Weather forecasting applies science and technology to predict atmospheric conditions, with informal attempts dating back thousands of years and formal methods emerging in the 19th century. Ancient civilizations like the Babylonians (650 BC) and Aristotle (350 BC) laid early groundwork, but modern forecasting relies on computer-based models that analyze vast atmospheric data, though human expertise remains crucial for selecting the best model. Forecasts are inherently limited by the chaotic nature of the atmosphere and computational constraints, making accuracy decrease as the forecast range extends. These predictions serve vital purposes—from weather warnings that protect lives and property to aiding agriculture, utility demand planning, and everyday clothing choices. The economic impact is substantial: in 2009, the US spent approximately $5.8 billion on forecasting, generating benefits estimated at six times that investment.