AI tools look for patterns in data over years to forecast weather accurately and faster than traditional methods
In the past year, something of a revolution has hit the world of weather forecasting as artificial intelligence-based weather forecasts have come to the fore. Traditional weather forecasting methods rely on creating a digital three-dimensional grid that replicates as closely as possible the state of the atmosphere at the start of the forecast.
Once this “initialised state” is determined, complex equations are used to predict how the state of the atmosphere will evolve in the hours and days ahead. For decades, much research has gone into improving these forecasts, focusing on getting the starting point right, increasing vertical and horizontal resolution of these grids, and, of course, making refinements to the equations.
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