Marine geochemical data assimilation in an efficient Earth system model of global biogeochemical cycling

Abstract

We have extended the 3-D ocean based "Grid EN-abled Integrated Earth system model" (GENIE-1) to help understand the role of ocean biogeochemistry and marine sediments in the long-term (∼100 to 100000 year) regulation of atmospheric CO2, and the importance of feedbacks between CO2 and climate. Here we describe the ocean carbon cycle, which in its first incarnation is based around a simple single nutrient (phosphate) control on biological productivity. The addition of calcium carbonate preservation in deep-sea sediments and its role in regulating atmospheric CO2 is presented elsewhere (Ridgwell and Hargreaves, 2007). We have calibrated the model parameters controlling ocean carbon cycling in GENIE-1 by assimilating 3-D observational datasets of phosphate and alkalinity using an ensemble Kalman filter method. The calibrated (mean) model predicts a global export production of particulate organic carbon (POC) of 8.9 PgC yr-1, and reproduces the main features of dissolved oxygen distributions in the ocean. For estimating biogenic calcium carbonate (CaCO 3) production, we have devised a parameterization in which the CaCO3POC export ratio is related directly to ambient saturation state. Calibrated global CaCO3 export production (1.2 PgC yr -1) is close to recent marine carbonate budget estimates. The GENIE-1 Earth system model is capable of simulating a wide variety of dissolved and isotopic species of relevance to the study of modern global biogeochemical cycles as well as past global environmental changes recorded in paleoceanographic proxies. Importantly, even with 12 active biogeochemical tracers in the ocean and including the calculation of feedbacks between atmospheric CO2 and climate, we achieve better than 1000 years per (2.4 GHz) CPU hour on a desktop PC. The GENIE-1 model thus provides a viable alternative to box and zonally-averaged models for studying global biogeochemical cycling over all but the very longest (> 1000000 year) time-scales.