Incorporating Scale and Predictability Information in Multi-Model Ensemble Climate Predictions

Lead PI: Dr. Michael K. Tippett

Unit Affiliation: International Research Institute for Climate and Society (IRI)

August 2010 - July 2013
Project Type: Research

DESCRIPTION: The project will work to take the recognition that seemingly different approaches to multi-model forecasting are just special cases of a Bayesian methodology into account to develop a new multi-model prediction system that is mathematically rigorous and consistent. Also, the project will investigate benefits of using Predictable Component Analysis.

OUTCOMES: Showed that the proposed model may be of value only over small areas of land. Results published. Showed that the proposed model has a larger skill than ordinary least squares, results summarized and published. Predictable Component Analysis showed substantial improvement in South America and Africa due to pre-filtering.