Combined Physical and Biogeochemical Assessment of Mesoscale Eddy Parameterisations in Ocean Models across Resolutions

Abstract

The ocean is a climate regulator in the Earth system, yet anthropogenic climate change is affecting the ocean with physical and biogeochemical consequences. Predictions of ocean dynamics are typically achieved through numerical ocean models, but the accuracy of the simulations is limited by model resolution due to computational cost reasons. In coarse resolution models, mesoscale eddies, small-scale features often referred to as the ""weather"" of the ocean, are not resolved, with a potential to lead to misrepresentation of the eddy-mean interactions and, consequently, the large-scale modelled physical and biogeochemical response. Commonly employed mesoscale eddy parameterisations, the Redi and McWilliams (GM) schemes, primarily focus on physical processes, but their biogeochemical implications are often neglected in studies. Motivated by previous works and results, in this document, we assess the performance of a more advanced GM scheme, the GEO-METRIC parameterisation, in terms of both the physical and biogeochemical response in a hierarchy of models with varying horizontal resolutions, ranging from non-eddy resolving and eddy-permitting models to eddy-resolving models.

An idealised ocean relevant model evolved with a biogeochemical model to represent the dynamics in the North Atlantic is considered, forced by pre-industrial conditions and a climate change scenario. The results show that the GEOMETRIC parameterisation can generally improve the physical and biogeochemical response in non-eddy resolving models and eddy-permitting models, leading to closer responses to the eddy-resolving models as a model truth. Our studies provide new evidence to support the use of the GEOMETRIC parameterisation and insights of the benefits and / or deficiencies of some existing mesoscale eddy parameterisations. The important baselines that we set for the evaluation can be adopted for future assessment of parameterisations, with the aim of alleviating the

Date of Award	2025
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Julian MAK (Supervisor)