Weather forecasting utilizes science and technology to predict atmospheric conditions for specific locations and times. While informal weather predictions have existed for millennia, formal forecasting emerged in the 19th century. It is a crucial application of scientific understanding to anticipate and prepare for future weather patterns.
In 1911, the Met Office began issuing the first marine weather forecasts via radio transmission, including gale and storm warnings for areas around Great Britain.
In 1922, Lewis Fry Richardson published "Weather Prediction By Numerical Process", which detailed a method for numerical weather prediction using finite differencing.
In 1925, the first public radio forecasts in the United States were made by Edward B. "E.B." Rideout on WEEI, the Edison Electric Illuminating station in Boston.
In 1931, G. Harold Noyes, from the U.S. Weather Bureau, began weather forecasting on WBZ.
In November 1936, the BBC experimentally broadcast the world's first televised weather forecasts, including the use of weather maps.
In either 1940 or 1947, James C. Fidler made experimental television forecasts in Cincinnati on the DuMont Television Network.
In either 1940 or 1947, James C. Fidler made experimental television forecasts in Cincinnati on the DuMont Television Network.
In 1954, George Cowling gave the first televised weather forecast while being televised in front of the map.
In 1955, practical use of numerical weather prediction began due to the development of programmable electronic computers.
In 1963, Edward Lorenz proposed that long range forecasts (two weeks or more) cannot definitively predict the state of the atmosphere due to the chaotic nature of fluid dynamics equations.
In 1982, John Coleman partnered with Frank Batten to launch The Weather Channel (TWC), a 24-hour cable network devoted to national and local weather reports.
In 2009, the US spent approximately $5.8 billion on weather forecasting, which produced benefits estimated at six times that amount.
In 2022, Huawei's Pangu-Weather model, Google's GraphCast, WindBorne's WeatherMesh model and Nvidia's FourCastNet emerged.
In 2023, Huawei's Pangu-Weather model, Google's GraphCast, WindBorne's WeatherMesh model, Nvidia's FourCastNet, and the European Centre for Medium-Range Weather Forecasts' Artificial Intelligence/Integrated Forecasting System, or AIFS all appeared.
In 2024, Lang et al. presented a study using the AIFS, showing 30-day ensemble simulations of the Madden-Julian oscillation.
In 2024, researchers at Google's DeepMind AI research laboratories published a paper in Nature describing their machine-learning model, called GenCast, which is expected to produce more accurate forecasts than traditional systems.
In 2024, the European Centre for Medium-Range Weather Forecasts' AIFS started to publish real-time forecasts, showing specific skill at predicting hurricane tracks, but lower-performing on the intensity changes of such storms relative to physics-based models.
The American Haines Index will be dropped in 2025, as forecasting of wind, precipitation, and humidity is essential for preventing and controlling wildfires. Indices such as the Canadian Forest fire weather index and the Australian Fire Danger Rating System, have been developed to predict areas more at risk of fire.
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