After being named the best weather forecaster, Microsoft introduces Aurora, its AI forecaster

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Key notes

  • Microsoft’s new AI model, Aurora, aims to improve weather forecast accuracy for various weather events.
  • Aurora leverages vast amounts of atmospheric data to make predictions, focusing on efficiency compared to traditional models.
  • The model’s versatility extends beyond weather, potentially aiding air quality monitoring and other environmental tasks.
Microsoft Start Weather trends historical weather

Microsoft researchers have introduced a new AI model, Aurora, which can improve weather forecasting accuracy and efficiency.

Aurora can address limitations identified in current models. The model uses extensive atmospheric data to improve its predictions, with a particular focus on extreme weather events.

Aurora’s versatility is its main feature. It can forecast a variety of atmospheric factors, including

  • temperature,
  • wind speed,
  • air quality measurements, and
  • greenhouse gas concentrations.

Compared to traditional weather forecasting models, Aurora is said to use computational efficiency. This is attributed in part to its foundation model architecture, which lets for adaptation to diverse forecasting tasks.

The research team says that Aurora can be a big turning point in Earth system modeling. The model’s ability to perform well with limited data means it can perform well in the data-sparse regions, such as developing countries and polar areas. This can have positive impacts on sectors like agriculture, transportation, and disaster preparedness.

Overall, Aurora has the potential to significantly improve weather forecasting and provide valuable insights to communities around the world.

This announcement comes after Microsoft bagged the title for the most accurate forecast provider 2 years running. They really have been making some big strides in the field of weather forecasting with Microsoft Start’s new Weather Trends page offering historical weather data. More about it here.

More here.

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