Offline Fennel: A high-performance and computationally efficient biogeochemical model within the Regional Ocean Modeling System (ROMS)

Abstract

Ocean biogeochemical models are essential for advancing our understanding of oceanographic processes. Here, we present the Offline Fennel model, a biogeochemical model that relies on previously computed physical fields, within the Regional Ocean Modeling System (ROMS). We evaluated the model performance against a fully coupled physical–biogeochemical online application in the northern Gulf of Mexico, a region with intense biogeochemical activity, including rather frequent hypoxia events. By leveraging physical hydrodynamic outputs, we ran the Offline Fennel model using various time-step multiples from the coupled configuration, significantly enhancing computational efficiency and reducing simulation computational time by up to 87 %. The accuracy of the offline model was assessed using three different mixing schemes: the generic length scale (GLS), Large–McWilliams–Doney (LMD), and Mellor and Yamada 2.5 (MY25). The offline model achieved an average skill score of 93 %, with minimal impact on performance from the time-step choice. While the GLS configuration yielded the highest accuracy, all three mixing schemes performed well. Although some discrepancies appeared between offline and coupled simulation outputs, these were smaller than those observed when using different mixing schemes within the same model configuration. A significant challenge identified was the simulation of ammonium (NH4), which exhibited the largest discrepancies due to its rapid-turnover timescale compared to other tracers. The promising results achieved so far validate the Offline Fennel model's capability and efficiency, thus offering a powerful tool for researchers aiming to conduct extensive biogeochemical simulations without rerunning the hydrodynamic component, thus significantly reducing computational demands.