Hyperlocal Weather Forecasting for Safer UAS Operation

Atmo has developed an AI-based weather supercomputing platform that replaces expensive legacy systems at one-tenth the cost while providing 10X the performance. Atmo’s platform is a tightly integrated hardware and software system for high-precision weather and climate forecasting. Using Artificial Intelligence – especially Deep Learning techniques – Atmo both improves forecast quality and drastically reduces the cost of supercomputing required to get comparable results. Then, by integrating data assimilation, AI-enabled numerical weather prediction, data post-processing, an advanced 3D map interface and forecast delivery in a single system, Atmo reduces the complexity of integration and deployment while maintaining an open platform for local scientists and meteorologists to contribute their own weather and climate models.  Furthermore, Atmo has created an Unmanned Aircraft Systems (UAS)/drone weather safety platform that provides hyper-localized identification of conditions such as icing and turbulence detection. This information is then used to plot out optimized flight paths, a capability which has been validated through collaborations with Thales and Leonardo, the major defense suppliers to the French and Italian militaries. Together with the portability, modularity, and ruggedization of the hardware system, Atmo provides an AI-enabled, high-precision climate forecasting and UAS weather safety platform that can be deployed anywhere in the world.