Options
GODAE systems in operation
Author(s)
Language
English
Obiettivo Specifico
4.6. Oceanografia operativa per la valutazione dei rischi in aree marine
Status
Published
JCR Journal
N/A or not JCR
Title of the book
Issue/vol(year)
3/22 (2009)
Publisher
The oceanograohy Society, USA
Pages (printed)
76-91
Issued date
September 2009
Abstract
During the last 15 years, operational oceanography systems have been
developed in several countries around the world. These developments have been
fostered primarily by the Global Ocean Data Assimilation Experiment (GODAE),
which coordinated these activities, encouraged partnerships, and facilitated
constructive competition. This multinational coordination has been very beneficial
for the development of operational oceanography. Today, several systems provide
routine, real-time ocean analysis, forecast, and reanalysis products. These systems
are based on (1) state-of-the-art Ocean General Circulation Model (OGCM)
configurations, either global or regional (basin-scale), with resolutions that range
from coarse to eddy-resolving, and (2) data assimilation techniques ranging from
analysis correction to advanced three- or four-dimensional variational schemes. These
systems assimilate altimeter sea level anomalies, sea surface temperature data, and
in situ profiles of temperature and salinity, including Argo data. Some systems have
implemented downscaling capacities, which consist of embedding higher-resolution
local systems in global and basin-scale models (through open boundary exchange of
data), especially in coastal regions, where small scale-phenomena are important, and
also increasing the spatial resolution for these regional/coastal systems to be able to
resolve smaller scales (so-called downscaling). Others have implemented coupling
with the atmosphere and/or sea ice. This paper provides a short review of these
operational GODAE systems.
developed in several countries around the world. These developments have been
fostered primarily by the Global Ocean Data Assimilation Experiment (GODAE),
which coordinated these activities, encouraged partnerships, and facilitated
constructive competition. This multinational coordination has been very beneficial
for the development of operational oceanography. Today, several systems provide
routine, real-time ocean analysis, forecast, and reanalysis products. These systems
are based on (1) state-of-the-art Ocean General Circulation Model (OGCM)
configurations, either global or regional (basin-scale), with resolutions that range
from coarse to eddy-resolving, and (2) data assimilation techniques ranging from
analysis correction to advanced three- or four-dimensional variational schemes. These
systems assimilate altimeter sea level anomalies, sea surface temperature data, and
in situ profiles of temperature and salinity, including Argo data. Some systems have
implemented downscaling capacities, which consist of embedding higher-resolution
local systems in global and basin-scale models (through open boundary exchange of
data), especially in coastal regions, where small scale-phenomena are important, and
also increasing the spatial resolution for these regional/coastal systems to be able to
resolve smaller scales (so-called downscaling). Others have implemented coupling
with the atmosphere and/or sea ice. This paper provides a short review of these
operational GODAE systems.
References
Hurlburt, H.E., D.N. Fox, and E.J. Metzger. 1990.
Cummings, J.A. 2005. Operational multivariate ocean
Statistical inference of weakly correlated subther-
data assimilation. Quarterly Journal of the Royal
mocline fields from satellite altimeter data. Journal
Meteorological Society 131:3,583–3,604.
of Geophysical Research 95(C7):11,375–11,409.
Dai, A., and K.E. Trenberth. 2003. New estimates
Hurlburt, H.E., E.P. Chassignet, J.A. Cummings, A.B.
of continental discharge and oceanic freshwater
Kara, E.J. Metzger, J.F. Shriver, O.M. Smedstad,
transport. Paper presented at the Symposium on
A.J. Wallcraft, C.N. Barron. 2008. Eddy-resolving
Observing and Understanding the Variability of
global ocean prediction. Pp. 353–381 in Ocean
Water in Weather and Climate. February 9–13,
Modeling in an Eddying Regime. Geophysical
2003, Long Beach, CA.
Monograph 177, M. Hecht and H. Hasumi, eds,
Dobricic, S., and N. Pinardi. 2008. An oceanographic
American Geophysical Union, Washington, DC.
three-dimensional variational data assimilation
Imawaki, S., H. Uchida, H. Ichikawa, M. Fukasawa,
scheme. Ocean Modelling 22 (3):89–105.
S. Umatani, and the ASUKA group. 2001. Satellite
Evensen, G. 2006. Data Assimilation: The Ensemble
altimeter monitoring the Kuroshio transport south
Kalman Filter. Springer, 280 pp.
of Japan. Geophysical Research Letters 28:17–20.
Fichefet, T., and M.A. Morales Maqueda. 1997.
Keghouche, I., L. Bertino, and K.A. Lisæter. 2009.
Sensitivity of a global sea ice model to the treat-
Parameterization of an iceberg drift model in the
ment of ice thermodynamics and dynamics.
Barrents Sea. Journal of Atmospheric and Oceanic
Journal of Geophysical Research 102:12,609–12,646.
Technology, doi:10.1175/2009JTECHO678.1.
Fox, D.N., W.J. Teague, C.N. Barron, M.R. Carnes,
rEFErENcE S Lee, T., and I. Fukumori. 2003. Interannual to decadal
and C.M. Lee. 2002. The Modular Ocean Data
Barron, C.N., A.B. Kara, P.J. Martin, R.C. Rhodes, and
variation of tropical-subtropical exchange in the
Assimilation System (MODAS). Journal of
L.F. Smedstad. 2006. Formulation, implementation
Pacific Ocean: Boundary versus interior pycnocline
Atmospheric and Oceanic Technology 19:240–252.
and examination of vertical coordinate choices in
transports. International Journal of Climatology
Fujii, Y., and M. Kamachi. 2003a. Three-dimensional
the global Navy Coastal Ocean Model (NCOM).
16:4,022–4,042.
analysis of temperature and salinity in the equa-
Ocean Modelling 11:347–375, doi:10.1016/j.
Le Provost, C. 2002. GODAE Internal Metrics for Model
torial Pacific using a variational method with
ocemod.2005.01.004.
Performance Evaluation and Intercomparison.
vertical coupled temperature-salinity EOF modes.
Barron, C.N., and A.B. Kara. 2006. Satellite-based daily
CNRS/LEGOS, ed, Toulouse, France, 12 pp.
Journal of Geophysical. Research 108(C9), 3297,
SSTs over the global ocean. Geophysical Research
Levitus, S. 1982. Climatological Atlas of the World
doi:10.1029/2002JC001745.
Letters 33, L15603, doi:10.1029/2006GL026356.
Ocean. Technical report, NOAA Prof. Pap. No. 13,
Fujii, Y, and M. Kamachi. 2003b. A reconstruction
Barron, C.N., L.F. Smedstad, J.M. Dastugue, and O.M.
US Government Printing Office, Washington, DC,
of observed profiles in the sea east of Japan using
Smedstad. 2007. Evaluation of ocean models using
173 pp.
vertical coupled temperature-salinity EOF modes.
observed and simulated drifter trajectories: Impact
Madec, G. 2008. NEMO Ocean Engine. Report, Institut
Journal of Oceanography 59:173–186.
of sea surface height on synthetic profiles for data
Pierre-Simon-Laplace (IPSL), France, No. 27 ISSN
Fujii, Y. 2005. Preconditioned optimizing utility for
assimilation. Journal of Geophysical Research 112,
No 1288-1619, 197 pp.
large-dimensional analyses (POpULar). Journal of
C07019, doi:10.1029/2006JC003982.
Madec, G., and M. Imbard. 1996. A global ocean mesh
Oceanography 61:167–181.
Bell, M.J., R.M. Forbes, and A. Hines. 2000.
to overcome the North Pole singularity. Climate
Fukumori, I. 2002. A partitioned Kalman filter
Assessment of the FOAM global data assimilation
Dynamics 12:381–388.
and smoother. Monthly Weather Review
system for real-time operational ocean forecasting.
Martin, M.J., A. Hines, and M.J. Bell. 2007. Data
130:1,370–1,383.
Journal of Marine Systems 25:1–22.
assimilation in the FOAM operational short-range
Giraud, S., S. Baudel, E. Dombrowsky, and P. Bahurel.
Bertino, L., and K.A. Lisæter. 2008. The TOPAZ
ocean forecasting system: A description of the
1997. The SOPRANE project: Real-time moni-
monitoring and prediction system for the
scheme and its impact. Quarterly Journal of the
toring of the North-East Atlantic—ocean circula-
Atlantic and Arctic oceans. Journal of Operational
Royal Meteorological Society 133:981–995.
tion nowcast/forecast for oceanographic scientific
Oceanography 1:15–19.
Metzger, E.J., O.M. Smedstad, P. Thoppil, H.E.
campaigns. In Proceedings of the International
Bleck, R. 2002. An oceanic general circulation model
Hurlburt, A.J. Wallcraft, D.S. Franklin, J.F. Shriver,
Symposium: Monitoring the Oceans in the 2000s: An
framed in hybrid isopycnic-cartesian coordinates.
and L.F. Smedstad. 2008. Validation Test Report for
Integrated Approach. October 15–17, 1997. Biarritz,
Ocean Modelling 4:55–88.
the Global Ocean Predictions System V3.0 - 1/12°
France, CNES, Toulouse, France.
Brassington, G.B., T. Pugh, C. Spillman, E. Schulz, H.
HYCOM/NCODA: Phase I. NRL Memorandum
Griffies, S.M., M.J. Harrison, R.C. Pacanowski, and A.
Beggs, A. Schiller, and P.R. Oke. 2007. BLUElink>
Report, NRL/MR/7320--08-9148, 88 pp.
Rosati. 2004. A technical guide to MOM4 GFDL
Development of operational oceanography and
Oke, P.R., G.B. Brassington, D.A. Griffin, and A.
Ocean Group. Technical Report No. 5, NOAA/
servicing in Australia. Journal of Research and
Schiller. 2008. The Bluelink ocean data assimilation
Geophysical Fluid Dynamics Laboratory, 339 pp.
Practice in Information Technology 39:151–164
system (BODAS). Ocean Modelling 21(1–2):46–70.
Halkides, D., and T. Lee. 2009. Mechanisms control-
Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M.
Pham, D.T., J. Verron, and M.C. Roubaud. 1998. A
ling seasonal-to-interannual mixed-layer
Smedstad, J. Cummings, G.R. Halliwell, R. Bleck,
singular evolutive extended Kalman filter for data
temperature variability in the southeastern tropical
R. Barialle, A.J. Wallcraft, C. Lozano, and others.
assimilation in oceanography. Journal of Marine
Indian Ocean. Journal of Geophysical Research 114,
2009. US GODAE: Global Ocean Prediction with
Systems 16(3–4):323–340.
C02012, doi:10.1029/2008JC004949.
the HYbrid Coordinate Ocean Model (HYCOM).
Pinardi, N., I. Allen, E. Demirov, P. De Mey ,
Hellerman, S., and M. Rosenstein. 1983. Normal
Oceanography 22(2):64–75.
G. Korres, A. Lascaratos, P.-Y. Le Traon, C.
monthly wind stress over the world ocean with
Counillon, F., and L. Bertino. 2009. High-resolution
Maillard, G. Manzella, and C. Tziavos. 2003. The
error estimates. Journal of Physical Oceanography
ensemble forecasting for the Gulf of Mexico eddies
Mediterranean ocean forecasting system: First
13:1,093–1,104.
and fronts. Ocean Dynamics 59(1):83–95.
phase of implementation (1998–2001). Annales
Geophysicae 21:3–20 c.
Van Woert, M.L., C.-Z. Zou, W.N. Meier, P.D. Hovey,
Purser, R.J., W.-S. Wu, D.F. Parrish, and N.M. Roberts.
R.H. Preller, and P.G. Posey. 2004. Forecast verifi-
2003a. Numerical aspects of the application of
cation of the Polar Ice Prediction System (PIPS) sea
recursive filters to variational statistical analysis.
ice concentration fields. Journal of Atmospheric and
Part I: Spatially homogeneous and isotropic
Oceanic Technology 21:944–957.
Gaussian covariances. Monthly Weather Review
Wallcraft, A.J., A.B. Kara, H.E. Hurlburt, and P.A.
131:1,524–1,535.
Rochford. 2003. The NRL Layered Ocean
Purser, R.J., W.-S. Wu, D.F. Parrish, and N.M. Roberts.
Model (NLOM) with an embedded mixed
2003b. Numerical aspects of the application of
layer sub-model: Formulation and tuning.
recursive filters to variational statistical analysis.
Journal of Atmospheric and Oceanic Technology
Part II: Spatially inhomogeneous and anisotropic
20:1,601–1,615.
general covariances. Monthly Weather Review
Wunsch, C. and P. Heimbach. 2007. Practical global
131:1,536–1,548.
oceanic state estimation. Physica D-Nonlinear
Rhodes, R.C., H.E. Hurlburt, A.J. Wallcraft, C.N.
Phenomena 230:197–208.
Barron, P.J. Martin, O.M. Smedstad, S.L. Cross,
Wunsch, C., P. Heimbach, R.M. Ponte, I. Fukumori,
E.J. Metzger, J.F. Shriver, A.B. Kara, and D.S. Ko.
and the ECCO-GODAE Consortium Members.
2002. Navy real-time global modeling systems.
2009. The global general circulation of the
Oceanography 15(1):29–43.
ocean estimated by the ECCO-Consortium.
Schiller, A., P.R. Oke, G.B. Brassington, M. Entel, R.
Oceanography 22(2):88–103.
Fiedler, D.A. Griffin, and J. Mansbridge. 2008.
Yan, C.X., J. Zhu, R.F. Li, and G.Q.Zhou. 2004. Roles
Eddy-resolving ocean circulation in the Asian-
of vertical correlation of background error and
Australian region inferred from an ocean reanal-
T-S relations in estimation temperature and
ysis effort. Progress in Oceanography 76:334–365.
salinity profiles from sea surface dynamic height.
Seaman, R., W. Bourke, P. Steinle, T. Hart, G. Embery,
Journal of Geophysical Research 109, C08010,
M. Naughton, and L. Rikus. 1995. Evolution of the
doi:10.1029/2003JC002224,2004.
Bureau of Meteorology’s global assimilation and
Zhang, R.-H., and M. Endoh. 1992. A free surface
prediction system. Part 1: Analyses and initializa-
general circulation model for the tropical
tion. Australian Meteorological Magazine 44:1–18.
Pacific Ocean. Journal of Geophysical Research
Shriver, J.F., H.E. Hurlburt, O.M. Smedstad, A.J.
97(C7):11,237–11,255.
Wallcraft, and R.C. Rhodes. 2007. 1/32°real-time
Zhu, J., and C.X. Yan. 2006. Nonlinear balance
global ocean prediction and value-added over
constraints in 3DVAR data assimilation. Science in
1/16°resolution. Journal of Marine Systems 65:3–26.
China Series D 49(3):331–336. Available online at:
Smedstad, O.M., H.E. Hurlburt, E.J. Metzger, R.C.
http://www.springerlink.com/content/g42n172648
Rhodes, J.F. Shriver, A.J. Wallcraft, and A.B. Kara.
66/?p=f225c9eb3d5c4f4cb21e172ae05123bc&pi=43
2003. An operational eddy-resolving 1/16° global
ocean nowcast/forecast system. Journal of Marine
Systems 40–41:341–361.
Stammer, D., C. Wunsch, R. Giering, C. Eckert,
P. Heimbach, J. Marotzke, A. Adcroft, C.N.
Hill, and J. Marshall. 2003. Volume, heat, and
freshwater transports of the global ocean circu-
lation 1993–2000, estimated from a general
circulation model constrained by World
Ocean Circulation Experiment (WOCE) data.
Journal of Geophysical Research 108 (C1), 3007,
doi:10.1029/2001JC001115.
Tonani, M., N. Pinardi, S. Dobricic, I. Pujol, and
C. Fratianni. 2008. A high resolution free
surface model on the Mediterranean Sea. Ocean
Science 4:1–14.
Tranchant, B., C.E. Testut, L. Renault, N. Ferry, E.
Obligis, C. Boone, and G. Larnicol. 2008. Data
assimilation of simulated SSS SMOS products in
an ocean forecasting system. Journal of Operational
Oceanography 2008(2):19–27(9).
Troccoli, A., and P. Kallberg. 2004. Precipitation
Correction in the ERA-40 Reanalysis. ERA-40
Project Report Series, ECMWF, Reading, UK.
Usui, N., S. Ishizaki, Y. Fujii, H. Tsujino, T. Yasuda,
and M. Kamachi. 2006. Meteorological Research
Institute Multivariate Ocean Variational Estimation
(MOVE) System: Some early results. Advances in
Space Research 37:806–822.
Cummings, J.A. 2005. Operational multivariate ocean
Statistical inference of weakly correlated subther-
data assimilation. Quarterly Journal of the Royal
mocline fields from satellite altimeter data. Journal
Meteorological Society 131:3,583–3,604.
of Geophysical Research 95(C7):11,375–11,409.
Dai, A., and K.E. Trenberth. 2003. New estimates
Hurlburt, H.E., E.P. Chassignet, J.A. Cummings, A.B.
of continental discharge and oceanic freshwater
Kara, E.J. Metzger, J.F. Shriver, O.M. Smedstad,
transport. Paper presented at the Symposium on
A.J. Wallcraft, C.N. Barron. 2008. Eddy-resolving
Observing and Understanding the Variability of
global ocean prediction. Pp. 353–381 in Ocean
Water in Weather and Climate. February 9–13,
Modeling in an Eddying Regime. Geophysical
2003, Long Beach, CA.
Monograph 177, M. Hecht and H. Hasumi, eds,
Dobricic, S., and N. Pinardi. 2008. An oceanographic
American Geophysical Union, Washington, DC.
three-dimensional variational data assimilation
Imawaki, S., H. Uchida, H. Ichikawa, M. Fukasawa,
scheme. Ocean Modelling 22 (3):89–105.
S. Umatani, and the ASUKA group. 2001. Satellite
Evensen, G. 2006. Data Assimilation: The Ensemble
altimeter monitoring the Kuroshio transport south
Kalman Filter. Springer, 280 pp.
of Japan. Geophysical Research Letters 28:17–20.
Fichefet, T., and M.A. Morales Maqueda. 1997.
Keghouche, I., L. Bertino, and K.A. Lisæter. 2009.
Sensitivity of a global sea ice model to the treat-
Parameterization of an iceberg drift model in the
ment of ice thermodynamics and dynamics.
Barrents Sea. Journal of Atmospheric and Oceanic
Journal of Geophysical Research 102:12,609–12,646.
Technology, doi:10.1175/2009JTECHO678.1.
Fox, D.N., W.J. Teague, C.N. Barron, M.R. Carnes,
rEFErENcE S Lee, T., and I. Fukumori. 2003. Interannual to decadal
and C.M. Lee. 2002. The Modular Ocean Data
Barron, C.N., A.B. Kara, P.J. Martin, R.C. Rhodes, and
variation of tropical-subtropical exchange in the
Assimilation System (MODAS). Journal of
L.F. Smedstad. 2006. Formulation, implementation
Pacific Ocean: Boundary versus interior pycnocline
Atmospheric and Oceanic Technology 19:240–252.
and examination of vertical coordinate choices in
transports. International Journal of Climatology
Fujii, Y., and M. Kamachi. 2003a. Three-dimensional
the global Navy Coastal Ocean Model (NCOM).
16:4,022–4,042.
analysis of temperature and salinity in the equa-
Ocean Modelling 11:347–375, doi:10.1016/j.
Le Provost, C. 2002. GODAE Internal Metrics for Model
torial Pacific using a variational method with
ocemod.2005.01.004.
Performance Evaluation and Intercomparison.
vertical coupled temperature-salinity EOF modes.
Barron, C.N., and A.B. Kara. 2006. Satellite-based daily
CNRS/LEGOS, ed, Toulouse, France, 12 pp.
Journal of Geophysical. Research 108(C9), 3297,
SSTs over the global ocean. Geophysical Research
Levitus, S. 1982. Climatological Atlas of the World
doi:10.1029/2002JC001745.
Letters 33, L15603, doi:10.1029/2006GL026356.
Ocean. Technical report, NOAA Prof. Pap. No. 13,
Fujii, Y, and M. Kamachi. 2003b. A reconstruction
Barron, C.N., L.F. Smedstad, J.M. Dastugue, and O.M.
US Government Printing Office, Washington, DC,
of observed profiles in the sea east of Japan using
Smedstad. 2007. Evaluation of ocean models using
173 pp.
vertical coupled temperature-salinity EOF modes.
observed and simulated drifter trajectories: Impact
Madec, G. 2008. NEMO Ocean Engine. Report, Institut
Journal of Oceanography 59:173–186.
of sea surface height on synthetic profiles for data
Pierre-Simon-Laplace (IPSL), France, No. 27 ISSN
Fujii, Y. 2005. Preconditioned optimizing utility for
assimilation. Journal of Geophysical Research 112,
No 1288-1619, 197 pp.
large-dimensional analyses (POpULar). Journal of
C07019, doi:10.1029/2006JC003982.
Madec, G., and M. Imbard. 1996. A global ocean mesh
Oceanography 61:167–181.
Bell, M.J., R.M. Forbes, and A. Hines. 2000.
to overcome the North Pole singularity. Climate
Fukumori, I. 2002. A partitioned Kalman filter
Assessment of the FOAM global data assimilation
Dynamics 12:381–388.
and smoother. Monthly Weather Review
system for real-time operational ocean forecasting.
Martin, M.J., A. Hines, and M.J. Bell. 2007. Data
130:1,370–1,383.
Journal of Marine Systems 25:1–22.
assimilation in the FOAM operational short-range
Giraud, S., S. Baudel, E. Dombrowsky, and P. Bahurel.
Bertino, L., and K.A. Lisæter. 2008. The TOPAZ
ocean forecasting system: A description of the
1997. The SOPRANE project: Real-time moni-
monitoring and prediction system for the
scheme and its impact. Quarterly Journal of the
toring of the North-East Atlantic—ocean circula-
Atlantic and Arctic oceans. Journal of Operational
Royal Meteorological Society 133:981–995.
tion nowcast/forecast for oceanographic scientific
Oceanography 1:15–19.
Metzger, E.J., O.M. Smedstad, P. Thoppil, H.E.
campaigns. In Proceedings of the International
Bleck, R. 2002. An oceanic general circulation model
Hurlburt, A.J. Wallcraft, D.S. Franklin, J.F. Shriver,
Symposium: Monitoring the Oceans in the 2000s: An
framed in hybrid isopycnic-cartesian coordinates.
and L.F. Smedstad. 2008. Validation Test Report for
Integrated Approach. October 15–17, 1997. Biarritz,
Ocean Modelling 4:55–88.
the Global Ocean Predictions System V3.0 - 1/12°
France, CNES, Toulouse, France.
Brassington, G.B., T. Pugh, C. Spillman, E. Schulz, H.
HYCOM/NCODA: Phase I. NRL Memorandum
Griffies, S.M., M.J. Harrison, R.C. Pacanowski, and A.
Beggs, A. Schiller, and P.R. Oke. 2007. BLUElink>
Report, NRL/MR/7320--08-9148, 88 pp.
Rosati. 2004. A technical guide to MOM4 GFDL
Development of operational oceanography and
Oke, P.R., G.B. Brassington, D.A. Griffin, and A.
Ocean Group. Technical Report No. 5, NOAA/
servicing in Australia. Journal of Research and
Schiller. 2008. The Bluelink ocean data assimilation
Geophysical Fluid Dynamics Laboratory, 339 pp.
Practice in Information Technology 39:151–164
system (BODAS). Ocean Modelling 21(1–2):46–70.
Halkides, D., and T. Lee. 2009. Mechanisms control-
Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M.
Pham, D.T., J. Verron, and M.C. Roubaud. 1998. A
ling seasonal-to-interannual mixed-layer
Smedstad, J. Cummings, G.R. Halliwell, R. Bleck,
singular evolutive extended Kalman filter for data
temperature variability in the southeastern tropical
R. Barialle, A.J. Wallcraft, C. Lozano, and others.
assimilation in oceanography. Journal of Marine
Indian Ocean. Journal of Geophysical Research 114,
2009. US GODAE: Global Ocean Prediction with
Systems 16(3–4):323–340.
C02012, doi:10.1029/2008JC004949.
the HYbrid Coordinate Ocean Model (HYCOM).
Pinardi, N., I. Allen, E. Demirov, P. De Mey ,
Hellerman, S., and M. Rosenstein. 1983. Normal
Oceanography 22(2):64–75.
G. Korres, A. Lascaratos, P.-Y. Le Traon, C.
monthly wind stress over the world ocean with
Counillon, F., and L. Bertino. 2009. High-resolution
Maillard, G. Manzella, and C. Tziavos. 2003. The
error estimates. Journal of Physical Oceanography
ensemble forecasting for the Gulf of Mexico eddies
Mediterranean ocean forecasting system: First
13:1,093–1,104.
and fronts. Ocean Dynamics 59(1):83–95.
phase of implementation (1998–2001). Annales
Geophysicae 21:3–20 c.
Van Woert, M.L., C.-Z. Zou, W.N. Meier, P.D. Hovey,
Purser, R.J., W.-S. Wu, D.F. Parrish, and N.M. Roberts.
R.H. Preller, and P.G. Posey. 2004. Forecast verifi-
2003a. Numerical aspects of the application of
cation of the Polar Ice Prediction System (PIPS) sea
recursive filters to variational statistical analysis.
ice concentration fields. Journal of Atmospheric and
Part I: Spatially homogeneous and isotropic
Oceanic Technology 21:944–957.
Gaussian covariances. Monthly Weather Review
Wallcraft, A.J., A.B. Kara, H.E. Hurlburt, and P.A.
131:1,524–1,535.
Rochford. 2003. The NRL Layered Ocean
Purser, R.J., W.-S. Wu, D.F. Parrish, and N.M. Roberts.
Model (NLOM) with an embedded mixed
2003b. Numerical aspects of the application of
layer sub-model: Formulation and tuning.
recursive filters to variational statistical analysis.
Journal of Atmospheric and Oceanic Technology
Part II: Spatially inhomogeneous and anisotropic
20:1,601–1,615.
general covariances. Monthly Weather Review
Wunsch, C. and P. Heimbach. 2007. Practical global
131:1,536–1,548.
oceanic state estimation. Physica D-Nonlinear
Rhodes, R.C., H.E. Hurlburt, A.J. Wallcraft, C.N.
Phenomena 230:197–208.
Barron, P.J. Martin, O.M. Smedstad, S.L. Cross,
Wunsch, C., P. Heimbach, R.M. Ponte, I. Fukumori,
E.J. Metzger, J.F. Shriver, A.B. Kara, and D.S. Ko.
and the ECCO-GODAE Consortium Members.
2002. Navy real-time global modeling systems.
2009. The global general circulation of the
Oceanography 15(1):29–43.
ocean estimated by the ECCO-Consortium.
Schiller, A., P.R. Oke, G.B. Brassington, M. Entel, R.
Oceanography 22(2):88–103.
Fiedler, D.A. Griffin, and J. Mansbridge. 2008.
Yan, C.X., J. Zhu, R.F. Li, and G.Q.Zhou. 2004. Roles
Eddy-resolving ocean circulation in the Asian-
of vertical correlation of background error and
Australian region inferred from an ocean reanal-
T-S relations in estimation temperature and
ysis effort. Progress in Oceanography 76:334–365.
salinity profiles from sea surface dynamic height.
Seaman, R., W. Bourke, P. Steinle, T. Hart, G. Embery,
Journal of Geophysical Research 109, C08010,
M. Naughton, and L. Rikus. 1995. Evolution of the
doi:10.1029/2003JC002224,2004.
Bureau of Meteorology’s global assimilation and
Zhang, R.-H., and M. Endoh. 1992. A free surface
prediction system. Part 1: Analyses and initializa-
general circulation model for the tropical
tion. Australian Meteorological Magazine 44:1–18.
Pacific Ocean. Journal of Geophysical Research
Shriver, J.F., H.E. Hurlburt, O.M. Smedstad, A.J.
97(C7):11,237–11,255.
Wallcraft, and R.C. Rhodes. 2007. 1/32°real-time
Zhu, J., and C.X. Yan. 2006. Nonlinear balance
global ocean prediction and value-added over
constraints in 3DVAR data assimilation. Science in
1/16°resolution. Journal of Marine Systems 65:3–26.
China Series D 49(3):331–336. Available online at:
Smedstad, O.M., H.E. Hurlburt, E.J. Metzger, R.C.
http://www.springerlink.com/content/g42n172648
Rhodes, J.F. Shriver, A.J. Wallcraft, and A.B. Kara.
66/?p=f225c9eb3d5c4f4cb21e172ae05123bc&pi=43
2003. An operational eddy-resolving 1/16° global
ocean nowcast/forecast system. Journal of Marine
Systems 40–41:341–361.
Stammer, D., C. Wunsch, R. Giering, C. Eckert,
P. Heimbach, J. Marotzke, A. Adcroft, C.N.
Hill, and J. Marshall. 2003. Volume, heat, and
freshwater transports of the global ocean circu-
lation 1993–2000, estimated from a general
circulation model constrained by World
Ocean Circulation Experiment (WOCE) data.
Journal of Geophysical Research 108 (C1), 3007,
doi:10.1029/2001JC001115.
Tonani, M., N. Pinardi, S. Dobricic, I. Pujol, and
C. Fratianni. 2008. A high resolution free
surface model on the Mediterranean Sea. Ocean
Science 4:1–14.
Tranchant, B., C.E. Testut, L. Renault, N. Ferry, E.
Obligis, C. Boone, and G. Larnicol. 2008. Data
assimilation of simulated SSS SMOS products in
an ocean forecasting system. Journal of Operational
Oceanography 2008(2):19–27(9).
Troccoli, A., and P. Kallberg. 2004. Precipitation
Correction in the ERA-40 Reanalysis. ERA-40
Project Report Series, ECMWF, Reading, UK.
Usui, N., S. Ishizaki, Y. Fujii, H. Tsujino, T. Yasuda,
and M. Kamachi. 2006. Meteorological Research
Institute Multivariate Ocean Variational Estimation
(MOVE) System: Some early results. Advances in
Space Research 37:806–822.
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