Data assimilation in the FOAM operational short‐range ocean forecasting system: a description of the scheme and its impact

A detailed description of the data assimilation scheme used in the Forecasting Ocean Assimilation Model (FOAM) operational ocean forecasting system is presented. The theoretical basis for the scheme is an improved version of the analysis correction scheme, which includes information from previously assimilated data. The scheme requires the a priori specification of error covariance information for the background model field and the observations. The way in which these error covariances have been estimated is described and some examples are given. The FOAM system assimilates sea surface temperature, sea-level anomaly, temperature profile, salinity profile and sea-ice concentration data. Aspects of the scheme that are specific to each of these observation types are described. Two sets of experiments demonstrating the impact of the data assimilation are presented. The first set are in an idealized identical-twin setting, using the ° -resolution North Atlantic FOAM configuration in which the state of the true ocean is assumed to be known. These experiments show that the analyses and forecasts are improved by assimilating the altimeter sea-level-anomaly data. The second set of experiments comprise data impact studies in a realistic hindcast setting. These experiments show a positive impact on the analyses from the Argo temperature- and salinity-profile data. Copyright © 2007 Royal Meteorological Society

[1]  Nancy Nichols,et al.  Assessment of wind‐stress errors using bias corrected ocean data assimilation , 2004 .

[2]  R. Daley.  Atmospheric Data Analysis , 1991 .

[3]  Jean-philippe Drecourt,et al.  Influence of systematic error correction on the temporal behavior of an ocean model , 2006 .

[4]  N. B. Ingleby,et al.  Bayesian quality control using multivariate normal distributions , 1993 .

[5]  R. S. Bell,et al.  The Meteorological Office analysis correction data assimilation scheme , 1991 .

[6]  M. Bell,et al.  The Forecasting Ocean Assimilation Model (Foam) System , 2006 .

[7]  Keith Haines,et al.  Salinity Assimilation Using S(T): Covariance Relationships , 2006 .

[8]  I. Totterdell,et al.  Production and export in a global ocean ecosystem model , 2001 .

[9]  A. Troccoli,et al.  Use of the Temperature Salinity Relation in a Data Assimilation Context , 1999 .

[10]  Andrew C. Lorenc,et al.  Analysis methods for numerical weather prediction , 1986 .

[11]  A. Lorenc.  Iterative analysis using covariance functions and filters , 1992 .

[12]  John F. B. Mitchell,et al.  The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments , 2000 .

[13]  Richard G. Forbes,et al.  Assessment of the FOAM global data assimilation system for real-time operational ocean forecasting , 2000 .

[14]  Sandipa Singh,et al.  Monthly Maps of Sea Surface Height in the North Atlantic and Zonal Indices for the Gulf Stream Using TOPEX/Poseidon Altimeter Data. , 1997 .

[15]  Arlindo da Silva,et al.  Data assimilation in the presence of forecast bias , 1998 .

[16]  Lawrence L. Takacs,et al.  Data Assimilation Using Incremental Analysis Updates , 1996 .

[17]  Nancy Nichols,et al.  Assimilation of data into an ocean model with systematic errors near the equator , 2004 .

[18]  A. Bratseth.  Statistical interpolation by means of successive corrections , 1986 .

[19]  Philippe Courtier,et al.  Unified Notation for Data Assimilation : Operational, Sequential and Variational , 1997 .

[20]  M. Huddleston,et al.  Quality control of ocean temperature and salinity profiles — Historical and real-time data , 2007 .

[21]  G. Evensen.  Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[22]  Peter Jan van Leeuwen,et al.  Balanced Ocean-Data Assimilation near the Equator , 2002 .

[23]  E. A. Martinsen,et al.  Implementation and testing of a lateral boundary scheme as an open boundary condition in a barotropic ocean model , 1987 .

[24]  John Derber,et al.  The National Meteorological Center's spectral-statistical interpolation analysis system , 1992 .

[25]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[26]  Anthony Hollingsworth,et al.  The statistical structure of short-range forecast errors as determined from radiosonde data , 1986 .

[27]  Keith Haines,et al.  Altimetric assimilation with water property conservation , 1996 .

[28]  C. Eden,et al.  The semi-prognostic method , 2004 .

[29]  P. Houtekamer,et al.  A Sequential Ensemble Kalman Filter for Atmospheric Data Assimilation , 2001 .