KAUST researchers studied the meteorological origins of sea-level extremes in the Red Sea using computer simulations and the ADCIRC storm surge model. They validated their datasets with hourly sea-level observations from six tidal gauges along the Saudi coast. The study found that wind variations over the southern part of the sea are the main drivers of basin-wide sea-level extremes. Why it matters: This research provides critical insights for managing and developing the Red Sea coastline, including megacity projects and tourism, while mitigating their impact on the marine environment.
Researchers have developed a CNN-based deep learning model for predicting coastal flooding in cities under various sea-level rise scenarios. The model utilizes a vision-based, low-resource DL framework and is trained on datasets from Abu Dhabi and San Francisco. Results show a 20% reduction in mean absolute error compared to existing methods, demonstrating potential for scalable coastal flood management.
A KAUST-led international team has published research detailing the potential of marine-based solutions to combat climate change. The study assesses the effectiveness of 13 ocean-based measures, including reducing greenhouse gas concentrations and protecting marine ecosystems. The research will inform decision-makers at COP24. Why it matters: Highlighting the potential of ocean-based solutions can broaden the scope of climate action strategies in the region, where coastal environments and marine resources are vital.
This paper introduces a deep vision-based framework for predicting coastal floods under climate change, addressing the challenges of limited training data and high-dimensional output. The framework employs and compares various deep learning models, including a custom compact CNN architecture, against geostatistical and traditional machine learning methods. A new synthetic dataset of flood inundation maps for Abu Dhabi's coast is also provided to benchmark future models.
A KAUST-led study analyzing over 100 years of satellite data indicates that Red Sea surface temperatures may be cooling rather than rising due to the Atlantic Multidecadal Oscillation (AMO). The research, utilizing KAUST's supercomputer Shaheen II, suggests a cooling phase in the coming decades that could temporarily counter global warming effects. The team collaborated with researchers from the University of Athens and the Hellenic Centre for Marine Research, using data from NOAA, NASA, and the UK Met Office. Why it matters: The finding challenges assumptions about uniform warming trends and highlights the role of natural climate oscillations in modulating regional temperature changes, informing more accurate climate modeling and adaptation strategies for the region.