Calibration of a simple and a complex model of global marine biogeochemistry

Iris Kriest

doi:10.5194/bg-14-4965-2017

Abstract

Abstract. The assessment of the ocean biota's role in climate change is often carried out with global biogeochemical ocean models that contain many components and involve a high level of parametric uncertainty. Because many data that relate to tracers included in a model are only sparsely observed, assessment of model skill is often restricted to tracers that can be easily measured and assembled. Examination of the models' fit to climatologies of inorganic tracers, after the models have been spun up to steady state, is a common but computationally expensive procedure to assess model performance and reliability. Using new tools that have become available for global model assessment and calibration in steady state, this paper examines two different model types – a complex seven-component model (MOPS) and a very simple four-component model (RetroMOPS) – for their fit to dissolved quantities. Before comparing the models, a subset of their biogeochemical parameters has been optimised against annual-mean nutrients and oxygen. Both model types fit the observations almost equally well. The simple model contains only two nutrients: oxygen and dissolved organic phosphorus (DOP). Its misfit and large-scale tracer distributions are sensitive to the parameterisation of DOP production and decay. The spatio-temporal decoupling of nitrogen and oxygen, and processes involved in their uptake and release, renders oxygen and nitrate valuable tracers for model calibration. In addition, the non-conservative nature of these tracers (with respect to their upper boundary condition) introduces the global bias (fixed nitrogen and oxygen inventory) as a useful additional constraint on model parameters. Dissolved organic phosphorus at the surface behaves antagonistically to phosphate, and suggests that observations of this tracer – although difficult to measure – may be an important asset for model calibration.

Highlights

Global biogeochemical ocean models are routinely used to assess the ocean biota’s role in climate change
Because many data that relate to tracers included in a model are only sparsely observed, assessment of model skill is often restricted to tracers that can be measured and assembled
Given the successful parameter optimisation of simpler models noted above, and to acknowledge the fact that these models have been popular and quite successful in global simulations of ocean biogeochemistry (e.g. Bacastow and Maier-Reimer, 1990, 1991; Matear and Hirst, 2003; Kwon and Primeau, 2006; Dutkiewicz et al, 2006), this paper presents an optimised model, which has been derived from downscaling the sevencomponent model MOPS (Kriest and Oschlies, 2015; Kriest et al, 2017) to a model that retains only three abiotic dissolved tracers and one biotic tracer

Summary

Introduction

Global biogeochemical ocean models are routinely used to assess the ocean biota’s role in climate change These models have become ever more complex with respect to the number of biogeochemical tracers they contain, they are often calibrated only against a subset of their components, mostly nutrients, oxygen and components of the carbon cycle A thorough and dense scan of the parameter space would be required for a fair assessment of the virtues of models of different complexity Such a scan usually requires many model evaluations, which, given the long equilibration timescales of coupled global models (Khatiwala, 2008; Wunsch and Heimbach, 2008; Primeau and Deleersnijder, 2009; Siberlin and Wunsch, 2011), is difficult to carry out. For assessment of only surface properties and processes, a short model spin-up may be sufficient; on a global scale, many centuries to millennia of coupled model simulations

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Conclusion