Abstract. Dryland ecosystems are the habitat supporting 2 billion people on Earth, and they strongly impact the global terrestrial carbon sink. Vegetation growth in drylands is mainly controlled by water availability with strong intra-seasonal variability. Timely availability of information at such scales (e.g., from days to weeks) is essential for early warning of potential catastrophic impacts of emerging climate extremes on crops and natural vegetation. However, the large-scale monitoring of intra-seasonal vegetation dynamics has been very challenging for drylands. Satellite solar-induced chlorophyll fluorescence (SIF) has emerged as a promising tool to characterize the spatiotemporal dynamics of photosynthetic carbon uptake and has the potential to detect intra-seasonal vegetation growth dynamics. However, few studies have evaluated its capability of detecting fast-changing intra-seasonal vegetation dynamics and advantages over traditional approaches in drylands based on vegetation indices (VIs). To fill this knowledge gap, this study utilized the vast dryland ecosystems in the Horn of Africa (HoA) as a testbed to characterize their intra-seasonal dynamics inferred from satellite SIF. The HoA is an ideal testbed because its dryland ecosystems have highly dynamic responses to short-term environmental changes. The satellite-data-based analysis was corroborated with a unique in situ SIF dataset collected in Kenya – so far, the only ground SIF time series collected on the continent of Africa. We found that SIF from the TROPOspheric Monitoring Instrument (TROPOMI) with daily revisit frequency identified highly dynamic week-to-week variations in both shrublands and grasslands; such rapidly changing vegetation dynamics corresponded to the up- and downregulation by the fluctuations in environmental variables (e.g., air temperature, vapor pressure deficit, soil moisture). However, neither reconstructed SIF products nor near-infrared reflectance of terrestrial vegetation (NIRv) from the Moderate Resolution Imaging Spectroradiometer (MODIS), which is widely used in the literature, was able to capture such fast-changing intra-seasonal variations. The same findings hold at the site scale, where we found that only TROPOMI SIF revealed two separate within-season growth cycles in response to extreme soil moisture and rainfall amount and duration, consistent with in situ SIF measurements. This study generates novel insights on the monitoring of dryland vegetation dynamics and the evaluation of their climate sensitivities, enabling the development of predictive and scalable understanding of how dryland ecosystems may respond to future climate change and informing the future design of effective vegetation monitoring systems for dryland vegetation.