Evaluating the performance of CMIP6 models in simulating Southern Ocean biogeochemistry

The Southern Ocean plays a vital role in global biogeochemical cycles, yet the quality of its representation in Earth System Models (ESMs) remains unquantified. This study evaluates the performance of 14 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating key biogeochemical variables south of 30° S, including austral-summer surface chlorophyll, deep chlorophyll maxima (DCMs), nitrate, silicate, dissolved iron, and yearly particulate organic carbon (POC). Model output for the period 2000–2014 is compared to multiple observational datasets, such as Copernicus for chlorophyll and POC, the World Ocean Atlas (WOA) for nitrate and silicate, and GEOTRACES for dissolved iron. Model performance is assessed using statistical metrics including mean bias error (MBE), standardised standard deviation (SSD), root mean squared deviation (RMSD), and correlation coefficient (CC). The results reveal substantial inter-model variability, with individual models exhibiting strengths in simulating different variables. GFDL-ESM4 best reproduces chlorophyll and DCM patterns, IPSL-CM6A-LR performs well for nutrients, MIROC-ES2L for dissolved iron, and CMCC-ESM2 for POC. Based on composite rankings, the top-performing models are IPSL-CM6A-LR, GFDL-ESM4, CMCC-ESM2, UKESM1-0-LL, and CNRM-ESM2-1. This work underscores the importance of multi-model evaluation for identifying model strengths and guiding future improvements in biogeochemical (BGC) model development, particularly in the context of understanding and projecting Southern Ocean biogeochemistry under climate change.