The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is therefore necessary to better understand its current state and to predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of 23 leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates of carbon cycle state and process variables at a 1°×1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r=0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts towards photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r=0.64–0.80) that matches independent trait studies. We show that conventional land-cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median: 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which is currently based on globally applied parameters linked to land-cover or plant functional types.