曹林兮,吴梦雯,罗亚丽,陈锋. 2024. 苏沪城市群区域“出梅后期”对流初生客观识别方法及其时空分布特征[J]. 气象学报, (0):-, doi:[doi]
苏沪城市群区域“出梅后期”对流初生客观识别方法及其时空分布特征
An Objective Identification Algorithm and Spatiotemporal Distributions of Convection Initialization over the Urban Agglomeration Region in Jiangsu-and-Shanghai during the Post-Meiyu Period.
投稿时间:2023-12-02  修订日期:2024-01-06
DOI:
中文关键词:  对流初生,客观算法,数据库构建,时空分布
英文关键词:Convection initiation, Objective algorithms, Database construction, Spatiotemporal distributions
基金项目:国家自然科学基金资助项目(42030610,42205006)
作者单位邮编
曹林兮 南京信息工程大学 210044
吴梦雯 浙江省气象科学研究所 310051
罗亚丽* 南京信息工程大学 210044
陈锋 浙江省气象科学研究所 310051
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中文摘要:
      本研究研发了一套利用天气雷达观测资料的对流新生(CI)客观识别算法。该算法定义“对流块”为雷达反射率因子达到35dBZ的连续强回波区域,如果某一对流块的前30min、周边一定范围内没有任何对流块,且它维持约20min以上,则该对流块被识别为CI。将这套CI客观识别算法应用于苏沪城市群区域“出梅后期”(从梅雨季结束到8月底,且排除热带气旋影响)CI识别,构建了该地区2019—2022年出梅后期高时空分辨率(10分钟、1千米)CI数据库,通过个例和统计研究,分析了CI识别结果对于算法中两个参数的敏感性。当判断对流回波是否为首次出现的区域半径(R)设为10 km时,对流块最小面积设为4 km2或2 km2(Test1,Test2)对CI识别结果的影响不大,两个实验都能识别出CI连续发生和相邻发生的复杂情况,Test1能够识别出Test2的83% CI事件,二者识别出的CI日数、逐日CI数、CI高频区分布、CI频次日变化等统计特征基本一致;当R设为30 km、对流块最小面积为4 km2(Test3),仅能识别出Test1的36% CI事件,其识别的CI数目不足,导致CI发生频次的空间分布和日变化的分析结果明显不同于Test1和Test2。识别结果表明,分析区域内有CI发生频次较高的3个子区域:沿长江的“上海—苏锡常—南京”城市带、从南通北部到黄海近海、分析区域西南侧的天目山系部分区域,CI频次日变化呈现午间(1100?—1400 BT)主峰特征。
英文摘要:
      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 35dBZ). Presence of a convective cell is identified as CI if two criteria are meet: 1) no convective cells exist around the convective cell in a 30min period prior to its presence; 2) this convective cell lasts for at least about 20 minutes. 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 30 August, and excluding the days influenced by tropical cyclones). As a result, a CI database with high spatiotemporal resolutions (10 minutes, 1 kilometer) over the region for the 2019-2022 post-Meiyu periods is constructed. The sensitivity of the CI identification results on two parameters in the algorithm is investigated by comparing three experiments in a case study and statistics analysis. When the radius of the area (R) used to determine whether the convective echo is the first occurrence is set to 10 km, whether the minimum area of the convective echo (minA) 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, distribution of CI high-occurrence frequency areas, and diurnal variations of CI occurrence frequency. When R is set to 30 km (with minA 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 the spatial distribution and diurnal variations of CI occurrence compared to those from Test1 and Test2. The results indicate 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 the northern Nantong to the offshore of the Yellow Sea, and part of the Tianmu mountain system in the southwest of the analysis region. The diurnal variation of the CI’s occurrence frequency is characterized by a major peak around noon (1100-1400 BT).
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