In the tropical Pacific, weak ventilation and intense microbial respiration at depth give rise to a low dissolved oxygen (O2) environment that is thought to be ventilated primarily by the equatorial current system (ECS). The role of mesoscale eddies and diapycnal mixing as potential pathways of O2 supply in this region, however, remains poorly known due to sparse observations and coarse model resolution. Using an eddy resolving simulation of ocean circulation and biogeochemistry, we assess the contribution of these processes to the O2 budget balance and find that turbulent mixing of O2 and its modulation by mesoscale eddies contribute substantially to the replenishment of O2 in the upper equatorial Pacific thermocline, complementing the advective supply of O2 by the ECS and meridional circulation at depth. These transport processes are strongly sensitive to seasonal forcing by the wind, with elevated mixing of O2 into the upper thermocline during summer and fall when the vertical shear of the lateral flow and eddy kinetic energy are intensified. The tight link between eddy activity and the downward mixing of O2 arises from the modulation of equatorial turbulence by Tropical Instability Waves via their eddy impacts on the vertical shear. This interaction of ocean processes across scales sustains a local pathway of O2 delivery into the equatorial Pacific interior and highlights the need for adequate observations and model representation of turbulent mixing and mesoscale processes for understanding and predicting the fate of the tropical Pacific O2 content in a warmer and more stratified ocean.

Over nine years of hourly surface current data from high-frequency radar (HFR) off the US West Coast are analyzed using a Bayesian least-squares fit for tidal components. The spatial resolution and geographic extent of HFR data allow us to assess the spatial structure of the non-phase-locked component of the tide. In the frequency domain, the record length and sampling rate allow resolution of discrete tidal lines corresponding to well-known constituents and the near-tidal broadband elevated continuum resulting from amplitude and phase modulation of the tides, known as cusps. The FES2014 tide model is used to remove the barotropic component of tidal surface currents in order to evaluate its contribution to the phase-locked variance and spatial structure. The mean time scale of modulation is 243 days for the M$_2$ constituent and 181 days for S$_2$, with overlap in their range of values. These constituents’ modulated amplitudes are significantly correlated in several regions, suggesting shared forcing mechanisms. Within the frequency band M$_2$ $\pm$ 5 cycles per year, an average of 48\% of energy is not at the phase-locked frequency. When we remove the barotropic model, this increases to 64\%. In both cases there is substantial regional variability. This indicates that a large fraction of tidal energy is not easily predicted (e.g. for satellite altimeter applications). The spatial autocorrelation of the non-phase-locked variance fraction drops to zero by 150 km, comparable to the width of the swath of the recently launched Surface Water and Ocean Topography (SWOT) altimeter.

We assess the Southern Ocean CO2 uptake (1985-2018) using data sets gathered in the REgional Carbon Cycle Assessment and Processes Project phase 2 (RECCAP2). The Southern Ocean acted as a sink for CO2 with close agreement between simulation results from global ocean biogeochemistry models (GOBMs, 0.75±0.28 PgCyr-1) and pCO2-observation-based products (0.73±0.07 PgCyr-1). This sink is only half that reported by RECCAP1. The present-day net uptake is to first order a response to rising atmospheric CO2, driving large amounts of anthropogenic CO2 (Cant) into the ocean, thereby overcompensating the loss of natural CO2 to the atmosphere. An apparent knowledge gap is the increase of the sink since 2000, with pCO2-products suggesting a growth that is more than twice as strong and uncertain as that of GOBMs (0.26±0.06 and 0.11±0.03 PgCyr-1 decade-1 respectively). This is despite nearly identical pCO2 trends in GOBMs and pCO2-products when both products are compared only at the locations where pCO2 was measured. Seasonal analyses revealed agreement in driving processes in winter with uncertainty in the magnitude of outgassing, whereas discrepancies are more fundamental in summer, when GOBMs exhibit difficulties in simulating the effects of the non-thermal processes of biology and mixing/circulation. Ocean interior accumulation of Cant points to an underestimate of Cant uptake and storage in GOBMs. Future work needs to link surface fluxes and interior ocean transport, build long overdue systematic observation networks and push towards better process understanding of drivers of the carbon cycle.

Given the role played by the historical and extensive coverage of sea ice concentration (SIC) observations in reconstructing the long-term variability of Antarctic sea ice, and the limited attention given to model-dependent parameters in current sea ice data assimilation studies, this study focuses on enhancing the performance of the Data Assimilation System for the Southern Ocean (DASSO) in assimilating SIC through optimizing the localization and observation error estimate, and two assimilation experiments were conducted from 1979 to 2018. By comparing the results with the sea ice extent of the Southern Ocean and the sea ice thickness in the Weddell Sea, it becomes evident that the experiment with optimizations outperforms that without optimizations due to achieving more reasonable error estimates. Investigating uncertainties of the SIV anomaly modeling reveals the nonnegligible role played by the sea ice-ocean interaction during the SIC assimilation, implying the necessity of assimilating more oceanic and sea-ice observations.

The Southern Ocean (SO) is the worlds largest high nutrient low chlorophyll region and has a plentiful supply of underutilised macronutrients due to light and iron limitation. These macronutrients supply the rest of the neighboring ocean basins, and are hugely important for global productivity and ocean carbon sequestration. Vertical mixing rates in the SO are known to vary by an order of magnitude temporally and spatially, however there is great uncertainty in the parameterization of this mixing, including in the specification of a background mixing value in coarse resolutation Earth System Models. Using a biogeochemical-ocean model we show that SO biomass is highly sensitive to altering the background diapycnal mixing over short timescales. Increasing mixing enhances biomass by altering key biogeochemical and physical parameters. An increased surface supply of iron is responsible for biomass increases in most areas, demonstrating the importance of year round diapycnal fluxes of iron to SO surface waters. These changes to SO biomass could potentially alter atmospheric CO2 concentration over longer timescales, demonstrating the importance of accurate representation of diapycnal mixing in climate models.

We investigate the impact of ocean data assimilation using the Ensemble Adjustment Kalman Filter (EAKF) from the Data Assimilation Research Testbed (DART) on the oceanic and atmospheric states of the Red Sea. Our study extends the ocean data assimilation experiment performed by Sanikommu et al. (2020) by utilizing the SKRIPS model coupling the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. Using a 50-member ensemble, we assimilate satellite-derived sea surface temperature and height and in-situ temperature and salinity profiles every three days for one year, starting January 01 2011. Atmospheric data are not assimilated in the experiments. To improve the ensemble realism, perturbations are added to the WRF model using several physics options and the stochastic kinetic energy backscatter (SKEB) scheme. Compared with the control experiments using uncoupled MITgcm with ECMWF ensemble forcing, the EAKF ensemble mean oceanic states from the coupled model are better or insignificantly worse (root-mean-square-errors are 30% to -2% smaller), especially when the atmospheric model uncertainties are accounted for with stochastic perturbations. We hypothesize that the ensemble spreads of the air–sea fluxes are better represented in the downscaled WRF ensembles when uncertainties are well accounted for, leading to improved representation of the ensemble oceanic states in EAKF. Although the feedback from ocean to atmosphere is included in this two-way regional coupled configuration, we find no significant effect of ocean data assimilation on the latent heat flux and 10-m wind speed, suggesting the improved skill is from downscaling the ensemble atmospheric forcings.

The Amundsen Sea in West Antarctica features rapidly thinning ice shelves and large, seasonally recurring polynyas. Within these polynyas, sizable spring phytoplankton blooms occur. Although considerable effort has gone into characterising heat fluxes between the Amundsen Sea, its associated ice shelves, and the overlying atmosphere, the effect of the phytoplankton blooms on the distribution of heat remains poorly understood. In this modelling study, we implement a feedback from biogeochemistry onto physics into MITgcm-BLING and use it to show, for the first time, that high levels of chlorophyll – concentrated in the Amundsen Sea Polynya and the Pine Island Polynya – accelerate springtime surface warming in polynyas through enhanced absorption of solar radiation. The warm midsummer anomaly (on average between +0.2°C and +0.3C°) at the surface is quickly dissipated to the atmosphere, by small increases in latent and longwave heat loss as well as a substantial (17.5%) increase in sensible heat loss from open water areas. The summertime warm anomaly also reduces the summertime sea ice volume, and stimulates enhanced seasonal melting near the fronts of ice shelves. However larger effects derive from the accompanying cold anomaly, caused by shading of deeper waters, which persists throughout the year and affects a decrease in the volume of Circumpolar Deep Water on the continental shelf. This cooling ultimately leads to an increase in wintertime sea ice volume, and reduces basal melting of Amundsen Sea ice shelves by approximately 7% relative to the model scenario with no phytoplankton bloom.

The Red Sea is an extremely warm tropical sea that hosts diverse ecosystems; thus, it is important to understand its ecology in the context of global warming. Using a coupled physical–biogeochemical model validated against in situ data, we provide the first report on the diel cycle (i.e., diel variability) in the Red Sea chlorophyll (CHL) concentration, revealing near-sunset CHL maxima at 17h ± 1h local time over the entire basin. This CHL peak time is considerably later than those reported in most other oceans, suggesting low grazing rates in this high-irradiance tropical sea. Model-based analyses reveal that CHL diel cycle is predominantly controlled by irradiance, whereas longer-timescale (e.g., seasonal) CHL variability is regulated by nutrient availability, suggesting a light-limited biological production at diel timescale. The identified CHL diel cycle comprises a fundamental component of the Red Sea ecology and has implications for CHL remote sensing and in situ measurements.

Mixing parameters can be inaccurate in ocean data assimilation systems, even if there is close agreement between observations and mixing parameters in the same modeling system when data are not assimilated. To address this, we investigate whether there are additional observations that can be assimilated by ocean modeling systems to improve their representation of mixing parameters and thereby gain knowledge of the global ocean’s mixing parameters. Observationally-derived diapycnal diffusivities–using a strain-based parameterization of finescale hydrographic structure–are included in the Estimating the Circulation & Climate of the Ocean (ECCO) framework and the GEOS-5 coupled Earth system model to test if adding observational diffusivities can reduce model biases. We find that adjusting ECCO-estimated and GEOS-5-calculated diapycnal diffusivity profiles toward profiles derived from Argo floats using the finescale parameterization improves agreement with independent diapycnal diffusivity profiles inferred from microstructure data. Additionally, for the GEOS-5 hindcast, agreement with observed mixed layer depths and temperature/salinity/stratification (i.e., hydrographic) fields improves. Dynamic adjustments arise when we make this substitution in GEOS-5, causing the model’s hydrographic changes. Adjoint model-based sensitivity analyses suggest that the assimilation of dissolved oxygen concentrations in future ECCO assimilation efforts would improve estimates of the diapycnal diffusivity field. Observationally-derived products for horizontal mixing need to be validated before conclusions can be drawn about them through similar analyses.

Waves generated by tropical cyclones can have devastating effects on coastal regions. However, the role of ocean currents in modifying wave amplitudes, wavelengths, and directions is commonly overlooked in wave forecasts, despite the fact that these interactions can lead to extreme wave conditions. Here, we use satellite observations and wave modeling to quantify the effects of ocean currents on the surface waves generated during a tropical cyclone event in the Arabian Sea. As a case study, this paper documents beams of wave heights originating from the eyewall of a tropical cyclone caused by current-induced refraction. Alternating regions of high and low wave heights in the model simulations are consistent with observations and extend for thousands of kilometers all the way to 100 m isobath. Our results highlight the importance of accounting for wave refraction by currents in order to accurately predict the impact of tropical cyclone generated waves on coastal regions.

Strong winds in Southern Ocean storms drive air-sea carbon and heat fluxes. These fluxes are integral to the global climate system and the wind speeds that drive them are increasing. The current scatterometer constellation measuring vector winds remotely undersamples these storms and the higher winds within them, leading to potentially large biases in Southern Ocean wind reanalyses and the fluxes that derive from them. This observing system design study addresses these issues in two ways. First, we describe an addition to the scatterometer constellation, called Southern Ocean Storms -- Zephyr, to increase the frequency of independent observations, better constraining high winds. Second, we show that potential reanalysis wind biases over the Southern Ocean lead to uncertainty over the sign of the net winter carbon flux. More frequent independent observations per day will capture these higher winds and reduce the uncertainty in estimates of the global carbon and heat budgets.

The Southern Ocean (SO) is the worlds largest high nutrient low chlorophyll region, and has a plentiful supply of underutilised macronutrients due to light and iron limitation. These macronutrients supply the rest of the neighboring ocean basins, and are hugely important for global productivity and ocean carbon sequestration. Vertical mixing rates in the SO are known to vary by an order of magnitude temporally and spatially, however there is great uncertainty in the parameterization of this mixing, including in the specification of a background value in coarse resolutation Earth System Models. Using a biogeochemical-ocean model we show that SO biomass is highly sensitive to altering the background diapycnal mixing over short timescales. Increasing mixing enhances biomass by altering key biogeochemical and physical parameters. An increased surface supply of iron is responsible for biomass increases in most areas, demonstrating the importance of year round diapycnal fluxes of iron to SO surface waters. These changes to SO biomass could potentially alter atmospheric CO2 concentration over longer timescales, alluding to the importance of accurate representation diapycnal mixing in climate models.