. The multi‑parameter fusion approach reduces false‑alarm rates inherent in single‑indicator systems, with transferable applications for other global transition seas.

 

Acknowledgment

This work was jointly supported by the Open Project of Key Laboratory of Intelligent Meteorological Observation Technology of China Meteorological Administration under Grant ZNGC2025MS26, and the Science Funds of Changdao National Climatic Observatory under Grant 2025cdkfz05.

 

References

[1] Almazroui M. Climatology of the Red Sea tropical cyclones from 1975 to 2020[J]. International Journal of Climatology, 2021, 41(8): 4039-4054.
[2] Virts K S, Wallace J M. Seasonal and regional variations in the lightning diurnal cycle over the Red Sea[J]. Journal of Geophysical Research: Atmospheres, 2020, 125(8): e2019JD032005.

How to cite: Xu, M., Fullekrug, M., Qie, X., Gu, C., Liang, L., Sun, H., Gao, C., Wang, J., and Qin, S.: Winter Convective Identification and Tracking in the Red Sea: An Algorithm Based on MTG-LI Lightning Observations, EMS Annual Meeting 2026, Utrecht, Netherlands, 6–11 Sep 2026, EMS2026-799, https://doi.org/10.5194/ems2026-799, 2026.