Geoscientific Model Development (Jun 2023)

Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones

  • D. Bianchi,
  • D. McCoy,
  • S. Yang

DOI
https://doi.org/10.5194/gmd-16-3581-2023
Journal volume & issue
Vol. 16
pp. 3581 – 3609

Abstract

Read online

Nitrogen (N) plays a central role in marine biogeochemistry by limiting biological productivity in the surface ocean; influencing the cycles of other nutrients, carbon, and oxygen; and controlling oceanic emissions of nitrous oxide (N2O) to the atmosphere. Multiple chemical forms of N are linked together in a dynamic N cycle that is especially active in oxygen minimum zones (OMZs), where high organic matter remineralization and low oxygen concentrations fuel aerobic and anaerobic N transformations. Biogeochemical models used to understand the oceanic N cycle and project its change often employ simple parameterizations of the network of N transformations and omit key intermediary tracers such as nitrite (NO2-) and N2O. Here we present a new model of the oceanic N cycle (Nitrogen cycling in Oxygen Minimum Zones, or NitrOMZ) that resolves N transformation occurring within OMZs and their sensitivity to environmental drivers. The model is designed to be easily coupled to current ocean biogeochemical models by representing the major forms of N as prognostic tracers and parameterizing their transformations as a function of seawater chemistry and organic matter remineralization, with minimal interference in other elemental cycles. We describe the model rationale, formulation, and numerical implementation in a one-dimensional representation of the water column that reproduces typical OMZ conditions. We further detail the optimization of uncertain model parameters against observations from the eastern tropical South Pacific OMZ and evaluate the model's ability to reproduce observed profiles of N tracers and transformation rates in this region. We conclude by describing the model's sensitivity to parameter choices and environmental factors and discussing the model's suitability for ocean biogeochemical studies.