Weather forecasting is the use of science and technology to predict atmospheric conditions for a specific location and time. While informal weather prediction has been practiced for thousands of years, formal forecasting methods have been developed since the 1800s.
In a groundbreaking development in 1911, the Met Office pioneered the transmission of marine weather forecasts using radio technology. These early forecasts played a vital role in ensuring maritime safety by providing gale and storm warnings for areas surrounding Great Britain.
Marking a significant milestone in 1922, English scientist Lewis Fry Richardson unveiled his groundbreaking work, "Weather Prediction By Numerical Process". This publication, stemming from Richardson's calculations and insights during his time as an ambulance driver in World War I, proposed a novel approach to weather prediction. Richardson's method involved simplifying complex equations governing atmospheric flow and employing a finite differencing scheme for time and space, ultimately paving the way for numerical prediction solutions.
Edward B. "E.B." Rideout etched his name in meteorological history in 1925 by delivering the first public radio weather forecasts in the United States. Broadcasting from WEEI, the Edison Electric Illuminating station in Boston, Rideout, affiliated with the U.S. Weather Bureau, ushered in a new era of accessibility to weather information for the public.
Furthering the reach of weather forecasting, G. Harold Noyes joined WBZ as a weather forecaster in 1931. Noyes, also from the U.S. Weather Bureau, contributed to the growing presence of meteorological information in the public domain through radio broadcasting.
November 1936 marked a pioneering moment in the dissemination of weather information with the BBC's experimental broadcast of the world's first televised weather forecasts. These early broadcasts, incorporating weather maps, provided viewers with a new and engaging way to receive meteorological information.
Following the experimental broadcasts in 1936, regular television weather forecasts became a reality in 1949. This marked a significant step towards integrating weather information into daily television programming.
In 1954, George Cowling took the helm as the first weather presenter to deliver forecasts while positioned in front of a weather map on television. This innovation enhanced the visual appeal and clarity of weather broadcasts, making it easier for viewers to grasp meteorological information.
The year 1955 witnessed a pivotal moment in the history of weather forecasting, as the practical application of numerical weather prediction commenced. This significant advancement was driven by the development of programmable electronic computers, ushering in a new era of accuracy and efficiency in weather forecasting.
In 1963, Edward Lorenz, a pioneer in chaos theory, brought to light the inherent limitations of long-range weather forecasts, specifically those extending two weeks or more into the future. Lorenz's work highlighted that the chaotic nature of the fluid dynamics equations governing atmospheric behavior rendered definitive predictions beyond this timeframe unreliable.
Driven by a shared vision to provide continuous weather information, John Coleman, a prominent figure in television weather forecasting, and Frank Batten, CEO of Landmark Communications, joined forces to launch The Weather Channel (TWC) in 1982. This 24-hour cable network revolutionized access to national and local weather reports, solidifying its place as a dedicated source for meteorological information.
In 2009, the US economy dedicated a substantial $5.8 billion to weather forecasting, demonstrating its significance. The return on this investment was noteworthy, as the generated benefits were estimated to be six times the initial expenditure.
The year 2024 marked a significant leap in artificial intelligence's role in weather prediction, as the Artificial Intelligence/Integrated Forecasting System (AIFS) commenced the publication of real-time forecasts. Demonstrating notable accuracy in predicting hurricane tracks, AIFS signaled the potential of AI in meteorology, although its performance in forecasting the intensity changes of such storms was noted to be less robust compared to physics-based models.