Enhancing Weather Downscaling and Forecasting

Enhancing Weather Downscaling and Forecasting

Internship Description

Global weather products can only be computed at coarse resolution, and therefore cannot resolve important sub-grid scale features such as clouds and topography. Downscaling methods are used to compute local weather forecasts at high resolution from the global products. Nudging and Spectral Nudging methods are popular techniques for constraining local models with global products. The goal of the internship is to explore and test more advanced downscaling techniques based on the recently developed continuous data assimilation framework and/or the ensemble Kalman filter.​​​​​

Faculty Name

Ibrahim Hoteit

Field of Study

Applied Mathematics, Meteorology, or any related field​