marine ecosystem models; reduction of model complexity; principal component analysis
Abstract :
[en] In the framework of model complexity reduction, we investigate the ability of the principal component analysis technique to represent in a compact form the dynamics of a coupled physical-ecosystem model. The biogeochemical model describes the evolution in time and depth of the partly decoupled nitrogen and carbon cycles of the pelagic food web in the Ligurian Sea (North Western Mediterranean Sea) through 19 biogeochemical state variables. The GHER hydrodynamic model (1D version) is used to represent the physical forcings. The coupled model presents a high variability in time and space that can be decomposed in modes by principal component analysis. To investigate the possibility of being represented in a compact form, the model is constrained to evolve in a reduced space spanned by its most dominant modes of variability that are the empirical orthogonal functions (EOFs). Different orthogonal bases (formed by 1D and OD EOFs) are used to investigate the performance and realism of the method. 1D vertical EOFs show a tendency to impose a spatial structure to model results according to the most dominant EOFs. In the case of OD EOFs, results of the reduced model can be very close to the original one, but it requires a large number of modes. (c) 2006 Elsevier B.V. All rights reserved.
Research center :
Centre Interfacultaire de Recherches en Océanologie - MARE - GHER
Disciplines :
Environmental sciences & ecology
Author, co-author :
Raick, Caroline ; Université de Liège - ULiège > Département des sciences et gestion de l'environnement > Océanologie
Achatz U., Schmitz G., and Greisinger K.-M. Principal interaction patterns in baroclinic wave life cycles. J. Atmos. Sci. 52 (1995) 3201-3213
Aubry N., Holmes P., Lumley J.L., and Stone E. The dynamics of coherent structures in the wall region of a turbulent boundary layer. J. Fluid Mech. 192 (1988) 115-173
Aubry N., Lian W.-Y., and Titi E. Preserving symmetries in the proper orthogonal decomposition. SIAM J. Sci. Comput. 14 (1993) 483-505
Brainerd K.E., and Gregg M.C. Surface mixed and mixing layer depths. Deep Sea Res. I 42 9 (1995) 1521-1543
Cazemier W., Verstappen R., and Veldman A. Propoer orthogonal decomposition and low dimensional models for driven cavity flows. Phys. Fluids 10 (1998) 1685-1699
Crommelin D.T., and Majda A.J. Strategies for model reduction: comparing different optimal bases. J. Atmos. Sci. 61 (2004) 2206-2217
DelSole T. Optimal Persistence Patterns in time-varying fields. J. Atmos. Sci. 58 (2001) 1341-1356
Ettema, J., 2002. Analysis of wind fields for wind climate assessment of The Netherlands. A Literature Survey. Royal Netherlands Meteorological Institute (KNMI).
Flierl, G.R., Davis, C.S., 1996. Reduction of complexity in coupled biological-physical models. J. Mar. Res., 54:xxx-xxx.
Fulton E.A., Parslow J.S., Smith A.D.M., and Johnson C.R. Biogeochemical marine ecosystem models. II. The effect of physiological detail on model performance. Ecol. Model. 173 (2004) 371-406
Fulton E.A., Smith A.D.M., and Johnson C.R. Effect of complexity in marine ecosystem models. Mar. Ecol. Progr. Ser. 253 (2003) 1-16
Fulton E.A., Smith A.D.M., and Johnson C.R. Mortality and predation in ecosystem models: is it important how these are expressed?. Ecol. Model. 169 (2003) 157-178
Hasselman K. PIPs and POPs: The reduction of complex dynamical systems using principal interaction and oscillation patterns. J. Geophys. Res. 93 (1988) 11015-11021
Joliffe, I., 2002. Principal Component Analysis, 2nd ed., Springer.
Kirchner J.W., Hooper R.P., Kendall C., Neal C., and Leavesley G. Testing and validating environmental models. Sci. Total Environ. 183 (1996) 33-47
Kriest I., and Evans G.T. 1D vertically resolved model for phytoplankton aggregation. Earth Planet. Sci. 109 4 (2000) 453-469
Kwasniok F. The reduction of complex dynamical systems using principal interaction patterns. Non-linear Anal. Theory, Meth. Appl. 30 (1996) 489-494
Kwasniok F. Low-dimensional models of complex systems using principal interaction patterns. Non-linear analysis theory. Meth. Appl. 30 (1997) 489-494
Kwasniok F. Empirical low-order models of barotropic flow. J. Atmos. Sci. 61 (2004) 235-245
Kwasniok, F., in press. Reduced atmospheric model using dynamically motivated basis functions. J. Atmos. Sci.
Lacroix G., and Grégoire M. Revisited ecosystem model (MODECOGeL) of the Ligurian Sea: seasonal and interannual variability due to atmospheric forcing. J. Mar. Syst. 37 4 (2002) 229-258
Lacroix G., and Nival P. Influence of meteorological variability on primary production dynamics in the Ligurian Sea (NW Mediterranean Sea) with a hydrodynamic/biological model. J. Mar. Syst. 16 (1998) 23-50
Marty J.-C., Chiaverini J., Pizay M.-D., and Avril B. Seasonal and interannual dynamics of nutrients and phytoplankton pigments in the western Mediterranean Sea at the DYFAMED times-series station (1991-1999). Deep Sea Res. II 49 (2002) 1965-1985
Raick, C., Alvera-Azcarate, A., Barth, A., Brankart, J.-M., Soetaert, K., Grégoire, M., in press. Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: twin experiments and real data assimilation. J. Mar. Syst.
Raick C., Delhez E.J.M., Soetaert K., and Grégoire M. Study of the seasonal cycle of the biogeochemical processes in the Ligurian Sea using an 1D interdisciplinary model. J. Mar. Syst. 55 3-4 (2005) 177-203
Raick, C., Soetaert, K., and Grégoire, M., 2005b. Model complexity and performance: how far can we simplify? Progr. Oceanogr., submitted for publication.
Rinne J., and Karhilla V. A spectral barotrophic model in horizontal empirical orthogonal functions. Quart. J.R. Met. Soc. 101 (1975) 365-382
Schubert S.D. A statistical-dynamical study of empirically determined modes of atmospheric variability. J. Atmos. Sci. 42 (1985) 3-17
Schubert S.D. The structure, energetics and evolution of the dominant frequency-dependent three-dimensional atmospheric modes. J. Atmos. Sci. 43 (1986) 1210-1237
Selten F.M. Toward an optimal description of atmospheric flow. J. Atmos. Sci. 50 (1993) 861-877
Selten F.M. An efficient description of the dynamics of barotrophic flow. J. Atmos. Sci. 52 (1995) 915-936
Selten F.M. Baroclinic empirical orthogonal functions a basis functions in an atmospheric model. J. Atmos. Sci. 54 (1997) 2100-2114
Sirovich L. Chaotic dynamics of coherent structures. Phys. D 37 (1989) 126-145
Soetaert K., deClippere V., and Herman P.M.J. Femme, a flexible environment for mathematically modelling the environment. Ecol. Model. 151 (2002) 177-193
Von Storch H., and Zwiers F.W. Statistical Analysis in Climate Research (1999), Cambridge University Press
Young P., Parkinson S., and Lees M. Simplicty out of complexity in environmental modelling: Occam's razor revisited. J. Appl. Stat. 23 (1996) 165-210
