347 research outputs found

    Accuracy of wind observations from open-ocean buoys: Correction for flow distortion

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    The comparison of equivalent neutral winds obtained from (a) four WHOI buoys in the subtropics and (b) scatterometer estimates at those locations reveals a root-mean-square (RMS) difference of 0.56-0.76 m/s. To investigate this RMS difference, different buoy wind error sources were examined. These buoys are particularly well suited to examine two important sources of buoy wind errors because: (1) redundant anemometers and a comparison with numerical flow simulations allow us to quantitatively assess flow distortion errors, and (2) one-minute sampling at the buoys allows us to examine the sensitivity of buoy temporal sampling/averaging in the buoy-scatterometer comparisons. The inter-anemometer difference varies as a function of wind direction relative to the buoy wind vane and is consistent with the effects of flow distortion expected based on numerical flow simulations. Comparison between the anemometers and scatterometer winds supports the interpretation that the inter-anemometer disagreement, which can be up to 5% of the wind speed, is due to flow distortion. These insights motivate an empirical correction to the individual anemometer records and subsequent comparison with scatterometer estimates show good agreement

    Comparative Genomics of Leuconostoc carnosum

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    Leuconostoc carnosum is a known colonizer of meat-related food matrices. It reaches remarkably high loads during the shelf life in packaged meat products and plays a role in spoilage, although preservative effects have been proposed for some strains. In this study, the draft genomes of 17 strains of L. carnosum (i.e., all the strains that have been sequenced so far) were compared to decipher their metabolic and functional potential and to determine their role in food transformations. Genome comparison and pathway reconstruction indicated that L. carnosum is a compact group of closely related heterofermentative bacteria sharing most of the metabolic features. Adaptation to a nitrogen-rich environment, such as meat, is evidenced by 23 peptidase genes identified in the core genome and by the autotrophy for nitrogen compounds including several amino acids, vitamins, and cofactors. Genes encoding the decarboxylases yielding biogenic amines were not present. All the strains harbored 1–4 of 32 different plasmids, bearing functions associated to proteins hydrolysis, transport of amino acids and oligopeptides, exopolysaccharides, and various resistances (e.g., to environmental stresses, bacteriophages, and heavy metals). Functions associated to bacteriocin synthesis, secretion, and immunity were also found in plasmids. While genes for lactococcin were found in most plasmids, only three harbored the genes for leucocin B, a class IIa antilisterial bacteriocin. Determinants of antibiotic resistances were absent in both plasmids and chromosomes

    Can simple models predict large-scale surface ocean isoprene concentrations?

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    We use isoprene and related field measurements from three different ocean data sets together with remotely sensed satellite data to model global marine isoprene emissions. We show that using monthly mean satellite-derived chl a concentrations to parameterize isoprene with a constant chl a normalized isoprene production rate underpredicts the measured oceanic isoprene concentration by a mean factor of 19 ± 12. Improving the model by using phytoplankton functional type dependent production values and by decreasing the bacterial degradation rate of isoprene in the water column results in only a slight underestimation (factor 1.7 ± 1.2). We calculate global isoprene emissions of 0.21 Tg C for 2014 using this improved model, which is twice the value calculated using the original model. Nonetheless, the sea-to-air fluxes have to be at least 1 order of magnitude higher to account for measured atmospheric isoprene mixing ratios. These findings suggest that there is at least one missing oceanic source of isoprene and, possibly, other unknown factors in the ocean or atmosphere influencing the atmospheric values. The discrepancy between calculated fluxes and atmospheric observations must be reconciled in order to fully understand the importance of marine-derived isoprene as a precursor to remote marine boundary layer particle formation

    Detailed investigation of the role of buoy wind errors in buoyscatterometer disagreement

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    The comparison of equivalent neutral winds obtained from (a) four WHOI buoys in the subtropics and (b) scatterometer estimates at those locations reveals a very low root-mean-square difference (RMS) on the order of 0.5-0.7 m/s and a seasonal cycle in the RMS. To investigate this RMS, different buoy wind error sources were examined. Our buoys are particularly well suited to examine two important sources of buoy error: (1) redundant anemometers and a comparison with numerical flow simulations allow us to quantitatively assess flow distortion errors, and (2) one-minute sampling at the buoys allows us to examine the sensitivity of buoy temporal sampling/averaging in the buoy-scatterometer comparisons. The flow distortion can be estimated to up to 5% of the relative difference of the anemometers. Application of this error to the individual anemometer and subsequent comparison with scatterometer estimates show a good agreement. Application of a reasonable time averaging, subtraction of a mean bias, and application of a viscosity correction generally reduces the RMS but cannot explain the seasonal cycle of it

    Detailed investigation of the role of buoy wind errors in buoyscatterometer disagreement

    Get PDF
    The comparison of equivalent neutral winds obtained from (a) four WHOI buoys in the subtropics and (b) scatterometer estimates at those locations reveals a very low root-mean-square difference (RMS) on the order of 0.5-0.7 m/s and a seasonal cycle in the RMS. To investigate this RMS, different buoy wind error sources were examined. Our buoys are particularly well suited to examine two important sources of buoy error: (1) redundant anemometers and a comparison with numerical flow simulations allow us to quantitatively assess flow distortion errors, and (2) one-minute sampling at the buoys allows us to examine the sensitivity of buoy temporal sampling/averaging in the buoy-scatterometer comparisons. The flow distortion can be estimated to up to 5% of the relative difference of the anemometers. Application of this error to the individual anemometer and subsequent comparison with scatterometer estimates show a good agreement. Application of a reasonable time averaging, subtraction of a mean bias, and application of a viscosity correction generally reduces the RMS but cannot explain the seasonal cycle of it

    Marine isoprene production and consumption in the mixed layer of the surface ocean – A field study over 2 oceanic regions.

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    Parameterizations of surface ocean isoprene concentrations are numerous, despite the lack of source/sink process understanding. Here we present isoprene and related field measurements in the mixed layer from the Indian Ocean and the eastern Pacific Ocean to investigate the production and consumption rates in two contrasting regions, namely oligotrophic open ocean and the coastal upwelling region. Our data show that the ability of different phytoplankton functional types (PFTs) to produce isoprene seems to be mainly influenced by light, ocean temperature, and salinity. Our field measurements also demonstrate that nutrient availability seems to have a direct influence on the isoprene production. With the help of pigment data, we calculate in-field isoprene production rates for different PFTs under varying biogeochemical and physical conditions. Using these new calculated production rates, we demonstrate that an additional significant and variable loss, besides a known chemical loss and a loss due to air–sea gas exchange, is needed to explain the measured isoprene concentration. We hypothesize that this loss, with a lifetime for isoprene between 10 and 100 days depending on the ocean region, is potentially due to degradation or consumption by bacteria
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