The storm mistEO was founded on.
The field behind these words is not a generative animation. It is the 2018 Kerala flood, the event this company was founded to answer, reconstructed from ERA5 reanalysis and advected particle by particle.
In August 2018, an exceptionally active southwest monsoon stalled over the Western Ghats. Over two weeks Kerala received more than 40% above its normal rainfall; reservoirs filled, dams opened without enough warning, and the resulting floods displaced over a million people. It was one of the most consequential weather events in the state's recorded history.
mistEO's founding is rooted in that event. What it exposed was not a shortage of data; it was a shortage of usable intelligence. Forecasts existed, but the institutions carrying the risk (governments, agencies, operators) could not turn atmospheric signal into action fast enough to matter. The gap between what the atmosphere was doing and what anyone could do about it is the gap mistEO was built to close.
So the field above is that specific storm, held at its most intense hour on 15 August. Each streamline is a particle carried by the real 10 m wind, sampled from ERA5, the ECMWF reanalysis that reconstructs the global atmosphere hour by hour. The westerlies driving onto the coast are the monsoon flow that fed the rain; warmer colour marks stronger wind.
How it was made
We pulled the u and v wind components for a grid of points across Kerala, the Arabian Sea, and the Western Ghats for the flood peak, via the open ERA5 archive. Each grid cell becomes a vector; the page samples that vector field with smoothed bilinear interpolation and advects a few thousand particles along it, exactly the way an operational wind map does. Because real wind is not divergence-free, the particles converge where the air was rising, over the same terrain that was flooding.
This is a small illustration of what mistEO now does at scale: take the physical state of the atmosphere and turn it into something you can read and act on. Here it is a picture. In production it is a heat-stress index, an aviation risk surface, a parametric trigger.