Phytoplankton primary production is a crucial component of Arctic Ocean (AO) biogeochemistry, playing a pivotal role in the carbon cycling by supporting higher trophic levels and removing atmospheric carbon dioxide. The advent of satellite observations measuring chlorophyll a concentration (Chl_ a) has yielded unprecedented insights into the distribution of AO phytoplankton, enhancing our ability to assess oceanic productivity. However, the optical properties of AO waters differ significantly from those of lower‐latitude waters, and standard Chl_a algorithms perform poorly in the AO. In particular, Chl_a retrievals are challenged by interferences from other marine constituents including higher pigment packaging and higher proportion of light absorption by colored dissolved organic matter. To derive phytoplankton-originating signature as well as mitigate those effects, solar-induced chlorophyll fluorescence (SIF) emerges as a valuable tool for acquiring physiological insights into the direct photosynthetic processes in the AO. In this study, we leverage satellite-based SIF measurements to assess their correlation with a set of predictive factors influencing phytoplankton photosynthesis. We extend the temporal coverage of AO SIF data to cover the period 2004 - 2020. This novel dataset offers a pathway to monitor the physiological interactions of phytoplankton with changes in climate, promising to significantly improve our understanding of the Arctic water’s productivity. The application of this data is expected to provide insights into how phytoplankton respond to shifts in environmental changes, contributing to a more nuanced understanding of their role in High-Latitude Northern Oceans ecosystems.

Surface ocean temperature and velocity anomalies at meso- and sub-meso-scales induce wind stress anomalies. These wind-front interactions, referred to as thermal (TFB) and current (CFB) feedbacks, respectively, have been studied in isolation at mesoscale, yet they have rarely been considered in tandem. Here, we assess the combined influence of TFB and CFB and their relative impact on surface wind stress derivatives. Analyses are based on output from two regions of the Southern Ocean in a 4-6 km-resolution coupled simulation. Considering both TFB and CFB shows regimes of interference, which remain mostly linear down to the simulation resolution. The jointly-generated wind stress curl anomalies approach 10-5 N-3, ~20 times stronger than at mesoscale. The synergy of both feedbacks improves the ability to reconstruct wind stress curl magnitude and structure from both surface vorticity and SST gradients by 12-37% on average, compared with using either one alone.

Satellite radar interferometry data reveals that the grounding line of Petermann Glacier, Greenland migrates by several kilometers during the tidal cycle, bringing pressurized, subsurface, warm ocean waters in regular contact with a large sector of grounded ice. We use the Massachusetts Institute of Technology general circulation model in two dimensions to calculate the ice melt rates as a function of grounding zone width and ocean thermal forcing. Ice melt rates are found to be higher in the grounding zone cavity than anywhere else in the ice shelf cavity. The melt rates increase sub-linearly with the width of the grounding zone and ocean thermal forcing. The model results agree well with remote sensing estimates of ice melt. High basal ice melt rates in tidally-flushed grounding zones imply that marine-terminating glaciers are more sensitive to ocean thermal forcing than anticipated, which will increase their projected contribution to sea level rise.

While the preindustrial ocean was assumed to be in equilibrium with the atmosphere, the modern ocean is a carbon sink, resulting from natural variability and anthropogenic perturbations, such as fossil fuel emissions and changes in riverine exports over the past two centuries. Here we use a suite of sensitivity experiments based on the ECCO-Darwin global-ocean biogeochemistry model to evaluate the response of air-sea CO2 flux and carbon cycling to present-day lateral fluxes of carbon, nitrogen, and silica. We generate a daily export product by combining point-source freshwater discharge from JRA55-do with the Global NEWS 2 watershed model, accounting for lateral fluxes from 5171 watersheds worldwide. From 2000 to 2019, carbon exports increase CO2 outgassing by 0.22 Pg C yr-1 via the solubility pump, while nitrogen exports increase the ocean sink by 0.17 Pg C yr-1 due to phytoplankton fertilization. On regional scales, exports to the Tropical Atlantic and Arctic Ocean are dominated by organic carbon, which originates from terrestrial vegetation and peats and increases CO2 outgassing (+10 and +20%, respectively). In contrast, Southeast Asia is dominated by nitrogen from anthropogenic sources, such as agriculture and pollution, leading to increased CO2 uptake (+7%). Our results demonstrate that the magnitude and composition of riverine exports, which are determined in part from upstream watersheds and anthropogenic perturbations, substantially impact present-day regional-to-global-ocean carbon cycling. Ultimately, this work stresses that lateral fluxes must be included in ocean biogeochemistry and Earth System Models to better constrain the transport of carbon, nutrients, and metals across the land-ocean-aquatic-continuum.

A document by Joseph K. Ansong. Click on the document to view its contents.

As a marine Carbon Dioxide Removal (mCDR) approach, Ocean Alkalinity Enhancement (OAE) is emerging as a viable method for removing anthropogenic CO2 emissions from the atmosphere to mitigate climate change. To achieve substantial carbon reduction using this method, OAE would need to be widespread and scaled-up across the global ocean. However, the efficiency of OAE varies substantially across a range of space-time scales and as such field deployments must be carefully planned to maximize efficiency and minimize logistical costs and risks. Here we develop a mCDR efficiency framework based on the data-assimilative ECCO-Darwin ocean biogeochemistry model, which examines two key factors over seasonal to multi-decadal timescales: 1) mCDR potential, which quantifies the CO2 solubility of the upper ocean; and 2) dynamical mCDR efficiency, representing the full-depth impact of ocean advection, mixing, and air-sea CO2 exchange. To isolate and quantify the factors that determine dynamical efficiency, we develop a reduced complexity 1-D model, rapid-mCDR, as a computationally-efficient tool for evaluation of mCDR efficiency. Combining the rapid-mCDR model with ECCO-Darwin allows for rapid characterization of OAE efficiency at any location globally. This research contributes to our understanding and optimization of OAE deployments (i.e., deploying experiments in the real-world ocean) as an effective mCDR strategy and elucidates the regional differences and mechanistic processes that impact mCDR efficiency. The modeling tools developed in this study can be readily employed by research teams and industry to plan and complement future field deployments and provide essential Monitoring, Reporting, and Verification (MRV).

The future wide-swath satellite altimeters, such as the upcoming Surface Water Ocean Topography (SWOT) mission, will provide instantaneous 2D measurements of sea level down to the spatial scale of O(10 km) for the first time. However, the validity of the geostrophic assumption for estimating surface currents from these instantaneous maps is not known a priori. In this study, we quantify the accuracy of geostrophy for the estimation of surface currents from a knowledge of instantaneous sea level using the hourly snapshots from a tide- and eddy-resolving global numerical simulation. Geostrophic balance is found to be the leading-order balance in frontal regions characterized by large kinetic energy, such as the western boundary currents and the Antarctic Circumpolar Current. Everywhere else, geostrophic approximation ceases to be a useful predictor of ocean velocity, which may result in significant high-frequency contamination of geostrophically computed velocities by fast variability (e.g., inertial and higher). As expected, the validity of geostrophy is shown to improve at low frequencies (typically$<$0.5 cpd). Global estimates of the horizontal momentum budget reveal that the tropical and mid-latitude regions where geostrophic balance fails are dominated by fast variability and turbulent stress divergence terms rather than higher-order geostrophic terms. These findings indicate that the estimation of velocity from geostrophy applied on SWOT instantaneous sea level maps may be challenging away from energetic areas.

We present improvements in the modeling of the vertical wavenumber spectrum of the internal gravity wave continuum in high-resolution regional ocean simulations. We focus on model sensitivities to mixing parameters and comparisons to McLane moored profiler observations in a Pacific region near the Hawaiian Ridge, which features strong semidiurnal tidal beams. In these simulations, the modeled continuum exhibits high sensitivity to the background mixing components of the K-Profile Parameterization (KPP) vertical mixing scheme. Without the KPP background mixing, stronger vertical gradients in velocity are sustained in the simulations and the modeled kinetic energy and shear spectral slopes are significantly closer to the observations. The improved representation of internal wave dynamics in these simulations makes them suitable for improving ocean mixing estimates and for the interpretation of satellite missions such as the Surface Water and Ocean Topography (SWOT) mission.

A submesoscale-permitting global ocean model is used to study the upper ocean turbulence. Submesoscale processes peak in winter and, consequently, geostrophic kinetic energy (KE) spectra tend to be relatively shallow in winter (∼k-2) with steeper spectra in summer (∼k-3). This seasonal transition from steep to shallow power-law in the KE spectra indicates a transition from quasi-geostrophic (QG) turbulence in summer to pronounced surface-QG-like turbulence in winter. It is shown that this transition in KE spectral scaling has two phases. In the first phase (late autumn), KE spectra show a presence of two spectral regimes: ∼k-3 scaling in mesoscales (100-300 km) and ∼k-2 scaling in submesoscales (<50 km), indicating the coexistence of QG, surface-QG, and frontal dynamics. In the second phase (late winter), mixed-layer instabilities convert available potential energy into KE, which cascades upscale leading to flattening of the KE spectra at larger scales, and k-2 power-law develops in mesoscales too.

We present results from a new, global, high-resolution (~4-km for ocean and ~7-km for atmosphere) realistic earth system simulation. This simulation allows us to examine aspects of small-scale air-sea interaction beyond what previous studies have reported. Our study focuses on recurring intermittent wind events in the Gulf Stream region. These events induce local air-sea heat fluxes above Sea Surface Temperature (SST) anomalies with horizontal scales smaller than 500-km. In particular, strong latent heat bursts above warm SST anomalies are observed during these wind events. We show that such wind events are associated with a secondary circulation that acts to fuel the latent heat bursts by transferring dry air and momentum down to the surface. The intensity of this secondary circulation is related to the strength of small-scale SST fronts that border SST anomalies. The study of such phenomena requires high-resolution in both the atmospheric and oceanic components of the model.