Uncertainties in eddy covariance air–sea CO<sub>2</sub> flux measurements and implications for gas transfer velocity parameterisations

Air–sea carbon dioxide (CO2) flux is often indi�rectly estimated by the bulk method using the air–sea difference in CO2 fugacity (1f CO2) and a parameterisation of the gas transfer velocity (K). Direct flux measurements by eddy covariance (EC) provide an independent reference for bulk flux estimates and are often used to study processes that drive K. However, inherent uncertainties in EC air–sea CO2 flux measurements from ships have not been well quantified and may confound analyses of K. This paper evaluates the uncertainties in EC CO2 fluxes from four cruises. Fluxes were measured with two state-of-the-art closed-path CO2 analysers on two ships. The mean bias in the EC CO2 flux is low, but the random error is relatively large over short timescales. The uncertainty (1 standard deviation) in hourly averaged EC air–sea CO2 fluxes (cruise mean) ranges from 1.4 to 3.2 mmolm−2 d−1. This corresponds to a relative uncertainty of ∼ 20 % during two Arctic cruises that observed large CO2 flux magnitude. The relative uncertainty was greater (∼ 50 %) when the CO2 flux magnitude was small during two Atlantic cruises. Random uncertainty in the EC CO2 flux is mostly caused by sampling error. Instrument noise is relatively unimportant. Random uncertainty in EC CO2 fluxes can be reduced by averaging for longer. However, averaging for too long will result in the inclusion of more natural variability. Auto-covariance analysis of CO2 fluxes suggests that the optimal timescale for averaging EC CO2 flux measurements ranges from 1 to 3 h, which increases the mean signal-to-noise ratio of the four cruises to higher than 3. Applying an appropriate averaging timescale and suitable 1f CO2 threshold (20 µatm) to EC flux data enables an optimal analysis of K

A novel membrane inlet-infrared gas analysis (MI-IRGA) system for monitoring of seawater carbonate system

Increased atmospheric CO 2 concentrations are driving changes in ocean chemistry at unprecedented rates resulting in ocean acidification, which is predicted to impact the functioning of marine biota, in particular of marine calcifiers. However, the precise understanding of such impacts relies on an analytical system that determines the mechanisms and impact of elevated pCO 2 on the physiology of organisms at scales from species to entire communities. Recent work has highlighted the need within experiments to control all aspects of the carbonate system to resolve the role of different inorganic carbon species on the physiological responses observed across taxa in real-time. Presently however, there are limited options available for continuous quantification of physiological responses, coupled with real-time calculation of the seawater carbonate chemistry system within microcosm environments. Here, we describe and characterise the performance of a novel pCO 2 membrane equilibrium system (the Membrane Inlet Infra-Red Gas Analyser, MI-IRGA) integrated with a continuous pH and oxygen monitoring platform. The system can detect changes in the seawater carbonate chemistry and determine organism physiological responses, while providing the user with real-time control over the microcosm system. We evaluate the systems control, response time and associated error, and demonstrate the flexibility of the system to operate under field conditions and within a laboratory. We use the system to measure physiological parameters (photosynthesis and respiration) for the corals Pocillipora damicornis and Porites cylindrica; in doing so we present a novel dataset examining the interactive role of temperature, light and pCO 2 on the physiology of P. cylindrica

Automated Analysis of Cryptococcal Macrophage Parasitism Using GFP-Tagged Cryptococci

The human fungal pathogens Cryptococcus neoformans and C. gattii cause life-threatening infections of the central nervous system. One of the major characteristics of cryptococcal disease is the ability of the pathogen to parasitise upon phagocytic immune effector cells, a phenomenon that correlates strongly with virulence in rodent models of infection. Despite the importance of phagocyte/Cryptococcus interactions to disease progression, current methods for assaying virulence in the acrophage system are both time consuming and low throughput. Here, we introduce the first stable and fully characterised GFP–expressing derivatives of two widely used cryptococcal strains: C. neoformans serotype A type strain H99 and C. gattii serotype B type strain R265. Both strains show unaltered responses to environmental and host stress conditions and no deficiency in virulence in the macrophage model system. In addition, we report the development of a method to effectively and rapidly investigate macrophage parasitism by flow cytometry, a technique that preserves the accuracy of current approaches but offers a four-fold improvement in speed

Near‐Surface Stratification Due to Ice Melt Biases Arctic Air‐Sea CO 2 Flux Estimates

Air-sea carbon dioxide (CO2) flux is generally estimated by the bulk method using upper ocean CO2 fugacity measurements. In the summertime Arctic, sea-ice melt results in stratification within the upper ocean (top ∼10 m), which can bias bulk CO2 flux estimates when the seawater CO2 fugacity is taken from a ship's seawater inlet at ∼6 m depth (fCO2w_bulk). Direct flux measurements by eddy covariance are unaffected by near-surface stratification. We use eddy covariance CO2 flux measurements to infer sea surface CO2 fugacity (fCO2w_surface) in the Arctic Ocean. In sea-ice melt regions, fCO2w_surface values are consistently lower than fCO2w_bulk by an average of 39 μatm. Lower fCO2w_surface can be partially accounted for by fresher (≥27%) and colder (17%) melt waters. A back-of-the-envelope calculation shows that neglecting the summertime sea-ice melt could lead to a 6%–17% underestimate of the annual Arctic Ocean CO2 uptake

Building ensembles of adaptive nested dichotomies with random-pair selection

A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems. Such a system recursively applies binary splits to divide the set of classes into two subsets, and trains a binary classifier for each split. Although ensembles of nested dichotomies with random structure have been shown to perform well in practice, using a more sophisticated class subset selection method can be used to improve classification accuracy. We investigate an approach to this problem called random-pair selection, and evaluate its effectiveness compared to other published methods of subset selection. We show that our method outperforms other methods in many cases when forming ensembles of nested dichotomies, and is at least on par in all other cases. The software related to this paper is available at https://svn.cms.waikato.ac.nz/svn/weka/trunk/packages/ internal/ensemblesOfNestedDichotomies/

Higgs production as a probe of anomalous top couplings

The LHC may be currently seeing the first hints of the Higgs boson. The dominant production mode for the Higgs at the LHC involves a top-quark loop. An accurate measurement of Higgs production cross-sections and decay widths can thus be used to obtain limits on anomalous top couplings. We find that such an exercise could potentially yield constraints that are stronger than those derived from low-energy observables as well as direct bounds expected from the top pair-production process.Comment: Version published in JHE

Measurements of the transverse-momentum-dependent cross sections of J /ψ production at mid-rapidity in proton+proton collisions at s =510 and 500 GeV with the STAR detector

We present measurements of the differential cross sections of inclusive J/ψ meson production as a function of transverse momentum (pTJ/ψ) using the μ+μ- and e+e- decay channels in proton+proton collisions at center-of-mass energies of 510 and 500 GeV, respectively, recorded by the STAR detector at the Relativistic Heavy Ion Collider. The measurement from the μ+μ- channel is for

Bulk properties of the system formed in Au+Au collisions at sNN =14.5 GeV at the BNL STAR detector

We report systematic measurements of bulk properties of the system created in Au+Au collisions at sNN=14.5 GeV recorded by the STAR detector at the Relativistic Heavy Ion Collider (RHIC). The transverse momentum spectra of π±, K±, and p(p) are studied at midrapidity (|y|<0.1) for nine centrality intervals. The centrality, transverse momentum (pT), and pseudorapidity (η) dependence of inclusive charged particle elliptic flow (v2), and rapidity-odd charged particles directed flow (v1) results near midrapidity are also presented. These measurements are compared with the published results from Au+Au collisions at other energies, and from Pb+Pb collisions at sNN=2.76 TeV. The results at sNN=14.5 GeV show similar behavior as established at other energies and fit well in the energy dependence trend. These results are important as the 14.5-GeV energy fills the gap in μB, which is of the order of 100 MeV, between sNN=11.5 and 19.6 GeV. Comparisons of the data with UrQMD and AMPT models show poor agreement in general

Measurement of inclusive J/ψ suppression in Au+Au collisions at sNN=200 GeV through the dimuon channel at STAR

J/ψ suppression has long been considered a sensitive signature of the formation of the Quark-Gluon Plasma (QGP) in relativistic heavy-ion collisions. In this letter, we present the first measurement of inclusive J/ψ production at mid-rapidity through the dimuon decay channel in Au+Au collisions at sNN=200 GeV with the STAR experiment. These measurements became possible after the installation of the Muon Telescope Detector was completed in 2014. The J/ψ yields are measured in a wide transverse momentum (pT) range of 0.15 GeV/c to 12 GeV/c from central to peripheral collisions. They extend the kinematic reach of previous measurements at RHIC with improved precision. In the 0-10% most central collisions, the J/ψ yield is suppressed by a factor of approximately 3 for pT>5 GeV/c relative to that in p+p collisions scaled by the number of binary nucleon-nucleon collisions. The J/ψ nuclear modification factor displays little dependence on pT in all centrality bins. Model calculations can qualitatively describe the data, providing further evidence for the color-screening effect experienced by J/ψ mesons in the QGP