Cordero, Theresa J., Frank O Bryan, Julie L McClean, Sarah T Gille, and Gustavo Marques, August 2026: A glacial fjord box model: Derivation and representation of glacially modified water. Journal of Advances in Modeling Earth Systems, 18(8), DOI:10.1029/2024MS004794. Abstract
Fjords are a crucial connection between the Greenland Ice Sheet and the ocean, but remain unrepresented at the scale of many Earth System Models. To parameterize mixing within them, we modify a two-layer estuary box model to include buoyant plumes, which are common features of glacial fjords. This fjord box model allows us to estimate primarily the salinity of the water mass exported to the open ocean. We compare high-resolution MITgcm simulations and observations to both the fjord box model and results from buoyant plume theory. The volume transport out of the fjord is increased in the fjord box model compared to a buoyant plume alone. However, the volume of shelf water entrained into the buoyant plume is a key control on the properties of the water mass exported from the fjord into the open ocean. This model is also used to estimate the temperature of glacially modified water by using the temperature of the water mass entering the fjord as a tuning parameter. We find that the fjord box model could improve the salt flux into the ocean from fjords, but that temperature is highly sensitive to the effective temperature of the freshwater flux, which is based on a ratio of meltwater and subglacial discharge and is challenging to estimate.
Dukhovskoy, Dmitry S., Theresa J Cordero, Katherine Hedstrom, Michael A Alexander, Michael G Jacox, Robert Hallberg, Matthew J Harrison, and Jessie Liu, August 2026: Design and implementation of a Newtonian relaxation scheme in the NOAA GFDL Sea Ice Model (SIS2). Geoscientific Model Development, 19(15), DOI:10.5194/gmd-19-7169-20267169-7196. Abstract
Regional sea ice models often do not cover the full extent of polar ice and instead include open ocean boundaries that are not ice-free year-round. This necessitates the specification of lateral boundary conditions for sea ice, an inherently challenging task for most sea ice models. Although this issue is less critical for pan-polar domains, the interior ice state still needs to be constrained for many applications. In this study, we present the design and evaluation of a Newtonian relaxation algorithm for sea ice, implemented in the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) Sea Ice Simulator (SIS2). The algorithm can be applied both at the lateral boundaries to impose open boundary conditions and within the interior domain to constrain sea ice thickness and concentration toward prescribed target fields. The method is flexible and can be applied anywhere in the domain, making it especially well-suited for regional applications of sea ice models with variable ice cover along their boundaries. The method is evaluated within a regional forecasting system based on the NOAA GFDL ocean model (MOM6) coupled with sea ice model (SIS2) for two regional configurations: the Northeast Pacific and the Arctic Ocean. Sensitivity experiments spanning a range of relaxation time scales and nudging strengths demonstrate that the method substantially improves the representation of sea ice and associated ocean surface fields, offering a practical solution for both boundary and interior constraints in regional sea ice modeling.
The Laurentian Great Lakes share several physical characteristics with the coastal ocean, including atmosphere–water interactions, rotational dynamics, and ice cover processes. However, their weak density stratification, relatively small surface area, and distinct seasonal mixing cycles pose unique challenges for numerical modeling. Modeling approaches and parameterizations developed for global applications, however, may yet provide valuable pathways for addressing persistent biases in lake models. To examine these possibilities, we develop a 3D hydrodynamic model for Lake Michigan-Huron (LMH) using the Modular Ocean Model version 6.0 coupled with the Sea Ice Simulator version 2.0 (MOM6-SIS2). Originally designed for global ocean and earth system modeling, MOM6 offers flexible vertical coordinate systems (VCSs) to maintain density gradients and improved handling of complex bathymetry, both potential advantages for application in inland water bodies like the Great Lakes. This is the first study to investigate MOM6-SIS2's ability to simulate key features of hydrography and circulation in freshwater systems under different VCSs. This study tested z∗ (depth-based) and hybrid (depth and isopycnal) VCSs. Simulations were performed for the years 2017 and 2018 and evaluated against in situ and remote sensing observations, as well as outputs from a contemporary Finite Volume Community Ocean Model (FVCOM) of LMH (LMH-FVCOM), used in an operational forecast system. MOM6-SIS2-LMH skillfully simulated daily averaged lake surface temperature (LST), vertical thermal structure, and ice concentration, with biases in LST and ice concentration generally below 0.5 °C and 2 %, respectively. It also produced comparable results to LMH-FVCOM in terms of LST, vertical thermal structure, and ice concentration. Both VCSs (z∗ and hybrid) successfully captured large-scale circulation patterns and seasonal overturning. The hybrid VCS, reduced excessive thermocline diffusion in deep waters, observed in both FVCOM and MOM6-SIS2 with z∗ VCS and allowed the model to maintain ecologically important deep cold water in the summer months. These improvements highlight the potential of MOM6-SIS2 to successfully simulate lake dynamics and offer the potential to more accurately resolve the delicate balance of thermal structure and mixing in stratified lake environments. However, the limited nearshore resolution resulting from MOM6's structured grid degraded the simulation of flows through the Straits of Mackinac, as well as nearshore temperature and water level variability.
Regional ocean models enable the generation of computationally affordable and regionally tailored ensembles of near-term forecasts and long-term projections of sufficient resolution to serve marine resource management. Climate change, however, has created marine resource challenges, such as shifting stock distributions, that cut across domestic and international management boundaries and have pushed regional modeling efforts toward “coastwide” approaches. Here, we present and evaluate a multidecadal hindcast with a Northeast Pacific regional implementation of the Modular Ocean Model, version 6, with sea ice and biogeochemistry that extends from the Chukchi Sea to the Baja California Peninsula at 10 km horizontal resolution (MOM6-COBALT-NEP10k, or NEP10k). This domain includes an Arctic-adjacent system with a broad, shallow shelf seasonally covered by sea ice (the eastern Bering Sea), a sub-Arctic system with upwelling in the Alaska Gyre and predominant downwelling winds and large freshwater forcing along the coast (the Gulf of Alaska), and a temperate, eastern boundary upwelling ecosystem (the California Current Ecosystem). The coastwide model was able to recreate seasonal and cross-ecosystem contrasts in numerous ecosystem-critical properties including temperature, salinity, inorganic nutrients, oxygen, carbonate saturation states, and chlorophyll. Spatial consistency between modeled quantities and observations generally extended to plankton ecosystems, though small to moderate biases were also apparent. Fidelity with observed zooplankton biomass, for example, was limited to first-order seasonal and cross-system contrasts. Temporally, simulated monthly surface and bottom temperature anomalies in coastal regions (<500 m deep) closely matched estimates from data-assimilative ocean reanalyses. Performance, however, was reduced in some nearshore regions coarsely resolved by the model's 10 km resolution grid and for point measurements. The time series of satellite-based chlorophyll anomaly estimates proved more difficult to match than temperature. System-specific ecosystem indicators were also assessed. In the eastern Bering Sea, NEP10k robustly matched observed variations, including recent large declines, in the area of the summer bottom water “cold pool” (<2 °C), which exerts a profound influence on eastern Bering Sea fisheries. In the Gulf of Alaska, the simulation captured patterns of sea surface height variability and variations in thermal, oxygen, and acidification risk associated with local modes of interannual to decadal climate variability. In the California Current Ecosystem, the simulation robustly captured variations in upwelling indices and coastal water masses, though discrepancies in the latter were evident in the Southern California Bight. Enhanced model resolution may reduce such discrepancies, but any benefits must be carefully weighed against computational costs given the intended use of this system for ensemble predictions and projections. Meanwhile, the demonstrated NEP10k skill level herein, particularly in recreating cross-ecosystem contrasts and the time variation of ecosystem indicators over multiple decades, suggests considerable immediate utility for coastwide retrospective and predictive applications.
Chlorophyll underpins ocean productivity yet simulating chlorophyll across biomes, seasons and depths remains challenging for earth system models. Inconsistencies are often attributed to misrepresentation of the myriad nutrient supply, growth and loss processes that govern phytoplankton biomass. They may also arise, however, from unresolved or misspecified photoacclimation or photoadaptation responses. A series of global ocean ecosystem simulations were conducted to assess these latter sensitivities: alternative photoacclimation schemes implicitly modulated investments in light harvesting versus photodamage avoidance and other cellular functions. Photoadaptation experiments probed the impact of adding low- and high-light adapted phytoplankton ecotypes. Results showed that photoacclimation and photoadaptation alternatives generate chlorophyll differences exceeding a factor of 2 in some regions and seasons. In stratified waters, photoadaptation and acclimation to light levels over mixing depths consistent with the timescale of photoadaptation (days) benefitted model performance. In regions and seasons with deep mixed layers, surface-skewed photoacclimation yielded improved fidelity across satellite chlorophyll products. Large photoacclimation-driven differences in chlorophyll concentration had small impacts on primary productivity and carbon export, unlike those arising from changes in the nutrient supply. Improved photoacclimation and photoadaption constraints are thus needed to reduce ambiguities in the drivers of chlorophyll change and their biogeochemical implications.
