Optimization and evaluation of a high-resolution, regional, East-Antarctic ocean biogeochemistry model with novel in-situ physical and biogeochemical observations

• Main Authors: Nakayama, Y., Carroll, D., Wongpan, P., Takao, S., Makabe, R., Zhang, H., Menemenlis, D.
• Format: Conference Object
• Language: English
• Published: 2023
• Subjects: Antarctic; Antarctic Ocean; Shackleton; Southern Ocean; The Antarctic; Antarc*; Ice Shelves; Sea ice
• Online Access: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5016032

The Southern Ocean plays a fundamental role in the global carbon cycle. Physical and biogeochemical processes, including primary production and the upwelling of carbon-rich water masses, govern carbon exchange between the atmosphere and ocean carbon reservoirs. To study this region, we configured a regional East-Antarctic simulation derived from ECCO-Darwin, a global-ocean biogeochemistry model that assimilates both physical and biogeochemical observations. Our regional ocean model extends from the Antarctic Continent to 60°S and from 100°E to 150°E with horizontal grid spacing of 3–4 km. The model domain includes the Shackleton, Conger, Totten, Moscow University, Holmes, Dibble, and Mertz ice shelves. Since the biogeochemical component of ECCO-Darwin is optimized to best fit global observations, model-data agreement for the East Antarctic region requires further adjustments. For example, (1) simulated upper-100 m nutrient fields are biased high and typical Circumpolar-Deep-Water characteristics with nutrient-rich waters are not clearly simulated and (2) plankton types in the ECCO-Darwin do not include Phaeocystis, an abundant type that plays a key role in the Southern Ocean climate system. In this study, we adjust a small number of physical and biogeochemical model parameters and lateral boundary conditions to achieve improved model-data agreement. We define the cost function as a sum of weighted model-data differences based on both novel in-situ observations and further optimize our simulation using a Green's Functions approach. This work demonstrates downscaling methods for developing regional cutouts from the global-ocean ECCO-Darwin model, which allows for high-resolution coastal studies that include optimized sea ice, ocean physics, and biogeochemistry.