Regionally Enhanced Global (REG) Local Ensemble Transform KalmanFilter (LETKF)
Abstract
Funds are provided to conduct research to develop a data assimilation technique that prepares global NWP analysis and limited area NWP analyses by a single computational process. The main advantages of the technique are a reduction of the complexity and maintenance cost of the data assimilation computer codes, a lower overall computational cost of data assimilation, and potentially more accurate global and limited area analyses and forecasts. The PI has previously developed a prototype data assimilation system by implementing the technique on the operational model and data assimilation computer codes of the Navy. The goal of the 3-year research project is to further improve the performance of the prototype system by replacing 4D-Var with a Local Ensemble Transform Kalman Filter (LETKF), which he expects to reduce the complexity of the computer codes, the overall cost of the computations, and the global and limited area forecast errors. He will develop and test the prototype Regionally Enhanced Global (REG) LETKF in close collaboration with NRL scientists. This effort aims to improve U.S. Navy weather analyses and forecasts for global and regional areas.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 26, 2018
- Source ID
- N000141812509
Entities
People
- István Szunyogh
Organizations
- Office of Naval Research
- Texas A&M University
- United States Navy