Global Data (global + data)

Distribution by Scientific Domains

Terms modified by Global Data

  • global data set

  • Selected Abstracts

    APEX-Map: a parameterized scalable memory access probe for high-performance computing systems,

    Erich Strohmaier
    Abstract The memory wall between the peak performance of microprocessors and their memory performance has become the prominent performance bottleneck for many scientific application codes. New benchmarks measuring data access speeds locally and globally in a variety of different ways are needed to explore the ever increasing diversity of architectures for high-performance computing. In this paper, we introduce a novel benchmark, APEX-Map, which focuses on global data movement and measures how fast global data can be fed into computational units. APEX-Map is a parameterized, synthetic performance probe and integrates concepts for temporal and spatial locality into its design. Our first parallel implementation in MPI and various results obtained with it are discussed in detail. By measuring the APEX-Map performance with parameter sweeps for a whole range of temporal and spatial localities performance surfaces can be generated. These surfaces are ideally suited to study the characteristics of the computational platforms and are useful for performance comparison. Results on a global-memory vector platform and distributed-memory superscalar platforms clearly reflect the design differences between these different architectures. Published in 2007 by John Wiley & Sons, Ltd. [source]

    Climate, climate change and range boundaries

    Chris D. Thomas
    Abstract Aim, A major issue in ecology, biogeography, conservation biology and invasion biology is the extent to which climate, and hence climate change, contributes to the positions of species' range boundaries. Thirty years of rapid climate warming provides an excellent opportunity to test the hypothesis that climate acts as a major constraint on range boundaries, treating anthropogenic climate change as a large-scale experiment. Location, UK and global data, and literature. Methods, This article analyses the frequencies with which species have responded to climate change by shifting their range boundaries. It does not consider abundance or other changes. Results, For the majority of species, boundaries shifted in a direction that is concordant with being a response to climate change; 84% of all species have expanded in a polewards direction as the climate has warmed (for the best data available), which represents an excess of 68% of species after taking account of the fact that some species may shift in this direction for non-climatic reasons. Other data sets also show an excess of animal range boundaries expanding in the expected direction. Main conclusions, Climate is likely to contribute to the majority of terrestrial and freshwater range boundaries. This generalization excludes species that are endemic to specific islands, lakes, rivers and geological outcrops, although these local endemics are not immune from the effects of climate change. The observed shifts associated with recent climate change are likely to have been brought about through both direct and indirect (changes to species' interactions) effects of climate; indirect effects are discussed in relation to laboratory experiments and invasive species. Recent observations of range boundary shifts are consistent with the hypothesis that climate contributes to, but is not the sole determinant of, the position of the range boundaries of the majority of terrestrial animal species. [source]

    Prediction and validation of the potential global distribution of a problematic alien invasive species , the American bullfrog

    Gentile Francesco Ficetola
    ABSTRACT Predicting the probability of successful establishment and invasion of alien species at global scale, by matching climatic and land use data, is a priority for the risk assessment. Both large- and local-scale factors contribute to the outcome of invasions, and should be integrated to improve the predictions. At global scale, we used climatic and land use layers to evaluate the habitat suitability for the American bullfrog Rana catesbeiana, a major invasive species that is among the causes of amphibian decline. Environmental models were built by using Maxent, a machine learning method. Then, we integrated global data with information on richness of native communities and hunting pressure collected at the local scale. Global-scale data allowed us to delineate the areas with the highest suitability for this species. Predicted suitability was significantly related to the invasiveness observed for bullfrog populations historically introduced in Europe, but did not explain a large portion of variability in invasion success. The integration of data at the global and local scales greatly improved the performance of models, and explained > 57% of the variance in introduction success: bullfrogs were more invasive in areas with high suitability and low hunting pressure over frogs. Our study identified the climatic factors entailing the risk of invasion by bullfrogs, and stresses the importance of the integration of biotic and abiotic data collected at different spatial scales, to evaluate the areas where monitoring and management efforts need to be focused. [source]

    Global statistical analysis of MISR aerosol data: a massive data product from NASA's Terra satellite

    ENVIRONMETRICS, Issue 7 2007
    Tao Shi
    Abstract In climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have been put in place to collect global data. However, missing and noisy observations impose considerable difficulties for scientists researching the global distribution of aerosols, aerosol transportation, and comparisons between satellite observations and global-climate-model outputs. In this paper, we fit a Spatial Mixed Effects (SME) statistical model to predict the missing values, denoise the observed values, and quantify the spatial-prediction uncertainties. The computations associated with the SME model are linear scalable to the number of data points, which makes it feasible to process massive global satellite data. We apply the methodology, which is called Fixed Rank Kriging (FRK), to the level-3 Aerosol Optical Depth (AOD) dataset collected by NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument flying on the Terra satellite. Overall, our results were superior to those from non-statistical methods and, importantly, FRK has an uncertainty measure associated with it that can be used for comparisons over different regions or at different time points. Copyright © 2007 John Wiley & Sons, Ltd. [source]

    Below-ground carbon flux and partitioning: global patterns and response to temperature

    FUNCTIONAL ECOLOGY, Issue 6 2008
    C. M. Litton
    Summary 1The fraction of gross primary production (GPP) that is total below-ground carbon flux (TBCF) and the fraction of TBCF that is below-ground net primary production (BNPP) represent globally significant C fluxes that are fundamental in regulating ecosystem C balance. However, global estimates of the partitioning of GPP to TBCF and of TBCF to BNPP, as well as the absolute size of these fluxes, remain highly uncertain. 2Efforts to model below-ground processes are hindered by methodological difficulties for estimating below-ground C cycling, the complexity of below-ground interactions, and an incomplete understanding of the response of GPP, TBCF and BNPP to climate change. Due to a paucity of available data, many terrestrial ecosystem models and ecosystem-level studies of whole stand C use efficiency rely on assumptions that: (i) C allocation patterns across large geographic, climatic and taxonomic scales are fixed; and (ii) c. 50% of TBCF is BNPP. 3Here, we examine available information on GPP, TBCF, BNPP, TBCF : GPP and BNPP : TBCF from a diverse global data base of forest ecosystems to understand patterns in below-ground C flux and partitioning, and their response to mean annual temperature (MAT). 4MAT and mean annual precipitation (MAP) covaried strongly across the global forest data base (37 mm increase in MAP for every 1 °C increase in MAT). In all analyses, however, MAT was the most important variable explaining observed patterns in below-ground C processes. 5GPP, TBCF and BNPP all increased linearly across the global scale range of MAT. TBCF : GPP increased significantly with MAT for temperate and tropical ecosystems (> 5 °C), but variability was high across the data set. BNPP : TBCF varied from 0·26 to 0·53 across the entire MAT gradient (,5 to 30 °C), with a much narrower range of 0·42 to 0·53 for temperate and tropical ecosystems (5 to 30 °C). 6Variability in the data sets was moderate and clear exceptions to the general patterns exist that likely relate to other factors important for determining below-ground C flux and partitioning, in particular water availability and nutrient supply. Still, our results highlight global patterns in below-ground C flux and partitioning in forests in response to MAT that in part confirm previously held assumptions. [source]

    Searching for mid-term variations in different aspects of solar activity , looking for probable common origins and studying temporal variations of magnetic polarities

    E. Forgács-Dajka
    ABSTRACT Several studies have examined the temporal variability of the solar activity, and many variations are reported in the literature. We also (re)analyse the statistical properties of the following kinds of data series of solar activity phenomena: magnetic synoptic charts, hemispherical relative sunspot numbers, solar flare index, coronal index, solar radio flux, interplanetary magnetic field and proton speed in the solar wind, in order to find common mid-term periods during solar cycles 21,23. As a new approach, we focus on the magnetic polarity relations and we define new quantities (e.g. magnetic positive,negative polarity asymmetry) to explore the connections between several aspects of the solar activity from different points of view. According to our survey, the mid-term periodicities (1,2 yr) are manifest in almost all data with the exception of the coronal index and the 10.7-cm solar flux data. In the case of these latter two we note that these surveys produce global data on the solar corona, so the Sun is studied on these bandwidths as a star. Besides these, with the accumulation of helioseismic data over the last 10 yr, it has become possible to study the temporal variation in the rotational rate residuals in tachocline region. In addition, we examine possible common origins of different activity markers and/or possible connections to differential rotation. [source]

    Flow dependence of background errors and their vertical correlations for radiance-data assimilation

    Reinhold Hess
    Abstract This article examines the dependence of background-error statistics on synoptic conditions and flow patterns. Error variances and vertical correlations of background temperatures as used for variational radiance-data assimilation are estimated for two different weather regimes over Europe using the NMC method. The results are validated with real observations, i.e. radiosonde data and microwave satellite radiances and generalised with half a year of global data from the ECMWF forecasting system, where weather conditions are distinguished using model fields of wind speed, mean sea level pressure, and relative vorticity. Strong winds, low pressure, and cyclonic flow generally induce larger background errors of 500 hPa temperature than calm winds, high pressure, and anticyclonic flow, and also broader temperature correlations in the vertical with other tropospheric levels. Copyright © 2010 Royal Meteorological Society [source]