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  • 2010-2014  (17)
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  • 1
    Online Resource
    Online Resource
    Oxford :Oxford University Press, Incorporated,
    Keywords: Food chains (Ecology). ; Ecology. ; Electronic books.
    Description / Table of Contents: Food webs describe biological communities in terms of feeding interactions. This book integrates the latest work on community dynamics, ecosystems energetics, and stability to dispel categorisation of the field into separate subdiciplines of population, community, and ecosystem ecology.
    Type of Medium: Online Resource
    Pages: 1 online resource (344 pages)
    Edition: 1st ed.
    ISBN: 9780191646416
    Series Statement: Oxford Series in Ecology and Evolution Series
    DDC: 577.16
    Language: English
    Note: Cover -- Contents -- Chapter 1 Approaches to studying food webs -- 1.1 Introduction -- 1.2 Traditions in ecology -- 1.2.1 The community perspective -- 1.2.2 The ecosystem perspective -- 1.3 Food webs and traditions in ecology -- 1.3.1 Theoretically based food webs -- 1.3.2 Empirically based food webs: architecture -- 1.3.3 Empirically based food webs: information -- 1.3.4 How useful are these descriptions? -- 1.4 Bridging perspectives through energetics -- 1.4.1 Core concepts and elements -- 1.4.2 Comments on our approach to studying food webs -- 1.5 An overview of the parts and chapters -- 1.6 Summary -- Part I: Modeling simple andmultispecies communities -- Chapter 2 Models of simple and complex systems -- 2.1 Introduction -- 2.2 Model structure and assumptions -- 2.3 Stability -- 2.4 Simple food chains -- 2.5 The dynamics of primary-producer-based and detritus-based models -- 2.6 Summary and conclusions -- Chapter 3 Connectedness food webs -- 3.1 Introduction -- 3.2 Soil food webs -- 3.3 The CPER soil food web -- 3.4 Summary and conclusions -- Chapter 4 Energy flux food webs -- 4.1 Introduction -- 4.2 Biomass and physiological parameters -- 4.3 Feeding rates and mineralization rates -- 4.4 Energy flux descriptions -- 4.5 Summary and conclusions -- Chapter 5 Functional webs -- 5.1 Introduction -- 5.2 Interaction strengths -- 5.3 A functional food web for the CPER -- 5.4 Summary and conclusions -- Part II: The dynamics and stability of simple and complex communities -- Chapter 6 Energetic organization and food web stability -- 6.1 Introduction -- 6.2 Energetic organization and stability -- 6.3 Distribution of interaction strengths: trophic-level-dependent interaction strengths -- 6.4 Summary and conclusions -- Chapter 7 Enrichment, trophic structure, and stability -- 7.1 Introduction -- 7.2 Simple primary-producer-based and detritus-based models. , 7.3 Trophic structure and dynamics along a productivity gradient -- 7.4 More complex models -- 7.5 Connections to real-world productivity -- 7.6 Summary and conclusions -- Chapter 8 Modeling compartments -- 8.1 Introduction -- 8.2 Complexity, diversity, compartments, and stability -- 8.3 Defining compartments -- 8.4 Approaches to studying compartments -- 8.5 The energy channel -- 8.6 Energy channels-structure and stability -- 8.7 Summary and conclusions -- Chapter 9 Productivity, dynamic stability, and species richness -- 9.1 Introduction -- 9.2 Trophic structure, dynamics, and productivity -- 9.3 Feasibility revisited -- 9.4 Feasibility and the hump-shaped curve -- 9.5 Trophic structure and the diversity of production -- 9.6 A review of hypotheses -- 9.7 Summary and conclusions -- Part III: Dynamic food web architectures -- Chapter 10 Species-based versus biomass-based food web descriptions -- 10.1 Introduction -- 10.2 Dynamic food webs-playing Jenga -- 10.3 Two case studies -- 10.4 Stability, disturbance, and transition -- 10.5 Summary and conclusions -- Chapter 11 Dynamic architectures and stability of complex systems along productivity gradients -- 11.1 Introduction -- 11.2 Food web structure in a cave ecosystem -- 11.3 Food web structure and stability along the primary succession gradient at the Wadden island of Schiermonnikoog, The Netherlands -- 11.4 Food web structure in a changing Arctic -- 11.5 General framework -- 11.6 Summary and conclusions -- Chapter 12 Food web dynamics beyond asymptotic behavior -- 12.1 Introduction -- 12.2 Variability, equilibrium states, and asymptotic stability -- 12.3 Transient dynamics -- 12.4 Spatial systems -- 12.5 Asymptotically ambiguous states -- 12.6 Reconciling asymptotic stability, spatial structure, and transient dynamics -- 12.7 Summary and conclusions -- References -- Index -- A -- B -- C -- D -- E. , F -- H -- I -- J -- K -- L -- M -- O -- P -- R -- S -- T -- V -- W.
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  • 2
    Online Resource
    Online Resource
    San Diego :Elsevier,
    Keywords: Climatic changes -- Mathematical models. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (494 pages)
    Edition: 1st ed.
    ISBN: 9780128005835
    DDC: 551.60151
    Language: English
    Note: Front Cover -- Mathematical and Physical Fundamentals of Climate Change -- Copyright -- Contents -- Preface: Interdisciplinary Approaches to Climate Change Research -- Chapter 1: Fourier Analysis -- 1.1 Fourier Series and Fourier Transform -- 1.2 Bessel's Inequality and Parseval's Identity -- 1.3 Gibbs Phenomenon -- 1.4 Poisson Summation Formulas and Shannon Sampling Theorem -- 1.5 Discrete Fourier Transform -- 1.6 Fast Fourier Transform -- 1.7 Heisenberg Uncertainty Principle -- 1.8 Case Study: Arctic Oscillation Indices -- Problems -- Bibliography -- Chapter 2: Time-Frequency Analysis -- 2.1 Windowed Fourier Transform -- 2.2 Wavelet Transform -- 2.3 Multiresolution Analyses and Wavelet Bases -- 2.3.1 Multiresolution Analyses -- 2.3.2 Discrete Wavelet Transform -- 2.3.3 Biorthogonal Wavelets, Bivariate Wavelets,and Wavelet Packet -- 2.4 Hilbert Transform, Analytical Signal, and Instantaneous Frequency -- 2.5 Wigner-Ville Distribution and Cohen's Class -- 2.6 Empirical Mode Decompositions -- Problems -- Bibliography -- Chapter 3: Filter Design -- 3.1 Continuous Linear Time-Invariant Systems -- 3.2 Analog Filters -- 3.3 Discrete Linear Time-Invariant Systems -- 3.3.1 Discrete Signals -- 3.3.2 Discrete Convolution -- 3.3.3 Discrete System -- 3.3.4 Ideal Digital Filters -- 3.3.5 Z-Transforms -- 3.3.6 Linear Difference Equations -- 3.4 Linear-Phase Filters -- 3.4.1 Four Types of Linear-Phase Filters -- 3.4.2 Structure of Linear-Phase Filters -- 3.5 Designs of FIR Filters -- 3.5.1 Fourier Expansions -- 3.5.2 Window Design Method -- 3.5.3 Sampling in the Frequency Domain -- 3.6 IIR Filters -- 3.6.1 Impulse Invariance Method -- 3.6.2 Matched Z-Transform Method -- 3.6.3 Bilinear Transform Method -- 3.7 Conjugate Mirror Filters -- Problems -- Bibliography -- Chapter 4: Remote Sensing -- 4.1 Solar and Thermal Radiation. , 4.2 Spectral Regions and Optical Sensors -- 4.3 Spatial Filtering -- 4.4 Spatial Blurring -- 4.5 Distortion Correction -- 4.6 Image Fusion -- 4.7 Supervised and Unsupervised Classification -- 4.8 Remote Sensing of Atmospheric Carbon Dioxide -- 4.9 Moderate Resolution Imaging Spectroradiometer Data Products and Climate Change -- Problems -- Bibliography -- Chapter 5: Basic Probability and Statistics -- 5.1 Probability Space, Random Variables, and Their Distributions -- 5.1.1 Discrete Random Variables -- 5.1.2 Continuous Random Variables -- 5.1.3 Properties of Expectations and Variances -- 5.1.4 Distributions of Functions of Random Variables -- 5.1.5 Characteristic Functions -- 5.2 Jointly Distributed Random Variables -- 5.3 Central Limit Theorem and Law of Large Numbers -- 5.4 Minimum Mean Square Error -- 5.5 2-Distribution, t-Distribution, and F-Distribution -- 5.6 Parameter Estimation -- 5.7 Confidence Interval -- 5.8 Tests of Statistical Hypotheses -- 5.9 Analysis of Variance -- 5.10 Linear Regression -- 5.11 Mann-Kendall Trend Test -- Problems -- Bibliography -- Chapter 6: Empirical Orthogonal Functions -- 6.1 Random Vector Fields -- 6.2 Classical EOFs -- 6.3 Estimation of EOFs -- 6.4 Rotation of EOFs -- 6.5 Complex EOFs and Hilbert EOFs -- 6.6 Singular Value Decomposition -- 6.7 Canonical Correlation Analysis -- 6.8 Singular Spectrum Analysis -- 6.9 Principal Oscillation Patterns -- 6.9.1 Normal Modes -- 6.9.2 Estimates of Principal Oscillation Patterns -- Problems -- Bibliography -- Chapter 7: Random Processes and Power Spectra -- 7.1 Stationary and Non-stationary Random Processes -- 7.2 Markov Process and Brownian Motion -- 7.3 Calculus of Random Processes -- 7.4 Spectral Analysis -- 7.4.1 Linear Time-Invariant System for WSS Processes -- 7.4.2 Power Spectral Density -- 7.4.3 Shannon Sampling Theorem for Random Processes -- 7.5 Wiener Filtering. , 7.6 Spectrum Estimation -- 7.7 Significance Tests of Climatic Time Series -- 7.7.1 Fourier Power Spectra -- 7.7.2 Wavelet Power Spectra -- Problems -- Bibliography -- Chapter 8: Autoregressive Moving Average Models -- 8.1 ARMA Processes -- 8.1.1 AR(p) Processes -- 8.1.2 MA(q) Processes -- 8.1.3 Shift Operator -- 8.1.4 ARMA(p,q) Processes -- 8.2 Yule-Walker Equation andSpectral Density -- 8.3 Prediction Algorithms -- 8.3.1 Innovation Algorithm -- 8.3.2 Durbin-Lovinson Algorithm -- 8.3.3 Kolmogorov's Formula -- 8.4 Asymptotic Theory -- 8.4.1 Gramer-Wold Device -- 8.4.2 Asymptotic Normality -- 8.5 Estimates of Means and CovarianceFunctions -- 8.6 Estimation for ARMA Models -- 8.6.1 General Linear Model -- 8.6.2 Estimation for AR(p) Processes -- 8.6.3 Estimation for ARMA(p,q) Processes -- 8.7 ARIMA Models -- 8.8 Multivariate ARMA Processes -- 8.9 Application in Climatic and Hydrological Research -- Problems -- Bibliography -- Chapter 9: Data Assimilation -- 9.1 Concept of Data Assimilation -- 9.2 Cressman Method -- 9.3 Optimal Interpolation Analysis -- 9.4 Cost Function and Three-Dimensional Variational Analysis -- 9.5 Dual of the Optimal Interpolation -- 9.6 Four-Dimensional Variational Analysis -- 9.7 Kalman Filter -- Problems -- Bibliography -- Chapter 10: Fluid Dynamics -- 10.1 Gradient, Divergence, and Curl -- 10.2 Circulation and Flux -- 10.3 Green's Theorem, Divergence Theorem, and Stokes's Theorem -- 10.4 Equations of Motion -- 10.4.1 Continuity Equation -- 10.4.2 Euler's Equation -- 10.4.3 Bernoulli's Equation -- 10.5 Energy Flux and Momentum Flux -- 10.6 Kelvin Law -- 10.7 Potential Function and Potential Flow -- 10.8 Incompressible Fluids -- Problems -- Bibliography -- Chapter 11: Atmospheric Dynamics -- 11.1 Two Simple Atmospheric Models -- 11.1.1 The Single-Layer Model -- 11.1.2 The Two-Layer Model -- 11.2 Atmospheric Composition. , 11.3 Hydrostatic Balance Equation -- 11.4 Potential Temperature -- 11.5 Lapse Rate -- 11.5.1 Adiabatic Lapse Rate -- 11.5.2 Buoyancy Frequency -- 11.6 Clausius-Clapeyron Equation -- 11.6.1 Saturation Mass Mixing Radio -- 11.6.2 Saturation Adiabatic Lapse Rate -- 11.6.3 Equivalent Potential Temperature -- 11.7 Material Derivatives -- 11.8 Vorticity and Potential Vorticity -- 11.9 Navier-Stokes Equation -- 11.9.1 Navier-Stokes Equation in an Inertial Frame -- 11.9.2 Navier-Stokes Equation in a Rotating Frame -- 11.9.3 Component Form of the Navier-Stokes Equation -- 11.10 Geostrophic Balance Equations -- 11.11 Boussinesq Approximation and Energy Equation -- 11.12 Quasi-Geostrophic Potential Vorticity -- 11.13 Gravity Waves -- 11.13.1 Internal Gravity Waves -- 11.13.2 Inertia Gravity Waves -- 11.14 Rossby Waves -- 11.15 Atmospheric Boundary Layer -- Problems -- Bibliography -- Chapter 12: Oceanic Dynamics -- 12.1 Salinity and Mass -- 12.2 Inertial Motion -- 12.3 Oceanic Ekman Layer -- 12.3.1 Ekman Currents -- 12.3.2 Ekman Mass Transport -- 12.3.3 Ekman Pumping -- 12.4 Geostrophic Currents -- 12.4.1 Surface Geostrophic Currents -- 12.4.2 Geostrophic Currents from Hydrography -- 12.5 Sverdrup's Theorem -- 12.6 Munk's Theorem -- 12.7 Taylor-Proudman Theorem -- 12.8 Ocean-Wave Spectrum -- 12.8.1 Spectrum -- 12.8.2 Digital Spectrum -- 12.8.3 Pierson-Moskowitz Spectrum -- 12.9 Oceanic Tidal Forces -- Problems -- Bibliography -- Chapter 13: Glaciers and Sea Level Rise -- 13.1 Stress and Strain -- 13.2 Glen's Law and Generalized Glen's Law -- 13.3 Density of Glacier Ice -- 13.4 Glacier Mass Balance -- 13.5 Glacier Momentum Balance -- 13.6 Glacier Energy Balance -- 13.7 Shallow-Ice and Shallow-Shelf Approximations -- 13.8 Dynamic Ice Sheet Models -- 13.9 Sea Level Rise -- 13.10 Semiempirical Sea Level Models -- Problems -- Bibliography. , Chapter 14: Climate and Earth System Models -- 14.1 Energy Balance Models -- 14.1.1 Zero-Dimensional EBM -- 14.1.2 One-Dimensional EBM -- 14.2 Radiative Convective Models -- 14.3 Statistical Dynamical Models -- 14.4 Earth System Models -- 14.4.1 Atmospheric Models -- 14.4.2 Oceanic Models -- 14.4.3 Land Surface Models -- 14.4.4 Sea Ice Models -- 14.5 Coupled Model Intercomparison Project -- 14.6 Geoengineering Model Intercomparison Project -- Problems -- Bibliography -- Index.
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  • 3
    Publication Date: 2023-07-10
    Keywords: Araneidae; Clubionidae; Dictynidae; Gnaphosidae; Linyphiidae; LTER_ToolikL; Lycosidae; MULT; Multiple investigations; Philodromidae; Salticidae; Site; Theridiidae; Thomisidae; Time coverage; Toolik Lake, Alaska
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 4
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    PANGAEA
    In:  Supplement to: Sun, Bo; Moore, John C; Zwinger, Thomas; Zhao, Liyun; Steinhage, Daniel; Tang, Xueyuan; Zhang, Dong; Cui, Xiangbin; Martín, Carlos (2014): How old is the ice beneath Dome A, Antarctica? The Cryosphere, 8(3), 1121-1128, https://doi.org/10.5194/tc-8-1121-2014
    Publication Date: 2023-11-21
    Description: Chinese scientists will start to drill a deep ice core at Kunlun station near Dome A in the near future. Recent work has predicted that Dome A is a location where ice older than 1 million years can be found. We model flow, temperature and the age of the ice by applying a three-dimensional, thermomechanically coupled full-Stokes model to a 70 × 70 km**2 domain around Kunlun station, using isotropic non-linear rheology and different prescribed anisotropic ice fabrics that vary the evolution from isotropic to single maximum at 1/3 or 2/3 depths. The variation in fabric is about as important as the uncertainties in geothermal heat flux in determining the vertical advection which in consequence controls both the basal temperature and the age profile. We find strongly variable basal ages across the domain since the ice varies greatly in thickness, and any basal melting effectively removes very old ice in the deepest parts of the subglacial valleys. Comparison with dated radar isochrones in the upper one third of the ice sheet cannot sufficiently constrain the age of the deeper ice, with uncertainties as large as 500 000 years in the basal age. We also assess basal age and thermal state sensitivities to geothermal heat flux and surface conditions. Despite expectations of modest changes in surface height over a glacial cycle at Dome A, even small variations in the evolution of surface conditions cause large variation in basal conditions, which is consistent with basal accretion features seen in radar surveys.
    Keywords: AWI_Glac; Glaciology @ AWI
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 5
    Publication Date: 2023-12-01
    Keywords: AC; Airborne radio-echo sounding; Aircraft; Antarctica; ARES; AWI_Glac; DoCo_2007/08; DoCo_2007/08_083118; Glaciology @ AWI; LATITUDE; LONGITUDE; POLAR 5; Sample code/label; Two-way traveltime
    Type: Dataset
    Format: text/tab-separated-values, 70712 data points
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  • 6
    Publication Date: 2023-11-22
    Keywords: Abbreviation; Age; Datum level; DEPTH, ice/snow; Difference; Event label; Glacier; Himalaya; Holtedahl_core05; ICEDRILL; Ice drill; Latitude of event; Lomonosov_core97; Longitude of event; MtEverest_core02; Svalbard; Vestfonna_core95; Year of eruption
    Type: Dataset
    Format: text/tab-separated-values, 180 data points
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  • 7
    Publication Date: 2023-12-01
    Keywords: AC; Airborne radio-echo sounding; Aircraft; Antarctica; ARES; AWI_Glac; DoCo_2007/08; DoCo_2007/08_083119; Glaciology @ AWI; LATITUDE; LONGITUDE; POLAR 5; Sample code/label; Two-way traveltime
    Type: Dataset
    Format: text/tab-separated-values, 154273 data points
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  • 8
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    PANGAEA
    In:  Supplement to: Beaudon, Emilie; Arppe, Laura; Jonsell, Ulf; Martma, Tõnu; Möller, Marco; Pohjola, Veijo A; Scherer, Dieter; Moore, John C (2011): Spatial and temporal variability of net accumulation from shallow cores from vestfonna ice cap (Nordaustlandet, Svalbard). Geografiska Annaler Series A-Physical Geography, 93A(4), 287-299, https://doi.org/10.1111/j.1468-0459.2011.00439.x
    Publication Date: 2024-02-03
    Description: We analyse ice cores from Vestfonna ice cap (Nordaustlandet, Svalbard). Oxygen isotopic measurements were made on three firn cores (6.0, 11.0 and 15.5 m deep) from the two highest summits of the glacier located on the SW-NE and NW-SE central ridges. Sub-annual d18O cycles were preserved and could be counted visually in the uppermost parts of the cores, but deeper layers were affected by post-depositional smoothing. A pronounced d18O minimum was found near the bottom of the three cores. We consider candidates for this d18O signal to be a valuable reference horizon since it is also seen elsewhere in Nordaustlandet. We attribute it to isotopically depleted snow precipitation, which NCEP/NCAR reanalysis shows was unusual for Vestfonna, and came from northerly air during the cold winter of 1994/95. Finding the 1994/95 time marker allows establishment of a precise depth/age scale for the three cores. The derived annual accumulation rates indirectly fill a geographical gap in mass balance measurements and thus provide information on spatial and temporal variability of precipitation over the glacier for the period spanned by the cores (1992-2009). Comparing records at the two locations also reveals that the snow net accumulation at the easternmost part of Vestfonna was only half of that in the western part over the last 17 years.
    Keywords: Accumulation of snow/ice per year; Accumulation rate per year, standard deviation; Age, relative, number of years; Ahlmann_Ahl07; Ahlmann_Ahl09; Austfonna99; Eastern_E07; Elevation of event; Event label; Ice_core_diverse; ICEDRILL; Ice drill; International Polar Year (2007-2008); International Polar Year 2007-2008; Interval comments; IPY; IPY-4; Isotope ratio mass spectrometry; Latitude of event; Longitude of event; Reference/source; Sample ID; Sampling/drilling ice; Svalbard; Vestfonna95; δ18O, standard deviation; δ18O, water
    Type: Dataset
    Format: text/tab-separated-values, 36 data points
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  • 9
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    PANGAEA
    In:  Supplement to: Gough, Laura; Moore, John C; Shaver, Gauis R; Simpson, Rodney T; Johnson, David R (2012): Above- and belowground responses of arctic tundra ecosystems to altered soil nutrients and mammalian herbivory. Ecology, 93(7), 1683-1694, https://doi.org/10.1890/11-1631.1
    Publication Date: 2023-12-13
    Description: Theory and observation indicate that changes in the rate of primary production can alter the balance between the bottom-up influences of plants and resources and the top-down regulation of herbivores and predators on ecosystem structure and function. The Exploitation Ecosystem Hypothesis (EEH) posited that as aboveground net primary productivity (ANPP) increases, the additional biomass should support higher trophic levels. We developed an extension of EEH to include the impacts of increases in ANPP on belowground consumers in a similar manner as aboveground, but indirectly through changes in the allocation of photosynthate to roots. We tested our predictions for plants aboveground and for phytophagous nematodes and their predators belowground in two common arctic tundra plant communities subjected to 11 years of increased soil nutrient availability and/or exclusion of mammalian herbivores. The less productive dry heath (DH) community met the predictions of EEH aboveground, with the greatest ANPP and plant biomass in the fertilized plots protected from herbivory. A palatable grass increased in fertilized plots while dwarf evergreen shrubs and lichens declined. Belowground, phytophagous nematodes also responded as predicted, achieving greater biomass in the higher ANPP plots, whereas predator biomass tended to be lower in those same plots (although not significantly). In the higher productivity moist acidic tussock (MAT) community, aboveground responses were quite different. Herbivores stimulated ANPP and biomass in both ambient and enriched soil nutrient plots; maximum ANPP occurred in fertilized plots exposed to herbivory. Fertilized plots became dominated by dwarf birch (a deciduous shrub) and cloudberry (a perennial forb); under ambient conditions these two species coexist with sedges, evergreen dwarf shrubs, and Sphagnum mosses. Phytophagous nematodes did not respond significantly to changes in ANPP, although predator biomass was greatest in control plots. The contrasting results of these two arctic tundra plant communities suggest that the predictions of EEH may hold for very low ANPP communities, but that other factors, including competition and shifts in vegetation composition toward less palatable species, may confound predicted responses to changes in productivity in higher ANPP communities such as the MAT studied here.
    Keywords: International Polar Year (2007-2008); IPY; LTER_ToolikL; MULT; Multiple investigations; Toolik Lake, Alaska
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 10
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    PANGAEA
    In:  Supplement to: Moore, John C; Beaudon, Emilie; Kang, Shichang; Divine, Dmitry V; Isaksson, Elisabeth; Pohjola, Veijo A; van de Wal, Roderik S W (2012): Statistical extraction of volcanic sulphate from nonpolar ice cores. Journal of Geophysical Research, 117(D3), D03306, https://doi.org/10.1029/2011JD016592
    Publication Date: 2023-12-13
    Description: Ice cores from outside the Greenland and Antarctic ice sheets are difficult to date because of seasonal melting and multiple sources (terrestrial, marine, biogenic and anthropogenic) of sulfates deposited onto the ice. Here we present a method of volcanic sulfate extraction that relies on fitting sulfate profiles to other ion species measured along the cores in moving windows in log space. We verify the method with a well dated section of the Belukha ice core from central Eurasia. There are excellent matches to volcanoes in the preindustrial, and clear extraction of volcanic peaks in the post-1940 period when a simple method based on calcium as a proxy for terrestrial sulfate fails due to anthropogenic sulfate deposition. We then attempt to use the same statistical scheme to locate volcanic sulfate horizons within three ice cores from Svalbard and a core from Mount Everest. Volcanic sulfate is 〈5% of the sulfate budget in every core, and differences in eruption signals extracted reflect the large differences in environment between western, northern and central regions of Svalbard. The Lomonosovfonna and Vestfonna cores span about the last 1000 years, with good extraction of volcanic signals, while Holtedahlfonna which extends to about AD1700 appears to lack a clear record. The Mount Everest core allows clean volcanic signal extraction and the core extends back to about AD700, slightly older than a previous flow model has suggested. The method may thus be used to extract historical volcanic records from a more diverse geographical range than hitherto.
    Keywords: International Polar Year (2007-2008); IPY
    Type: Dataset
    Format: application/zip, 2 datasets
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