Reproducibility comparison among multiangle spectrophotometers

New color-measuring instruments known as multiangle spectrophotometers have been recently created to measure and characterize the goniochromism of special-effect pigments in many materials with a particular visual appearance (metallic, interference, pearlescent, sparkle, or glitter). These devices measure the gonioapparent color from the spectral relative reflectance factor and the L*a*b* values of the sample with different illumination and observation angles. These angles usually coincide with requirements marked in American Society for Testing and Materials (ASTM) and Deutsches Institut Für Normung standards relating to the gonioapparent color, but the results of comparisons between these instruments are still inconclusive. Therefore, the main purpose of this study is to compare several multiangle spectrophotometers at a reproducibility level according to ASTM E2214-08 guidelines. In particular, we compared two X-Rite multi-gonio spectrophotometers (MA98 and MA68II), a Datacolor multi-gonio spectrophotometer (FX10), and a BYK multi-gonio spectrophotometer (BYK-mac). These instruments share only five common measurement geometries: 45° × −30° (as 15°), 45° × −20° (as 25°), 45° × 0° (as 45°), 45° × 30° (as 75°), 45° × 65° (as 110°). Specific statistical studies were used for the reproducibility comparison, including a Hotelling test and a statistical intercomparison test to determine the confidence interval of the partial color differences ΔL*, Δa*, Δb*, and the total color difference ΔE*ab. This was conducted using a database collection of 88 metallic and pearlescent samples that were measured 20 times without the replacement of all the instruments. The final findings show that in most measurement geometries, the reproducibility differences between pairs of instruments are statistically significant, although in general, there is a better reproducibility level at certain common geometries for newer instruments (MA98 and BYK-mac). This means that these differences are due to systematic or bias errors (angle tolerances for each geometry, photometric scales, white standards, etc.), but not exclusively to random errors. However, neither of the statistical tests used is valid to discriminate and quantify the detected bias errors in this comparison between instruments.

Global database of surface ocean particulate organic carbon export fluxes diagnosed from the 234Th technique

Through the processes of the biological pump, carbon is exported to the deep ocean in the form of dissolved and particulate organic matter. There are several ways by which downward export fluxes can be estimated. The great attraction of the 234Th technique is that its fundamental operation allows a downward flux rate to be determined from a single water column profile of thorium coupled to an estimate of POC/234Th ratio in sinking matter. We present a database of 723 estimates of organic carbon export from the surface ocean derived from the 234Th technique. Data were collected from tables in papers published between 1985 and 2013 only. We also present sampling dates, publication dates and sampling areas. Most of the open ocean Longhurst provinces are represented by several measurements. However, the Western Pacific, the Atlantic Arctic, South Pacific and the South Indian Ocean are not well represented. There is a variety of integration depths ranging from surface to 220m. Globally the fluxes ranged from -22 to 125 mmol of C/m**2/d. We believe that this database is important for providing new global estimate of the magnitude of the biological carbon pump.

Results of calculated surface air temperature anomaly of COSMOS Pliocene experiment 2 in NetCDF format

In this manuscript we describe the experimental procedure employed at the Alfred Wegener Institute in Germany in the preparation of the simulations for the Pliocene Model Intercomparison Project (PlioMIP). We present a description of the utilized Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) and document the procedures that we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project mid-Pliocene reconstruction into model forcing fields. The model setup and spin-up procedure are described for both the paleo- and preindustrial (PI) time slices of PlioMIP experiments 1 and 2, and general results that depict the performance of our model setup for mid-Pliocene conditions are presented. The mid-Pliocene, as simulated with our COSMOS setup and PRISM boundary conditions, is both warmer and wetter in the global mean than the PI. The globally averaged annual mean surface air temperature in the mid-Pliocene standalone atmosphere (fully coupled atmosphere-ocean) simulation is 17.35 °C (17.82 °C), which implies a warming of 2.23 °C (3.40 °C) relative to the respective PI control simulation.

Geospatial data quality indicators

Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset’s fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label.

GEO Label – quality information interrogation tool for geospatial datasets:towards effective visualization of quality metadata

Although the importance of dataset fitness-for-use evaluation and intercomparison is widely recognised within the GIS community, no practical tools have yet been developed to support such interrogation. GeoViQua aims to develop a GEO label which will visually summarise and allow interrogation of key informational aspects of geospatial datasets upon which users rely when selecting datasets for use. The proposed GEO label will be integrated in the Global Earth Observation System of Systems (GEOSS) and will be used as a value and trust indicator for datasets accessible through the GEO Portal. As envisioned, the GEO label will act as a decision support mechanism for dataset selection and thereby hopefully improve user recognition of the quality of datasets. To date we have conducted 3 user studies to (1) identify the informational aspects of geospatial datasets upon which users rely when assessing dataset quality and trustworthiness, (2) elicit initial user views on a GEO label and its potential role and (3), evaluate prototype label visualisations. Our first study revealed that, when evaluating quality of data, users consider 8 facets: dataset producer information; producer comments on dataset quality; dataset compliance with international standards; community advice; dataset ratings; links to dataset citations; expert value judgements; and quantitative quality information. Our second study confirmed the relevance of these facets in terms of the community-perceived function that a GEO label should fulfil: users and producers of geospatial data supported the concept of a GEO label that provides a drill-down interrogation facility covering all 8 informational aspects. Consequently, we developed three prototype label visualisations and evaluated their comparative effectiveness and user preference via a third user study to arrive at a final graphical GEO label representation. When integrated in the GEOSS, an individual GEO label will be provided for each dataset in the GEOSS clearinghouse (or other data portals and clearinghouses) based on its available quality information. Producer and feedback metadata documents are being used to dynamically assess information availability and generate the GEO labels. The producer metadata document can either be a standard ISO compliant metadata record supplied with the dataset, or an extended version of a GeoViQua-derived metadata record, and is used to assess the availability of a producer profile, producer comments, compliance with standards, citations and quantitative quality information. GeoViQua is also currently developing a feedback server to collect and encode (as metadata records) user and producer feedback on datasets; these metadata records will be used to assess the availability of user comments, ratings, expert reviews and user-supplied citations for a dataset. The GEO label will provide drill-down functionality which will allow a user to navigate to a GEO label page offering detailed quality information for its associated dataset. At this stage, we are developing the GEO label service that will be used to provide GEO labels on demand based on supplied metadata records. In this presentation, we will provide a comprehensive overview of the GEO label development process, with specific emphasis on the GEO label implementation and integration into the GEOSS.

How good are citizen weather stations? Addressing a biased opinion

The UK is home to a dense network of Citizen Weather Stations (CWS) primarily set up by members of the public. The majority of these stations record air temperature, relative humidity and precipitation, amongst other variables, at sub-hourly intervals. This high resolution network could have benefits in many applications, but only if the data quality is well characterised. Here we present results from an intercomparison field study, in which popular CWS models were tested against Met Office standard equipment. The study identifies some common instrumental biases and their dependencies, which will help us to quantify and correct such biases from the CWS network.

Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection.

Quantifying uncertainty in citizen weather data

The sheer volume of citizen weather data collected and uploaded to online data hubs is immense. However as with any citizen data it is difficult to assess the accuracy of the measurements. Within this project we quantify just how much data is available, where it comes from, the frequency at which it is collected, and the types of automatic weather stations being used. We also list the numerous possible sources of error and uncertainty within citizen weather observations before showing evidence of such effects in real data. A thorough intercomparison field study was conducted, testing popular models of citizen weather stations. From this study we were able to parameterise key sources of bias. Most significantly the project develops a complete quality control system through which citizen air temperature observations can be passed. The structure of this system was heavily informed by the results of the field study. Using a Bayesian framework the system learns and updates its estimates of the calibration and radiation-induced biases inherent to each station. We then show the benefit of correcting for these learnt biases over using the original uncorrected data. The system also attaches an uncertainty estimate to each observation, which would provide real world applications that choose to incorporate such observations with a measure on which they may base their confidence in the data. The system relies on interpolated temperature and radiation observations from neighbouring professional weather stations for which a Bayesian regression model is used. We recognise some of the assumptions and flaws of the developed system and suggest further work that needs to be done to bring it to an operational setting. Such a system will hopefully allow applications to leverage the additional value citizen weather data brings to longstanding professional observing networks.

Sulfate and nitrate firn concentrations on the Greenland ice sheet

Intercomparison of three new chemical ice core records from northern Greenland (covering the time span from approximately 1500 A.D. to present) with previously published records for southern and central Greenland reveals a uniform timing of anthropogenic changes in sulfate and nitrate firn concentrations over the entire ice sheet. The anthropogenic sulfate increase started around 1890, was interrupted by a transient decrease in the 1930s, and has resumed a major increase since 1950. Since the late 1970s though, a significant 30% decline in Greenland sulfate firn levels can be documented. The maximum anthropogenic increase in northern Greenland sulfate firn concentrations (up to 200-230 ppb) is 2-3 times larger than in southern and central Greenland. Nitrate records show an essentially steady increase since 1950 and, documented for the first time, a slight reduction during most recent years. Maximum nitrate firn levels of 100-130 ppb exceed the preindustrial background by 100% all over the Greenland ice sheet. Comparison with anthropogenic SO2 and NO x emission records indicates that the major increase in sulfate firn concentrations since 1950 can be attributed to Eurasian sources, while firn levels during the first half of this century appear to be dominated by North American emissions. A stronger North American source contribution is indicated over the entire 20th century in the case of nitrate. Applying a macroscopic deposition model separate time series for wet and dry deposition were derived which revealed a close correspondence of wet deposited sulfate with the timing of U.S. emissions, while the temporal evolution of Eurasian emissions is mainly reflected in the dry sulfate deposition record. During this century wet sulfate deposition increased by a factor of two while the total dry sulfate deposition flux increased by more than 500%. Wet and dry nitrate deposition both increased by 100% during the same period.

Sources and mixing state of size-resolved elemental carbon particles in a European megacity: Paris

An Aerosol Time-Of-Flight Mass Spectrometer (ATOFMS) was deployed to investigate the size-resolved chemical composition of single particles at an urban background site in Paris, France, as part of the MEGAPOLI winter campaign in January/February 2010. ATOFMS particle counts were scaled to match coincident Twin Differential Mobility Particle Sizer (TDMPS) data in order to generate hourly size-resolved mass concentrations for the single particle classes observed. The total scaled ATOFMS particle mass concentration in the size range 150–1067 nm was found to agree very well with the sum of concurrent High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and Multi-Angle Absorption Photometer (MAAP) mass concentration measurements of organic carbon (OC), inorganic ions and black carbon (BC) (R2 = 0.91). Clustering analysis of the ATOFMS single particle mass spectra allowed the separation of elemental carbon (EC) particles into four classes: (i) EC attributed to biomass burning (ECbiomass), (ii) EC attributed to traffic (ECtraffic), (iii) EC internally mixed with OC and ammonium sulfate (ECOCSOx), and (iv) EC internally mixed with OC and ammonium nitrate (ECOCNOx). Average hourly mass concentrations for EC-containing particles detected by the ATOFMS were found to agree reasonably well with semi-continuous quantitative thermal/optical EC and optical BC measurements (r2 = 0.61 and 0.65–0.68 respectively, n = 552). The EC particle mass assigned to fossil fuel and biomass burning sources also agreed reasonably well with BC mass fractions assigned to the same sources using seven-wavelength aethalometer data (r2 = 0.60 and 0.48, respectively, n = 568). Agreement between the ATOFMS and other instrumentation improved noticeably when a period influenced by significantly aged, internally mixed EC particles was removed from the intercomparison. 88% and 12% of EC particle mass was apportioned to fossil fuel and biomass burning respectively using the ATOFMS data compared with 85% and 15% respectively for BC estimated from the aethalometer model. On average, the mass size distribution for EC particles is bimodal; the smaller mode is attributed to locally emitted, mostly externally mixed EC particles, while the larger mode is dominated by aged, internally mixed ECOCNOx particles associated with continental transport events. Periods of continental influence were identified using the Lagrangian Particle Dispersion Model (LPDM) "FLEXPART". A consistent minimum between the two EC mass size modes was observed at approximately 400 nm for the measurement period. EC particles below this size are attributed to local emissions using chemical mixing state information and contribute 79% of the scaled ATOFMS EC particle mass, while particles above this size are attributed to continental transport events and contribute 21% of the EC particle mass. These results clearly demonstrate the potential benefit of monitoring size-resolved mass concentrations for the separation of local and continental EC emissions. Knowledge of the relative input of these emissions is essential for assessing the effectiveness of local abatement strategies.

Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs Gamma-A nifH genes abundance, computed from a collection of source data sets.

Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.