Snow's Ghost

Snow’s Ghost refers to a correction method in climate modeling that helps improve predictions of cold, snowy conditions. It involves analyzing discrepancies between different model outputs and observations to identify where models may underestimate or overestimate snowfall. By adjusting these models based on the "ghost" patterns identified—small discrepancies that persist across simulations—scientists can achieve more accurate forecasts of winter weather. Essentially, Snow’s Ghost is a technique to refine climate models, ensuring they better represent real-world snowfall dynamics, leading to improved seasonal weather predictions and understanding of climate behavior in cold regions.