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EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led and NSF co-funded field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite information and state of the art technology.
Abstract Extreme El Niño events have outsized global impacts and control the El Niño Southern Oscillation (ENSO) warm/cold phases asymmetries. Yet, a consensus regarding the relative contributions of atmospheric and oceanic nonlinearities to their genesis remains elusive. Here, we isolate the contribution of oceanic nonlinearities by conducting paired experiments forced with opposite wind stress anomalies in an oceanic general circulation model, which realistically simulates extreme El Niño events and oceanic nonlinearities thought to contribute to ENSO skewness (Tropical Instability Waves (TIWs), Nonlinear Dynamical Heating (NDH)). Our findings indicate a weak contribution of oceanic nonlinearities to extreme El Niño events in the eastern Pacific, owing to compensatory effects between lateral (NDH and TIWs) and vertical processes. These results hold across different vertical mixing schemes and modifications of the upper‐ocean heat budget mixed layer criterion. Our study reinforces previous research underscoring the pivotal role of atmospheric nonlinearities in shaping extreme El Niño events.
Patterns of sea surface temperature (SST) variability over the northern oceans arise from a combination of atmospheric, oceanic, and coupled processes. In this work, we use a novel methodology and a suite of observations to quantify the processes contributing to the dominant patterns of interannual SST variability over these regions. We decompose the upper ocean heat content tendency associated with such dominant patterns into contributions from different heat fluxes: (a) atmospherically driven, (b) surface feedbacks, and (c) oceanic. We find that in the subtropics, cloud radiative flux, turbulent heat flux, and residual oceanic processes each contributes substantially to North Pacific SST variability, whereas turbulent heat flux primarily induces North Atlantic SST variability. Cloud radiative fluxes therefore provide a major source of interannual SST variability in the North Pacific but not in the North Atlantic. In midlatitudes, SST fluctuations over the northern oceans are driven by the combination of turbulent and oceanic heat fluxes.
A deterministic numerical model of the coupled evolution of the tropical ocean and atmosphere was used to forecast all El Nino/Southern Oscillation (ENSO) events from 1970 to 1986. More particularly, the model, originally developed for studying large-scale ocean-atmosphere interactions in the tropics, successfully predicted the characteristics of the spatial and temporal structure of ENSO observed in the study interval. The model indicated that rainfall moving eastward over the Pacific slackens the surface winds that would otherwise cool the eastern Pacific by drawing up cooler subsurface waters. The oceanic thermocline increases, a poleward flow of westerly flowing warn waters deplets the equatorial warm water reservoir, and sea surface temperatures decline. These ENSO conditions are statistically tractable with the model several months in advance, provided upper ocean layer thermal data are available.
As part of the verification phase of the TOPEX/POSEIDON mission, 10-day gridded fields of altimeter data derived from TOPEX geophysical data records are compared with 10-day gridded fields of dynamic height derived from more than 60 moorings of the Tropical Ocean and Global Atmosphere-Tropical Atmosphere Ocean (TOGA-TAO) array in the equatorial Pacific Ocean. Access to TAO data in real time permits the first 500 days of the TOPEX/POSEIDON mission to be placed in the context of complementary, in-situ measurements of surface winds, sea surface temperatures, and upper ocean thermal structure, as well as the time history of these variables prior to launch. Analysis of the space-time structure in the TOPEX and TAO surface topography data increases sea level variability primarily due to equatorial Kelvin wave activity generated by intense wind bursts west of the date line in association with the 1991-1993 El Nino. Cross correlations between the two data sets are generally greater than 0.7, with root mean square (RMS) differences less than 4 cm. However, for reasons not fully understood, correlations drop to less than 0.5 in certain regions off the equator in the eastern Pacific and RMS differences can be greater than 5 cm north of the equator in the central and eastern Pacific.
This study models formation of ice bands in the marginal ice zones. A one-dimensional coupled ice-ocean model is used in which the ice model is coupled to a reduced gravity ocean model through interfacial stresses. The internal ice stresses are important only at high ice concentrations (90-100 percent); otherwise, the main balance for the ice motion is between the air-ice stress and the ice-water stress, i.e., free drift. The drag coefficients were chosen so that the air-ice momentum flux is 3 times greater than the air-ocean momentum flux. Thus the Ekman transport is larger under the ice than in the open water, so that winds parallel to the ice edge, with the ice on the right, produce upwelling. The upwelling simulation was extended to include temporally varying forcing, which was chosen to vary sinusoidally with a 4-day period. This forcing resembles successive cyclone passings perpendicular to the ice edge. When the oceanic upper layer was thin, which means that the dynamics are strongly nonlinear, the ice bands were formed. The up/downwelling signals do not disappear in wind reversals because of nonlinear advection. This leads to convergences and divergences in oceanic and ice velocities that manifest themselves as ice banding. At least one wind reversal is needed to produce one ice band.
Ocean color satellite missions, like the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) or the Moderate Resolution Imaging Spectroradiometer (MODIS) projects, are tasked with acquiring a global ocean color data set, validating and monitoring the accuracy and quality of the data, processing the radiometric data into geophysical units using a set of atmospheric and bio-optical algorithms, and distributing the final products to the scientific community. The long-standing requirement of the SeaWiFS Project, for example, is to produce spectral water-leaving radiances, LW(lambda), to within 5% absolute (lambda denotes wavelength) and chlorophyll a concentrations to within 35% (Hooker and Esaias 1993), and most ocean color sensors have the same or similar requirements. Although a diverse set of activities are required to ensure the accuracy requirements are met (Hooker and McClain 2000), the perspective here is with field observations. The accurate determination of upper ocean apparent optical properties (AOPs) is essential for the vicarious calibration of ocean color data and the validation of the derived data products, because the sea-truth measurements are used to evaluate the satellite observations (Hooker and McClain 2000). The uncertainties with in situ AOP measurements have various sources: a) the sampling procedures used in the field, including the environmental conditions encountered; b) the absolute characterization of the radiometers in the laboratory; c) the conversion of the light signals to geophysical units in a processing scheme, and d) the stability of the radiometers in the harsh environment they are subjected to during transport and use. Assuming ideal environmental conditions, so this aspect can be neglected, the SeaWiFS ground-truth uncertainty budget can only be satisfied if each uncertainty is on the order of 1-2%, or what is generally referred to as 1% radiometry. In recent years, progress has been made in estimating the magnitude of some of these uncertainties and in defining procedures for minimizing them. For the SeaWiFS Project, the first step was to convene a workshop to draft the SeaWiFS Ocean Optics Protocols (hereafter referred to as the Protocols). The Protocols initially adhered to the Joint Global Ocean Flux Study (JGOFS) sampling procedures (JGOFS 1991) and defined the standards for optical measurements to be used in SeaWiFS calibration and validation activities (Mueller and Austin 1992). Over time, the Protocols were revised (Mueller and Austin 1995), and then recurringly updated on essentially an annual basis (Mueller 2000, 2002, and 2003) as part of the Sensor Inter-comparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project. 98
The (Sea-Ice Ocean and Coupled Assimilation) SOCA project focuses on meshing atmospheric and marine data assimilation efforts to create innovative data assimilation systems. One of the main goals ofSOCA is to make use of surface-sensitive radiances to constrain sea-ice and upper ocean fields (e.g., salinity, temperature, sea-ice fraction, sea-ice temperature, etc.). the focus of this research is to build first elements toward an ocean/sea-ice/atmosphere coupled data assimilation capability, with a focus on supporting and developing the assimilation of observations sensitive to multiple sub-domains. We Setup the existing Joint Effort for Data assimilation Integration (JEDI) coupled UFO (CRTM related) for surface sensitive microwave radiances (SST and SSS) focusing on Global Precipitation Measurement (GPM) Imager (GMI) and Soil Moisture Active Passive (SMAP).
The Joint Effort for Data assimilation Integration (JEDI) is a collaborative development led by the Joint Center for Satellite Data Assimilation (JCSDA) in conjunction with NASA, NOAA and the Department of Defense (NAVY and Air Force). The (Sea-Ice Ocean and Coupled Assimilation) SOCA as one of the JCSDA projects, focuses on the application of JEDI to marine data assimilation. One of the goals of SOCA is to make use of surface-sensitive radiances to constrain sea-ice and upper ocean fields (e.g., salinity, temperature, sea-ice fraction, sea-ice temperature, etc.). The first elements toward an ocean/atmosphere coupled data assimilation capability within JEDI, with a focus on supporting and developing the assimilation of radiance observations sensitive to the ocean and atmosphere has been implemented. The direct radiance assimilation of surface sensitive microwave radiances focusing on Global Precipitation Measurement (GPM) Imager (GMI) for the SST Constraint and Soil Moisture Active Passive (SMAP) for the Sea Surface Salinity (SSS) has been the main focus. Also, in UFO the capability to calculate the cool skin layer depth and skin temperature has been implemented similar to the GEOS-5. It has been tested with GMI sea surface temperature retrievals. This is important because Satellite and in-situ observations of the Sea-Surface Temperature (SST) show high variability, including a diurnal cycle and very thin, cool skin layer in contact with the atmosphere, and Incorporating a realistic skin SST is essential for atmosphere-ocean coupled data assimilation.
A reduced gravity primitive equation modeling and assimilation system is used to study the evolution of the tropical Pacific during the 1997/1998 ENSO cycle. The modeling/assimilation scheme ingests satellite altimeter data and TAO temperature profiles and uses SSM/I satellite derived winds as surface boundary forcing. The four-dimensional structure of the upper ocean circulation structure will be compared against available in situ observations across the Pacific basin. In particular, variability near the Galapagos Islands will be highlighted during the spring of 1998 when phytoplankton concentrations were observed to increase a hundred-fold over a two week period.
Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.
The effect of ice-ocean albedo feedback (a kind of ice-albedo feedback) on sea-ice decay is demonstrated over the Antarctic sea-ice zone from an analysis of satellite-derived hemispheric sea ice concentration and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. Sea ice concentration in December (time of most active melt) correlates better with the meridional component of the wind-forced ice drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic sea-ice covered ocean. Daily time series of ice , concentration show that the ice concentration anomaly increases toward the time of maximum sea-ice melt. These findings can be explained by the following positive feedback effect: once ice concentration decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in ice concentration by the oceanic heat. Results obtained fi-om a simple ice-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the sea-ice cover in summer.
The Energy Exascale Earth System Model (E3SM) is a state-of-the-science Earth system model (ESM) with the ability to focus horizontal resolution of its multiple components in specific areas. Regionally refined global ESMs are motivated by the need to explicitly resolve, rather than parameterize, relevant physics within the regions of refined resolution, while offering significant computational cost savings relative to the respective cost of configurations with high-resolution (HR) everywhere on the globe. In this paper, we document results from the first Arctic regionally refined E3SM configuration for the ocean and sea-ice components (E3SM-Arctic-OSI), while employing data-based atmosphere, land, and hydrology components. Our aim is an improved representation of the Arctic coupled ocean and sea-ice state, its variability and trends, and the exchanges of mass and property fluxes between the Arctic and the sub-Arctic. We find that E3SM-Arctic-OSI increases the realism of simulated Arctic ocean and sea-ice conditions compared to a similar low-resolution E3SM simulation without the Arctic regional refinement in ocean and sea-ice components (E3SM-LR-OSI). In particular, exchanges through the main Arctic gateways are greatly improved with respect to E3SM-LR-OSI. Other aspects, such as the Arctic freshwater content variability and sea-ice trends, are also satisfactorily simulated. Yet, other features, such as the upper-ocean stratification and the sea-ice thickness distribution, need further improvements, involving either more advanced parameterizations, model tuning, or additional grid refinements. Overall, E3SM-Arctic-OSI offers an improved representation of the Arctic system relative to E3SM-LR-OSI, at a fraction (15 %) of the computational cost of comparable global high-resolution configurations, while permitting exchanges with the lower-latitude oceans that cannot be directly accounted for in Arctic regional models.
Open-ocean polynyas formed over the Maud Rise, in the Weddell Sea, during the winters of 2016–2017. Such polynyas are rare events in the Southern Ocean and are associated with deep convection, affecting regional carbon and heat budgets. Using an ocean state estimate, we found that during 2017, early sea ice melting occurred in response to enhanced vertical mixing of heat, which was accompanied by mixing of salt. The melting sea ice compensated for the vertically mixed salt, resulting in a net buoyancy gain. An additional salt input was then necessary to destabilize the upper ocean. This came from a hitherto unexplored polynya-formation mechanism: an Ekman transport of salt across a jet girdling the northern flank of the Maud Rise. Such transport was driven by intensified eastward surface stresses during 2015–2018. Our results illustrate how highly localized interactions between wind, ocean flow and topography can trigger polynya formation in the open Southern Ocean.
Fluids generated from subducted slabs participate in the cycling of deep carbon in the crust and upper mantle. In these fluids, aqueous carbon species vary in oxidation state between +IV and -IV depending on whether the fluids are oxidizing or reducing, respectively. Most studies of subduction-zone fluids have focused on oxidized carbon species. However, recent studies of natural samples have demonstrated the occurrence of deep, reducing fluids, generated in both subducted oceanic upper mantle and crustal rocks. CH 4 -H 2 -rich fluid inclusions in subducted carbonated serpentinites have demonstrated the existence of abiotic, immiscible, hydrocarbon fluids at upper mantle conditions. To investigate the formation of such immiscible hydrocarbon fluids during the evolution of subducted carbonated serpentinites, we used equilibrium constants from the Deep Earth Water model to carry out predictive chemical mass transfer modeling to simulate the alteration reactions. A novel feature of the models was the inclusion of an immiscible hydrocarbon fluid containing six components (CH 4,f , C 2 H 6,f , C 3 H 8,f , isoC 4 H 10,f , CO 2,f , H 2,f ). This feature enabled prediction of the formation of a separate immiscible fluid in equilibrium with aqueous species and minerals. We developed a predictive reaction path model of invasive H 2,f reacting with carbonated serpentinites and interstitial aqueous fluids for comparison with the natural samples from the Lanzo Massif, western Italian Alps. Over a range of temperatures and pressures, immiscible hydrocarbon fluids formed in association with altered mineral assemblages. Reaction progress caused the transformation of carbonated serpentinites and the formation of clinopyroxene, brucite, graphite, and hydrocarbon fluids, along with changes of pH, logfO 2 , and aqueous species. CH 4,f was the most abundant hydrocarbon species in all the models. The overall results at 2.0 GPa and 400 to 450 °C were consistent with the natural samples from the Lanzo Massif. Interestingly, large amounts of H 2 O formed due to oxidation of H 2 . More hydrocarbons and H 2 O formed in models with lower fluid/rock mass ratios or with more reactant H 2 . Models at different pressure and temperature conditions showed similar results with some variation in the relative stabilities of aragonite, graphite and olivine solid solution, and associated differences in mineral sequences, hydrocarbon fluids, values of aqueous species, and the final log fO 2 and pH. As a result, our models strongly support the laboratory and field evidence that reduction of carbonated serpentinites by infiltrating H 2 fluids can cause the formation of immiscible, abiotic hydrocarbon fluids in subduction zones.
Abstract Changes in ocean heat content (OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum. According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ (1 Zetta Joules = 10 21 Joules); and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins (the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier—fresh gets fresher” pattern, also reached its highest level on record in 2022, implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Niña event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.
Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper-ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.
Model results indicate that understanding summer heat balance and freshwater balance in the polar oceans requires knowledge of how much goes into vertical and lateral sea ice melt. In addition to thickness, two of the key ice parameters that affect melt rate are ice concentration and floe size. Smaller ice floes and more open water enables more heat to go into lateral melt preferentially to vertical melt, thereby enhancing warming up the upper ocean and increasing stratification. Using ERS-1 SAR imagery along two areas, one in the Beaufort Sea and another in the Chukchi Sea, floe size distributions were obtained during the summer period in 1992. Comparisons will be made of floe distributions, together with meteorological and buoy measurements, to examine the differences between an ice sink region (Chukchi) and a multiyear ice region (Beaufort) in the summer melt process.