Identifying the core of the convective cloud is paramount important to the identification of the Mesoscale Convective System (MCS) and its evolution is of great significance in the weather and climate system. To study the initiation and development of convective core systems, an automatic tracking algorithm named “Convective cell Identification and TRAcking (CITRA)” has been developed to identify and track the convective cells in MCSs using Doppler Weather Radar reflectivity images based Optical Character Recognition using Long Shortterm Memory Neural Network. Further, CITRA algorithm calculates the convective cell physical properties such as centroid, convective core size and area, duration, maximum extent, distance and direction from the Radar centre. CITRA algorithm tested on 1255 convective cells identification and tracked 90 distinct convective system families along with physical properties through their evolution during the monsoon periods of 2017–2019. The details of CITRA algorithm is described in the present paper.

识别对流云的核心对于识别中尺度对流系统（MCS）至关重要，其演化在天气和气候系统中具有重要意义。为了研究对流核心系统的启动和发展，开发了一种名为“对流细胞识别和跟踪（CITRA）”的自动跟踪算法，使用基于多普勒天气雷达反射率图像的多普勒天气雷达反射率图像识别和跟踪 MCS 中的对流细胞。短期记忆神经网络。此外，CITRA 算法计算对流单元物理特性，例如质心、对流核心大小和面积、持续时间、最大范围、距雷达中心的距离和方向。CITRA 算法对 1255 个对流单元的识别进行了测试，并通过它们在 2017-2019 年季风期间的演变跟踪了 90 个不同的对流系统家族及其物理特性。CITRA 算法的细节在本文中描述。