Ocean Data Assimilation Systems for GODAE

Ocean data assimilation has reached a sufficient level of maturity such that observations are routinely combined with model forecasts to produce a variety of ocean products. Approaches to ocean data assimilation vary widely both in terms of the sophistication of the method and the observations assimilated, and also in terms of specification of the forecast error covariances, model biases, observation errors, and quality-control procedures. In this paper, we describe some of the ocean data assimilation systems that have been developed within the Global Ocean Data Assimilation Experiment (GODAE) community. We discuss assimilation methods, observations assimilated, and techniques used to specify error covariances. In addition, we describe practical implementation aspects and present analysis performance results for some of the analysis systems. Finally, we describe plans for improving the assimilation systems in the post-GODAE time period beyond 2008.

[1]  Sophie Ricci,et al.  Incorporating State-Dependent Temperature–Salinity Constraints in the Background Error Covariance of Variational Ocean Data Assimilation , 2005 .

[2]  Yosuke Fujii,et al.  Formation process of the Kuroshio large meander in 2004 , 2008 .

[3]  E. Joseph Metzger,et al.  Eddy Resolving Global Ocean Prediction , 2009, 2009 DoD High Performance Computing Modernization Program Users Group Conference.

[4]  Jérôme Vialard,et al.  Three- and Four-Dimensional Variational Assimilation with a General Circulation Model of the Tropical Pacific Ocean. Part I: Formulation, Internal Diagnostics, and Consistency Checks , 2003 .

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

[6]  F. Hernandez,et al.  A mean dynamic topography computed over the world ocean from altimetry, in situ measurements, and a geoid model , 2004 .

[7]  Geir Evensen,et al.  Assimilation of ice concentration in a coupled ice–ocean model, using the Ensemble Kalman filter , 2003 .

[8]  Jiang Zhu,et al.  Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific , 2008 .

[9]  T. Motoi,et al.  Reevaluation of the Takano–Oonishi Scheme for Momentum Advection on Bottom Relief in Ocean Models , 1999 .

[10]  Pierre Brasseur,et al.  Expected impact of the future SMOS and Aquarius Ocean surface salinity missions in the Mercator Ocean operational systems: New perspectives to monitor ocean circulation , 2008 .

[11]  Y. Fujii,et al.  Three-dimensional analysis of temperature and salinity in the equatorial Pacific using a variational method with vertical coupled temperature-salinity empirical orthogonal function modes , 2003 .

[12]  I. Fukumori,et al.  Origin and Pathway of Equatorial 13°C Water in the Pacific Identified by a Simulated Passive Tracer and Its Adjoint , 2009 .

[13]  A. Samuelsen,et al.  Influence of horizontal model grid resolution on the simulated primary production in an embedded primary production model in the Norwegian Sea , 2009 .

[14]  Jacques Verron,et al.  A singular evolutive extended Kalman filter for data assimilation in oceanography , 1998 .

[15]  B. Cornuelle,et al.  Interannual to Decadal Changes in the ECCO Global Synthesis , 2007 .

[16]  C. Wunsch,et al.  Decadal Trends in Sea Level Patterns : 1993-2004 , 2007 .

[17]  Peter R. Oke,et al.  Representation Error of Oceanic Observations for Data Assimilation , 2008 .

[18]  David L. T. Anderson,et al.  The ECMWF Ocean Analysis System: ORA-S3 , 2008 .

[19]  P. Oke,et al.  Eddy-resolving ocean circulation in the Asian Australian region inferred from an ocean reanalysis effort , 2008 .

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

[21]  Jean-Michel Brankart,et al.  Implementation of a multivariate data assimilation scheme for isopycnic coordinate ocean models: Application to a 1993–1996 hindcast of the North Atlantic Ocean circulation , 2003 .

[22]  Geir Evensen,et al.  Assimilating synthetic CryoSat sea ice thickness in a coupled ice-ocean model , 2007 .

[23]  Roger Daley,et al.  NAVDAS: Formulation and Diagnostics , 2001 .

[24]  Serge Gratton,et al.  Limited‐memory preconditioners, with application to incremental four‐dimensional variational data assimilation , 2008 .

[25]  P. Oke,et al.  Implications of the Form of the Ensemble Transformation in the Ensemble Square Root Filters , 2008 .

[26]  Mounir Benkiran,et al.  A Multivariate Reduced-order Optimal Interpolation Method and its Application to the Mediterranean Basin-scale Circulation , 2002 .

[27]  Peter R. Oke,et al.  Impacts of localisation in the EnKF and EnOI: experiments with a small model , 2007 .

[28]  J. Ridley,et al.  Sea ice concentration and motion assimilation in a sea ice−ocean model , 2008 .

[29]  Keith Haines,et al.  Ocean altimeter assimilation with observational‐ and model‐bias correction , 2008 .

[30]  Carl Wunsch,et al.  Global ocean circulation during 1992-1997, estimated from ocean observations and a general circulation model , 2002 .

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

[32]  Dimitris Menemenlis,et al.  Atmospheric and oceanic excitation of decadal‐scale Earth orientation variations , 2005 .

[33]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[34]  Tong Lee,et al.  On the cause of eastern equatorial Pacific Ocean T‐S variations associated with El Niño , 2004 .

[35]  Patrick Heimbach,et al.  NASA Supercomputer Improves Prospects for Ocean Climate Research , 2005 .

[36]  Ichiro Fukumori,et al.  Fitting Dynamic Models to the Geosat Sea Level Observations in the Tropical Pacific Ocean. Part II: A Linear, Wind-driven Model , 1993 .

[37]  P. Delecluse,et al.  Three- and Four-Dimensional Variational Assimilation with a General Circulation Model of the Tropical Pacific Ocean. Part II: Physical Validation , 2003 .

[38]  Peter R. Oke,et al.  The Bluelink ocean data assimilation system (BODAS) , 2008 .

[39]  Adrian Hines,et al.  Data assimilation in the FOAM operational short‐range ocean forecasting system: a description of the scheme and its impact , 2007 .

[40]  H. Tsujino,et al.  Dynamics of Kuroshio path variations in a high-resolution general circulation model , 2006 .

[41]  Nori,et al.  “ An Approximate Kalman Filter for Ocean Data Assimilation ; An Example with an Idealized Gulf Stream Modelt , 1995 .

[42]  G. Evensen.  Data Assimilation: The Ensemble Kalman Filter , 2006 .

[43]  H. Hasumi,et al.  Deep Pacific Circulation Controlled by Vertical Diffusivity at the Lower Thermocline Depths , 2000 .

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

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

[46]  Pierre Brasseur,et al.  Dynamical evolution of the error statistics with the SEEK filter to assimilate altimetric data in eddy‐resolving ocean models , 2001 .

[47]  D. Menemenlis,et al.  A Near-Uniform Basin-Wide Sea Level Fluctuation of the Mediterranean Sea , 2007 .

[48]  L. Perelman,et al.  A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers , 1997 .

[49]  D. Stammer,et al.  Decadal Sea Level Changes in the 50-Year GECCO Ocean Synthesis , 2008 .

[50]  Yosuke Fujii,et al.  Application of Nonlinear Constraints in a Three-Dimensional Variational Ocean Analysis , 2005 .

[51]  P. Oke,et al.  Impact of Argo, SST, and altimeter data on an eddy‐resolving ocean reanalysis , 2007 .

[52]  Thomas M. Smith,et al.  An Improved In Situ and Satellite SST Analysis for Climate , 2002 .

[53]  D. Chelton,et al.  Geographical Variability of the First Baroclinic Rossby Radius of Deformation , 1998 .

[54]  M. Kanamitsu,et al.  NCEP–DOE AMIP-II Reanalysis (R-2) , 2002 .

[55]  M. Balmaseda,et al.  Ensemble estimation of background‐error variances in a three‐dimensional variational data assimilation system for the global ocean , 2009 .

[56]  Yosuke Fujii,et al.  Meteorological research institute multivariate ocean variational estimation (MOVE) system : Some early results , 2006 .

[57]  P. Courtier,et al.  Correlation modelling on the sphere using a generalized diffusion equation , 2001 .

[58]  Y. Fujii,et al.  A Reconstruction of Observed Profiles in the Sea East of Japan Using Vertical Coupled Temperature-Salinity EOF Modes , 2003 .

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

[60]  Y. Fujii.  Preconditioned Optimizing Utility for Large-dimensional analyses (POpULar) , 2005 .

[61]  C. Donlon,et al.  OSTIA : An operational, high resolution, real time, global sea surface temperature analysis system , 2007, OCEANS 2007 - Europe.

[62]  J. Wilkin,et al.  Ocean Interpolation by Four-Dimensional Weighted Least Squares—Application to the Waters around Australasia , 2002 .

[63]  G. Evensen,et al.  Assimilation of ocean colour data into a biochemical model of the North Atlantic: Part 1. Data assimilation experiments , 2003 .

[64]  A nonlinear preconditioned quasi-Newton method without inversion of a first-guess covariance matrix in variational analyses , 2003 .

[65]  P. Delecluse,et al.  OPA 8.1 Ocean General Circulation Model reference manual , 1998 .

[66]  G. Evensen,et al.  Sequential Data Assimilation Techniques in Oceanography , 2003 .

[67]  Peter R. Oke,et al.  Ensemble data assimilation for an eddy‐resolving ocean model of the Australian region , 2005 .

[68]  Sylvain Bouillon,et al.  LIM3, an advanced sea ice model for climate simulation and operational oceanography , 2008 .

[69]  M. Kamachi,et al.  Global statistical space-time scales of oceanic variability estimated from the TOPEX/ POSEIDON altimeter data , 2000 .

[70]  Ichiro Fukumori,et al.  Mechanisms Controlling the Interannual Variation of Mixed Layer Temperature Averaged over the Niño-3 Region , 2007 .

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

[72]  Eric Blayo,et al.  A reduced-order strategy for 4D-Var data assimilation , 2005, 0709.2825.

[73]  H. Tsujino,et al.  Generation of a trigger meander for the 2004 Kuroshio large meander , 2008 .

[74]  Ichiro Fukumori,et al.  What Is Data Assimilation Really Solving, and How Is the Calculation Actually Done? , 2006 .

[75]  Yosuke Fujii,et al.  Short-range prediction experiments of the Kuroshio path variabilities south of Japan , 2006 .

[76]  A. Vidard,et al.  Multi-model multi-method multi-decadal ocean analyses from the ENACT project , 2006 .

[77]  Ichiro Fukumori,et al.  A Partitioned Kalman Filter and Smoother , 2002 .

[78]  J. Cummings,et al.  Operational multivariate ocean data assimilation , 2005 .