A Sweeping Climate Model of the Red Sea: Supporting Saudi Arabia’s Sustainable Future

KAUST researchers have developed a groundbreaking climate model that predicts future atmospheric and oceanic changes in the Red Sea region, providing crucial insights for sustainable city planning and environmental protection. The Red Sea, a vital natural and economic resource for Saudi Arabia, is increasingly affected by rapid population growth, industrialization, and the impacts of global warming. This new climate model is central to ensuring that the country’s megacity projects, such as those along the Red Sea coastline, are designed with long-term sustainability in mind.

Led by Ibrahim Hoteit, KAUST's international team combined expertise in various scientific fields, including weather, marine ecosystems, and data visualization, to create an all-encompassing climate model. Using satellite and surface observations, the model offers high-resolution analyses of oceanic and atmospheric processes over the past 40 years, revealing how these systems interact and influence the region. One key discovery was the Indian monsoon's impact on the Red Sea’s seasonal circulation patterns, helping explain unusual summer chlorophyll blooms in the southern Red Sea.

The model can forecast numerous environmental factors, including ocean and atmospheric circulation, marine ecosystems, air pollution, and the spread of oil spills. These insights are already assisting academia, government, and industry in Saudi Arabia, supporting environmental policymaking, biodiversity research, and the planning of renewable energy projects and flood protection systems. For instance, the team's reconstruction of extreme wave heights along the shoreline contributed to the design of the sea wall protecting the King Abdullah Economic City.

As the system evolves, it will be enhanced with seasonal forecasting and urban environment simulations, ultimately aiming to become an accessible, online tool for local authorities and industries to solve environmental challenges in the region.

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