EGU25-6767, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-6767
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Tuesday, 29 Apr, 14:00–15:45 (CEST), Display time Tuesday, 29 Apr, 08:30–18:00
 
vPoster spot 5, vP5.9
Convection Initiation Identification and The Construction of A High-value Dataset Using the Fengyun-4A Satellite
Lili Peng1,2,3, Chengzhi Ye1,2,3, and Xiaofeng Ou1,2,3
Lili Peng et al.
  • 1Hunan Meteorological Research Institute, Changsha, China
  • 2Hunan Key Laboratory of Meteorological Disaster Prevention and Reduction, Changsha, China
  • 3Key Laboratory of High Impact Weather China Meteorological Administration, Changsha, China

Based on the traditional satellite-based convective initiation (CI) detection method, an improved algorithm for the identification and tracking of CIs using satellite data has been proposed. This algorithm then undergoes spatio-temporal matching with ground-based observation data such as radar and precipitation data. Incorporating experts domain knowledge, the algorithm utilizes a subjective-objective interactive approach to complete the verification and calibration of the satellite-drived CI identification results. This process results in a high-resolution annotation dataset of convective initiation that can be used for detection and forecasting of CI and artificial intelligence models.

Firstly, within a spatial-temporal window of 30 minutes before and after the satellite CIs trigger time and a radius of 20km, the satellite-derived CIs are matched with radar-identified CIs. Additionally, within a spatial-temporal window of 60 minutes after the satellite CI trigger and extending 2km outside the CI cloud clusters movement zone, the satellite-derived CIs are also matched with precipitation data. The two matching results are combined to form a comprehensive identification of CIs. Furthermore, using a calibration system and a back-to-back verification method by forecasters, the CI annotation results are revised, resulting in a high-resolution and reliable CI annotation dataset.

Using this methodology, a high spatio-temporal resolution CI dataset was established for the years 2018-2023, which allowed for the statistical analysis of CI distributions across different precipitation levels in each month. The highest proportion of CI events occurred in August, followed by July. Among these, CI events with moderate precipitation accounted for 46.2%, weak precipitation accounted for 34.4%, and strong precipitation accounted for 19.3%.

It can be seen that there is a noticeable northward shift in the occurrence of CI events, especially those associated with heavy precipitation, from April to August. In April, these events are mainly concentrated in a few provinces in the central and southern parts of the country. Subsequently, they gradually expand from south to north, covering the entire central and eastern research area by August. In September, they retreat back to the central and southern regions. This spatial evolution pattern of CI events once again verifies that the occurrence of severe convection events is closely related to the position changes of the Intertropical Convergence Zone (ITCZ) and the monsoon.The frequency of CI occurrences has also been proven to peak between 11 a.m. and 3 p.m., regardless of precipitation intensity.

How to cite: Peng, L., Ye, C., and Ou, X.: Convection Initiation Identification and The Construction of A High-value Dataset Using the Fengyun-4A Satellite, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6767, https://doi.org/10.5194/egusphere-egu25-6767, 2025.