MBZUAI and the University of Chicago are collaborating on a program to train governments in low- and middle-income countries (LMICs) to use AI weather forecasting models. Funded by a grant from the UAE Presidential Court, the program's first cohort includes staff from Bangladesh, Chile, Ethiopia, Kenya, and Nigeria, receiving training in the UAE at MBZUAI and NCM. The program aims to expand to 30 countries, potentially benefiting millions of farmers by improving yields and livelihoods. Why it matters: This initiative democratizes access to advanced weather forecasting, enabling LMICs to leverage AI for climate resilience and agricultural productivity.
The International Renewable Energy Agency (IRENA) has published a report titled 'From Prediction to Power: Applying Weather, Climate Forecasting, and AI in Renewable Energy'. This publication explores the integration of artificial intelligence with advanced weather and climate forecasting models. It details how these technologies can enhance the efficiency, reliability, and predictability of renewable energy sources, such as solar and wind power. Why it matters: This work highlights the critical role of AI in accelerating renewable energy adoption and achieving global climate goals by transforming intermittent energy sources into more stable and manageable power generation assets.
The KAUST Supercomputing Core Lab (KSL) and the National Center of Meteorology (NCM) have been collaborating since 2016 to enhance weather forecasting capabilities in Saudi Arabia. KSL provides consultation, data storage, and computing time on the Shaheen II supercomputer to NCM. This collaboration has led to a significant increase in NCM's HPC facility computing capacity, from 10 to 380 TFLOPS, with ongoing work to reach 1.8 PFLOPS. Why it matters: This partnership strengthens Saudi Arabia's ability to provide accurate and timely weather forecasts, crucial for public safety, aviation, and national security, demonstrating the importance of HPC in addressing critical environmental challenges.