DO I NEED AN UMBRELLA?

Have you ever asked your Google assistant “Hey Google!! Is it going to rain today?”

It immediately gives you the weather report based on the data given by the meteorological department of the government which is responsible for weather forecast in your location. But this going to change in the future;

Think about Google answering your same question based on the results of Google DeepMind with more accuracy than just the results of the meteorological department; Think of going out of the house without an umbrella on a rainy day; To add to our woes, on certain days, even the weather forecasts have failed us horribly in anticipating the likelihood of rain.

There’s going to be a more accurate solution to this problem in the coming future

Google’s DeepMind scientists have created an artificial intelligence-based forecasting system that can predict the chance of rain in the next two hours more precisely than existing methods.

The system learned how to identify common patterns of rainfall, using UK radar maps from 2016 to 2018, was tested on maps from 2019, and found, by 50 Met Office meteorologists, to be accurate in 89% of cases.

The weather predictions are driven by powerful numerical weather prediction (NWP) systems. By solving physical equations, NWPs provide essential planet-scale predictions several days ahead. However, they struggle to generate high-resolution predictions for short lead times under two hours. Nowcasting fills the performance gap in this crucial time interval.

Nowcasting is essential for sectors like water management, agriculture, aviation, emergency planning, and outdoor events. Advances in weather sensing have made high-resolution radar data–which measures the amount of precipitation at ground level–available at high frequency (e.g., every 5 mins at 1 km resolution). This combination of a crucial area where existing methods struggle, and the availability of high-quality data provides the opportunity for machine learning to make its contributions to nowcasting.

The research, published in the journal Nature, found: “Meteorologists significantly preferred the [AI] approach to competing methods.”

DeepMind senior scientist Shakir Mohamed said: “It’s very early days but this trial shows that AI could be a powerful tool, enabling forecasters to spend less time trawling through ever-growing piles of prediction data and instead focus on better understanding the implications of their forecasts.

“This will be integral for mitigating the adverse effects of climate change today, supporting adaptation to changing weather patterns and potentially saving lives.”