## 3 Convective-Tracking Method and Dataset
### Convective-Tracking  
Cloud top IR BT variations from two successive images observed by a GEO satellite are used to track convective storm system development, as introduced in Section 1. In this study, in order to better identify developing convective initiation systems, we screen cloud clusters using an IR BT threshold below 273 K at the 10.4 \(\upmu\)m band observed by H08/AHI. This IR threshold can help us to further identify potential cloud clusters, which might grow into strong convection systems. After screening warm cloud cluster, a classical area-overlapped method [35] is applied to track the cloud cluster movement based on two consecutive H08/AHI observation data within a 10 min interval. For the  
Figure 1: Spatial distributions of three typical convective storm systems from April to October of 2016. Gray, orange, and red solid circles respectively represent slight (or none), medium, and severe convective storm systems.  
tracked cloud system objects, we use the equations (1) and (2) to calculate the two consecutive cloud top cool rates (\(R\)) at the 10.4 \(\upmu\)m band as follows:  
\[R_{1}=\frac{\min\left(BT_{A3,1}BT_{A3,2}\sim BT_{A3,2}\right)-\min\left(BT_{A1,2} BT_{A1,2}\sim BT_{A1,2}\right)}{t_{2}-t_{1}}, \tag{1}\]  
\[R_{2}=\frac{\min\left(BT_{A3,1}BT_{A3,2}\sim BT_{A1,k}\right)-\min\left(BT_{A3,2 }BT_{A2,2}\sim BT_{A2,k}\right)}{t_{3}-t_{2}}, \tag{2}\]  
where the symbol min represents the minimum function. \(A_{1,\,2,\,3}\) and \(t_{1,\,2,\,3}\) mean the tracked and overlapped convective storm cloud cluster area and observation time, respectively. The numbers from one to n denote the pixel number in the cloud cluster area, \(A_{1}\), \(A_{2}\), or \(A_{3}\). If both the cooling rates of \(R_{1}\) and \(R_{2}\) reach \(-16\) K/hour or lower [36], the related cloud system will be marked or considered to be a potential or developing convective cloud cluster. To better track sudden convective storm systems and ignore large-scale convective systems (they are always closely associated with frontal cloud systems) [37], the SWIPE model only identifies the convective cloud cluster areas with a total pixel number ranging from 10 to 80,000 (maximum area is about 600 km \(\times\) 600 km). Thus, three consecutive observation BT images should be used to compute two continuous cloud top cooling rates, which could help the algorithm to better identify the rapidly developing convective cloud clusters.  
Figure 2 is an example of this convective-tracking method using three continuous BT images within a 10 min observation interval. It shows a real case of a tracked convective storm system at 19:30 UTC on 05 July 2016 in Guangdong province of China using H08/AHI observations. The small colorful sub-figures in the left panel column represent the 10.4 \(\upmu\)m BT images at 19:10, 19:20, and 19:30 UTC, respectively. For this case, it can be seen that the two continuous cloud top cooling rates are less than \(-16\) K/h, and the BT at the coldest part of convective cluster at 19:30 UTC is lower than 200 K. This severe local convective storm system ultimately generated a maximum rain rate of 26.4 mm/h.  
Figure 2: A real case of tracked convective storm system at 19:30 UTC on 05 July 2016 in Guangdong province of China based on H08/AHI observations. The first small sub-figure at the upper-left corner is the grayscale 10.4 \(\upmu\)m BT image with coast line (yellow solid line). The other three small colorful sub-figures at the left panel represent 10.4 \(\upmu\)m BT images at 19:10, 19:20, and 19:30 UTC, respectively. The colorful area in right panel represents the pixels of H08/AHI with BT\(<\)238 K at 19:30 UTC on 05 July 2016.