Gone are the days of complaining that you can't understand what the meteorologists are saying on the news.

As extreme weather events become more frequent, more intense, and more unpredictable, we need technology that can alert us when extreme weather events are about to occur. Weather agencies around the world are focusing on artificial intelligence to provide these warnings.

The India Meteorological Department leverages AI to generate public alerts for heatwaves and disease outbreaks such as malaria. Importantly, AI models don't require a lot of money.

“AI models do not require the high costs of running a supercomputer. They can be run from a high-quality desktop,” said Saurabh Rathore, assistant professor at the Indian Institute of Technology in Delhi, according to Reuters.

Other weather agencies also rely on AI. The Met Office says researchers from the Alan Turing Institute and the Met Office are working together to develop an AI model that has “the potential to revolutionize weather forecasting”.

Dr Jean Innes, Chief Executive Officer of the Alan Turing Institute, said: “This project addresses a major holdout problem in weather forecasting – that is, impacts that can unfortunately have devastating consequences for local communities. “The aim is to address the challenge of predicting certain weather phenomena quickly and accurately.” “This is a hugely ambitious project.…We aim to save lives, protect infrastructure and push the boundaries of scientific understanding for the benefit of both here in the UK and the international community. ”

Elsewhere, a Google-funded AI weather prediction model was found to outperform traditional weather forecasting methods.

“Numerical models used to predict weather are large, complex, computationally intensive, and do not learn from past weather patterns,” a study summary published in the journal Science says.Uses machine learning-based methods trained directly from historical atmospheric state reanalysis data [researchers] Hundreds of weather variables around the world could be rapidly predicted in high resolution up to 10 days in advance. ”

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