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1. Autonomous seawater <i>p</i>CO₂ and pH time series from 40 surface buoys and the emergence of anthropogenic trends

   https://doi.org/10.5194/essd-11-421-2019  

   Sutton, Adrienne J.; Feely, Richard A.; Maenner-Jones, Stacy; Musielwicz, Sylvia; Osborne, John; Dietrich, Colin; Monacci, Natalie; Cross, Jessica; Bott, Randy; Kozyr, Alex; et al (January 2019, Earth System Science Data)

   Abstract. Ship-based time series, some now approaching over 3 decades long, are critical climate records that have dramatically improved our ability to characterize natural and anthropogenic drivers of ocean carbon dioxide (CO2) uptake and biogeochemical processes. Advancements in autonomous marine carbon sensors and technologies over the last 2 decades have led to the expansion of observations at fixed time series sites, thereby improving the capability of characterizing sub-seasonal variability in the ocean. Here, we present a data product of 40 individual autonomous moored surface ocean pCO2 (partial pressure of CO2) time series established between 2004 and 2013, 17 also include autonomous pH measurements. These time series characterize a wide range of surface ocean carbonate conditions in different oceanic (17 sites), coastal (13 sites), and coral reef (10 sites) regimes. A time of trend emergence (ToE) methodology applied to the time series that exhibit well-constrained daily to interannual variability and an estimate of decadal variability indicates that the length of sustained observations necessary to detect statistically significant anthropogenic trends varies by marine environment. The ToE estimates for seawater pCO2 and pH range from 8 to 15 years at the open ocean sites, 16 to 41 years at the coastal sites, and 9 to 22 years at the coral reef sites. Only two open ocean pCO2 time series, Woods Hole Oceanographic Institution Hawaii Ocean Time-series Station (WHOTS) in the subtropical North Pacific and Stratus in the South Pacific gyre, have been deployed longer than the estimated trend detection time and, for these, deseasoned monthly means show estimated anthropogenic trends of 1.9±0.3 and 1.6±0.3 µatm yr−1, respectively. In the future, it is possible that updates to this product will allow for the estimation of anthropogenic trends at more sites; however, the product currently provides a valuable tool in an accessible format for evaluating climatology and natural variability of surface ocean carbonate chemistry in a variety of regions. Data are available at https://doi.org/10.7289/V5DB8043 and https://www.nodc.noaa.gov/ocads/oceans/Moorings/ndp097.html (Sutton et al., 2018). 

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2. Synthesis Product for Ocean Time Series (SPOTS) – a ship-based biogeochemical pilot

   https://doi.org/10.5194/essd-16-1901-2024  

   Lange, Nico; Fiedler, Björn; Álvarez, Marta; Benoit-Cattin, Alice; Benway, Heather; Buttigieg, Pier Luigi; Coppola, Laurent; Currie, Kim; Flecha, Susana; Gerlach, Dana S; et al (April 2024, Earth System Science Data)

   Abstract. The presented pilot for the Synthesis Product for Ocean Time Series (SPOTS) includes data from 12 fixed ship-based time-series programs. The related stations represent unique open-ocean and coastal marine environments within the Atlantic Ocean, Pacific Ocean, Mediterranean Sea, Nordic Seas, and Caribbean Sea. The focus of the pilot has been placed on biogeochemical essential ocean variables: dissolved oxygen, dissolved inorganic nutrients, inorganic carbon (pH, total alkalinity, dissolved inorganic carbon, and partial pressure of CO2), particulate matter, and dissolved organic carbon. The time series used include a variety of temporal resolutions (monthly, seasonal, or irregular), time ranges (10–36 years), and bottom depths (80–6000 m), with the oldest samples dating back to 1983 and the most recent one corresponding to 2021. Besides having been harmonized into the same format (semantics, ancillary data, units), the data were subjected to a qualitative assessment in which the applied methods were evaluated and categorized. The most recently applied methods of the time-series programs usually follow the recommendations outlined by the Bermuda Time Series Workshop report (Lorenzoni and Benway, 2013), which is used as the main reference for “method recommendations by prevalent initiatives in the field”. However, measurements of dissolved oxygen and pH, in particular, still show room for improvement. Additional data quality descriptors include precision and accuracy estimates, indicators for data variability, and offsets compared to a reference and widely recognized data product for the global ocean: the GLobal Ocean Data Analysis Project (GLODAP). Generally, these descriptors indicate a high level of continuity in measurement quality within time-series programs and a good consistency with the GLODAP data product, even though robust comparisons to the latter are limited. The data are available as (i) a merged comma-separated file that is compliant with the World Ocean Circulation Experiment (WOCE) exchange format and (ii) a format dependent on user queries via the Environmental Research Division's Data Access Program (ERDDAP) server of the Global Ocean Observing System (GOOS). The pilot increases the data utility, findability, accessibility, interoperability, and reusability following the FAIR philosophy, enhancing the readiness of biogeochemical time series. It facilitates a variety of applications that benefit from the collective value of biogeochemical time-series observations and forms the basis for a sustained time-series living data product, SPOTS, complementing relevant products for the global interior ocean carbon data (GLobal Ocean Data Analysis Project), global surface ocean carbon data (Surface Ocean CO2 Atlas; SOCAT), and global interior and surface methane and nitrous oxide data (MarinE MethanE and NiTrous Oxide product). Aside from the actual data compilation, the pilot project produced suggestions for reporting metadata, implementing quality control measures, and making estimations about uncertainty. These recommendations aim to encourage the community to adopt more consistent and uniform practices for analysis and reporting and to update these practices regularly. The detailed recommendations, links to the original time-series programs, the original data, their documentation, and related efforts are available on the SPOTS website. This site also provides access to the data product (DOI: https://doi.org/10.26008/1912/bco-dmo.896862.2, Lange et al., 2024) and ancillary data. 

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3. An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

   https://doi.org/10.3390/s19194285  

   Sathyendranath, Shubha; Brewin, Robert; Brockmann, Carsten; Brotas, Vanda; Calton, Ben; Chuprin, Andrei; Cipollini, Paolo; Couto, André; Dingle, James; Doerffer, Roland; et al (October 2019, Sensors)

   Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel. 

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4. Data-constrained assessment of ocean circulation changes since the middle Miocene in an Earth system model

   https://doi.org/10.5194/cp-17-2223-2021  

   Crichton, Katherine A.; Ridgwell, Andy; Lunt, Daniel J.; Farnsworth, Alex; Pearson, Paul N. (January 2021, Climate of the Past)

   Abstract. Since the middle Miocene (15 Ma, million years ago), the Earth's climate has undergone a long-term cooling trend, characterised by a reduction in ocean temperatures of up to 7–8 ∘C. The causes of this cooling are primarily thought to be due to tectonic plate movements driving changes in large-scale ocean circulation patterns, and hence heat redistribution, in conjunction with a drop in atmospheric greenhouse gas forcing (and attendant ice-sheet growth and feedback). In this study, we assess the potential to constrain the evolving patterns of global ocean circulation and cooling over the last 15 Ma by assimilating a variety of marine sediment proxy data in an Earth system model. We do this by first compiling surface and benthic ocean temperature and benthic carbon-13 (δ13C) data in a series of seven time slices spaced at approximately 2.5 Myr intervals. We then pair this with a corresponding series of tectonic and climate boundary condition reconstructions in the cGENIE (“muffin” release) Earth system model, including alternative possibilities for an open vs. closed Central American Seaway (CAS) from 10 Ma onwards. In the cGENIE model, we explore uncertainty in greenhouse gas forcing and the magnitude of North Pacific to North Atlantic salinity flux adjustment required in the model to create an Atlantic Meridional Overturning Circulation (AMOC) of a specific strength, via a series of 12 (one for each tectonic reconstruction) 2D parameter ensembles. Each ensemble member is then tested against the observed global temperature and benthic δ13C patterns. We identify that a relatively high CO2 equivalent forcing of 1120 ppm is required at 15 Ma in cGENIE to reproduce proxy temperature estimates in the model, noting that this CO2 forcing is dependent on the cGENIE model's climate sensitivity and that it incorporates the effects of all greenhouse gases. We find that reproducing the observed long-term cooling trend requires a progressively declining greenhouse gas forcing in the model. In parallel to this, the strength of the AMOC increases with time despite a reduction in the salinity of the surface North Atlantic over the cooling period, attributable to falling intensity of the hydrological cycle and to lowering polar temperatures, both caused by CO2-driven global cooling. We also find that a closed CAS from 10 Ma to present shows better agreement between benthic δ13C patterns and our particular series of model configurations and data. A final outcome of our analysis is a pronounced ca. 1.5 ‰ decline occurring in atmospheric (and ca. 1 ‰ ocean surface) δ13C that could be used to inform future δ13C-based proxy reconstructions. 

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5. A Lagrangian View of Trace Elements and Isotopes in the North Pacific

   https://doi.org/10.1029/2019JC015862  

   Hayes, Christopher T.; Fitzsimmons, Jessica N.; Jensen, Laramie T.; Lanning, Nathan T.; Hatta, Mariko; McGee, David; Boyle, Edward A. (March 2020, Journal of Geophysical Research: Oceans)

   Abstract Ocean time‐series sites are influenced by both temporal variability, as in situ conditions change, as well as spatial variability, as water masses move across the fixed observation point. To remove the effect of spatial variability, this study made sub‐daily Lagrangian observations of trace elements and isotopes (Al, Sc, Mn, Fe, Co, Ni, Cu, Zn, Cd, Pb,²³²Th, and²³⁰Th) in surface water over a 12‐day period (July–August 2015) in the North Pacific near the Hawaii Ocean Time‐series Station ALOHA. Additionally, a vertical profile in the upper 250 m was analyzed. This dataset is intercalibrated with GEOTRACES standards and provides a consistent baseline for trace element studies in the oligotrophic North Pacific. No diel changes in trace elements could be resolved, although day‐to‐day variations were resolved for some elements (Fe, Cu, and Zn), which may be related to organic matter cycling or ligand availability. Pb concentrations remained relatively constant during 1997–2015, presenting a change from previous decreases. Nutrient to trace element stoichiometric ratios were compared to those observed in phytoplankton as an indication of the extent of biological trace element utilization in this ecosystem, providing a basis for future ecological trace element studies. 

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