Meteorology has always relied on massive amounts of data. Weather satellites, weather stations, airplanes, radar systems, and sea monitoring devices continuously gather information about the atmosphere.

Conventionally, sophisticated computers process this information using numerical weather prediction models. These models simulate physical processes like air motion, temperature, pressure, and humidity. The models are highly valuable, yet they take lots of computer power.

AI adds another dimension to weather forecasting.

Machine learning models can be taught based on vast amounts of historical weather data. Rather than calculating all atmospheric processes anew, the AI model can learn patterns in previous observations and predictions and apply these patterns to generate its own predictions.

Recently, scientists have created AI-based forecasting tools capable of predicting the weather way faster than numerical models.

An area of great interest is the prediction of severe weather phenomena. Scientists are looking into whether AI could help improve predictions of storms, precipitation, and other hazardous events through pattern recognition.

The magazine Nature listed AI-driven meteorology among technologies to pay attention to in 2026. It turns out that certain AI systems have proven to be able to make useful forecasts several days ahead with significantly smaller computing costs than traditional systems.

However, AI will not replace classical meteorology.

Even if a weather model will provide a spectacular forecast, the meteorologists need to understand the importance of this forecast, its validity and potential uncertainties.

There is another disadvantage. The AI algorithms operate on historical data. Therefore, an uncommon weather event may turn out to be hard to predict since it will not be present in the database.

This is why a number of researchers are interested in the joint use of AI and physical weather models.

The advantage may be immense.

Faster forecasts will allow weather organizations to make more forecasts, to update them more frequently and to warn about upcoming hazardous weather in time.

On the other hand, the AI will enable high-resolution forecasting in countries with inadequate computer capabilities.

However, more accurate forecasting is not only about speed.

It is mostly about accuracy and interpretation of uncertainties.

The weather affects agriculture, transportation, power grids, emergency plans, people's lives and many other aspects. Therefore, even a small improvement in forecasting weather would be a great achievement.

AI cannot change the rules of weather.

But it could change the speed with which we interpret the atmosphere's