Cao Linxi, Wu Mengwen, Luo Yali, Chen Feng. 2024. An Objective Identification Algorithm and Spatiotemporal Distributions of Convection Initiation over the Urban Agglomeration Region in Jiangsu-and-Shanghai during the Post-Meiyu Period. Acta Meteorologica Sinica, 82(X):1-14. DOI: 10.11676/qxxb2024.20230168
Citation: Cao Linxi, Wu Mengwen, Luo Yali, Chen Feng. 2024. An Objective Identification Algorithm and Spatiotemporal Distributions of Convection Initiation over the Urban Agglomeration Region in Jiangsu-and-Shanghai during the Post-Meiyu Period. Acta Meteorologica Sinica, 82(X):1-14. DOI: 10.11676/qxxb2024.20230168

An Objective Identification Algorithm and Spatiotemporal Distributions of Convection Initiation over the Urban Agglomeration Region in Jiangsu-and-Shanghai during the Post-Meiyu Period

  • In this study, an objective algorithm to identify convection initiation (CI) based on weather radar observations is developed. In this algorithm, a convective cell is defined as a continuous area of strong radar echo (reflectivity factor reaching 35 dBz). The presence of a convective cell is identified as CI if two criteria are met: (1) no convective cells exist around the convective cell in a 30 min period prior to its presence; (2) this convective cell lasts for at least 20 min. This algorithm is applied to the urban agglomeration region over Jiangsu-and-Shanghai during the post-Meiyu period (from the end of the Meiyu season to 31 August, and excluding days influenced by tropical cyclones). Based on the results, A CI database with high spatiotemporal resolutions (10 min, 1 km) over the region for the 2019—2022 post-Meiyu periods is constructed. The sensitivity of the CI identification to two parameters in the algorithm is investigated by comparing three experiments in a case study and also based on statistics analysis. When the radius of the area (R), which is used to determine whether the convective echo is the first occurrence, is set to 10 km, whether the minimum area of the convective echo ( Amin) is set to 4 km2 or 2 km2 (Test1, Test2) does not significantly influence the CI identification results. Both experiments can identify the complex situations with continuous and adjacent CI events, with Test1 being able to identify 83% of Test2's CI events. The statistical characteristics of CI events identified by the two experiments are essentially the same, including the number of CI days, daily CI numbers, the distribution of CI high-occurrence frequency areas, and the diurnal variation of CI occurrence frequency. When R is set to 30 km (with Amin of 4 km2; Test3), only 36% of the CI events identified in Test1 can be identified in Test3. The insufficient number of identified CI events results in significant differences in spatial distribution and diurnal variation of CI occurrence compared to those from Test1 and Test2. The results indicate that there are three subregions of high occurrence frequency of CI in the analysis region, i.e., the "Shanghai-Suzhou-Wuxi-Changzhou-Nanjing" city belt along the Yangtze river, from northern Nantong to the offshore of the Yellow sea, and part of the Tianmu mountain in the southwest of the analysis region. The diurnal variation of CI occurrence frequency is characterized by a major peak around noon (1100-1400 BT).
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