A Comparison of Variational and Ensemble-Based Data Assimilation Systems for Reanalysis of Sparse Observations

Jeffrey S. Whitaker Physical Sciences Division, NOAA Earth System Research Laboratory, Boulder, Colorado

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Gilbert P. Compo Climate Diagnostics Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado, and Physical Sciences Division, NOAA Earth System Research Laboratory, Boulder, Colorado

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Jean-Noël Thépaut European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Abstract

An observing system experiment, simulating a surface-only observing network representative of the 1930s, is carried out with three- and four-dimensional variational data assimilation systems (3D-VAR and 4D-VAR) and an ensemble-based data assimilation system (EnsDA). It is found that 4D-VAR and EnsDA systems produce analyses of comparable quality and that both are much more accurate than the analyses produced by the 3D-VAR system. The EnsDA system also produces useful estimates of analysis error, which are not directly available from the variational systems.

Corresponding author address: Jeffrey S. Whitaker, NOAA/Earth System Research Laboratory, 325 Broadway R/PSD1, Boulder, CO 80305-3328. Email: jeffrey.s.whitaker@noaa.gov

Abstract

An observing system experiment, simulating a surface-only observing network representative of the 1930s, is carried out with three- and four-dimensional variational data assimilation systems (3D-VAR and 4D-VAR) and an ensemble-based data assimilation system (EnsDA). It is found that 4D-VAR and EnsDA systems produce analyses of comparable quality and that both are much more accurate than the analyses produced by the 3D-VAR system. The EnsDA system also produces useful estimates of analysis error, which are not directly available from the variational systems.

Corresponding author address: Jeffrey S. Whitaker, NOAA/Earth System Research Laboratory, 325 Broadway R/PSD1, Boulder, CO 80305-3328. Email: jeffrey.s.whitaker@noaa.gov

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