Oliver, S., Khatiwala, S., Cartis, C., Ward, Ben and Kriest, Iris (2024) Using Shortened Spin‐Ups to Speed Up Ocean Biogeochemical Model Optimization. Journal of Advances in Modeling Earth Systems, 16 (9). Art.Nr.: e2023MS003941. DOI 10.1029/2023MS003941.

Preview

Text J Adv Model Earth Syst - 2024 - Oliver - Using Shortened Spin‐Ups to Speed Up Ocean Biogeochemical Model Optimization.pdf - Published Version Available under License Creative Commons: Attribution 4.0. Download (1MB) | Preview

Abstract

The performance of global ocean biogeochemical models can be quantified as the misfit between modeled tracer distributions and observations, which is sought to be minimized during parameter optimization. These models are computationally expensive due to the long spin‐up time required to reach equilibrium, and therefore optimization is often laborious. To reduce the required computational time, we investigate whether optimization of a biogeochemical model with shorter spin‐ups provides the same optimized parameters as one with a full‐length, equilibrated spin‐up over several millennia. We use the global ocean biogeochemical model MOPS with a range of lengths of model spin‐up and calibrate the model against synthetic observations derived from previous model runs using a derivative‐free optimization algorithm (DFO‐LS). When initiating the biogeochemical model with tracer distributions that differ from the synthetic observations used for calibration, a minimum spin‐up length of 2,000 years was required for successful optimization due to certain parameters which influence the transport of matter from the surface to the deeper ocean, where timescales are longer. However, preliminary results indicate that successful optimization may occur with an even shorter spin‐up by a judicious choice of initial condition, here the synthetic observations used for calibration, suggesting a fruitful avenue for future research.

Plain Language Summary

Global ocean biogeochemical models allow us to simulate ocean biological and chemical variables throughout the global ocean, and are necessary for climate change projections. They are very computationally expensive due to the required spin‐up needed for the model to reach a steady state, and so any improvements to the model need to be sought in an efficient way. One way we investigate here is to first make the model less computationally expensive by using a shorter spin‐up, and then we apply an efficient optimization algorithm to tune the model to observations. By shortening the spin‐up from 3,000 to 2,000 years we show that we can still reach a successfully optimized model. Preliminary results indicate that successful optimization may occur with an even shorter spin‐up when the biogeochemical model is initialized from a more accurate state, which highlights a future avenue for research that may encourage more systematic tuning of computationally expensive ocean biogeochemical models.

Key Points

Global ocean biogeochemical models are computationally expensive due to the long spin‐up time required to reach equilibrium
A shortened spin up of 2,000 years during parameter optimization can be successfully optimized
How short a spin‐up one can successfully optimize is influenced by the parameters being calibrated and the initial conditions of the model

Actions (login required)

View Item