Research
The West Antarctic Peninsula exhibits pronounced oceanographic and ecological variability, driven by complex interactions between physical and biogeochemical processes. Yet how these interactions shape the biological pump and its role in climate regulation remains poorly understood. This project builds a hybrid modeling framework that combines long-term ecological observations with machine learning techniques and a mechanistic biogeochemical model incorporating deep learning based data assimilation and parameter optimization. The goal is to quantify the key controls on the biological pump and air-sea CO2 flux in the region. We examine physical and biological drivers — including sea ice dynamics, freshwater inputs, stratification, and phytoplankton community composition — to determine their role in regulating carbon export and uptake. Earth System Model simulations are also incorporated to evaluate potential shifts in carbon cycling, and we seek to better constrain the contribution of vertical mixing to dissolved organic matter export, a process that remains a major source of uncertainty in the regional carbon budget.
Selected publications:
Connors, E. J., Waite, N., Chamberlain, E. J., Stammerjohn, S., Goodell, E., Eveleth, R., Dierssen, H., Munro, D., Turner, T., Bowman, J., Schofield, O., and Kim, H. H. Unveiling drivers of Antarctic primary production using machine learning. Under Review, Geophysical Research Letters.
Kim, H. H., Bowman, J. S., Luo, Y.-W., Ducklow, H. W., Schofield, O. M., Steinberg, D. K., and Doney, S. C (2022). Modeling polar marine ecosystem functions guided by bacterial physiological and taxonomic traits. Biogeosciences, 19, 117-136.
Photosynthesis produces approximately 100 gigatons of organic carbon per year in the surface ocean, yet only a small fraction reaches the mesopelagic zone, where respiration and remineralization by heterotrophic bacteria and zooplankton consume most of this carbon. Studies have revealed significant imbalances between carbon supply and demand in the mesopelagic layer, with particle flux attenuation up to two orders of magnitude lower than heterotrophic metabolism. This indicates that particle export alone cannot meet the carbon demand of mesopelagic biota, pointing to additional, unaccounted-for sources of organic carbon. This project reassesses the mesopelagic carbon budget at the Bermuda Atlantic Time-series Study (BATS) site by developing a high-resolution model that resolves multiple carbon export and attenuation pathways — including zooplankton diel vertical migration (active flux), vertical mixing of dissolved organic carbon, and particle sinking — within a hybrid modeling framework.
Selected publications:
Kim, H. H., Mao, S., Archibald, K. M., Terhaar, J., and Thomason, R. M. (2025). Bacterial control of metabolic balance in the Sargasso Sea near Bermuda: Insights from data-assimilative biogeochemical modeling. Journal of Geophysical Research: Biogeosciences, 130, e2025JG008919.
The Southern Ocean is central to global carbon cycling and air-sea CO2 exchange, yet significant uncertainties persist in estimating its net CO2 flux, particularly near the West Antarctic Peninsula. Conflicting estimates from profiling floats and atmospheric models underscore the need for improved regional assessments. This project combines long-term ecological research, satellite remote sensing, and biogeochemical modeling to investigate phytoplankton dynamics, sea ice variability, and their influence on air-sea CO2 exchange. By leveraging hyperspectral satellite missions, Imaging Flow CytoBot data, and numerical models, we aim to quantify phytoplankton community composition, refine estimates of net primary production and CO2 uptake, and assess how physical and biological drivers shape long-term carbon cycling trends along the West Antarctic Peninsula.
Selected publications:
Czajka, C. R., Turner, J. S., Stammerjohn, S., Kim, H. H., Schofield, O., Saenz, B. T., and Doney, S. C. Modeling upper ocean ecosystem dynamics in response to interannual sea-ice variability in the Western Antarctic Peninsula. Under Review, Journal of Geophysical Research: Biogeosciences.
Kim, H. H., Luo, Y.-W., Ducklow, H. W., Schofield, O. M., Steinberg, D. K., and Doney, S. C (2021). WAP-1D-VAR v1.0: Development and evaluation of a one-dimensional variational data assimilation model for the marine ecosystem along the West Antarctic Peninsula. Geoscientific Model Development, 14, 4939-4975.
Marine heterotrophic bacteria are the hidden architects of ocean biogeochemistry, processing vast quantities of carbon through complex metabolic networks that determine whether it is returned to the upper ocean and atmosphere or sequestered in the deep sea. Yet current Earth System Models lack mechanistic representations of bacterial metabolism, severely limiting our ability to predict how these processes respond to and shape environmental change. This project bridges this critical "bacterial gap" by developing a multi-scale modeling framework that connects metabolic models with ocean biogeochemical models. Driven by metabolic translators, we are building coupled biogeochemical models that translate microbial metabolism — modeled through genome-scale Flux Balance Analysis — into ecosystem-scale processes. This approach enables effective scale transitions, providing a more mechanistic representation of microbial functions in global ocean biogeochemical models.
Selected publications:
Kim, H. H., Wolfe, W., Lawrence, E., Doney, S., Moran, M. A., Freilich, M., Krinos, A., Yang, M., Covert, M., Braakman, R., Scott, H., Segrè, D., Litchman, E., Weissman, J. L., and Agmon, E. Scalable, substrate-explicit metabolic network modeling of heterotrophic bacteria for ocean biogeochemistry. In Prep., Invited Perspective, Proceedings of the National Academy of Sciences.
Chamberlain, E. J., Boulton, W., Connors, E. J., Calianos, T., Bowman, J., Creamean, J., Mock, T., and Kim, H. H. Machine learning as a decoder from microbial diversity to microbial function. Under Review, Frontiers in Microbiology.
Kim, H. H., Laufkötter, C., Lovato, T., Doney, S. C., and Ducklow, H. W. (2023). Projected 21stcentury changes in marine heterotrophic bacteria under climate change. Frontiers in Microbiology, 14:1049579.
Ocean Alkalinity Enhancement (OAE) alters seawater carbonate chemistry by introducing alkaline materials, shifting the balance of dissolved inorganic carbon and buffering capacity in marine environments. This project evaluates the feasibility, effectiveness, and potential ecological impacts of OAE through an integrated approach combining fieldwork, laboratory experiments, and numerical modeling. Laboratory experiments assess biological responses of key marine species and the engineering safety of alkalinity additions under controlled conditions. To test OAE in real-world settings, we conduct small-scale, closely monitored field trials, including the release of non-toxic tracer dyes and liquid alkalinity in offshore waters. Results from these trials inform our coupled physical-biogeochemical ocean model, which simulates broader regional effects to predict changes in ocean chemistry, carbon uptake, and ecosystem responses.
Selected publications:
Rheuban, J. E., Kim, H. H., Chen, K., Lima, I. D., McCorkle, D. C., Michel, A. P., Wang, Z. A., and Subhas, A. V. (2025). Carbonate system site selection characteristics for ocean alkalinity enhancement in the US Northeast Shelf and Slope. Journal of Geophysical Research: Biogeosciences, 130(12).
Guo, Y., Chen, K., Subhas, A. V., Rheuban, J. E., Wang, Z. A., McCorkle, D. C., Michel, A., and Kim, H. H. (2025). Site selection for ocean alkalinity enhancement informed by passive tracer simulations. Communications Earth and Environment, 6, 535.