Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach.

摘要

The long-term goal of this project is to quantify the extent to which reduced-order models can be used for the description, understanding and prediction of atmospheric, oceanic and sea ice variability on time scales of 1 12 months and beyond.