Why accurate weather forecasting is still so difficult — and why real-time data matters

When you open a forecasting app, you simply select a location, choose an hour and read the answer.

Behind that screen, however, lies one of the hardest prediction problems in science.

The atmosphere is a three-dimensional, constantly changing system.

Before a model can predict what it will do next, it must first answer a surprisingly difficult question: what exactly is the atmosphere doing right now? We never see the whole atmosphere No single instrument provides a complete picture of the weather.

Weather radars detect precipitation particles.

Satellites observe clouds, moisture and temperatures from space.

Ground stations measure conditions at individual locations.

Weather balloons and aircraft provide information from different altitudes.

Each source has its own resolution, update frequency, coverage gaps and measurement errors.

Building the current state of the atmosphere is therefore like reconstructing traffic across an entire city using cameras that point in different directions, refresh at different times and leave many streets completely invisible.

Meteorologists call the process of combining observations with a previous forecast “data assimilation”.

It produces an estimate of the current atmospheric state, known as an analysis, from which the next forecast begins.

As ECMWF explains, forecast quality depends crucially on the accuracy of this analysis.

Even an excellent model will struggle if its starting picture is incomplete, inaccurate or already out of date.