Understanding how rain events form, grow, and fade is crucial for weather and climate research. However, tracking these events over time and space is difficult due to their complex behavior. In this study, we developed a new method to identify and analyze individual rain events using a 3D shape-based approach. We also introduced a model that describes the full lifecycle of each event—from start to peak to end—using a simplified curve. We applied these tools to three major rainfall datasets over the U.S. from 2001 to 2021 and found that our method works reliably across all datasets. To better understand common patterns in rain events, we grouped them into four types based on their shapes and timing, such as fast or slow-developing storms, and short or long-lasting events. These types appeared consistently across the different datasets, showing that our method can be used broadly. This work provides a new way to study how rain behaves over time and how it might be changing with the climate.