Storm chasing for data scientists: A Hurricane Milton case study
On Wednesday, October 9, 2024, Hurricane Milton made landfall. The storm reached the west coast of Florida during the evening hours. It was the strongest tropical cyclone in 2024 so far.
Here, I explore how the AI weather model PanguWeather predicted hurricane Milton. Code snippets are included to help you replicate and extend my analysis.
AI weather models use historical weather data to predict today’s weather.
To generate your own AI weather forecast, you need a pretrained weather model and initialization data. Both are available on Github via the European Center for Medium-Range Weather Forecasting (ECMWF).
I used the pretrained model and initialization data provided by the European Center for Medium-Range Weather Forecasting to create a global weather forecast.
Follow the installation instructions and start the forecast:
ai-models --assets panguweather --input ecmwf-open-data panguweather
The start date for my forecast was Tuesday, October 8, 08:00 AM local time (EDT). It took 1.4 hours to complete on a laptop CPU. With a GPU, PanguWeather could deliver a global forecast in minutes.