Testing a marine ecosystem model: Sensitivity analysis and parameter optimization

A data assimilation technique is used with a simple but widely used marine ecosystem model to optimize poorly known model parameters. A thorough analysis of the a posteriori errors to be expected for the estimated parameters was carried out. The errors have been estimated by calculating the Hessian matrices for different problem formulations based on identical twin experiments. The error analysis revealed inadequacies in the formulation of the optimization problem and insufficiencies of the applied data set. Modifications of the actual problem formulation, which improved the accuracy of the estimated parameters considerably, are discussed. The optimization procedure was applied to real measurements of nitrate and chlorophyll at the Atlantic Bermuda site. The parameter optimization gave poor results. We suggest this to be due to features of the ecosystem that are unresolved by the present model formulation. Our results emphasize the necessity of an error analysis to accompany any parameter optimization study.

[1]  N Oreskes,et al.  Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences , 1994, Science.

[2]  Eileen E. Hofmann,et al.  A data assimilation technique applied to a predator-prey model , 1995 .

[3]  William Carlisle Thacker,et al.  The role of the Hessian matrix in fitting models to measurements , 1989 .

[4]  Isabelle Dadou,et al.  Assimilation of surface data in a one-dimensional physical-biogeochemical model of the surface ocean. 2. Adjusting a simple trophic model to chlorophyll, temperature, nitrate, and pCO2 data , 1996 .

[5]  H. Drange,et al.  A 3-dimensional isopycnic coordinate model of the seasonal cycling of carbon and nitrogen in the Atlantic Ocean , 1996 .

[6]  G. Hurtt,et al.  A pelagic ecosystem model calibrated with BATS data , 1996 .

[7]  George C. Hurtt,et al.  A pelagic ecosystem model calibrated with BATS and OWSI data , 1999 .

[8]  R. Giering.  Tangent linear and adjoint model compiler users manual , 1996 .

[9]  Mark R. Abbott,et al.  Configuring an ecosystem model using data from the Bermuda Atlantic Time Series (BATS) , 2001 .

[10]  Eric P. Chassignet,et al.  Ocean modeling and parameterization , 1998 .

[11]  Craig Leohle,et al.  Evaluation of theories and calculation tools in ecology , 1983 .

[12]  V. Echevin,et al.  Assimilation of surface data in a one-dimensional physical-biogeochemical model of the surface ocean , 1996 .

[13]  Jens Schröter,et al.  Parameter Estimation in Dynamical Models , 1998 .

[14]  M. Ehrhardt,et al.  Methods of Seawater Analysis (3rd Edition) , 1999 .

[15]  Rainer Bleck,et al.  Salinity-driven Thermocline Transients in a Wind- and Thermohaline-forced Isopycnic Coordinate Model of the North Atlantic , 1992 .

[16]  Richard J. Matear,et al.  Parameter optimization and analysis of ecosystem models using simulated annealing: a case study at Station P , 1995 .

[17]  A. Oschlies,et al.  An eddy‐permitting coupled physical‐biological model of the North Atlantic: 1. Sensitivity to advection numerics and mixed layer physics , 1999 .

[18]  David M. Glover,et al.  A new coupled, one-dimensional biological-physical model for the upper ocean: Applications to the JGOFS Bermuda Atlantic Time-series Study (BATS) site , 1996 .

[19]  Claude Lemaréchal,et al.  Some numerical experiments with variable-storage quasi-Newton algorithms , 1989, Math. Program..

[20]  H. Ducklow,et al.  A nitrogen-based model of plankton dynamics in the oceanic mixed layer , 1990 .

[21]  E. Hofmann,et al.  Time series sampling and data assimilation in a simple marine ecosystem model , 1996 .

[22]  W. Fennel.  A model of the yearly cycle of nutrients and plankton in the Baltic Sea , 1995 .

[23]  Philippe Gaspar,et al.  Modeling the Seasonal Cycle of the Upper Ocean , 1988 .

[24]  Manfred Ehrhardt,et al.  Methods of seawater analysis , 1999 .

[25]  I. Totterdell,et al.  Production and export in a global ocean ecosystem model , 2001 .

[26]  G. Evans,et al.  The role of local models and data sets in the Joint Global Ocean Flux Study , 1999 .

[27]  G. Evans,et al.  The Use of Optimization Techniques to Model Marine Ecosystem Dynamics at the JGOFS Station at 47 degrees N 20 degrees W [and Discussion] , 1995 .

[28]  Katja Fennel,et al.  Convection and the Timing of Phytoplankton Spring Blooms in the Western Baltic Sea , 1999 .

[29]  Anthony H. Knap,et al.  Overview of the U.S. JGOFS Bermuda Atlantic Time-series Study and the Hydrostation S program , 1996 .

[30]  Andreas Oschlies,et al.  Parameter estimates of a zero-dimensional ecosystem model applying the adjoint method , 2001 .

[31]  James G. Richman,et al.  Data assimilation and a pelagic ecosystem model: parameterization using time series observations , 1998 .

[32]  Andreas Oschlies,et al.  Eddy-induced enhancement of primary production in a model of the North Atlantic Ocean , 1998, Nature.