These systems require massive computational resources and take time to process.Īlso, according to the authors, the ability to accurately predict forecasts further out, from several weeks to months, decreases significantly. The forecast gave communities time to weatherize structures and evacuate before the Category 4 Typhoon hit, saving lives, and reducing overall damage to the region.Ĭurrent weather forecasting relies on supercomputers processing large amounts of global data such as temperature, pressure, humidity, and wind speed.

In 2019, meteorologists warned local and national leaders in the Philippines of a torrential rainstorm looming about 3 weeks out. Short-term and seasonal weather forecasting can play a large role in decreasing the socioeconomic and human costs of extreme weather. According to a recent NOAA report, last year the US experienced 20 separate climate-induced weather disasters, each totaling over $1 billion in damage. The study, recently published in the J ournal of Advances in Modeling Earth Systems, could help identify potential extreme weather 2–6 weeks into the future. Accurate predictions of extreme weather with a longer lead time give communities and critical sectors such as public health, water management, energy, and agriculture more time to prepare for and mitigate potential disasters.Ĭlimate change is amplifying the intensity and frequency of extreme weather events, with 2021 shattering storm, heatwave, flood, and drought records across the globe. New weather-forecasting research using AI is fast-tracking global weather predictions.

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