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  • 1
    facet.materialart.
    Unknown
    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
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
    facet.materialart.
    Unknown
    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
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
    facet.materialart.
    Unknown
    Literature synthesis data of surface energy fluxes and environmental drivers from 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. This dataset describes the data generated in a literature synthesis, covering 358 study sites on vegetation or glacier (〉=60°N latitude), which contained surface energy budget observations. The literature synthesis comprised 148 publications searched on the ISI Web of Science Core Collection.
    Keywords: Arctic; Arctic_SEB_1; Arctic_SEB_1951-2009_1; Arctic_SEB_1965-2000_1; Arctic_SEB_1965-2000_2; Arctic_SEB_1965-2000_3; Arctic_SEB_1965-2000_4; Arctic_SEB_1969-2013_1; Arctic_SEB_1970-1972_1; Arctic_SEB_1970-1979_1; Arctic_SEB_1972-2004_1; Arctic_SEB_1972-2004_10; Arctic_SEB_1972-2004_11; Arctic_SEB_1972-2004_2; Arctic_SEB_1972-2004_3; Arctic_SEB_1972-2004_4; Arctic_SEB_1972-2004_5; Arctic_SEB_1972-2004_6; Arctic_SEB_1972-2004_7; Arctic_SEB_1972-2004_8; Arctic_SEB_1972-2004_9; Arctic_SEB_1979-1995_1; Arctic_SEB_1979-1995_2; Arctic_SEB_1979-1995_3; Arctic_SEB_1979-1995_4; Arctic_SEB_1979-2005_1; Arctic_SEB_1980-1981_1; Arctic_SEB_1981-1997_1; Arctic_SEB_1981-1997_2; Arctic_SEB_1983-2005_1; Arctic_SEB_1983-2005_2; Arctic_SEB_1983-2005_3; Arctic_SEB_1984-1991_1; Arctic_SEB_1985-1989_1; Arctic_SEB_1985-2016_1; Arctic_SEB_1988-1988_1; Arctic_SEB_1988-1988_2; Arctic_SEB_1988-1988_3; Arctic_SEB_1988-1988_4; Arctic_SEB_1988-1988_5; Arctic_SEB_1989-1990_1; Arctic_SEB_1990-1991_1; Arctic_SEB_1991-1991_1; Arctic_SEB_1991-1999_1; Arctic_SEB_1991-1999_2; Arctic_SEB_1991-1999_3; Arctic_SEB_1992-1992_1; Arctic_SEB_1992-1997_1; Arctic_SEB_1994-1994_1; Arctic_SEB_1994-1994_2; Arctic_SEB_1994-1994_3; Arctic_SEB_1994-1994_4; Arctic_SEB_1994-1996_1; Arctic_SEB_1994-1996_10; Arctic_SEB_1994-1996_11; Arctic_SEB_1994-1996_12; Arctic_SEB_1994-1996_13; Arctic_SEB_1994-1996_14; Arctic_SEB_1994-1996_15; Arctic_SEB_1994-1996_16; Arctic_SEB_1994-1996_17; Arctic_SEB_1994-1996_2; Arctic_SEB_1994-1996_3; Arctic_SEB_1994-1996_4; Arctic_SEB_1994-1996_5; Arctic_SEB_1994-1996_6; Arctic_SEB_1994-1996_7; Arctic_SEB_1994-1996_8; Arctic_SEB_1994-1996_9; Arctic_SEB_1994-2008_1; Arctic_SEB_1994-2008_2; Arctic_SEB_1994-2009_1; Arctic_SEB_1994-2015_1; Arctic_SEB_1994-2015_2; Arctic_SEB_1994-2015_3; Arctic_SEB_1994-2015_4; Arctic_SEB_1994-2015_5; Arctic_SEB_1994-2015_6; Arctic_SEB_1995-1995_1; Arctic_SEB_1995-1995_2; Arctic_SEB_1995-1996_1; Arctic_SEB_1995-1997_1; Arctic_SEB_1995-1997_2; Arctic_SEB_1995-1997_3; Arctic_SEB_1995-1997_4; Arctic_SEB_1995-1998_1; Arctic_SEB_1995-1999_1; Arctic_SEB_1996-1997_1; Arctic_SEB_1996-1999_1; Arctic_SEB_1996-2005_1; Arctic_SEB_1996-2005_2; Arctic_SEB_1996-2005_3; Arctic_SEB_1997-1998_1; Arctic_SEB_1997-1999_1; Arctic_SEB_1997-2018_1; Arctic_SEB_1997-2018_10; Arctic_SEB_1997-2018_11; Arctic_SEB_1997-2018_12; Arctic_SEB_1997-2018_13; Arctic_SEB_1997-2018_14; Arctic_SEB_1997-2018_15; Arctic_SEB_1997-2018_16; Arctic_SEB_1997-2018_17; Arctic_SEB_1997-2018_18; Arctic_SEB_1997-2018_19; Arctic_SEB_1997-2018_2; Arctic_SEB_1997-2018_20; Arctic_SEB_1997-2018_21; Arctic_SEB_1997-2018_22; Arctic_SEB_1997-2018_23; Arctic_SEB_1997-2018_24; Arctic_SEB_1997-2018_25; Arctic_SEB_1997-2018_3; Arctic_SEB_1997-2018_4; Arctic_SEB_1997-2018_5; Arctic_SEB_1997-2018_6; Arctic_SEB_1997-2018_7; Arctic_SEB_1997-2018_8; Arctic_SEB_1997-2018_9; Arctic_SEB_1998-1998_1; Arctic_SEB_1998-1999_1; Arctic_SEB_1998-2000_1; Arctic_SEB_1998-2001_1; Arctic_SEB_1998-2005_1; Arctic_SEB_1998-2011_1; Arctic_SEB_1998-2011_2; Arctic_SEB_1998-2011_3; Arctic_SEB_1998-2013_1; Arctic_SEB_1999-1999_1; Arctic_SEB_1999-2000_1; Arctic_SEB_1999-2008_1; Arctic_SEB_1999-2008_2; Arctic_SEB_1999-2009_1; Arctic_SEB_1999-2014_1; Arctic_SEB_2000-2000_1; Arctic_SEB_2000-2000_2; Arctic_SEB_2000-2000_3; Arctic_SEB_2000-2000_4; Arctic_SEB_2000-2002_1; Arctic_SEB_2000-2002_2; Arctic_SEB_2000-2002_3; Arctic_SEB_2000-2003_1; Arctic_SEB_2000-2003_2; Arctic_SEB_2000-2003_3; Arctic_SEB_2000-2007_1; Arctic_SEB_2000-2007_2; Arctic_SEB_2000-2007_3; Arctic_SEB_2000-2007_4; Arctic_SEB_2000-2008_1; Arctic_SEB_2000-2010_1; Arctic_SEB_2000-2011_1; Arctic_SEB_2000-2011_10; Arctic_SEB_2000-2011_11; Arctic_SEB_2000-2011_2; Arctic_SEB_2000-2011_3; Arctic_SEB_2000-2011_4; Arctic_SEB_2000-2011_5; Arctic_SEB_2000-2011_6; Arctic_SEB_2000-2011_7; Arctic_SEB_2000-2011_8; Arctic_SEB_2000-2011_9; Arctic_SEB_2000-2014_1; Arctic_SEB_2001-2003_1; Arctic_SEB_2002-2002_1; Arctic_SEB_2002-2003_1; Arctic_SEB_2002-2003_2; Arctic_SEB_2002-2004_1; Arctic_SEB_2002-2010_1; Arctic_SEB_2002-2012_1; Arctic_SEB_2002-2012_2; Arctic_SEB_2002-2012_3; Arctic_SEB_2003-2003_1; Arctic_SEB_2003-2004_1; Arctic_SEB_2003-2007_1; Arctic_SEB_2003-2008_1; Arctic_SEB_2003-2008_2; Arctic_SEB_2003-2010_1; Arctic_SEB_2003-2010_2; Arctic_SEB_2003-2010_3; Arctic_SEB_2003-2011_1; Arctic_SEB_2004-2004_1; Arctic_SEB_2004-2006_1; Arctic_SEB_2004-2013_1; Arctic_SEB_2005-2005_1; Arctic_SEB_2006-2006_1; Arctic_SEB_2006-2006_2; Arctic_SEB_2006-2007_1; Arctic_SEB_2006-2007_10; Arctic_SEB_2006-2007_11; Arctic_SEB_2006-2007_12; Arctic_SEB_2006-2007_13; Arctic_SEB_2006-2007_14; Arctic_SEB_2006-2007_2; Arctic_SEB_2006-2007_3; Arctic_SEB_2006-2007_4; Arctic_SEB_2006-2007_5; Arctic_SEB_2006-2007_6; Arctic_SEB_2006-2007_7; Arctic_SEB_2006-2007_8; Arctic_SEB_2006-2007_9; Arctic_SEB_2006-2008_1; Arctic_SEB_2006-2008_2; Arctic_SEB_2006-2009_1; Arctic_SEB_2007-2007_1; Arctic_SEB_2007-2008_1; Arctic_SEB_2007-2009_1; Arctic_SEB_2007-2009_2; Arctic_SEB_2007-2010_1; Arctic_SEB_2007-2014_1; Arctic_SEB_2007-2015_1; Arctic_SEB_2007-2015_2; Arctic_SEB_2008-2008_1; Arctic_SEB_2008-2008_2; Arctic_SEB_2008-2008_3; Arctic_SEB_2008-2009_1; Arctic_SEB_2008-2010_1; Arctic_SEB_2008-2010_2; Arctic_SEB_2008-2010_3; Arctic_SEB_2008-2011_1; Arctic_SEB_2008-2012_1; Arctic_SEB_2008-2012_2; Arctic_SEB_2008-2012_3; Arctic_SEB_2009-2012_1; Arctic_SEB_2009-2012_2; Arctic_SEB_2009-2012_3; Arctic_SEB_2009-2012_4; Arctic_SEB_2009-2012_5; Arctic_SEB_2009-2014_1; Arctic_SEB_2009-2014_2; Arctic_SEB_2010-2014_1; Arctic_SEB_2010-2014_2; Arctic_SEB_2010-2014_3; Arctic_SEB_2010-2014_4; Arctic_SEB_2010-2014_5; Arctic_SEB_2011-2011_1; Arctic_SEB_2011-2013_1; Arctic_SEB_2011-2014_1; Arctic_SEB_2012-2012_1; Arctic_SEB_2012-2013_1; Arctic_SEB_2012-2013_2; Arctic_SEB_2012-2013_3; Arctic_SEB_2012-2013_4; Arctic_SEB_2012-2014_1; Arctic_SEB_2012-2015_1; Arctic_SEB_2012-2015_2; Arctic_SEB_2012-2015_3; Arctic_SEB_2012-2015_4; Arctic_SEB_2012-2015_5; Arctic_SEB_2013-2013_1; Arctic_SEB_2013-2014_1; Arctic_SEB_2013-2015_1; Arctic_SEB_2013-2015_2; Arctic_SEB_2013-2015_3; Arctic_SEB_2014-2014_1; Arctic_SEB_2014-2015_1; Arctic_SEB_2014-2016_1; Arctic_SEB_2015-2015_1; Arctic_SEB_2015-2015_2; Arctic_SEB_2015-2015_3; ArcticTundraSEB; Arctic Tundra Surface Energy Budget; Author(s); Classification; Comment; Data collection methodology; Data type; Date/Time of event; dry tundra; Eddy covariance; eddy heat flux; ELEVATION; Energy budget, description; Event label; Field observation; First year of observation; glacier; glaciers; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Identification; Journal/report title; Land-Atmosphere; Land-cover; Last year of observation; latent and sensible heat; latent heat flux; LATITUDE; Location; LONGITUDE; longwave radiation; meteorological data; observatory data; Peat bog; Persistent Identifier; Publication type; Radiation fluxes; Radiative energy budget; Resolution; Season; sensible heat flux; shortwave radiation; shrub tundra; Spatial coverage; surface energy balance; synthetic data; Title; tundra vegetation; Type of study; Variable; Vegetation type; wetland; wetlands; Year of publication
    Type: Dataset
    Format: text/tab-separated-values, 8650 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 4
    facet.materialart.
    Unknown
    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
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
    facet.materialart.
    Unknown
    Harmonized in-situ observations of surface energy fluxes and environmental drivers at 64 Arctic vegetation and glacier sites - Environmental conditions (2022)
    PANGAEA
    Details
    Publication Date: 2024-05-05
    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 describes the environmental conditions for 64 tundra and glacier sites (〉=60°N latitude) across the Arctic, for which in situ measurements of surface energy budget components were harmonized (see Oehri et al. 2022). These environmental conditions are (proxies of) potential drivers of SEB-components and could therefore be called SEB-drivers. The associated environmental conditions, include the vegetation types graminoid tundra, prostrate dwarf-shrub tundra, erect-shrub tundra, wetland complexes, barren complexes (≤ 40% horizontal plant cover), boreal peat bogs and glacier. These land surface types (apart from boreal peat bogs) correspond to the main classification units of the Circumpolar Arctic Vegetation Map (CAVM, Raynolds et al. 2019). For each site, additional climatic and biophysical variables are available, including cloud cover, snow cover duration, permafrost characteristics, climatic conditions and topographic conditions.
    Keywords: 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; Aspect; Aspect, coefficient of variation; Calculated average/mean values; Cloud cover; Cloud cover, standard deviation; Cloud top pressure; Cloud top pressure, standard deviation; Cloud top temperature; Cloud top temperature, standard deviation; Conrad's continentality index; Daily maximum; Daily mean; Data source; Date/Time of event; dry tundra; Eddy covariance; eddy heat flux; ELEVATION; Elevation, standard deviation; Event label; Field observation; glacier; graminoids; ground heat flux and net radiation; harmonized data; high latitude; Humidity, relative; Land-Atmosphere; Land-cover; Land cover classes; Land cover type; latent and sensible heat; latent heat flux; LATITUDE; Location ID; LONGITUDE; longwave radiation; Mean values; Median values; meteorological data; Number of vegetation types; observatory data; Peat bog; Permafrost, type; Permafrost extent; Permafrost ice content, description; Precipitation; Precipitation, coefficient of variation; Precipitation, daily, maximum; Precipitation, snow; Precipitation, sum; Pressure, atmospheric; p-value; Radiation fluxes; Radiative energy budget; Reference/source; sensible heat flux; Shannon Diversity Index; Shannon Diversity Index, maximum; shortwave radiation; shrub tundra; Site; Slope; Slope, coefficient of variation; Slope, mathematical; Snow, onset, day of the year; Snow cover, number of days; Snowfall, coefficient of variation; Snow-free days; Snow type; Soil water content, volumetric; Species present; Summer warmth index; surface energy balance; synthetic data; Temperature, air, annual mean; Temperature, air, coefficient of variation; Temperature, annual mean range; tundra vegetation; Type of study; Uniform resource locator/link to reference; Vapour pressure deficit; Vegetation type; wetland; Wind speed; Zone
    Type: Dataset
    Format: text/tab-separated-values, 4705 data points
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    DATA PANGAEA
  • 6
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    Seasonal Variations of the Relative Optical Air Mass Function for Background Aerosol and Thin Cirrus Clouds at Arctic and Antarctic Sites (2015)
    In:  EPIC3Remote Sensing, 7, pp. 7157-7180
    Details
    Publication Date: 2020-03-05
    Description: New calculations of the relative optical air mass function are made over the 0°–87° range of apparent solar zenith angle θ, for various vertical profiles of background aerosol, diamond dust and thin cirrus cloud particle extinction coefficient in the Arctic and Antarctic atmospheres. The calculations were carried out by following the Tomasi and Petkov (2014) procedure, in which the above-mentioned vertical profiles derived from lidar observations were used as weighting functions. Different sets of lidar measurements were examined, recorded using: (i) the Koldewey-Aerosol-Raman Lidar (KARL) system (AWI, Germany) at Ny-Ålesund (Spitsbergen, Svalbard) in January, April, July and October 2013; (ii) the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite-based sensor over Barrow (Alaska), Eureka (Nunavut, Canada) and Sodankylä (northern Finland), and Neumayer III, Mario Zucchelli and Mirny coastal stations in Antarctica in the local summer months of the last two years; (iii) the National Institute of Optics (INO), National Council of Research (CNR) Antarctic lidar at Dome C on the Antarctic Plateau for a typical “diamond dust” case; and (iv) the KARL lidar at Ny-Ålesund and the University of Rome/National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) lidar at Thule (northwestern Greenland) for some cirrus cloud layers in the middle and upper troposphere. The relative optical air mass calculations are compared with those obtained by Tomasi and Petkov (2014) to define the seasonal changes produced by aerosol particles, diamond dust and cirrus clouds. The results indicate that the corresponding air mass functions generally decrease as angle θ increases with rates that are proportional to the increase in the pure aerosol, diamond dust and cirrus cloud particle optical thickness.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 7
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    Synergistic use of Lagrangian dispersion and radiative transfer modelling with satellite and surface remote sensing measurements for the investigation of volcanic plumes: the Mount Etna eruption of 25–27 October 2013 (2018)
    Details
    Publication Date: 2018-03-20
    Description: In this paper we combine SO2 and ash plume dispersion modelling with satellite and surface remote sensing observations to study the regional influence of a relatively weak volcanic eruption from Mount Etna on the optical and micro-physical properties of Mediterranean aerosols. We analyse the Mount Etna eruption episode of 25–27 October 2013. The evolution of the plume along the trajectory is investigated by means of the FLEXible PARTicle Lagrangian dispersion (FLEXPART) model. The satellite data set includes true colour images, retrieved values of volcanic SO2 and ash, estimates of SO2 and ash emission rates derived from MODIS (MODerate resolution Imaging Spectroradiometer) observations and estimates of cloud top pressure from SEVIRI (Spinning Enhanced Visible and InfraRed Imager). Surface remote sensing measurements of aerosol and SO2 made at the ENEA Station for Climate Observations (35.52 N, 12.63 E; 50ma.s.l.) on the island of Lampedusa are used in the analysis. The combination of these different data sets suggests that SO2 and ash, despite the initial injection at about 7.0 km altitude, reached altitudes around 10–12 km and influenced the column average aerosol particle size distribution at a distance of more than 350 km downwind. This study indicates that even a relatively weak volcanic eruption may produce an observable effect on the aerosol properties at the regional scale. The impact of secondary sulfate particles on the aerosol size distribution at Lampedusa is discussed and estimates of the clear-sky direct aerosol radiative forcing are derived. Daily shortwave radiative forcing efficiencies, i.e. radiative forcing per unit AOD (aerosol optical depth), are calculated with the LibRadtran model. They are estimated between 39 and 48Wm^-2 AOD^ -1 at the top of the atmosphere and between 66 and 49Wm^-2 AOD^-1 at the surface, with the variability in the estimates mainly depending on the aerosol single scattering albedo. These results suggest that sulfate particles played a large role in the transported plume composition and radiative forcing, while the contribution by ash particles was small in the volcanic plume arriving at Lampedusa during this event.
    Description: Published
    Description: 6841–6861
    Description: 5V. Dinamica dei processi eruttivi e post-eruttivi
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: 2SR. VULCANI - Servizi e ricerca per la Società
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
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    Biogenic Aerosol in the Artic from Eight Years of MSA Data from Ny Ålesund (Svalbard Islands) and Thule (Greenland) (2019)
    Details
    Publication Date: 2022-06-09
    Description: In remote marine areas, biogenic productivity and atmospheric particulate are coupled through dimethylsulfide (DMS) emission by phytoplankton. Once in the atmosphere, the gaseous DMS is oxidized to produce H2SO4 and methanesulfonic acid (MSA); both species can a ect the formation of cloud condensation nuclei. This study analyses eight years of biogenic aerosol evolution and variability at two Arctic sites: Thule (76.5 N, 68.8 W) and Ny Ålesund (78.9 N, 11.9 E). Sea ice plays a key role in determining the MSA concentration in polar regions. At the beginning of the melting season, in April, up to June, the biogenic aerosol concentration appears inversely correlated with sea ice extent and area, and positively correlated with the extent of the ice-free area in the marginal ice zone (IF-MIZ). The upper ocean stratification induced by sea ice melting might have a role in these correlations, since the springtime formation of this surface layer regulates the accumulation of phytoplankton and nutrients, allowing the DMS to escape from the sea to the atmosphere. The multiyear analysis reveals a progressive decrease in MSA concentration in May at Thule and an increase in July August at Ny Ålesund. Therefore, while the MSA seasonal evolution is mainly related with the sea ice retreat in April, May, and June, the IF-MIZ extent appears as the main factor a ecting the longer-term behavior of MSA.
    Description: MIUR PRIN 2007 and PRIN 2009, PNRA 2010-2012, PNRA 2015-2016, PNRA 2016-2018
    Description: Published
    Description: id 349
    Description: 5A. Ricerche polari e paleoclima
    Description: JCR Journal
    Keywords: biogenic aerosol, Arctic, sea ice extent, MSA ; 01.01. Atmosphere
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
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    The impact of Mount Etna sulfur emissions on the atmospheric composition and aerosol properties in the central Mediterranean: A statistical analysis over the period 2000–2013 based on observations and Lagrangian modelling (2018)
    Details
    Publication Date: 2022-06-09
    Description: The emission of gases and aerosols due to volcanic activity may impact significantly atmospheric composition, cloud occurrence and properties, and the regional and global climate. While the effects of strong explosive (stratospheric) eruptions are relatively well known, limited information on the impacts of small to moderate volcanic activities, including passive degassing, is available. In this paper, the downwind impact of Mount Etna's sulfur emissions on the central Mediterranean is investigated on a statistical basis over the period 2000e2013 using: (a) daily sulfur dioxide emission rates measured near crater at Mount Etna with ground-based ultraviolet spectrophotometers, (b) Lagrangian trajectories and simulated plume dispersion obtained with the FLEXPART (FLEXible PARTicle dispersion) model, and (c) long-term observations of column SO2 concentration and aerosol Ångstr€om exponent a at Lampedusa (35.5 N, 12.6 E). This statistical analysis has allowed, for the first time, the characterization of decadal impact of Mount Etna's sulfur emissions on the sulfur dioxide and the aerosol microphysical/optical properties in the central Mediterranean. On average, statistically significant higher SO2 concentrations and smaller aerosol sizes are present when air masses from Mount Etna overpass Lampedusa. Despite being upwind of Lampedusa for only 5% of the time, Mount Etna is potentially responsible for up to 40% and 20% of the SO2 and a extreme values (exceedances of a fixed threshold), respectively, at this location. The most important factor determining this perturbation is the prevailing dynamics, while the magnitude of the SO2 emission rates from Mount Etna appears to be likely important only for relatively strong emissions. The observed perturbations to the aerosol size distribution are expected to produce a direct regional radiative effect in this area.
    Description: Published
    Description: 77-88
    Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio
    Description: JCR Journal
    Keywords: 04.08. Volcanology ; 01.01. Atmosphere ; climatology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
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    On the Radiative Impact of Biomass-Burning Aerosols in the Arctic: The August 2017 Case Study (2022)
    MDPI
    Details
    Publication Date: 2023-03-30
    Description: Boreal fires have increased during the last years and are projected to become more intense and frequent as a consequence of climate change. Wildfires produce a wide range of effects on the Arctic climate and ecosystem, and understanding these effects is crucial for predicting the future evolution of the Arctic region. This study focuses on the impact of the long-range transport of biomass-burning aerosol into the atmosphere and the corresponding radiative perturbation in the shortwave frequency range. As a case study, we investigate an intense biomass-burning (BB) event which took place in summer 2017 in Canada and subsequent northeastward transport of gases and particles in the plume leading to exceptionally high values (0.86) of Aerosol Optical Depth (AOD) at 500 nm measured in northwestern Greenland on 21 August 2017. This work characterizes the BB plume measured at the Thule High Arctic Atmospheric Observatory (THAAO; 76.53∘N, 68.74∘W) in August 2017 by assessing the associated shortwave aerosol direct radiative impact over the THAAO and extending this evaluation over the broader region (60∘N–80∘N, 110∘W–0∘E). The radiative transfer simulations with MODTRAN6.0 estimated an aerosol heating rate of up to 0.5 K/day in the upper aerosol layer (8–12 km). The direct aerosol radiative effect (ARE) vertical profile shows a maximum negative value of −45.4 Wm−2 for a 78∘ solar zenith angle above THAAO at 3 km altitude. A cumulative surface ARE of −127.5 TW is estimated to have occurred on 21 August 2017 over a portion (∼3.1×106 km2) of the considered domain (60∘N–80∘N, 110∘W–0∘E). ARE regional mean daily values over the same portion of the domain vary between −65 and −25 Wm−2. Although this is a limited temporal event, this effect can have significant influence on the Arctic radiative budget, especially in the anticipated scenario of increasing wildfires.
    Description: This research was partially funded by the Italian Ministry of University and Research (MIUR) within the framework of OASIS-YOPP—Observations of the Arctic Stratosphere In Support of YOPP (PNRA 2016–2018); CLARA2—CLouds And Radiation in the Arctic and Antarctica (PNRA 2019–2021), and ECAPAC—Effects of changing albedo and precipitation on the Arctic climate (PRA 2021–2023). The work of F. Calì Quaglia and G. Muscari was also partially funded under the INGV environmental project MACMAP—A Multidisciplinary Analysis of Climate change indicators in the Mediterranean And Polar regions (2020–2023). The NCAR FTIR observation program at Thule, Greenland is supported under contract by the National Aeronautics and Space Administration (NASA). The National Center for Atmospheric Research (NCAR) is sponsored by the U.S. National Science Foundation (NSF). The Thule work is also supported by the NSF Office of Polar Programs (OPP).
    Description: Published
    Description: 313
    Description: 5A. Ricerche polari e paleoclima
    Description: JCR Journal
    Keywords: biomass-burning (BB) ; wildfires ; Arctic ; aerosol radiative effect ; 01.01. Atmosphere
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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