We present a spatially and vertically resolved global grid of dissolved barium concentrations ([Ba]) in seawater determined using Gaussian Process Regression machine learning. This model was trained using 4,345 quality-controlled GEOTRACES data from the Arctic, Atlantic, Pacific, and Southern Oceans. Model output was validated by assessing the accuracy of [Ba] simulations in the Indian Ocean, noting that none of the Indian Ocean data were seen by the model during training. We identify a model that can accurate predict [Ba] in the Indian Ocean using seven features: depth, temperature, salinity, as well as dissolved dioxygen, phosphate, nitrate, and silicate concentrations. This model achieves a mean absolute percentage error of 6.0 %, which we assume represents the generalization error. This model was used to simulate [Ba] on a global basis using predictor data from the World Ocean Atlas 2018. The global model of [Ba] is on a 1°x 1° grid with 102 depth levels from 0 to 5,500 m. The dissolved [Ba] output was then used to simulate dissolved Ba* (barium-star), which is the difference between 'observed' and [Ba] predicted from co-located [Si]. Lastly, [Ba] data were combined with temperature, salinity, and pressure data from the World Ocean Atlas to calculate the saturation state of seawater with respect to barite. The model reveals that the volume-weighted mean oceanic [Ba] and and saturation state are 89 nmol/kg and 0.82, respectively. These results imply that the total marine Ba inventory is 122(±7) ×10¹² mol and that the ocean below 1,000 m is at barite equilibrium.
more »
« less
Barium in seawater: dissolved distribution, relationship to silicon, and barite saturation state determined using machine learning
Abstract. Barium is widely used as a proxy for dissolved silicon and particulateorganic carbon fluxes in seawater. However, these proxy applications arelimited by insufficient knowledge of the dissolved distribution of Ba([Ba]). For example, there is significant spatial variability in thebarium–silicon relationship, and ocean chemistry may influence sedimentaryBa preservation. To help address these issues, we developed 4095 models forpredicting [Ba] using Gaussian process regression machine learning. Thesemodels were trained to predict [Ba] from standard oceanographic observationsusing GEOTRACES data from the Arctic, Atlantic, Pacific, and Southernoceans. Trained models were then validated by comparing predictions againstwithheld [Ba] data from the Indian Ocean. We find that a model trained usingdepth, temperature, and salinity, as well as dissolved dioxygen, phosphate,nitrate, and silicate, can accurately predict [Ba] in the Indian Ocean with amean absolute percentage deviation of 6.0 %. We use this model tosimulate [Ba] on a global basis using these same seven predictors in theWorld Ocean Atlas. The resulting [Ba] distribution constrains the Ba budgetof the ocean to 122(±7) × 1012 mol and revealsoceanographically consistent variability in the barium–silicon relationship. We then calculate the saturation state of seawater with respect to barite. This calculation reveals systematic spatial and vertical variations in marine barite saturation and shows that the ocean below 1000 m is at equilibrium with respect tobarite. We describe a number of possible applications for our model outputs, ranging from use in mechanistic biogeochemical models to paleoproxy calibration. Ourapproach demonstrates the utility of machine learning in accurately simulatingthe distributions of tracers in the sea and provides a framework that couldbe extended to other trace elements. Our model, the data used in training and validation, and global outputs are available in Horner and Mete (2023, https://doi.org/10.26008/1912/bco-dmo.885506.2).
more »
« less
- NSF-PAR ID:
- 10462216
- Date Published:
- Journal Name:
- Earth System Science Data
- Volume:
- 15
- Issue:
- 9
- ISSN:
- 1866-3516
- Page Range / eLocation ID:
- 4023 to 4045
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Abstract Processes controlling dissolved barium (dBa) were investigated along the GEOTRACES GA03 North Atlantic and GP16 Eastern Tropical Pacific transects, which traversed similar physical and biogeochemical provinces. Dissolved Ba concentrations are lowest in surface waters (∼35–50 nmol kg−1) and increase to 70–80 and 140–150 nmol kg−1in deep waters of the Atlantic and Pacific transects, respectively. Using water mass mixing models, we estimate conservative mixing that accounts for most of dBa variability in both transects. To examine nonconservative processes, particulate excess Ba (pBaxs) formation and dissolution rates were tracked by normalizing particulate excess230Th activities. Th‐normalized pBaxsfluxes, with barite as the likely phase, have subsurface maxima in the top 1,000 m (∼100–200 μmol m−2 year−1average) in both basins. Barite precipitation depletes dBa within oxygen minimum zones from concentrations predicted by water mass mixing, whereas inputs from continental margins, particle dissolution in the water column, and benthic diffusive flux raise dBa above predications. Average pBaxsburial efficiencies along GA03 and GP16 are ∼37% and 17%–100%, respectively, and do not seem to be predicated on barite saturation indices in the overlying water column. Using published values, we reevaluate the global freshwater dBa river input as 6.6 ± 3.9 Gmol year−1. Estuarine mixing processes may add another 3–13 Gmol year−1. Dissolved Ba inputs from broad shallow continental margins, previously unaccounted for in global marine summaries, are substantial (∼17 Gmol year−1), exceeding terrestrial freshwater inputs. Revising river and shelf dBa inputs may help bring the marine Ba isotope budget more into balance.
-
Marine barite (BaSO4) is a relatively ubiquitous, though minor, component of ocean sediments. Modern studies of the accumulation of barite in ocean sediments have demonstrated a robust correlation between barite accumulation rates and carbon export to the deep ocean. This correlation has been used to develop quantitative relationships between barite accumulation rates and export production and is used to reconstruct export production in the geologic past, particularly during times of dynamic changes in the carbon cycle. We review the processes that affect the formation and preservation of marine barite, as well as those controlling the relationship between the barium (Ba) and carbon biogeochemical cycles. Additionally, we take a new approach to modeling the marine Ba cycle as a two-box model, specifically evaluating Ba utilization in the surface ocean and refining the equation describing the relationship between export production and barite formation. We compare these new results with past modeling efforts. The new model demonstrates that increases in export production can lead to sustained increases in barite accumulation in marine sediments without resulting in complete surface water Ba depletion, which is distinctly different from previous modeling results.more » « less
-
null (Ed.)The West Antarctic Ice Sheet (WAIS) is largely marine based and thus highly sensitive to both climatic and oceanographic changes. Therefore, the WAIS has likely had a very dynamic history over the last several million years. A complete collapse of the WAIS would result in a global sea level rise of 3.3–4.3 m, yet the world’s scientific community is not able to predict its future behavior. Moreover, knowledge about past behavior of the WAIS is poor, in particular during geological times with climatic conditions similar to those expected for the near and distant future. Reconstructions and quantifications of partial or complete WAIS collapses in the past are urgently needed for constraining and testing ice sheet models that aim to predict future WAIS behavior and the potential contribution of the WAIS to global sea level rise. Large uncertainties exist regarding the chronology, extent, rates, and spatial and temporal variability of past advances and retreats of the WAIS across the continental shelves. These uncertainties largely result from the fundamental lack of data from drill cores recovered proximal to the WAIS. The continental shelf and rise of the Amundsen Sea are prime targets for drilling because the records are expected to yield archives of pure WAIS dynamics unaffected by other ice sheets and the WAIS sector draining into the Amundsen Sea Embayment (ASE) currently experiences the largest ice loss in Antarctica (Paolo et al., 2015). We propose a series of drill sites for the ASE shelf where seismic data reveal seaward-dipping sedimentary sequences that span from the preglacial depositional phase to the most recent glacial periods. Our strategy is to drill a transect from the oldest sequences close to the bedrock/basin boundary at the middle–inner shelf transition to the youngest sequences on the outer shelf in the eastern ASE. If the eastern ASE is inaccessible due to sea ice cover, a similar transect of sites can be drilled on the western ASE. The core transect will provide a detailed history of the glacial cycles in the Amundsen Sea region and allow comparison to the glacial history from the Ross Sea sector. In addition, deep-water sites on the continental rise of the Amundsen Sea are selected for recovering continuous records of glacially transported sediments and detailed archives of climatic and oceanographic changes throughout glacial–interglacial cycles. We will apply a broad suite of analytical techniques, including multiproxy analyses, to address our objectives of reconstructing the onset of glaciation in the greenhouse to icehouse transition, processes of dynamic ice sheet behavior during the Neogene and Quaternary, and ocean conditions associated with the glacial cycles. The five principal objectives of Expedition 379 are as follows: 1. To reconstruct the glacial history of West Antarctica from the Paleogene to recent times and the dynamic behavior of the WAIS during the Neogene and Quaternary, especially possible partial or full WAIS collapses, and the WAIS contribution to past sea level changes. Emphasis is placed in particular on studying the response of the WAIS at times when the pCO2 in Earth’s atmosphere exceeded 400 ppm and atmospheric and oceanic temperatures were higher than at present. 2. To correlate the WAIS-proximal records of ice sheet dynamics in the Amundsen Sea with global records of ice volume changes and proxy records for air and seawater temperatures. 3. To study the relationship between incursions of warm Circumpolar Deep Water (CDW) onto the continental shelf of the Amundsen Sea Embayment and the stability of marine-based ice sheet margins under warm water conditions. 4. To reconstruct the processes of major WAIS advances onto the middle and outer shelf that are likely to have occurred since the middle Miocene and compare their timing and processes to those of other Antarctic continental shelves. 5. To identify the timing of the first ice sheet expansion onto the continental shelf of the ASE and its possible relationship to the uplift of Marie Byrd Land.more » « less
-
more » « less
Abstract Early studies revealed relationships between barium (Ba), particulate organic carbon and silicate, suggesting applications for Ba as a paleoproductivity tracer and as a tracer of modern ocean circulation.
But, what controls the distribution of barium (Ba) in the oceans? Here, we investigated the Arctic Ocean Ba cycle through a one‐of‐a‐kind data set containing dissolved (dBa), particulate (pBa), and stable isotope Ba ratio (δ138Ba) data from four Arctic GEOTRACES expeditions conducted in 2015. We hypothesized that margins would be a substantial source of Ba to the Arctic Ocean water column. The dBa, pBa, and δ138Ba distributions all suggest significant modification of inflowing Pacific seawater over the shelves, and the dBa mass balance implies that ∼50% of the dBa inventory (upper 500 m of the Arctic water column) was supplied by nonconservative inputs. Calculated areal dBa fluxes are up to 10 μmol m−2 day−1on the margin, which is comparable to fluxes described in other regions. Applying this approach to dBa data from the 1994 Arctic Ocean Survey yields similar results. The Canadian Arctic Archipelago did not appear to have a similar margin source; rather, the dBa distribution in this section is consistent with mixing of Arctic Ocean‐derived waters and Baffin Bay‐derived waters. Although we lack enough information to identify the specifics of the shelf sediment Ba source, we suspect that a sedimentary remineralization and terrigenous sources (e.g., submarine groundwater discharge or fluvial particles) are contributors.
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/essd-15-4023-2023
