data assimilation

Data assimilation is a process used to improve models by combining real-world observations with predictions. Imagine a weather forecast: it starts with mathematical models that simulate atmospheric behavior. By incorporating current data from satellites, weather stations, and other sources, data assimilation adjusts these models to provide a more accurate picture of the weather. This technique is essential in various fields, including meteorology, oceanography, and environmental science, as it enhances the reliability of forecasts and simulations, leading to better decision-making and planning based on accurate information.