Assessing the fidelity of shallow-water carbonates as records of the Ni isotope composition of surface seawater
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A study of applying laser Raman spectroscopy to remote sensing of the sulfate ion in sea water is in progress. The SO4 Raman spectrum has been obtained from true sea water samples in the laboratory using a CW laser Raman spectrometric system. Radiometric calculations indicate the feasibility of obtaining usable SO4 Raman signals in a field experiment. One of serious difficulties expected in the field experiment would be from fluorescence of phytoplankton and organics.
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A depth profile of the concentration of Re was measured in the Pacific Ocean using a technique developed for the clean chemical separation and the precise measurement of Re by isotope dilution and negative thermal ionization mass spectrometry (ID-NTIMS). We obtain a narrow range for Re from 7.20 +/- 0.03 to 7.38 +/- 0.03 ng/kg for depths between 45 m and 4700 m. This demonstrates that Re is relatively well mixed throughout the water column and confirms the theoretical prediction that the behavior of Re in the oceans is conservative. When examined in detail, both salinity and the concentration of Re increase by approximately 1.5 percent between 400 and 4700 m, a correlation consistent with conservative behavior. However, Re appears to be depleted relative to salinity by 1.0-1.5 percent at 100 m, and enriched by approximately 4 percent at the surface. These observations suggest a minor level of Re scavenging in near surface waters, and an input of Re to the ocean surface. This work demonstrates the utility of geochemical investigations of certain trace elements not previously been amenable to detailed study.
We performed multispectral in-situ fluorescence measurement of colored dissolved organic matter and chlorophyll in surface water of the West Florida Shelf using West Labs Spectral absorption and Fluorescence Instrument (SAFIre). Continuous measurements underway allowed us to simultaneously map the dispersion of riverine organic material and chlorophyll on the shelf. By using two fluorescence emission ratios we were able to differentiate between riverine and marine CDOM. Our data also showed unusually high concentrations of CDOM offshore. These were attributed to an intrusion of the Mississippi River Plume. We performed limited comparisons between in-situ chlorophyll concentrations measured with SAFIre and chlorophyll values obtained from SeaWiFS satellite data using OC4 and MODIS algorithm. Our results show that, although both algorithms overestimated chlorophyll, MODIS performed better than OC4, particularly in areas with high CDOM concentrations. Analysis of the relationship between chlorophyll and CDOM concentrations within the study area showed regional variability causes by differences in river source.
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 accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant (ε). Two new ε parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements and on the other hand on new laboratory measurements. These two approaches are fully independent. These new ε parametrizations are compared with each other and with the ε models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. The two new ε parametrizations are found to be in closer agreement than with earlier parametrizations for most common ocean conditions. We will further study to which extent the recent SMOS CCI+SSS v3 reprocessing confirms the above results and could help resolve remaining inconsistencies.
The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant. Two new parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements [1] (BV) and on the other hand on new laboratory measurements [3] (GW2020). These two approaches are fully independent. The brightness temperatures, Tb, simulated with the BV and GW2020 parametrizations are compared with each other and with the ones derived from dielectric constant models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Tb simulated with the BV and GW2020 parametrizations agree particularly well for most SSS and SST commonly observed over the open ocean and are found to be in closer agreement than with earlier parametrizations. Nevertheless, uncertainty remains at low SST where a ∼ 0.1 K relative difference between the two models is observed. A complete reprocessing of SMOS SSS (2010–2020) has been performed using the BV parametrization instead of the Klein and Swift (1977) model previously used in SMOS processing. When compared with Argo derived near surface salinity maps, clear improvements are observed in warm and cold regions. Remaining uncertainties in cold waters will be discussed relatively to the uncertainties in SMOS Tb linked to sea ice contamination and given the constraints given by the GW2020 laboratory measurements.
The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the reliability of the dielectric constant model. Two new parametrizations were recently developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements by Boutin et al. (2021) (BV), and on the other hand, on new George Washington University laboratory measurements by Zhou et al. (2021) (GW2020). These two approaches are fully independent. For most SSS and Sea Surface Temperature (SST) conditions commonly observed over the open ocean, the relative variations of brightness temperatures Tb simulated through the BV and GW2020 parametrizations agree particularly well, and better than with earlier parametrizations previously used in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. Nevertheless, uncertainty remains, especially below 10 °C where a ∼ 0.1 K relative difference between the two models is observed. This motivates the development of a revised parameterization, BVZ, based on a methodology similar to that used to derive BV but using GW2020 instead of SMOS measurements. Compared to the GW2020 parameterization, BVZ is derived with a reduced number of degrees of freedom, it relies on the TEOS10 PSS78 conductivity-salinity relationship, and on the previously derived static permittivity of fresh water. One month per season of SMOS data have been reprocessed in 2018 using BV, GW2020, and BVZ. We find the best overall agreement between SMOS SSS and Argo SSS with BVZ parametrization, with noticeable improvement in the 5 °C–15 °C SST range.
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Active metal and active metal intercalation electrode structures and battery cells having ionically conductive protective architecture including an active metal (e.g., lithium) conductive impervious layer separated from the electrode (anode) by a porous separator impregnated with a non-aqueous electrolyte (anolyte). This protective architecture prevents the active metal from deleterious reaction with the environment on the other (cathode) side of the impervious layer, which may include aqueous or non-aqueous liquid electrolytes (catholytes) and/or a variety electrochemically active materials, including liquid, solid and gaseous oxidizers. Safety additives and designs that facilitate manufacture are also provided.