A marine model optimization test-bed for ecosystem model evaluation: MarMOT version 1.0 description and user guide

Abstract

In response to scientific challenges in the modelling of plankton ecosystems and their role in biogeochemical cycles, the Marine Model Optimization Test-bed (MarMOT) software has been developed as a tool for comprehensive evaluation of plankton ecosystem models against observational data. It provides a common physical and computational environment in which different ecosystem models can be calibrated and compared. The system is designed specifically to support computationally intensive experiments involving parameter optimization, in which models are evaluated many times with different input data in a 1-D framework.

The core of the system is the MarMOT Model Evaluator (MME), which is implemented as a specific application within a system called the Generic Function Analyzer (GFAn). The MME runs one or more simulation cases, producing a cost function value summarizing the model-data misfit over all cases, together with detailed model output, diagnostics and misfit data for each case. It provides various options for modelling photosynthesis, each of which can be applied to any ecosystem model implemented.

GFAn provides a generic data management framework that adapts to the requirements of the application, together with an optimizer for cost function minimization and a flexible experiment control interface. The data management framework allows different instances of all model inputs (parameters, forcing data and initial conditions) to be easily combined in different ways to drive ensemble simulations for sensitivity and uncertainty analyses or multi-site calibration experiments.

A baseline version of the MarMOT system is described in which two ecosystem models are implemented. In future versions, it is expected that a wide range of ecosystem models will be made available for research purposes through collaborative work with different modelling groups. Investigations of all models should benefit from independent improvements in the functionality of the MME application and the GFAn system, extending the power and range of potential analyses.

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