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Improving Incremental Balance in the GSI 3DVAR Analysis System

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  • 1 Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, Maryland
  • | 2 Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland
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Abstract

The gridpoint statistical interpolation (GSI) analysis system is a unified global/regional three-dimensional variational data assimilation (3DVAR) analysis code that has been under development for several years at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center. It has recently been implemented into operations at NCEP in both the global and North American data assimilation systems (GDAS and NDAS, respectively). An important aspect of this development has been improving the balance of the analysis produced by GSI. The improved balance between variables has been achieved through the inclusion of a tangent-linear normal-mode constraint (TLNMC). The TLNMC method has proven to be very robust and effective. The TLNMC as part of the global GSI system has resulted in substantial improvement in data assimilation at NCEP.

* Additional affiliation: Science Applications International Corporation, Camp Springs, Maryland

+ Additional affiliation: Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

# Additional affiliation: Science Systems and Applications Incorporated, Lanham, Maryland

Corresponding author address: Daryl T. Kleist, NOAA Science Center 207, 5200 Auth Rd., Camp Springs, MD 20746-4304. Email: daryl.kleist@noaa.gov

Abstract

The gridpoint statistical interpolation (GSI) analysis system is a unified global/regional three-dimensional variational data assimilation (3DVAR) analysis code that has been under development for several years at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center. It has recently been implemented into operations at NCEP in both the global and North American data assimilation systems (GDAS and NDAS, respectively). An important aspect of this development has been improving the balance of the analysis produced by GSI. The improved balance between variables has been achieved through the inclusion of a tangent-linear normal-mode constraint (TLNMC). The TLNMC method has proven to be very robust and effective. The TLNMC as part of the global GSI system has resulted in substantial improvement in data assimilation at NCEP.

* Additional affiliation: Science Applications International Corporation, Camp Springs, Maryland

+ Additional affiliation: Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore County, Baltimore, Maryland

# Additional affiliation: Science Systems and Applications Incorporated, Lanham, Maryland

Corresponding author address: Daryl T. Kleist, NOAA Science Center 207, 5200 Auth Rd., Camp Springs, MD 20746-4304. Email: daryl.kleist@noaa.gov

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