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EarthNet: A multi-modal foundation model for global data assimilation of Earth observations
Global weather forecasts depend on petabyte scale datasets and are generated on some of the world’s largest supercomputers. Until now, the resources required have severely limited the number of organizations capable of producing global weather forecasts. Using generative AI, we have developed EarthNet, a multi-modal foundation model for global data assimilation of Earth observations with 1000x m
Tracking weather patterns with Zeus AI’s data assimilation system.
See our near real-time LENS-Analysis Demo covering the Caribbean region. We show wind speed, temperature, relative humidity, radar reflectively composite, and cloud cover percentage updated every 15-minutes. The visualization is shown at a reduced spatial resolution for performance purposes. Zeus AI is pleased to announce the release of LENS-Cast, a new weather nowcasting product, offering n
Synthetic radar and winds during Hurricane Idalia with mesoscale geostationary satellite imagery.
See our near real-time LENS-Analysis Demo covering the Caribbean region. We show wind speed, temperature, relative humidity, radar reflectively composite, and cloud cover percentage updated every 15-minutes. The visualization is shown at a reduced spatial resolution for performance purposes. Zeus AI is pleased to announce the release of LENS-Cast, a new weather nowcasting product, offeri
Zeus AI awarded DOE SBIR Phase I to develop multimodal foundation models for urban meteorology.
See our near real-time LENS-Analysis Demo covering the Caribbean region. We show wind speed, temperature, relative humidity, radar reflectively composite, and cloud cover percentage updated every 15-minutes. The visualization is shown at a reduced spatial resolution for performance purposes. Zeus AI is pleased to announce the release of LENS-Cast, a new weather nowcasting product, offeri