DATA ASSIMILATION IN BIOGEOCHEMICAL MODELLING
545
Evensen, G., 2003: The Ensemble Kalman Filter: theoretical formulation and practical
implementation. Ocean Dynamics, 53, 343–367.
Fasham, M. J. R., H. W. Ducklow, and S. M. McKelvie, 1990: A nitrogen–based model
of plankton dynamics in the oceanic mixed layer. J. Mar. Res., 48, 591–639
Fasham, M. J. R., J. L. Sarmiento, R. D. Slater, H. W. Ducklow, and R. Williams,
1993: Ecosystem behavior at Bermuda Station
”
S” and Ocean Weather Station India”: a general circulation model and observational analysis. Global Biogeochem.
Cycles, 7, 379–415.
Fasham, M. J. R., and G. T. Evans, 1995: The use of optimisation techniques to model
marine ecosystem dynamics at the JGOFS station at 47N 20W. Phil. Trans. Roy.
Soc. Lond. B, 348, 203–209.
Fennel, K., M. Losch, J. Schr¨ oter, and M. Wenzel, 2001: Testing a marine ecosystem
model: sensitivity analysis and parameter optimization. J. Mar. Syst., 28, 45–63.
Friedrichs, M. A. M., 2002: Assimilation of JGOFS EqPac and SeaWiFS data into a
marine ecosystem model of the central equatorial Pacific Ocean. Deep-Sea Res. II,
49, 289–319.
Gabric, A. J., R. Simo, R. A. Cropp, A. C. Hirst, and J. Dachs (2004), Modeling
estimates of the global emission of dimethylsulfide under enhanced greenhouse
conditions, Global Biogeochem. Cycles, 18, GB2014, doi:10.1029/2003GB002183.
Gunson, J., A. Oschlies, and V. Gar¸ con, 1999: Sensitivity of ecosystem parameters to
simulated satellite ocean colour data using a coupled physical-biological model of
the North Atlantic. J. Mar. Res., 57, 613–639.
Harmon, R., and P. Challenor, 1997: A Markov chain Monte Carlo method for estimation and assimilation into models. Ecol. Model., 101, 41–59.
Hemmings, J. C. P., M. A. Srokocz, P. Challenor, and M. J. R. Fasham, 2003: Assimilating satellite ocean-colour observations into oceanic ecosystem models. Phil.
Trans. R. Soc. Lond., A 361, 33–39.
Hurtt, G. C., and R. A. Armstrong, 1996: A pelagic ecosystem model calibrated with
BATS data. Deep-Sea Res. II, 43, 653–683.
Hurtt, G. C., and R. A. Armstrong, 1999: A pelagic ecosystem model calibrated with
BATS and OWSI data. Deep-Sea Res. I, 46, 27–61.
K¨ ahler, P., and W. Koeve, 2001: Marine dissolved organic matter: can its C:N ratio
explain carbon overconsumption? Deep–Sea Res. I, 48, 49–62.
Kalman, R. E., 1960: A new approach to linear filtering and prediction problems. J.
Basic. Eng., 82D, 35–45.
Klausmeier, C. A., E. Litchman, T. Daufresne, and S. A. Levin, 2004: Optimal
nitrogen-to-phosphorus stoichiometry of phytoplankton. Nature, 429, 171–174.
K¨ ortzinger, A., W. Koeve, P. K¨ ahler, and L. Mintrop, 2001: C:N ratios in the mixed
layer during the productive season in the Northeast Atlantic Ocean. Deep-Sea
Res. I, 48, 661–688.
Lawson, L. M., Y. H. Spitz, E. E. Hofmann, and R. B. Long, 1995: A data assimilation
technique applied to a predator-prey model. Bull. Math. Biology, 57, 625–651.
Loukos, H., P. Monfray, L. Bopp, and P. Lehody, 2003: Potential changes in skipjack
tuna (Katsuwonus pelamis) habitat from a global warming scenario: modelling
approach and preliminary results. Fisheries Oceanography, 12, 474–482.
Losa, S. N., G. A. Kivman, and V. A. Ryabchenko, 2004: Weak constraint parameter
estimation for a simple ocean ecosystem model: what can we learn about the model
and data? J. Mar. Syst., 45, 1–20.
”
545
Evensen, G., 2003: The Ensemble Kalman Filter: theoretical formulation and practical
implementation. Ocean Dynamics, 53, 343–367.
Fasham, M. J. R., H. W. Ducklow, and S. M. McKelvie, 1990: A nitrogen–based model
of plankton dynamics in the oceanic mixed layer. J. Mar. Res., 48, 591–639
Fasham, M. J. R., J. L. Sarmiento, R. D. Slater, H. W. Ducklow, and R. Williams,
1993: Ecosystem behavior at Bermuda Station
”
S” and Ocean Weather Station India”: a general circulation model and observational analysis. Global Biogeochem.
Cycles, 7, 379–415.
Fasham, M. J. R., and G. T. Evans, 1995: The use of optimisation techniques to model
marine ecosystem dynamics at the JGOFS station at 47N 20W. Phil. Trans. Roy.
Soc. Lond. B, 348, 203–209.
Fennel, K., M. Losch, J. Schr¨ oter, and M. Wenzel, 2001: Testing a marine ecosystem
model: sensitivity analysis and parameter optimization. J. Mar. Syst., 28, 45–63.
Friedrichs, M. A. M., 2002: Assimilation of JGOFS EqPac and SeaWiFS data into a
marine ecosystem model of the central equatorial Pacific Ocean. Deep-Sea Res. II,
49, 289–319.
Gabric, A. J., R. Simo, R. A. Cropp, A. C. Hirst, and J. Dachs (2004), Modeling
estimates of the global emission of dimethylsulfide under enhanced greenhouse
conditions, Global Biogeochem. Cycles, 18, GB2014, doi:10.1029/2003GB002183.
Gunson, J., A. Oschlies, and V. Gar¸ con, 1999: Sensitivity of ecosystem parameters to
simulated satellite ocean colour data using a coupled physical-biological model of
the North Atlantic. J. Mar. Res., 57, 613–639.
Harmon, R., and P. Challenor, 1997: A Markov chain Monte Carlo method for estimation and assimilation into models. Ecol. Model., 101, 41–59.
Hemmings, J. C. P., M. A. Srokocz, P. Challenor, and M. J. R. Fasham, 2003: Assimilating satellite ocean-colour observations into oceanic ecosystem models. Phil.
Trans. R. Soc. Lond., A 361, 33–39.
Hurtt, G. C., and R. A. Armstrong, 1996: A pelagic ecosystem model calibrated with
BATS data. Deep-Sea Res. II, 43, 653–683.
Hurtt, G. C., and R. A. Armstrong, 1999: A pelagic ecosystem model calibrated with
BATS and OWSI data. Deep-Sea Res. I, 46, 27–61.
K¨ ahler, P., and W. Koeve, 2001: Marine dissolved organic matter: can its C:N ratio
explain carbon overconsumption? Deep–Sea Res. I, 48, 49–62.
Kalman, R. E., 1960: A new approach to linear filtering and prediction problems. J.
Basic. Eng., 82D, 35–45.
Klausmeier, C. A., E. Litchman, T. Daufresne, and S. A. Levin, 2004: Optimal
nitrogen-to-phosphorus stoichiometry of phytoplankton. Nature, 429, 171–174.
K¨ ortzinger, A., W. Koeve, P. K¨ ahler, and L. Mintrop, 2001: C:N ratios in the mixed
layer during the productive season in the Northeast Atlantic Ocean. Deep-Sea
Res. I, 48, 661–688.
Lawson, L. M., Y. H. Spitz, E. E. Hofmann, and R. B. Long, 1995: A data assimilation
technique applied to a predator-prey model. Bull. Math. Biology, 57, 625–651.
Loukos, H., P. Monfray, L. Bopp, and P. Lehody, 2003: Potential changes in skipjack
tuna (Katsuwonus pelamis) habitat from a global warming scenario: modelling
approach and preliminary results. Fisheries Oceanography, 12, 474–482.
Losa, S. N., G. A. Kivman, and V. A. Ryabchenko, 2004: Weak constraint parameter
estimation for a simple ocean ecosystem model: what can we learn about the model
and data? J. Mar. Syst., 45, 1–20.
”