6.4 Regionally Enhanced Global (REG) Data Assimilation (DA)

Tuesday, 9 January 2018: 2:15 PM
Room 14 (ACC) (Austin, Texas)
Istvan Szunyogh, Texas A&M Univ., College Station, TX; and M. Herrera, A. Brainard, M. A. Gawryla, C. H. Bishop, and D. D. Kuhl

We discuss a data assimilation technique that prepares a global analysis and multiple limited area analyses by a single computational process. The technique computes a high-resolution global analysis increment, which it then uses to update both the global and limited area background state estimates. 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. We have already developed a prototype data assimilation system by implementing the technique on the operational model and data assimilation computer codes of the U.S. Navy. In this talk, we present the results of analysis/forecast experiments with a reduced resolution version of the prototype system for different choices of the background state estimates. The results suggest that REG DA leads to a 1-3% average reduction of the forecast errors in the 5-day forecast range for NAVGEM and the 3-day forecast range for COAMPS.
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