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  • 1
    facet.materialart.12
    Radiocarbon and climate change : mechanisms, applications and laboratory techniques (2016)
    [Cham] : Springer
    Details
    Call number: 9783319256436 (e-book)
    Description / Table of Contents: This book is a useful guide for researchers in ecology and earth science interested in the use of accelerator mass spectrometry technology. The development of research in radiocarbon measurements offers an opportunity to address the human impact on global carbon cycling and climate change. Presenting radiocarbon theory, history, applications, and analytical techniques in one volume builds a broad outline of the field of radiocarbon and its emergent role in defining changes in the global carbon cycle and links to climate change. Each chapter presents both classic and cutting-edge studies from different disciplines involving radiocarbon and carbon cycling. The book also includes a chapter on the history and discovery of radiocarbon, and advances in radiocarbon measurement techniques and radiocarbon theory. Understanding human alteration of the global carbon cycle and the link between atmospheric carbon dioxide levels and climate remains one of the foremost environmental problems at the interface of ecology and earth system science. Many people are familiar with the terms ‘global warming’ and ‘climate change’, but fewer are able to articulate the science that support these hypotheses. This book addresses general questions such as: what is the link between the carbon cycle and climate change; what is the current evidence for the fate of carbon dioxide added by human activities to the atmosphere, and what has caused past changes in atmospheric carbon dioxide? How can the radiocarbon and stable isotopes of carbon combined with other tools be used for quantifying the human impact on the global carbon cycle?
    Type of Medium: 12
    Pages: 1 Online-Ressource (VII, 315 Seiten) , Illustrationen, Diagramme
    ISBN: 9783319256436 , 978-3-319-25643-6
    URL: Ebook (access only within the AWI network)
    DOI: 10.1007/978-3-319-25643-6
    Language: English
    Note: Contents 1 Radiocarbon and the Global Carbon Cycle / E.A.G. Schuur, S.E. Trumbore, E.R.M. Druffel, J.R. Southon, A. Steinhof, R.E. Taylor and J.C. Turnbull 2 Radiocarbon Dating: Development of a Nobel Method / R.E. Taylor 3 Radiocarbon Nomenclature, Theory, Models, and Interpretation: Measuring Age, Determining Cycling Rates, and Tracing Source Pools / S.E. Trumbore, C.A. Sierra and C.E. Hicks Pries 4 Radiocarbon in the Atmosphere / J.C. Turnbull, H. Graven and N.Y. Krakauer 5 Radiocarbon in the Oceans / E.R.M. Druffel, S.R. Beaupré and L.A. Ziolkowski 6 Radiocarbon in Terrestrial Systems / E.A.G. Schuur, M.S. Carbone, C.E. Hicks Pries, F.M. Hopkins and S.M. Natali 7 Paleoclimatology / J.R. Southon, R. De Pol-Holz and E.R.M. Druffel 8 Accelerator Mass Spectrometry of Radiocarbon / Axel Steinhof 9 Preparation for Radiocarbon Analysis / S.E. Trumbore, X. Xu, G.M. Santos, C.I. Czimczik, S.R. Beaupré, M.A. Pack, F.M. Hopkins, A. Stills, M. Lupascu and L. Ziolkowski
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    E-BOOK
  • 2
    Electronic Resource
    Electronic Resource
    Ecosystem carbon storage in arctic tundra reduced by long-term nutrient fertilization (2004)
    [s.l.] : Macmillian Magazines Ltd.
    Nature 431 (2004), S. 440-443 
    Details
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Global warming is predicted to be most pronounced at high latitudes, and observational evidence over the past 25 years suggests that this warming is already under way. One-third of the global soil carbon pool is stored in northern latitudes, so there is considerable interest in understanding ...
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1038/nature02887
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    Paper (German National Licenses)
    Fulltext
  • 3
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    DOC, CDOM, FDOM and FTICR data of Arctic tundra soil leaching experiment (2017)
    PANGAEA
    In:  Supplement to: Zhang, Xiaowen; Hutchings, Jack A; Bianchi, Thomas S; Liu, Yina; Arellano, Ana R; Schuur, Edward A G (2017): Importance of lateral flux and its percolation depth on organic carbon export in Arctic tundra soil: implications from a soil leaching experiment. Journal of Geophysical Research: Biogeosciences, https://doi.org/10.1002/2016JG003754
    Details
    Publication Date: 2023-06-27
    Description: Temperature rise in the Arctic is causing deepening of active layers and resulting in the mobilization of deep permafrost dissolved organic matter (DOM). However, the mechanisms of DOM mobilization from Arctic soils, especially upper soil horizons which are drained most frequently through a year, are poorly understood. Here, we conducted a short-term leaching experiment on surface and deep organic active layer soils, from the Yukon River basin, to examine the effects of DOM transport on bulk and molecular characteristics. Our data showed a net release of DOM from surface soils equal to an average of 5% of soil carbon. Conversely, deep soils percolated with surface leachates retained up to 27% of bulk DOM-while releasing fluorescent components (up to 107%), indicating selective release of aromatic components (e.g. lignin, tannin), while retaining non-chromophoric components, as supported by spectrofluorometric and ultra high resolution mass spectroscopic techniques. Our findings highlight the importance of the lateral flux of DOM on ecosystem carbon balance as well as processing of DOM transport through organic active layer soils en route to rivers and streams. This work also suggests the potential role of leachate export as an important mechanism of C losses from Arctic soils, in comparison with the more traditional pathway from soil to atmosphere in a warming Arctic.
    Keywords: Alaska, USA; CDRILL; Core drilling; Eight-Mile-Lake; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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    DATA PANGAEA
  • 4
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    Geochemical, lithological, and geochronological characteristics of sediment samples from thermokarst deposits in Siberia and Alaska 1998-2016 (2020)
    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Details
    Publication Date: 2024-01-27
    Keywords: Age, dated; Age, error; Age, radiocarbon; Alaskan North Slope; AWI_Perma; Carbon, organic, total; Central Laptev Sea; climate feedbacks; Density, bulk, permafrost; DEPTH, sediment/rock; Dmitry Laptev Strait; Event label; Greenhouse gas source; Height above sea level; Ice content, intrasedimentary ice; Identification; IPA Action Group: The Yedoma Region; Kolyma Lowland; Late Pleistocene; Latitude of event; Lena Delta; Longitude of event; MULT; Multiple investigations; New Siberian Achipelago; Permafrost; Permafrost Research; PETA-CARB; PETA-CARB_ID1; PETA-CARB_ID14; PETA-CARB_ID15; PETA-CARB_ID17; PETA-CARB_ID18; PETA-CARB_ID19; PETA-CARB_ID22; PETA-CARB_ID4; PETA-CARB_ID6; PETA-CARB_ID8; PETA-CARB_ID9; Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool; Sample code/label; Seward Peninsula; thermokarst; Western Laptev Sea; Yedoma; Yedoma_Region; δ13C
    Type: Dataset
    Format: text/tab-separated-values, 1553 data points
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    DATA PANGAEA
  • 5
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    Geochemical, lithological, and geochronological characteristics of sediment samples from Yedoma and thermokarst deposit sites in Siberia and Alaska 1998-2016 (2020)
    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Details
    Publication Date: 2024-01-27
    Keywords: Alaska; Alaskan North Slope; Area/locality; AWI_Perma; Beaufort Sea; Central Laptev Sea; climate feedbacks; Coverage; Density, bulk, permafrost; Dmitry Laptev Strait; Event label; Greenhouse gas source; Identification; IPA Action Group: The Yedoma Region; Kolyma Lowland; Late Pleistocene; LATITUDE; Layer thickness; Lena Delta; LONGITUDE; MULT; Multiple investigations; New Siberian Achipelago; Permafrost; Permafrost Research; PETA-CARB; PETA-CARB_ID1; PETA-CARB_ID10; PETA-CARB_ID11; PETA-CARB_ID12; PETA-CARB_ID13; PETA-CARB_ID14; PETA-CARB_ID15; PETA-CARB_ID16; PETA-CARB_ID17; PETA-CARB_ID18; PETA-CARB_ID19; PETA-CARB_ID2; PETA-CARB_ID20; PETA-CARB_ID21; PETA-CARB_ID22; PETA-CARB_ID23; PETA-CARB_ID24; PETA-CARB_ID25; PETA-CARB_ID26; PETA-CARB_ID27; PETA-CARB_ID3; PETA-CARB_ID4; PETA-CARB_ID5; PETA-CARB_ID6; PETA-CARB_ID7; PETA-CARB_ID8; PETA-CARB_ID9; Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool; Sample amount; Seward Peninsula; Site; thermokarst; Western Laptev Sea; Yedoma; Yedoma_Region
    Type: Dataset
    Format: text/tab-separated-values, 193 data points
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    DATA PANGAEA
  • 6
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    Geochemical, lithological, and geochronological characteristics of sediment samples from Yedoma deposits in Siberia and Alaska 1998-2016 (2020)
    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Details
    Publication Date: 2024-01-27
    Keywords: Age, dated; Age, error; Age, radiocarbon; Alaska; Alaskan North Slope; AWI_Perma; Beaufort Sea; Carbon, organic, total; Central Laptev Sea; climate feedbacks; Density, bulk, permafrost; DEPTH, sediment/rock; Dmitry Laptev Strait; Event label; Greenhouse gas source; Height above sea level; Ice content, intrasedimentary ice; Ice wedge content; Identification; IPA Action Group: The Yedoma Region; Kolyma Lowland; Late Pleistocene; Latitude of event; Lena Delta; Longitude of event; MULT; Multiple investigations; New Siberian Achipelago; Permafrost; Permafrost Research; PETA-CARB; PETA-CARB_ID1; PETA-CARB_ID10; PETA-CARB_ID11; PETA-CARB_ID12; PETA-CARB_ID13; PETA-CARB_ID14; PETA-CARB_ID15; PETA-CARB_ID16; PETA-CARB_ID17; PETA-CARB_ID2; PETA-CARB_ID20; PETA-CARB_ID21; PETA-CARB_ID22; PETA-CARB_ID23; PETA-CARB_ID24; PETA-CARB_ID25; PETA-CARB_ID26; PETA-CARB_ID27; PETA-CARB_ID3; PETA-CARB_ID4; PETA-CARB_ID5; PETA-CARB_ID6; PETA-CARB_ID7; PETA-CARB_ID8; PETA-CARB_ID9; Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool; Sample code/label; thermokarst; Western Laptev Sea; Yedoma; Yedoma_Region; δ13C
    Type: Dataset
    Format: text/tab-separated-values, 5074 data points
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    DATA PANGAEA
  • 7
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    Geochemical, lithological, and geochronological characteristics of sediment samples from Yedoma and thermokarst deposits in Siberia and Alaska 1998-2016 (2020)
    PANGAEA
    Details
    Publication Date: 2024-01-27
    Description: This dataset merges data from the yedoma domain in Northern Siberia (RU) and Alaska (US). It includes numerous fieldwork campaigns, which take place since 1998 . In total 224 samples from drained Thermokarst, basins and 736 Yedoma samples are included from 27 sites (17 Siberia, 10 Alaska). The laboratory methods are the following: Total organic carbon (TOC) samples were measured with a carbon-nitrogen-sulphur analyser (Elementar Vario EL III) or a TOC analyser (Elementar Vario Max C). For ice content measurement needed for bulk density calculation (bulkdens), samples were weighed in wet and ovendry state during field expeditions or dried in the lab using a freeze dryer. BD was then calculated using its inverse relationship with porosity (see Strauss et al 2013 for details)). Because pore volume is assumed to be ice saturated, the pore volume can be directly inferred from the segregated ice content. Ice content was determined by dying in the file already or with an freeze dryer in the lab. 14C dates were compiled from different sources given with locations in Table S1 in the supplement of Strauss et al 2017. Areal estimation of yedoma and degraded sites were done with literature estimates including general estimates in Strauss et al 2013. Data from local- and regional-scale analyses of Yedoma deposit versus thermokarst-affected areas (summarised in Strauss et al 2013) indicate that ~70% of the Yedoma region area is affected by degradation. The remaining Yedoma deposit extent is ~416,000 km². We further estimate that ~10% of the Yedoma region is covered with lakes and rivers and thus underlain by unfrozen deposits (150,000 km²) and ~4% is covered with other deposits including deltaic and fluvial sediments (50,000 km²), leaving ~56% (775,000 km²) of the Yedoma region covered by frozen thermokarst deposits in drained thermokarst lakes. Detailed information about the methods can be found in Strauss et al 2013 and 2017 and the supplements (https://doi.org/doi:10.1002/2013GL058088, https://doi.org/10.1016/j.earscirev.2017.07.007).
    Keywords: AWI_Perma; AWI Arctic Land Expedition; Beringia/Kolyma_2008; BeringiaKolyma_2008_all; climate feedbacks; Greenhouse gas source; IPA Action Group: The Yedoma Region; Kytalyk2011; Kytalyk2011_all; Late Pleistocene; Lena2002_all; Lena2002, Laptev_Sea_2002; Lena2004; Lena2004_all; Lena2005; Lena2005_all; Lena2006; Lena2006_all; Lena2007; Lena2007_all; Lena2008; Lena2008_all; Lena2009; Lena2009_all; Lena2010; Lena2010_all; Lena2011; Lena2011_all; Lena2012; Lena2012_all; Lena2013; Lena2013_all; Lena2016_spring_all; Lena2016_spring, Lena2016_summer; Lena2016_summer_all; Lena-Anabar2003; Lena-Anabar2003_all; Lena-Delta1998; Lena-Delta1998_all; Lena-Delta1999; Lena-Delta1999_all; Lena-Delta2000; Lena-Delta2000_all; Lena-Delta2001; Lena-Delta2001_all; Lena-Delta2002_all; MULT; Multiple investigations; Permafrost; Permafrost Research; PETA-CARB; Rapid Permafrost Thaw in a Warming Arctic and Impacts on the Soil Organic Carbon Pool; RU-Land_1998_Lena; RU-Land_1999_Lena; RU-Land_2000_Lena; RU-Land_2001_Lena; RU-Land_2002_Lena; RU-Land_2003_Lena; RU-Land_2004_Lena; RU-Land_2005_Lena; RU-Land_2006_Lena; RU-Land_2007_Lena; RU-Land_2008_Kolyma; RU-Land_2008_Lena; RU-Land_2009_Lena; RU-Land_2010_Lena; RU-Land_2011_Kytalyk; RU-Land_2011_Lena; RU-Land_2012_Lena; RU-Land_2013_Lena; RU-Land_2016_Lena; thermokarst; Yedoma; Yedoma_Region
    Type: Dataset
    Format: application/zip, 3 datasets
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    DATA PANGAEA
  • 8
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    Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-12
    Description: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In-situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. Therefore, we here provide four datasets comprising: 1. Harmonized, standardized and aggregated in situ observations of SEB components at 64 vegetated and glaciated sites north of 60° latitude, in the time period 1994-2021 2. A description of all study sites and associated environmental conditions, including the vegetation types, which correspond to the classification of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). 3. Data generated in a literature synthesis from 358 study sites on vegetation or glacier (〉=60°N latitude) covered by 148 publications. 4. Metadata, including data contributor information and measurement heights of variables associated with Oehri et al. 2022.
    Keywords: Arctic; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; dry tundra; Eddy covariance; eddy heat flux; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Land-Atmosphere; Land-cover; latent and sensible heat; latent heat flux; longwave radiation; meteorological data; observatory data; Peat bog; Radiation fluxes; Radiative energy budget; sensible heat flux; shortwave radiation; shrub tundra; surface energy balance; synthetic data; tundra vegetation; wetland
    Type: Dataset
    Format: application/zip, 4 datasets
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    DATA PANGAEA
  • 9
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    Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Metadata (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-12
    Description: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset contains metadata information about surface energy budget components measured at 64 tundra and glacier sites 〉60° N across the Arctic. This information was taken from the open-access repositories FLUXNET, Ameriflux, AON, GC-Net and PROMICE. The contained datasets are associated with the publication vegetation type as an important predictor of the Arctic Summer Land Surface Energy Budget by Oehri et al. 2022, and intended to support research of surface energy budgets and their relationship with environmental conditions, in particular vegetation characteristics across the terrestrial Arctic.
    Keywords: Aggregation type; Arctic; Arctic_SEB_CA-SCB; Arctic_SEB_CP1; Arctic_SEB_Dye-2; Arctic_SEB_EGP; Arctic_SEB_FI-Lom; Arctic_SEB_GL-NuF; Arctic_SEB_GL-ZaF; Arctic_SEB_GL-ZaH; Arctic_SEB_KAN_B; Arctic_SEB_KAN_L; Arctic_SEB_KAN_M; Arctic_SEB_KAN_U; Arctic_SEB_KPC_L; Arctic_SEB_KPC_U; Arctic_SEB_MIT; Arctic_SEB_NASA-E; Arctic_SEB_NASA-SE; Arctic_SEB_NASA-U; Arctic_SEB_NUK_K; Arctic_SEB_NUK_L; Arctic_SEB_NUK_N; Arctic_SEB_NUK_U; Arctic_SEB_QAS_A; Arctic_SEB_QAS_L; Arctic_SEB_QAS_M; Arctic_SEB_QAS_U; Arctic_SEB_RU-Che; Arctic_SEB_RU-Cok; Arctic_SEB_RU-Sam; Arctic_SEB_RU-Tks; Arctic_SEB_RU-Vrk; Arctic_SEB_Saddle; Arctic_SEB_SCO_L; Arctic_SEB_SCO_U; Arctic_SEB_SE-St1; Arctic_SEB_SJ-Adv; Arctic_SEB_SJ-Blv; Arctic_SEB_SouthDome; Arctic_SEB_Summit; Arctic_SEB_TAS_A; Arctic_SEB_TAS_L; Arctic_SEB_TAS_U; Arctic_SEB_THU_L; Arctic_SEB_THU_U; Arctic_SEB_Tunu-N; Arctic_SEB_UPE_L; Arctic_SEB_UPE_U; Arctic_SEB_US-A03; Arctic_SEB_US-A10; Arctic_SEB_US-An1; Arctic_SEB_US-An2; Arctic_SEB_US-An3; Arctic_SEB_US-Atq; Arctic_SEB_US-Brw; Arctic_SEB_US-EML; Arctic_SEB_US-HVa; Arctic_SEB_US-ICh; Arctic_SEB_US-ICs; Arctic_SEB_US-ICt; Arctic_SEB_US-Ivo; Arctic_SEB_US-NGB; Arctic_SEB_US-Upa; Arctic_SEB_US-xHE; Arctic_SEB_US-xTL; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; Author(s); Data source; Date/Time of event; Day of the year; Description; dry tundra; Eddy covariance; eddy heat flux; Event label; Field observation; First year of observation; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Institution; Instrument; Land-Atmosphere; Land-cover; Last year of observation; latent and sensible heat; latent heat flux; LATITUDE; Location ID; LONGITUDE; longwave radiation; meteorological data; Method comment; observatory data; Peat bog; Radiation fluxes; Radiative energy budget; Sample height; sensible heat flux; shortwave radiation; shrub tundra; surface energy balance; synthetic data; tundra vegetation; Type of study; Unit; Variable; wetland
    Type: Dataset
    Format: text/tab-separated-values, 20562 data points
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    DATA PANGAEA
  • 10
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    Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Surface energy budget componenent data (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-12
    Description: Despite the importance of surface energy budgets (SEBs) for land-climate interactions in the Arctic, uncertainties in their prediction persist. In situ observational data of SEB components - useful for research and model validation - are collected at relatively few sites across the terrestrial Arctic, and not all available datasets are readily interoperable. Furthermore, the terrestrial Arctic consists of a diversity of vegetation types, which are generally not well represented in land surface schemes of current Earth system models. This dataset comprises harmonized, standardized and aggregated in-situ observations of surface energy budget components measured at 64 sites on vegetated and glaciated sites north of 60° latitude, in the time period from 1994 till 2021. The surface energy budget components include net radiation, sensible heat flux, latent heat flux, ground heat flux, net shortwave radiation, net longwave radiation, surface temperature and albedo, which were aggregated to daily mean, minimum and maximum values from hourly and half-hourly measurements. Data were retrieved from the monitoring networks FLUXNET, AmeriFlux, AON, GC-Net and PROMICE.
    Keywords: Albedo; Albedo, maximum; Albedo, minimum; Arctic; Arctic_SEB_CA-SCB; Arctic_SEB_CP1; Arctic_SEB_Dye-2; Arctic_SEB_EGP; Arctic_SEB_FI-Lom; Arctic_SEB_GL-NuF; Arctic_SEB_GL-ZaF; Arctic_SEB_GL-ZaH; Arctic_SEB_KAN_B; Arctic_SEB_KAN_L; Arctic_SEB_KAN_M; Arctic_SEB_KAN_U; Arctic_SEB_KPC_L; Arctic_SEB_KPC_U; Arctic_SEB_MIT; Arctic_SEB_NASA-E; Arctic_SEB_NASA-SE; Arctic_SEB_NASA-U; Arctic_SEB_NUK_K; Arctic_SEB_NUK_L; Arctic_SEB_NUK_N; Arctic_SEB_NUK_U; Arctic_SEB_QAS_A; Arctic_SEB_QAS_L; Arctic_SEB_QAS_M; Arctic_SEB_QAS_U; Arctic_SEB_RU-Che; Arctic_SEB_RU-Cok; Arctic_SEB_RU-Sam; Arctic_SEB_RU-Tks; Arctic_SEB_RU-Vrk; Arctic_SEB_Saddle; Arctic_SEB_SCO_L; Arctic_SEB_SCO_U; Arctic_SEB_SE-St1; Arctic_SEB_SJ-Adv; Arctic_SEB_SJ-Blv; Arctic_SEB_SouthDome; Arctic_SEB_Summit; Arctic_SEB_TAS_A; Arctic_SEB_TAS_L; Arctic_SEB_TAS_U; Arctic_SEB_THU_L; Arctic_SEB_THU_U; Arctic_SEB_Tunu-N; Arctic_SEB_UPE_L; Arctic_SEB_UPE_U; Arctic_SEB_US-A03; Arctic_SEB_US-A10; Arctic_SEB_US-An1; Arctic_SEB_US-An2; Arctic_SEB_US-An3; Arctic_SEB_US-Atq; Arctic_SEB_US-Brw; Arctic_SEB_US-EML; Arctic_SEB_US-HVa; Arctic_SEB_US-ICh; Arctic_SEB_US-ICs; Arctic_SEB_US-ICt; Arctic_SEB_US-Ivo; Arctic_SEB_US-NGB; Arctic_SEB_US-Upa; Arctic_SEB_US-xHE; Arctic_SEB_US-xTL; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; Bowen ratio; Calculated from Ground heat, flux / Net radiation; Calculated from Heat, flux, latent / Net radiation; Calculated from Heat, flux, sensible / Heat, flux, latent; Calculated from Heat, flux, sensible / Net radiation; Calculated from Heat, flux, sensible + Heat, flux, latent + Ground heat, flux; Calculated from Long-wave downward radiation, maximum - Long-wave upward radiation, maximum; Calculated from Long-wave downward radiation, minimum - Long-wave upward radiation, minimum; Calculated from Long-wave downward radiation - Long-wave upward radiation; Calculated from Long-wave net radiation / Net radiation; Calculated from Short-wave downward (GLOBAL) radiation, maximum - Short-wave upward (REFLEX) radiation, maximum; Calculated from Short-wave downward (GLOBAL) radiation, minimum - Short-wave upward (REFLEX) radiation, minimum; Calculated from Short-wave downward (GLOBAL) radiation - Short-wave upward (REFLEX) radiation; Calculated from Short-wave net radiation, maximum + Long-wave net radiation, maximum; Calculated from Short-wave net radiation, minimum + Long-wave net radiation, minimum; Calculated from Short-wave net radiation / Net radiation; Calculated from Short-wave net radiation + Long-wave net radiation; Calculated from Short-wave upward (REFLEX) radiation / Short-wave downward (GLOBAL) radiation; Calculated from Surface temperature, maximum - Temperature, air, maximum; Calculated from Surface temperature, minimum - Temperature, air, minimum; Calculated from Surface temperature - Temperature, air; Cloud coverage; Cloud coverage, maximum; Cloud coverage, minimum; Daily maximum; Daily mean; Daily minimum; Data source; DATE/TIME; Day of the year; dry tundra; Eddy covariance; eddy heat flux; ELEVATION; Event label; Field observation; glacier; graminoids; Ground heat, flux; Ground heat, flux, maximum; Ground heat, flux, minimum; Ground heat, flux/Net radiation ratio; ground heat flux and net radiation; harmonized data; Heat, flux, latent; Heat, flux, latent, maximum; Heat, flux, latent, minimum; Heat, flux, latent/Net radiation ratio; Heat, flux, sensible; Heat, flux, sensible, maximum; Heat, flux, sensible, minimum; Heat flux, sensible/Net radiation ratio; high latitude; Humidity, relative; Humidity, relative, maximum; Humidity, relative, minimum; Land-Atmosphere; Land-cover; latent and sensible heat; latent heat flux; LATITUDE; Location ID; LONGITUDE; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave net radiation; Long-wave net radiation, maximum; Long-wave net radiation, minimum; Long-wave net radiation/Net radiation ratio; longwave radiation; Long-wave upward radiation; Long-wave upward radiation, maximum; Long-wave upward radiation, minimum; meteorological data; Month; Net radiation; Net radiation, maximum; Net radiation, minimum; Normalized by X / Potential incoming solar radiation, maximum * 100; observatory data; Original variable; Peat bog; Potential incoming solar radiation; Potential incoming solar radiation, maximum; Potential incoming solar radiation, minimum; Precipitation; Precipitation, daily, maximum; Precipitation, daily, minimum; Pressure, atmospheric; Pressure, atmospheric, maximum; Pressure, atmospheric, minimum; Radiation fluxes; Radiative energy budget; sensible heat flux; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave net radiation; Short-wave net radiation, maximum; Short-wave net radiation, minimum; Short-wave net radiation/Net radiation ratio; shortwave radiation; Short-wave upward (REFLEX) radiation; Short-wave upward (REFLEX) radiation, maximum; Short-wave upward (REFLEX) radiation, minimum; shrub tundra; Soil water content, volumetric; Soil water content, volumetric, maximum; Soil water content, volumetric, minimum; surface energy balance; Surface temperature; Surface temperature, maximum; Surface temperature, minimum; synthetic data; Temperature, air; Temperature, air, maximum; Temperature, air, minimum; Temperature, soil; Temperature, soil, maximum; Temperature, soil, minimum; Temperature gradient, 0-2m above surface; Temperature gradient, 0-2m above surface, maximum; Temperature gradient, 0-2m above surface, minimum; tundra vegetation; Type of study; Vapour pressure deficit; Vapour pressure deficit, maximum; Vapour pressure deficit, minimum; wetland; Wind direction; Wind speed; Wind speed, maximum; Wind speed, minimum; Year of observation
    Type: Dataset
    Format: text/tab-separated-values, 17112737 data points
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