Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem  model of the North Atlantic with the EnKF: a twin experiment

Simon, E.; Bertino, L.

doi:https://doi.org/10.5194/os-5-495-2009

Articles | Volume 5, issue 4

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Articles | Volume 5, issue 4

https://doi.org/10.5194/os-5-495-2009

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The MERSEA Project

https://doi.org/10.5194/os-5-495-2009

Articles | Volume 5, issue 4

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03 Nov 2009

| 03 Nov 2009

Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem model of the North Atlantic with the EnKF: a twin experiment

E. Simon and L. Bertino

E. Simon

Nansen Environmental and Remote Sensing Center, Norway

L. Bertino

Nansen Environmental and Remote Sensing Center, Norway

Cited articles

Aksnes, D., Ulvestad, K., Bali{ñ}o, B., Berntsen, J., and Svendsen, E.: Ecological modelling in coastal waters: towards predictive physical-chemical-biological simulation models, Ophelia, 41, 5–36, 1995.

Allen, J. I., Eknes, M., and Evensen, G.: An Ensemble Kalman Filter with a complex marine ecosystem model: hindcasting phytoplankton in the Cretan Sea, Ann. Geophys., 21, 399–411, 2003.

Allen, J. I., Smyth, T. J., Siddorn, J. R., and Holt, J. T.: How well can we forecast high biomass algal bloom events in a eutrophic coastal sea?, Harmful Algae, 8(1), 70–76, 2008.

Bentsen, M., Evensen, G., Drange, H., and Jenkins, A. D.: Coordinate transformation on a sphere using conformal mapping, Mon. Weather Rev., 127, 2733–2740, 1999.

Bertino, L., Evensen, G., and Wackernagel, H.: Sequential {D}ata {A}ssimilation {T}echniques in {O}ceanography, Int. Statist. Rev., 71, 223–241, 2003.

Bertino, L. and Lisæter, K. A.: The TOPAZ monitoring and prediction system for the Atlantic and Arctic Oceans, J. Operational Oceanogr., 1(2), 15–19, 2008.

Bleck, R.: An oceanic general circulation model framed in isopycnic-cartesian coordinates, Ocean Model., 4, 55–88, 2002.

Campbell, J. W.: The lognormal distribution as a model for bio-optical variability in the sea, J. Geophys. Res., 100(C7), 13237–13254, 1995.

Carmillet, V., Brankart, J.-M., Brasseur, P., Drange, H., Evensen, G., and Verron, J.: A singular evolutive extended {K}alman filter to assimilate ocean color data in a coupled physical-biogeochemical model of the {N}orth {A}tlantic ocean, Ocean Model., 3, 167–192, 2001.

Chilès, J.-P. and Delfiner, P.: Geostatistics: Modeling Spatial Uncertainty, Wiley, New York, 1999.

Courtier, P., Th{é}paut, J. N., and Hollingsworth, A.: A strategy for operational implementation of 4{D}-{V}ar, using an incremental approach, Q. J. Roy. Meteorol. Soc., 120, 1367–1387, 1994.

Doucet, A., de Freitas, N., and Gordon, N.: Sequential Monte Carlo methods in practice, New York, Springer, 2001.

Drange, H. and Simonsen, K.: Formulation of air-sea fluxes in the {ESOP}2 version of MICOM, NERSC Report 125, Nansen Environmental and Remote Sensing Center, Norway, 1996.

Evensen, G.: Sequential data assimilation with a nonlinear quasi-geostrophic model using {M}onte {C}arlo methods to forecast error statistics, J. Geophys. Res., 99(C5), 10143–10182, 1994.

Evensen, G.: The {E}nsemble {K}alman filter: theorotical formulation and practical implementation, Ocean Dynam., 53, 343–367, 2003.

Evensen, G.: Data Assimilation, The Ensemble Kalman Filter, Springer, 2006.

Gregg, W. W.: Assimilation of S}ea{W}i{FS ocean chlorophyll data into a three-dimensional global ocean model, J. Mar. Syst., 69, 205–225, 2008.

Gregg, W. W. and Casey, N. W.: Global and regional evaluation of the S}ea{W}i{FS chlorophyll data set, Rem. Sens. Environ., 93, 463–479, 2004.

Gregg, W. W., Friedrichs, M. A. M., Robinson, A. R., Rose, K. A., Schlitzer, R., Thompson, K. R., and Doney, S. C.: Skill assessment in ocean biological data assimilation, J. Mar. Syst., 76(1–2), 16–33, 2009.

Hansen, C. and Samuelsen, A.: Influence of horizontal model grid resolution on the simulated primary production in an embedded primary production model in the {N}orwegian {S}ea, J. Mar. Syst., 75(1–2), 236–244, 2009.

Hunke, E. and Dukowicz, J.: An elastic-viscous-plastic model for sea-ice dynamics, J. Geophys. Res., 27, 1849–1867, 1999.

Johannessen, J. A., Hackett, B., Svendsen, E., Søiland, H., Røed, L. P., Winther, N., Albretsen, J., Danielsen, D., Pettersson, L., Skogen, M., and Bertino, L.: The Norwegian Coastal Current – oceanography and climate, Chapter 11, edited by: Sætre, R., Tapir Academic Press, 2007.

Kalman, R. E.: A new approach to linear filtering and prediction problems, Trans. ASME Ser. D, J. Basic Eng., 82D, 35–45,1960.

Lauvernet, C., Brankart, J.-M., Castruccio, F., Broquet, G., Brasseur, P., and Verron, J.: A truncated {G}aussian filter for data assimilation with inequality constraints: application to the hydrostatic stability condition in ocean models, Ocean Model., 27, 1–17, 2009.

Le Dimet, F.-X. and Talagrand, O.: Variational algorithms for analysis and assimilation of meteorological observations: {T}heorotical apects, Tellus, 38A, 97–110, 1986.

Lions, J. L.: Contrôle optimal des systèmes gouvern{é}s par des {é}quations aux d{é}riv{é}es partielles, Dunod, Paris, 1968.

Losa, S. N., Kivman, G. A., Schr{ö}ter, J., and Wenzel, M.: Sequential weak constraint parameter estimation in an ecosystem model, J. Mar. Syst., 43, 31–49, 2003.

Natvik, L. J. and Evensen, G.: Assimilation of ocean colour data into a biochemical model of the {N}orth {A}tlantic. {P}art 1. {D}ata assimilation experiments, J. Mar. Syst., 40–41, 127–153, 2003.

Natvik, L. J. and Evensen, G.: Assimilation of ocean colour data into a biochemical model of the {N}orth {A}tlantic. {P}art 2. {S}tatistical analysis, J. Mar. Syst., 40–41, 155–169, 2003.

Nerger, L. and Gregg, W. W.: Assimilation of S}ea{W}i{FS ocean chlorophyll data into a global ocean model using a local SEIK filter, J. Mar. Syst., 68, 237–254, 2007.

Pham, D. T., Verron, J., and Roubaud, M.-C.: A singular evolutive extended {K}alman filter for data assimilation in oceanography, J. Mar. Syst., 16(3–4), 323–340, 1998.

Pham, D. T.: Stochastic methods for sequential data assimilation in strongly nonlinear systems, Mon. Weather Rev., 129(5), 1194–1207, 2001.

Sasaki, Y.: A fundamental study of the numerical prediction based on the variational principle, J. Meteorol. Soc. Jpn., 33, 262–265, 1955.

Schölzel, C. and Friederichs, P.: Multivariate non-normally distributed random variables in climate research – introduction to the copula approach, Nonlin. Processes Geophys., 15, 761–772, 2008.

Skogen, M. and Søiland, H.: A user's guide to NORWECOM v2.0. {T}he {NORW}egian {E}cological {M}odel system, Technical {R}eport {F}isken og {H}avet 18, Institute of {M}arine {R}esearch, Norway,1998.

Thacker, W. C.: Data assimilation with inequality constraints, Ocean Model., 16, 264–276, 2007.

Torres, R., Allen, J. I., and Figueiras, F. G.: Sequential data assimilation in an upwelling influenced estuary, J. Mar. Syst., 60, 317–329, 2006.

Triantafyllou, G., Hoteit, I., and Petihakis, G.: A singular evolutive interpolated K}alman filter for efficient data assimilation in a 3-{D complex physical-biogeochemical model of the {C}retan {S}ea, J. Mar. Syst., 40–41, 213–231, 2003.