This $436,468 Project Grant award from the National Science Foundation's Polar Programs (CFDA 47.078) will support research led by Brown University to develop computational approaches for assessing and predicting Arctic maritime accessibility and extreme weather conditions. The key products and services to be delivered include:
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Using numerical weather prediction models to analyze the probability of icing conditions and dangerous sea ice convergence along Arctic maritime shipping routes.
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Deploying machine learning techniques to enhance the spatial resolution of sea ice projections for specific Arctic waterways and straits.
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Incorporating these insights into multi-model climate projections to generate more accurate scenarios of future marine accessibility under different climate change trajectories.
The research aims to improve understanding and forecasting of the extreme weather events and sea ice dynamics that impact safe Arctic maritime operations, with applications ranging from global shipping to local community activities. This award reflects NSF's mission to advance fundamental scientific knowledge and will train early-career researchers in computational techniques for addressing these critical Arctic challenges.
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