Data assimilation systems

Data assimilation systems are methods used to combine different sources of information—like observations and computer models—to create the most accurate picture of a physical system, such as the weather. By integrating real-world data with model predictions, they correct and update the system's state, improving forecasts and understanding. This process is essential in fields like meteorology, oceanography, and environmental science, as it helps reconcile discrepancies between models and actual observations, resulting in more reliable and precise predictions of natural phenomena.