Abstract
Abstract. We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton–ecosystem model (OPEM), implemented in the University of Victoria Earth System Climate Model (UVic-ESCM), using a Latin hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO3-, PO43-, O2, and surface chlorophyll a concentrations. The simulations closest to the data with respect to our metric exhibit very low rates of global N2 fixation and denitrification, indicating that in order to achieve rates consistent with independent estimates, additional constraints have to be applied in the calibration process. For identifying the reference parameter sets, we therefore also consider the model's ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO3- inventory. Global O2 varies by a factor of 2 and NO3- by more than a factor of 6 among all simulations. Remineralisation rate is the most important parameter for O2, which is also affected by the subsistence N quota of ordinary phytoplankton (Q0,phyN) and zooplankton maximum specific ingestion rate. Q0,phyN is revealed as a major determinant of the oceanic NO3- pool. This indicates that unravelling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via Q0,phyN, is a prerequisite for understanding the marine nitrogen inventory.
Highlights
Earth system climate models (ESCMs) are powerful tools for analysing variations in climate, while resolving interdependencies between changes in the atmosphere, on land, and in the ocean (Flato, 2011; Prinn, 2013)
We introduce a new marine ecosystem model coupled to the University of Victoria Earth System Climate Model (UVic-ESCM, based on the configurations of Keller et al, 2012; Getzlaff and Dietze, 2013; Nickelsen et al, 2015)
The importance of νdet was expected, because it is an important driver of nutrient recycling in the surface ocean (Thomas, 2002; Anderson and Sarmiento, 1994; Eppley and Peterson, 1979), which strongly affects net primary production (NPP), NPP and POC export (NCP), Chl, dissolved inorganic carbon (DIC), DFe, and N2 fixation (Kriest et al, 2012). νdet determines the rate of O2 consumption, the NO−3 level, due to denitrification in oxygen-deficient zones (ODZs) (Cavan et al, 2017)
Summary
Earth system climate models (ESCMs) are powerful tools for analysing variations in climate, while resolving interdependencies between changes in the atmosphere, on land, and in the ocean (Flato, 2011; Prinn, 2013). In this regard, the dynamics of marine ecosystems is a critical link. Fasham et al, 1990; Edwards, 2001) to global 3-D models (Sarmiento et al, 1993; Keller et al, 2012; Nickelsen et al, 2015) Most of these NPZD models lack a sound mechanistic foundation, preventing them from explicitly accounting for the organisms’ regulation of their internal physiological state. N2 fixation by algae is often diagnosed from
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