Collaborative Research: Enabling Petascale Ensemble-based Data Assimilation for the Numerical Analysis and Prediction of High-Impact Weather

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This proposal addresses the most challenging problems of very-high-resolution Numerical Weather Prediction, obtaining the optimal state estimations for initializing ensembles of predictions by assimilating the highest volume of weather observations available, and addressing problem sizes and scales that are only attainable on petascale computing platforms. The project is focused on the very hard problem of thunderstorm initiation, propagation and evolution. The effect of this investment in more accurate and timely forecast of thunderstorms can have a potentially transformative impact on hazard analysis and management.