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Research data keyboard_double_arrow_right Dataset , Other dataset type 2018 EnglishPANGAEA NSERC, EC | NunataryukNSERC ,EC| NunataryukCouture, Nicole; Irrgang, Anna Maria; Pollard, Wayne H; Lantuit, Hugues; Fritz, Michael;Narrowing uncertainties about carbon cycling is important in the Arctic where rapid environmental changes contribute to enhanced mobilization of carbon. Here we quantify soil organic carbon (SOC) contents of permafrost soils along the Yukon Coastal Plain and determine the annual fluxes from erosion. Different terrain units are assessed based on surficial geology, morphology, and ground ice conditions. To account for the volume of wedge ice and massive ice in a unit, sample SOC contents are reduced by 19% and sediment contents by 16%. The SOC content in a 1 m**2 column of soil varies according to the height of the bluff, ranging from 30 to 662 kg, with a mean value of 183 kg. Forty-four per cent of the SOC is within the top 1 m of soil and values vary based on surficial materials, ranging from 30 to 53 kg C/m**3, with a mean of 41 kg. Eighty per cent of the shoreline is erosive with a mean annual rate of change is 0.7 m/a. This results in a SOC flux per meter of shoreline of 131 kg C/m/a, and a total flux for the entire Yukon coast of 35.5 10**6 kg C/a (0.036 Tg C/a). The mean flux of sediment per meter of shoreline is 5.3 10**3 kg/m/a, with a total flux of 1,832.0 10**6 kg/a (1.832 Tg/a). Sedimentation rates indicate that approximately 13% of the eroded carbon is sequestered in nearshore sediments, where the overwhelming majority of organic carbon is of terrestrial origin. Supplement to: Couture, Nicole; Irrgang, Anna Maria; Pollard, Wayne H; Lantuit, Hugues; Fritz, Michael (2018): Coastal Erosion of Permafrost Soils Along the Yukon Coastal Plain and Fluxes of Organic Carbon to the Canadian Beaufort Sea. Journal of Geophysical Research: Biogeosciences
PANGAEA; PANGAEA - D... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceOther dataset type . 2018Data sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA; PANGAEA - D... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceOther dataset type . 2018Data sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019 EnglishPANGAEA NSF | Hindcasting the Ocean rad..., EC | NEWLOG, NSERC +23 projectsNSF| Hindcasting the Ocean radiocarbon history of the past 25,000 years ,EC| NEWLOG ,NSERC ,EC| TRACE ,EC| PACEMAKER ,NSF| Quantifying Changes in Thermohaline Circulation Rates During the Last 30 ka Using Radionuclides in Atlantic Sediments ,EC| ICE2ICE ,NSF| Collaborative Research: Insights into North African climate variability over the last 1.1 million years from dust fluxes and leaf wax isotopes ,UKRI| The bi-polar seesaw and CO2: Is there anything special about 'Terminal seesaw events'? ,ANR| RETRO ,NSF| US-France Cooperative Research: Variability in Thermohaline Circulation and North Atlantic Climate ,FCT| SFRH/BPD/1588/2000 ,EC| ACCLIMATE ,ARC| Discovery Early Career Researcher Award - Grant ID: DE150100107 ,UKRI| Instantaneous and inverse coupling between the South and North Atlantic during the last glacial period ,FCT| SFRH/BPD/36615/2007 ,UKRI| Changes in ocean circulation and the global carbon cycle during the last interglacial-glacial transition: Marine Isotope Stage 5a to 4 ,NSF| Collaborative Research: Bipolar Coupling of late Quaternary Ice Sheet Variability ,SNSF| SeaO2 - Past changes in Southern Ocean overturning circulation - implications for the partitioning of carbon and oxygen between the ocean and the atmosphere ,EC| PAST4FUTURE ,EC| SHARP ,UKRI| Assessing the role of millennial-scale variability in glacial-interglacial climate change ,NSF| Collaborative Research: Mathematics and Climate Change Research Network ,UKRI| Resolving the ocean's role in deglacial radiocarbon cycling (OCEAN-14) ,SNSF| Quantifying changes in the rate of North Atlantic Deep and Intermediate Water formation associated with abrupt climate changes during the late Quaternary ,UKRI| BGS-2012-DTG-Funding 2 StudentshipsAuthors: Waelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; +59 AuthorsWaelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; Pedro, Joel B; Dokken, Trond; Hajdas, Irka; Wacker, Lukas; Abbott, Peter M; Dumoulin, Jean-Pascal; Thil, François; Eynaud, Frédérique; Rossignol, Linda; Fersi, Wiem; Albuquerque, Ana Luiza Spadano; Arz, Helge Wolfgang; Austin, William EN; Came, Rosemarie E; Carlson, Anders Eskil; Collins, James A; Dennielou, Bernard; Desprat, Stéphanie; Dickson, Alex; Elliot, Mary; Farmer, Christa; Giraudeau, Jacques; Gottschalk, Julia; Henderiks, Jorijntje; Hughen, Konrad A; Jung, Simon; Knutz, Paul Cornils; Lebreiro, Susana Martin; Lund, David C; Lynch-Stieglitz, Jean; Malaizé, Bruno; Marchitto, Thomas M; Martínez Méndez, Gema; Mollenhauer, Gesine; Naughton, Filipa; Nave, Silvia Osorio; Nürnberg, Dirk; Oppo, Delia W; Peck, Victoria L; Peeters, Frank J C; Penaud, Aurélie; Portilho-Ramos, Rodrigo Costa; Repschläger, Janne; Roberts, Jenny; Rühlemann, Carsten; Salgueiro, Emilia; Sanchez Goñi, Maria Fernanda; Schönfeld, Joachim; Scussolini, Paolo; Skinner, Luke C; Skonieczny, Charlotte; Thornalley, David JR; Toucanne, Samuel; Van Rooij, David; Vidal, Laurence; Voelker, Antje H L; Wary, Mélanie; Weldeab, Syee; Ziegler, Martin;Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014 EnglishPANGAEA NSERC, EC | PAGE21NSERC ,EC| PAGE21Authors: Duguay, Claude R; Soliman, Aiman; Hachem, Sonia; Saunders, William;Duguay, Claude R; Soliman, Aiman; Hachem, Sonia; Saunders, William;This dataset is part of the ESA Data User Element (DUE) Permafrost Full Product Set (doi:10.1594/PANGAEA.780111).The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (25 km resolution) scales include weekly and monthly averages from 2000 to 2010 from which annual averages can also be calculated. The LST processing integrates the LST level 2 products from MODIS and AATSR distributed by NASA and ESA, respectively. Post-processing functions supply University Waterloo-level-3 weekly and monthly LST products for regional (1 km) and pan-Arctic (25 km) scales. Thepan-Arctic product, with a spatial resolution of 25 km, is produced by spatial averaging of 1-km observations. MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products. Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest. Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds. Each LST file contains 6 bands: the datafiles 001 to 006, bands 001, 003, 005 are the LST averages and bands 002, 004, 006 are supplementary quality information: Bands with averages of LST: 001 - Weekly or monthly aggregated average LST product based on equal weight of average day-time (003) and night-time (005) LST values. 003 - Average day-time weekly or monthly LST based on all cloud free observations falling during 6 a.m. to 6 p.m. local time. 005 - Average night-time weekly or monthly LST based on all cloud free observations falling into each pixel cell during 6 p.m. to 6 a.m. local time. Supplementary information bands: 002 - Number of LST cloud free observations falling into each pixel for the aggregation (weekly or monthly) period. Associated with LST file 001. 004 - Number of LST cloud free observations during day-time (6 a.m. to 6 p.m. local time) falling into each pixel. Associated with LST file 003. 006 - Number of LST cloud free observations during night-time (6 p.m. to 6 a.m. local time) falling into each pixel. Associated with LST file 005.
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visibility 167visibility views 167 download downloads 7 Powered bymore_vert PANGAEA - Data Publi... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020 EnglishPANGAEA UKRI | Methane and other greenho..., AKA | Short and long term effec..., AKA | Long term effects of fire... +5 projectsUKRI| Methane and other greenhouse gases in the Arctic - measurements, process studies and modelling (MAMM) ,AKA| Short and long term effects of forest fires on the stability of carbon pools in boreal forests. ,AKA| Long term effects of fire on carbon and nitrogen pools and fluxes in the arctic permafrost and subarctic forests (ARCTICFIRE) ,AKA| Mechanisms underlying large N2O emissions from cryoturbated peat soil in tundra ,AKA| Towards constraining the circumarctic nitrous oxide budget (NOCA) ,EC| PAGE21 ,AKA| Short and long term effects of forest fires on the stability of carbon pools in boreal forests ,NSERCVoigt, Carolina; van Delden, Lona; Marushchak, Maija E; Biasi, Christina; Abbott, Benjamin W; Elberling, Bo; Siciliano, Steven D; Sonnentag, Oliver; Stewart, Katherine J; Yang, Yuanhe; Martikainen, Pertti J;If not reported, water-filled pore space (WFPS) was calculated as follows: WFPS (%) = VWC/(1-BD/PD)*100, where VWC is the volumetric water content, BD is the bulk density, and PD is the particle density. If BD was not reported, BD was estimated from the SOM content using functions developed for Arctic soils (Hossain et al, 2015) as follows: 0.075+1.301*EXP(-0.06*SOM) for mineral soils, and 0.043*0+4.258*EXP(-0.047*SOM) for organic soils. If not reported, SOM via loss on ignition was derived from the soil carbon content as follows: SOM (%) = C content*2. If the resulting SOM value was >100%, SOM (%) = C content*1.724. PD can be derived as follows (Okruszko, 1971): PD = 0.011*(100-SOM)+1.451 (see references Okruszko, 1971 and Hossain et al, 2015). The term ”topsoil” depends on the exact depths the soil characteristics are reported in the individual publications, but generally the soil layer of 0–10cm was used. Column ”SOC” includes mostly total soil C content (reported in the majority of studies), and on some occasions total organic C. This dataset is a synthesis of published nitrous oxide (N2O) fluxes from permafrost-affected soils in Arctic, Antarctic, and Alpine permafrost regions. The data includes mean N2O flux rates measured under field (in situ) conditions and in intact plant-soil systems (mesocosms) under near-field conditions. The dataset further includes explanatory environmental parameters such as meteorological data, soil physical-chemical properties, as well as site and experimental information. Data has been synthesized from published studies (see 'Further details'), and in some cases the authors of published studies have been contacted for additional site-level information. The dataset includes studies published until 2019. We encourage linking additional N2O flux data from unpublished and future studies with similar metadata structure to this dataset, to produce a comprehensive, findable database for N2O fluxes from permafrost regions.
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Research data keyboard_double_arrow_right Dataset , Other dataset type 2018 EnglishPANGAEA NSERC, EC | NunataryukNSERC ,EC| NunataryukCouture, Nicole; Irrgang, Anna Maria; Pollard, Wayne H; Lantuit, Hugues; Fritz, Michael;Narrowing uncertainties about carbon cycling is important in the Arctic where rapid environmental changes contribute to enhanced mobilization of carbon. Here we quantify soil organic carbon (SOC) contents of permafrost soils along the Yukon Coastal Plain and determine the annual fluxes from erosion. Different terrain units are assessed based on surficial geology, morphology, and ground ice conditions. To account for the volume of wedge ice and massive ice in a unit, sample SOC contents are reduced by 19% and sediment contents by 16%. The SOC content in a 1 m**2 column of soil varies according to the height of the bluff, ranging from 30 to 662 kg, with a mean value of 183 kg. Forty-four per cent of the SOC is within the top 1 m of soil and values vary based on surficial materials, ranging from 30 to 53 kg C/m**3, with a mean of 41 kg. Eighty per cent of the shoreline is erosive with a mean annual rate of change is 0.7 m/a. This results in a SOC flux per meter of shoreline of 131 kg C/m/a, and a total flux for the entire Yukon coast of 35.5 10**6 kg C/a (0.036 Tg C/a). The mean flux of sediment per meter of shoreline is 5.3 10**3 kg/m/a, with a total flux of 1,832.0 10**6 kg/a (1.832 Tg/a). Sedimentation rates indicate that approximately 13% of the eroded carbon is sequestered in nearshore sediments, where the overwhelming majority of organic carbon is of terrestrial origin. Supplement to: Couture, Nicole; Irrgang, Anna Maria; Pollard, Wayne H; Lantuit, Hugues; Fritz, Michael (2018): Coastal Erosion of Permafrost Soils Along the Yukon Coastal Plain and Fluxes of Organic Carbon to the Canadian Beaufort Sea. Journal of Geophysical Research: Biogeosciences
PANGAEA; PANGAEA - D... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceOther dataset type . 2018Data sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA; PANGAEA - D... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceOther dataset type . 2018Data sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019 EnglishPANGAEA NSF | Hindcasting the Ocean rad..., EC | NEWLOG, NSERC +23 projectsNSF| Hindcasting the Ocean radiocarbon history of the past 25,000 years ,EC| NEWLOG ,NSERC ,EC| TRACE ,EC| PACEMAKER ,NSF| Quantifying Changes in Thermohaline Circulation Rates During the Last 30 ka Using Radionuclides in Atlantic Sediments ,EC| ICE2ICE ,NSF| Collaborative Research: Insights into North African climate variability over the last 1.1 million years from dust fluxes and leaf wax isotopes ,UKRI| The bi-polar seesaw and CO2: Is there anything special about 'Terminal seesaw events'? ,ANR| RETRO ,NSF| US-France Cooperative Research: Variability in Thermohaline Circulation and North Atlantic Climate ,FCT| SFRH/BPD/1588/2000 ,EC| ACCLIMATE ,ARC| Discovery Early Career Researcher Award - Grant ID: DE150100107 ,UKRI| Instantaneous and inverse coupling between the South and North Atlantic during the last glacial period ,FCT| SFRH/BPD/36615/2007 ,UKRI| Changes in ocean circulation and the global carbon cycle during the last interglacial-glacial transition: Marine Isotope Stage 5a to 4 ,NSF| Collaborative Research: Bipolar Coupling of late Quaternary Ice Sheet Variability ,SNSF| SeaO2 - Past changes in Southern Ocean overturning circulation - implications for the partitioning of carbon and oxygen between the ocean and the atmosphere ,EC| PAST4FUTURE ,EC| SHARP ,UKRI| Assessing the role of millennial-scale variability in glacial-interglacial climate change ,NSF| Collaborative Research: Mathematics and Climate Change Research Network ,UKRI| Resolving the ocean's role in deglacial radiocarbon cycling (OCEAN-14) ,SNSF| Quantifying changes in the rate of North Atlantic Deep and Intermediate Water formation associated with abrupt climate changes during the late Quaternary ,UKRI| BGS-2012-DTG-Funding 2 StudentshipsAuthors: Waelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; +59 AuthorsWaelbroeck, Claire; Lougheed, Bryan C; Vázquez Riveiros, Natalia; Missiaen, Lise; Pedro, Joel B; Dokken, Trond; Hajdas, Irka; Wacker, Lukas; Abbott, Peter M; Dumoulin, Jean-Pascal; Thil, François; Eynaud, Frédérique; Rossignol, Linda; Fersi, Wiem; Albuquerque, Ana Luiza Spadano; Arz, Helge Wolfgang; Austin, William EN; Came, Rosemarie E; Carlson, Anders Eskil; Collins, James A; Dennielou, Bernard; Desprat, Stéphanie; Dickson, Alex; Elliot, Mary; Farmer, Christa; Giraudeau, Jacques; Gottschalk, Julia; Henderiks, Jorijntje; Hughen, Konrad A; Jung, Simon; Knutz, Paul Cornils; Lebreiro, Susana Martin; Lund, David C; Lynch-Stieglitz, Jean; Malaizé, Bruno; Marchitto, Thomas M; Martínez Méndez, Gema; Mollenhauer, Gesine; Naughton, Filipa; Nave, Silvia Osorio; Nürnberg, Dirk; Oppo, Delia W; Peck, Victoria L; Peeters, Frank J C; Penaud, Aurélie; Portilho-Ramos, Rodrigo Costa; Repschläger, Janne; Roberts, Jenny; Rühlemann, Carsten; Salgueiro, Emilia; Sanchez Goñi, Maria Fernanda; Schönfeld, Joachim; Scussolini, Paolo; Skinner, Luke C; Skonieczny, Charlotte; Thornalley, David JR; Toucanne, Samuel; Van Rooij, David; Vidal, Laurence; Voelker, Antje H L; Wary, Mélanie; Weldeab, Syee; Ziegler, Martin;Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2014 EnglishPANGAEA NSERC, EC | PAGE21NSERC ,EC| PAGE21Authors: Duguay, Claude R; Soliman, Aiman; Hachem, Sonia; Saunders, William;Duguay, Claude R; Soliman, Aiman; Hachem, Sonia; Saunders, William;This dataset is part of the ESA Data User Element (DUE) Permafrost Full Product Set (doi:10.1594/PANGAEA.780111).The Land Surface Temperature (LST) products and services identified by users for the pan-Arctic (25 km resolution) scales include weekly and monthly averages from 2000 to 2010 from which annual averages can also be calculated. The LST processing integrates the LST level 2 products from MODIS and AATSR distributed by NASA and ESA, respectively. Post-processing functions supply University Waterloo-level-3 weekly and monthly LST products for regional (1 km) and pan-Arctic (25 km) scales. Thepan-Arctic product, with a spatial resolution of 25 km, is produced by spatial averaging of 1-km observations. MOD11_L2 and MYD11_L2 LST (Version 5 from NASA Terra and Aqua satellites) and ATS_NR_2P (from ESA Envisat satellite) products at 1 km resolution are used as input data to generate pan-Arctic and regional products. The original geo-located LST observations are characterized by an irregular distribution based on the satellite orbits. The Northern Hemisphere EASE-Grid Lambert Equal Area Azimuthal projection with a sphere datum (with a radius of 6371.228 km) was selected as the standard projection for the operational pan-Arctic and regional products. Original MODIS and AATSR LST level 2 observations are projected using the EASE-Grid coordinate system and interpolated to a regular EASE-Grid with 1 km spacing using triangulation. The EASE-Grid projection was chosen since this is the system adopted by the GlobSnow project and for most snow and ice products distributed by NSIDC. Local time is calculated using UTC acquisition time and longitude. UTC is extracted from ADS information for AATSR data and from the file name of MODIS level 2 (Terra and Aqua) products, yielding a temporal accuracy of ± 15 minutes, which is found to be sufficient for weekly and monthly products. Temporal aggregation is applied to both 1 km and 25 km data to produce weekly and monthly LST averages. Interpolated LST observations on a 1 km grid (regional product) and 25 km (pan-Arctic product) are aggregated into two bins; a day-time bin (from 6 a.m. to 6 p.m. local time) and a night-time bin (6 p.m. to 6 a.m. of the next day) within the aggregation period (week or month). The definition of day and night does not take in account the notion of polar darkness and does not consider the seasonal changes of day length. It was defined to force final products to have an equal number of observations around the day. A mid range average is calculated by taking the day-time and night-time average to avoid daily diurnal fluctuations during the week or month of interest. Known issues: the LST data are all measured during clear-sky conditions. The influence of clouds on surface temperature (e.g. temperature warmer under clouds in winter) is not reflected in the LSTs. This makes the LST colder than in reality due to the isolative effect of clouds. Each LST file contains 6 bands: the datafiles 001 to 006, bands 001, 003, 005 are the LST averages and bands 002, 004, 006 are supplementary quality information: Bands with averages of LST: 001 - Weekly or monthly aggregated average LST product based on equal weight of average day-time (003) and night-time (005) LST values. 003 - Average day-time weekly or monthly LST based on all cloud free observations falling during 6 a.m. to 6 p.m. local time. 005 - Average night-time weekly or monthly LST based on all cloud free observations falling into each pixel cell during 6 p.m. to 6 a.m. local time. Supplementary information bands: 002 - Number of LST cloud free observations falling into each pixel for the aggregation (weekly or monthly) period. Associated with LST file 001. 004 - Number of LST cloud free observations during day-time (6 a.m. to 6 p.m. local time) falling into each pixel. Associated with LST file 003. 006 - Number of LST cloud free observations during night-time (6 p.m. to 6 a.m. local time) falling into each pixel. Associated with LST file 005.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020 EnglishPANGAEA UKRI | Methane and other greenho..., AKA | Short and long term effec..., AKA | Long term effects of fire... +5 projectsUKRI| Methane and other greenhouse gases in the Arctic - measurements, process studies and modelling (MAMM) ,AKA| Short and long term effects of forest fires on the stability of carbon pools in boreal forests. ,AKA| Long term effects of fire on carbon and nitrogen pools and fluxes in the arctic permafrost and subarctic forests (ARCTICFIRE) ,AKA| Mechanisms underlying large N2O emissions from cryoturbated peat soil in tundra ,AKA| Towards constraining the circumarctic nitrous oxide budget (NOCA) ,EC| PAGE21 ,AKA| Short and long term effects of forest fires on the stability of carbon pools in boreal forests ,NSERCVoigt, Carolina; van Delden, Lona; Marushchak, Maija E; Biasi, Christina; Abbott, Benjamin W; Elberling, Bo; Siciliano, Steven D; Sonnentag, Oliver; Stewart, Katherine J; Yang, Yuanhe; Martikainen, Pertti J;If not reported, water-filled pore space (WFPS) was calculated as follows: WFPS (%) = VWC/(1-BD/PD)*100, where VWC is the volumetric water content, BD is the bulk density, and PD is the particle density. If BD was not reported, BD was estimated from the SOM content using functions developed for Arctic soils (Hossain et al, 2015) as follows: 0.075+1.301*EXP(-0.06*SOM) for mineral soils, and 0.043*0+4.258*EXP(-0.047*SOM) for organic soils. If not reported, SOM via loss on ignition was derived from the soil carbon content as follows: SOM (%) = C content*2. If the resulting SOM value was >100%, SOM (%) = C content*1.724. PD can be derived as follows (Okruszko, 1971): PD = 0.011*(100-SOM)+1.451 (see references Okruszko, 1971 and Hossain et al, 2015). The term ”topsoil” depends on the exact depths the soil characteristics are reported in the individual publications, but generally the soil layer of 0–10cm was used. Column ”SOC” includes mostly total soil C content (reported in the majority of studies), and on some occasions total organic C. This dataset is a synthesis of published nitrous oxide (N2O) fluxes from permafrost-affected soils in Arctic, Antarctic, and Alpine permafrost regions. The data includes mean N2O flux rates measured under field (in situ) conditions and in intact plant-soil systems (mesocosms) under near-field conditions. The dataset further includes explanatory environmental parameters such as meteorological data, soil physical-chemical properties, as well as site and experimental information. Data has been synthesized from published studies (see 'Further details'), and in some cases the authors of published studies have been contacted for additional site-level information. The dataset includes studies published until 2019. We encourage linking additional N2O flux data from unpublished and future studies with similar metadata structure to this dataset, to produce a comprehensive, findable database for N2O fluxes from permafrost regions.
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