Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.