An international team of scientists has found an innovative way of applying artificial intelligence to satellite data to yield 3D profiles of clouds. This is particularly news for those eagerly awaiting data from EarthCARE in their quest to advance climate science.
In their proof-of-concept study, the team analysed a year’s worth of archived CloudSat and MSG data from 2010 to demonstrate how artificial intelligence can extract new insights from existing satellite observations. The team aligned profiles from CloudSat profiles with images from MSG. This helped to understand how the ‘view from top’ and the corresponding cloud profiles were related. They then trained machine learning models to understand this mapping and derive cloud profiles from the 2D imagery. This allowed us to extend the CloudSat profiles in both space and time.
The team used AI on an MSG image (infrared channel) with a co-aligned CloudSat track. The model learns from the limited overlap of the MSG image and CloudSat track, and is able to extend the vertical cloud profile in space. Each MSG image spans 256 x 256 pixels, at a resolution of 3 km per pixel.
This animation shows how after the model is trained, predictions can be made for MSG images without corresponding CloudSat tracks, and 3D cloud maps can be created across space and time.
Read full story: AI-powered satellite data reveals clouds in 3D