Optimal Design of Data Assimilation for the Prediction of Hydrological Extremes

Research Overview

Drs. Ashley Payne (Climate and Space Sciences and Engineering), Yulin Pan (Naval Architecture and Marine Engineering) and the team use data science methods to improve the forecast of hydrological extremes (such as unprecedented floods). They use predictive modeling to select informative satellite remote sensing data, then use new data to improve model predictions. They will demonstrate these methods through the forecast of a class of phenomena known as atmospheric rivers that are related to hydrologic and wind extremes, and the replenishment of water resources.

Research Team

Ashley Payne, Assistant Professor, Climate and Space Sciences and Engineering

Yulin Pan, Assistant Professor, Naval Architecture and Marine Engineering

Xun Huan, Assistant Professor, Mechanical Engineering

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