A complex convective cloud with a horizontal scale area of more than 100 km, known as the mesoscale convective system (MCS), is important to the study as it brings heavy rainfall from its activity. The analysis of MCS with the flood-producing storm on the Indonesian Maritime Continent (IMC) receives less attention. The purpose of this study is to identify and evaluate the temporal variability of the MCS to the frequency of flood-producing storms in Greater Jakarta (GJ) during the 2013–2015 wet season. The image data of Multi-functional Transport Satellite (MTSAT) -1R, which represents an equivalent blackbody temperature (TBB), and the tracking algorithm “Grab ‘em Tag ‘em Graph ‘em” (GTG) were used to detect the events of MCS. We also used a rainfall graph in this analysis to measure rainfall threshold values in order to classify flood-producing storms. The results show that MCS around GJ has typical characteristics of tropical belt regions. There is a small TBB scale (maximum size ≥13,000 km²) distinguished by a deep cloud up to 14 km in height. Through the active effects of monsoon and ITCZ, the land-breeze and/or sea-breeze circulations that contribute to MCS growth are triggered. However, about 32 percent of the MCS contributed to the flood-producing storm around the GJ region.

水平尺度面积超过 100 公里的复杂对流云，被称为中尺度对流系统 (MCS)，对这项研究很重要，因为它的活动带来了强降雨。对 MCS 与印度尼西亚海洋大陆 (IMC) 上引发洪水的风暴的分析较少受到关注。本研究的目的是确定和评估 MCS 对 2013-2015 年雨季大雅加达 (GJ) 洪水产生风暴频率的时间变异性。多功能运输卫星（MTSAT）-1R的图像数据，代表等效黑体温度（TBB），跟踪算法“Grab 'em Tag 'em Graph 'em”（GTG）被用来检测事件MCS。我们还在此分析中使用了降雨图来测量降雨阈值，以便对引发洪水的风暴进行分类。结果表明，GJ周围的MCS具有典型的热带带区特征。TBB规模较小（最大规模≥13,000 km² ) 以高达 14 公里的深云为特征。通过季风和 ITCZ 的积极影响，触发了有助于 MCS 增长的陆风和/或海风环流。然而，大约 32% 的 MCS 促成了 GJ 地区周围的洪水风暴。