Weather Forecasting: From Ancient Methods to AI

Weather prediction dates back to ancient civilizations using persistent patterns. Today, supercomputers, satellites, and sophisticated algorithms have revolutionized forecasting, enabling precise predictions days in advance.

Synoptic meteorology, analyzing weather data over a wide area, predicts future states. It involves meticulous charting of atmospheric pressures, winds, and temperatures at different altitudes.

Numerical models simulate the atmosphere using mathematical equations. These models require vast amounts of data and immense computational power, improving consistently with advancements in technology.

Radiosondes are balloon-borne instruments measuring atmospheric parameters. Sent twice daily worldwide, they provide high-altitude data essential for weather models, often filling gaps where ground observations are scarce.

Doppler radar detects precipitation intensity, movement, and potential storm development. Its ability to observe wind velocity revolutionized severe weather prediction, particularly in tracking tornadoes.

Geostationary satellites continuously monitor Earth's weather, climate, and environment. They provide high-resolution imagery, critical for tracking hurricanes, volcanic ash dispersion, and large-scale climate phenomena like El Niño.

Artificial intelligence, especially machine learning, is a frontier in meteorology. AI can discern complex patterns in historical data, potentially predicting weather changes more accurately than traditional models.

Sharks change depth to avoid storms, acting as natural weather predictors.