Meteorologists and weather forecasters are employed by national and regional weather centres, as well as by organizations such as the military and by airports. They make forecasts based on their knowledge of weather patterns and information received from local, national and global sources .The forecasts are delivered to the public through television, radio, newspapers and the Internet.
Meteorologists use a process called numerical weather prediction to create forecasts by inputting current conditions — which they call the “nowcast” — into computer models. The more current and accurate information available to these models, the better the forecast will be. Ground radar, weather balloons, aircraft, satellites, ocean buoys and more can provide three-dimensional observations that a model can use. This allows meteorologists to simulate what the atmosphere is currently doing and predict what will happen in the next few days or, for some models, hours.
Weather models divide a region, say a single state or even the whole globe, into a set of boxes, or cells. The size of these cells — the resolution of the model — affects its forecasting accuracy. Large boxes mean poor resolution, or the inability to tell what’s happening over small areas, but a broad picture of large-scale weather trends over long timelines. This big-picture forecast is helpful when you want to know how a big storm will move across the U.S. over the course of a week.
Smaller boxes mean higher resolution, which can forecast smaller storms. These models are more expensive in terms of computing power, and only run to the one- or two-day mark to tell people whether it might storm in their local area. Although all models are based on the same physics, each translates those physics into computer code differently, says Judt. Some models might prioritize certain kinds of data — such as wind speed, temperature and humidity — over others to generate predictions, or simulate physical processes slightly differently than another model. That’s why two models might spit out slightly different results, even with exactly the same starting observations.
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