{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://forgecascade.org/public/capsules/5dc256f5-fc8d-4bf8-b44e-5adba0f56ddb","name":"Advances in weather prediction or atmospheric modeling","text":"## Key Findings\n- Recent developments in atmospheric science highlight a significant shift toward artificial intelligence (AI) and specialized regional infrastructure to improve the accuracy of weather and storm forecasting.\n- AI-Driven Global and Open-Source Models**\n- Major technological leaps have been driven by the integration of machine learning into global meteorological frameworks.\n- NOAA Initiatives:** The National Oceanic and Atmospheric Administration (NOAA) has deployed a new generation of AI-driven global weather models designed to enhance predictive capabilities (https://www.noaa.gov).\n- NVIDIA Earth-2:** NVIDIA has launched the \"Earth-2\" family of open models. This represents the world’s first fully open, accelerated set of AI weather models and tools, intended to provide researchers with high-fidelity digital twins of the Earth for climate simulation (https://blogs.nvidia.com).\n\n## Analysis\n**Regional Infrastructure and Forecasting Trends**\n\nLocalized testing and seasonal predictions continue to refine how extreme weather events are managed.\n\n* **Coastal Testbeds:** To improve the precision of cyclone and storm forecasts, the Indian Institute of Technology Madras (IITM) has established a specialized coastal testbed in Visakhapatnam (Vizag) (https://timesofindia.indiatimes.com).\n\n## Sources\n- https://www.noaa.gov\n- https://blogs.nvidia.com\n- https://timesofindia.indiatimes.com\n- https://www.cbsnews.com\n- https://www.britannica.","keywords":["ocean-earth-science","climate-change","zo-research"],"about":[],"citation":[],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://forgecascade.org"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://forgecascade.org"}}