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The CMCC-INGV Global Ocean Data Assimilation System (CIGODAS)
Sponsors
Centro Euro-Mediterraneo per i Cambiamenti Climatici, Bologna, Italy
Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy
Istituto Nazionale di Geofisica e Vulcanologia, Bologna, Italy
Language
English
Obiettivo Specifico
3.7. Dinamica del clima e dell'oceano
Status
Published
Peer review journal
Yes
Issued date
2009
Series/Report No.
Research Paper
RP0071
Abstract
This report summarizes the technical structure and main
characteristics of the CMCCINGV Global Ocean Data Assimilation System (CIGODAS) based on a Reduced Order Optimal Interpolation scheme and a coarse resolution Global Ocean Model for the assimilation of temperature and salinity observations. It is intended to be a reference guide for new users who are interested in setting up and running an experiment using this approach and producing estimates of the timevarying, threedimensional state of the global ocean.
characteristics of the CMCCINGV Global Ocean Data Assimilation System (CIGODAS) based on a Reduced Order Optimal Interpolation scheme and a coarse resolution Global Ocean Model for the assimilation of temperature and salinity observations. It is intended to be a reference guide for new users who are interested in setting up and running an experiment using this approach and producing estimates of the timevarying, threedimensional state of the global ocean.
References
Bellucci A., Masina S., Di Pietro P., and Navarra
A., 2007: Using temperaturesalinity
relations in
a global ocean implementation of a multivariate
data assimilation scheme., Monthly Weather Review,
vol. 135, pp. 37853807
Blanke, B. and Delecluse, P., 1993: Variability of
the tropical Atlantic Ocean simulated by a general
circulation model with two different mixedlayer
physics. J. Phys. Oceanogr., 23, 13631388.
Daley, R., 1991: Atmospheric Data Analysis. Cambridge
University Press, 457 pp.
De Mey, P., and M. Benkiran, 2002: A multivariate
reducedorder
optimal interpolation method and
its application to the Mediterranean basinscale
circulation. Ocean Forecasting: Conceptual Basis
and Applications, N. Pinardi and J. D. Woods,
Eds.,Springer Verlag, 281306.
Ide, K., Courtier, P., Ghil, M., and Lorenc A. C.,
1997: Unified notation for data assimilation: Operational,
sequential and variational. J. Meteor.
Soc. Japan, 75, 181189
Ingleby, B., and M. Huddleston, 2007: Quality control
of ocean temperature and salinity profiles historical
and realtime
data. Journal of Marine
Systems, 65, 158175
Lazar, A., G. Madec, and P. Delecluse, 1999: The
deep interior downwelling, the Veronis effect, and
mesoscale tracer transport parameterizations in
an OGCM. J. Phys. Oceanogr., 29, 29452961.
Levitus, S., and Coauthors, 1998: World Ocean
Database 1998. NOAA Atlas NESDIS 1, 346 pp.
Madec G., and M. Imbard, 1996: A global ocean
mesh to overcome the North Pole singularity.
Clim. Dyn., 12,381388.
Madec, G., Delecluse, P., Imbard, I. and Levy, C.,
1999: OPA 8.1 Ocean General Circulation Model
reference manual, Note du Pˆole de mod´elisation,,
Inst. PierreSimon
Laplace (IPSL), France, No.
11, 91 pp.
Sparnocchia, S., Pinardi, N., and Demirov, E., 2003:
Multivariate Empirical Orthogonal Function analysis
of the upper thermocline structure of the
Mediterranean Sea from observations and model
simulations, Ann. Geophysicae, this issue.
Troccoli, A., and P. Kallberg, 2004: Precipitation correction
in the ERA40
reanalysis. ERA40
Project
Rep. Series 13, 6 pp.
UNESCO, 1983: Algorithms for computation of fundamental
property of sea water. UNESCO Techn.
Paper in Mar. Sci.,44, Unesco, 53pp.
A., 2007: Using temperaturesalinity
relations in
a global ocean implementation of a multivariate
data assimilation scheme., Monthly Weather Review,
vol. 135, pp. 37853807
Blanke, B. and Delecluse, P., 1993: Variability of
the tropical Atlantic Ocean simulated by a general
circulation model with two different mixedlayer
physics. J. Phys. Oceanogr., 23, 13631388.
Daley, R., 1991: Atmospheric Data Analysis. Cambridge
University Press, 457 pp.
De Mey, P., and M. Benkiran, 2002: A multivariate
reducedorder
optimal interpolation method and
its application to the Mediterranean basinscale
circulation. Ocean Forecasting: Conceptual Basis
and Applications, N. Pinardi and J. D. Woods,
Eds.,Springer Verlag, 281306.
Ide, K., Courtier, P., Ghil, M., and Lorenc A. C.,
1997: Unified notation for data assimilation: Operational,
sequential and variational. J. Meteor.
Soc. Japan, 75, 181189
Ingleby, B., and M. Huddleston, 2007: Quality control
of ocean temperature and salinity profiles historical
and realtime
data. Journal of Marine
Systems, 65, 158175
Lazar, A., G. Madec, and P. Delecluse, 1999: The
deep interior downwelling, the Veronis effect, and
mesoscale tracer transport parameterizations in
an OGCM. J. Phys. Oceanogr., 29, 29452961.
Levitus, S., and Coauthors, 1998: World Ocean
Database 1998. NOAA Atlas NESDIS 1, 346 pp.
Madec G., and M. Imbard, 1996: A global ocean
mesh to overcome the North Pole singularity.
Clim. Dyn., 12,381388.
Madec, G., Delecluse, P., Imbard, I. and Levy, C.,
1999: OPA 8.1 Ocean General Circulation Model
reference manual, Note du Pˆole de mod´elisation,,
Inst. PierreSimon
Laplace (IPSL), France, No.
11, 91 pp.
Sparnocchia, S., Pinardi, N., and Demirov, E., 2003:
Multivariate Empirical Orthogonal Function analysis
of the upper thermocline structure of the
Mediterranean Sea from observations and model
simulations, Ann. Geophysicae, this issue.
Troccoli, A., and P. Kallberg, 2004: Precipitation correction
in the ERA40
reanalysis. ERA40
Project
Rep. Series 13, 6 pp.
UNESCO, 1983: Algorithms for computation of fundamental
property of sea water. UNESCO Techn.
Paper in Mar. Sci.,44, Unesco, 53pp.
Type
report
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