Climate models are numerical representations of the physical processes that govern the climate system—things like the atmosphere, oceans, land surface, and ice—built from the laws of physics and with parameterizations for small-scale processes. Climate projections are the outputs you get when those models are run under different future forcing scenarios, such as varying greenhouse gas emissions, land-use changes, and other drivers. They are not exact predictions; they tell you what the climate is likely to do under a given set of future conditions and come with uncertainties. Those uncertainties come from three main sources: natural, internal variability of the climate system; differences in model structure and how processes are represented (parameterizations); and the choices of future emissions and forcing scenarios used in the projections. This combination means projections provide a range or distribution of possible outcomes rather than a single exact forecast. This distinction also helps separate climate projections from weather forecasts, which aim to predict day-to-day conditions and are not scenario-based.