Perturbed Biology and Physics Signatures in a 1-D Ocean Biogeochemical Model Ensemble

Prima Anugerahanti,Shovonlal Roy,Keith Haines

doi:10.3389/fmars.2020.00549

Prima Anugerahanti, Shovonlal Roy + Show 1 more

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https://doi.org/10.3389/fmars.2020.00549

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Abstract

Sources of uncertainty in a marine biogeochemical model include input from physical processes and the choice of functional forms representing the strength and dependencies of biogeochemical processes. This study explores characteristic signatures from these uncertainties by generating ensembles from perturbing the biogeochemistry equations and perturbing physical input using a 1-D intermediately-complex model run at five oceanographic stations. Perturbed biogeochemistry ensemble (PBE) produces larger spreads than perturbed physics ensemble (PPE), and distinctly different ensemble variations. Fractions of nitrogen in phytoplankton pool from observations show a larger variability than in any single model-ensemble member, but the PBE spread generally captures this variability, whereas the PPE spread does not. The results show that the PBE method gives a more realistic representation of uncertainty than PPE in our 1D-model setup. Our method needs to be tested in more complex models in order to understand its significance on larger scales.

Highlights

Ocean biogeochemical (OBGC) models have been developed to understand how the ocean ecosystem responds to the changes in both the physics and the biogeochemistry (Doney et al, 2012; Yool et al, 2013; Butenschon et al, 2016)
NEMO-FOAM is a data assimilation product and biases in well observed quantities are small, for temperature and mixed layer depth (MLD) we introduce an additional bias correction to match the mean seasonal physical conditions observed at the stations
We examine the fractions of total nitrogen in the phytoplankton pool to reveal a signature of the processes which have been varied within the ensembles, in particular this distinguishes perturbed physics ensemble (PPE) from Perturbed biogeochemistry ensemble (PBE) induced variations

Summary

Introduction

Ocean biogeochemical (OBGC) models have been developed to understand how the ocean ecosystem responds to the changes in both the physics and the biogeochemistry (Doney et al, 2012; Yool et al, 2013; Butenschon et al, 2016). Key uncertainties that affect OBGC models include physical processes, with vertical mixing and upwelling of nutrients often poorly known (Doney, 1999; Friedrichs et al, 2006; Sinha et al, 2010), and the various choices for formulating the biological processes such as nutrient uptake, zooplankton grazing, and plankton mortality (Gentleman et al, 2003; Anderson et al, 2010; Adamson and Morozov, 2013) These biological processes are described by functional forms relating them to concentrations of plankton and nutrients, as well as ambient temperature and light availability.

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