IMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

L. Kwiatkowski,L. de Mora,M. Butenschön,P. R. Halloran,M.-F. Racault,R. Barciela,I. J. Totterdell,E. T. Buitenhuis,C. Le Quéré,J. I. Allen,B. Sinha,A. Yool,P. M. Cox,C. Enright,T. R. Anderson

doi:10.5194/bg-11-7291-2014

Abstract

Abstract. Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient–phytoplankton–zooplankton–detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry–climate interactions.

Highlights

Ocean biogeochemistry is a key part of the Earth system: it regulates the cycles of major biogeochemical elements and controls the associated feedback processes between the land, ocean and atmosphere
To ensure that the simulations were performed by the different modelling groups using an identical physical run, a flexible configuration management (FCM) branch of this version of Nucleus for European Modelling of the Ocean (NEMO) was created, and all biogeochemical models were implemented in parallel within this branch and run separately
The six ocean biogeochemical models analysed within this intercomparison cover a large range of ecosystem complexity, and result in a range of approximately five in computational costs

Summary

Introduction

Ocean biogeochemistry is a key part of the Earth system: it regulates the cycles of major biogeochemical elements and controls the associated feedback processes between the land, ocean and atmosphere. Changes in ocean biogeochemistry can have important implications for climate (Reid et al, 2009). Marine ecosystems are indirectly affected by anthropogenic environmental change (Jackson et al, 2001), through climate-induced changes. L. Kwiatkowski et al.: iMarNet: an ocean biogeochemistry model intercomparison project. N P Si Fe C Alkalinity O2 HadOCC √ √ √ √ Diat-HadOCC √ √ √ √ √ √ MEDUSA-2 √ PlankTOM6 √.

Methods

Discussion

Conclusion