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2012 N/A 

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Coupled Global-Regional Data Assimilation Using Joint States 

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Texas A&M University, Department of Atmospheric Sciences, 3150 

TAMU, College Station, TX, 77843-3150 

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Coupled Global-Regional Data Assimilation Using Joint States 

Istvan Szunyogh 

Texas A&M University, Department of Atmospheric Sciences, 3150 TAMU, College Station, TX, 

77843-3150 

phone: (979) 458-0553 fax: (979) 862-4466 email: szunyogh@tamu.edu 

Award Number: N00014-12-1-0785 
http://atmo.tamu.edu/profile/ISzunyogh 


LONG-TERM GOALS 

The main goal of this research project is to develop a data assimilation system to obtain a global 
atmospheric analysis for the U. S. Navy's Operational Global Atmospheric Prediction System 
(NOGAPS) model, as well as a set of limited area atmospheric analyses for multiple local domains for 
the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) model by a single data 
assimilation process. We will achieve this goal by developing a novel data assimilation system based 
on analyzing the joint states of the global and the limited area models. 


OBJECTIVES 

Similar to other major numerical prediction centers of the world, the Fleet Numerical Meteorology and 
Oceanography Center (FNMOC) prepares both global and limited area weather analyses and forecasts. 
In fact, FNMOC prepares limited area model products for more regions (more than 60) than any other 
center in the world. In the current implementation of the model suite, the global model is started from 
analyses prepared by the Naval Research Laboratory Atmospheric Variational Data Assimilation- 
Accelerated Presenter (NAVDAS-AR) data assimilation system, which is based on a 4D-VAR data 
assimilation scheme, while the regional model is started from analyses provided by the Naval Research 
Laboratory Atmospheric Variational Data Assimilation (NAVDAS) system for the atmosphere and the 
Navy Coupled Ocean Data Assimilation (NCODA) for the ocean. Both NAVDAS and NCODA are 
3D-VAR schemes. In this configuration, deterministic model information is propagated from the 
global model to the regional analysis through the lateral boundary conditions. Building on the results 
of our earlier research, we are developing a data assimilation algorithm, in which information flows in 
both directions between the global and the limited area data assimilation systems. We expect both the 
global and the limited area analyses to benefit from the coupled approach. In particular, we expect that 
in the coupled data assimilation system, the global analyses will benefit from the availability of the 
high-resolution limited area model information in regions where the presence of small scale 
atmospheric flow features (e.g., in a tropical cyclone or over complex terrain) severely restrict the 
representativeness of the observations at the scales resolved by the global model. 

In addition, we hope that in the process of developing and testing the data assimilation system, we will 
gain new knowledge about the mechanisms by which mesoscale processes influence synoptic and 


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global scale predictability. Such new knowledge will help make strategic decisions about the 
development of the analysis and forecast systems of the future. 


APPROACH 

Our approach takes advantage of the results of our earlier theoretical and modeling efforts on coupling 
the global and the limited area data assimilation processes (Merkova et al. 2011; Holt 2011; Holt et al. 
2012; Yoon et al. 2012) and the advances made by Dr. Craig Bishop and his NRL Monterey-based 
research group by incorporating ensemble-based flow-dependent information into NAVDAS. Dr. 
Bishop and his group have developed an ensemble-based, highly portable version of NAVDAS for 
NOGAPS and COAMPS. We work in close collaboration with Dr. Bishop’s group. The relevance of 
our research is expected to highly benefit from using a state-of-the-art operational system that includes 
capabilities to assimilate satellite radiance observations and to perfonn nonnal mode initialization. In 
addition, using the NRL system is expected to greatly accelerate the transfer of the research results to 
NRL, Monterey, and eventually to FNMOC. 


WORK COMPLETED 

The project has just begun. We are currently in the process of transferring the model and data 
assimilation codes from the Naval Research Laboratory, Monterey to Texas A&M University, where 
the code development will be carried out. 

REFERENCES 

Holt, C. R., I. Szunyogh, and G. Gyarmati, 2012: Can a moderate resolution limited-area data 
assimilation system add value to the global analysis of tropical cyclones? Mon. Wea. Rev. (under 
review). 

Holt, C. R., 2011: Testing a coupled global-limited area data assimilation system using observations 
from the 2004 Pacific typhoon season. Master of Science Thesis, Texas A&M University, 60 pp. 

Merkova, D., I. Szunyogh, and E. Ott, 2011: Strategies for coupling global and limited-area ensemble 
Kalman filter assimilation. Nonlin. Processes Geophys., 18, 415-430. 

Yoon, Y.-N., B. R. Hunt, E. Ott, and I. Szunyogh, 2012: Ensemble regional data assimilation using 
joint states. Tellus (in press). 


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