GLORIA

GEOMAR Library Ocean Research Information Access

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Document type
Keywords
Years
  • 1
    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
    BibTip Others were also interested in ...
  • 2
    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
    BibTip Others were also interested in ...
  • 3
    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
    BibTip Others were also interested in ...
  • 4
    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
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2024-04-20
    Description: This dataset contains information about the state of the central Arctic lower atmosphere during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Through the merging of MOSAiC radiosonde, 10-m meteorological tower, ceilometer, and radiation station observations, this dataset provides information about the atmospheric boundary layer (depth and stability), temperature features (near-surface temperature and temperature inversion characteristics), wind features (near-surface wind speed and low-level jet characteristics), moisture features (near-surface mixing ratio and cloud characteristics), and surface radiation budget (up- and downwelling longwave and shortwave radiative flux) at the time of each MOSAiC radiosonde launch (approximately 4 times per day between September 2019 and October 2020). The dataset is structured in a NetCDF4 file, which follows the CF-1.10 convention. The objective of this dataset is to provide the user community with a consistent description of general lower atmospheric conditions throughout the MOSAiC year.
    Keywords: ABL; Arctic; Arctic Ocean; Atmosphere; Automatic weather station; AWS; FLUX_TOWER; Flux tower; meteorological data; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; North Greenland Sea; Polarstern; PS122/1; PS122/1_10-103; PS122/1_10-105; PS122/1_10-106; PS122/1_10-107; PS122/1_10-108; PS122/1_10-135; PS122/1_10-21; PS122/1_10-22; PS122/1_10-23; PS122/1_10-24; PS122/1_10-28; PS122/1_10-29; PS122/1_10-3; PS122/1_10-30; PS122/1_10-31; PS122/1_10-4; PS122/1_10-53; PS122/1_10-54; PS122/1_10-56; PS122/1_10-57; PS122/1_10-73; PS122/1_10-74; PS122/1_10-75; PS122/1_10-76; PS122/1_10-94; PS122/1_10-95; PS122/1_10-99; PS122/1_11-10; PS122/1_11-29; PS122/1_11-30; PS122/1_11-31; PS122/1_11-32; PS122/1_11-33; PS122/1_11-43; PS122/1_11-44; PS122/1_11-45; PS122/1_11-46; PS122/1_11-5; PS122/1_11-6; PS122/1_11-7; PS122/1_11-8; PS122/1_11-9; PS122/1_1-299; PS122/1_1-341; PS122/1_1-345; PS122/1_2-100; PS122/1_2-101; PS122/1_2-103; PS122/1_2-104; PS122/1_2-105; PS122/1_2-106; PS122/1_2-107; PS122/1_2-110; PS122/1_2-111; PS122/1_2-112; PS122/1_2-113; PS122/1_2-115; PS122/1_2-116; PS122/1_2-117; PS122/1_2-118; PS122/1_2-119; PS122/1_2-120; PS122/1_2-121; PS122/1_2-122; PS122/1_2-123; PS122/1_2-127; PS122/1_2-135; PS122/1_2-136; PS122/1_2-137; PS122/1_2-139; PS122/1_2-140; PS122/1_2-141; PS122/1_2-143; PS122/1_2-144; PS122/1_2-145; PS122/1_2-146; PS122/1_2-147; PS122/1_2-148; PS122/1_2-149; PS122/1_2-150; PS122/1_2-160; PS122/1_2-161; PS122/1_2-162; PS122/1_2-163; PS122/1_2-171; PS122/1_2-172; PS122/1_2-173; PS122/1_2-174; PS122/1_2-179; PS122/1_2-180; PS122/1_2-181; PS122/1_2-182; PS122/1_2-184; PS122/1_2-185; PS122/1_2-186; PS122/1_2-187; PS122/1_2-188; PS122/1_2-189; PS122/1_2-190; PS122/1_2-191; PS122/1_2-192; PS122/1_2-193; PS122/1_2-51; PS122/1_2-52; PS122/1_2-53; PS122/1_2-54; PS122/1_2-55; PS122/1_2-56; PS122/1_2-59; PS122/1_2-60; PS122/1_2-61; PS122/1_2-62; PS122/1_2-69; PS122/1_2-70; PS122/1_2-71; PS122/1_2-72; PS122/1_2-73; PS122/1_2-74; PS122/1_2-75; PS122/1_2-76; PS122/1_2-77; PS122/1_2-78; PS122/1_2-79; PS122/1_2-80; PS122/1_2-81; PS122/1_2-82; PS122/1_2-83; PS122/1_2-85; PS122/1_2-86; PS122/1_2-87; PS122/1_2-88; PS122/1_2-91; PS122/1_2-92; PS122/1_2-93; PS122/1_2-94; PS122/1_4-19; PS122/1_4-20; PS122/1_4-21; PS122/1_4-22; PS122/1_4-30; PS122/1_4-31; PS122/1_4-32; PS122/1_4-33; PS122/1_4-35; PS122/1_4-36; PS122/1_4-4; PS122/1_4-5; PS122/1_4-6; PS122/1_4-7; PS122/1_4-8; PS122/1_4-9; PS122/1_5-10; PS122/1_5-11; PS122/1_5-12; PS122/1_5-13; PS122/1_5-20; PS122/1_5-21; PS122/1_5-22; PS122/1_5-23; PS122/1_5-31; PS122/1_5-32; PS122/1_5-33; PS122/1_5-34; PS122/1_5-36; PS122/1_5-38; PS122/1_5-39; PS122/1_5-49; PS122/1_5-50; PS122/1_5-51; PS122/1_5-52; PS122/1_5-6; PS122/1_5-7; PS122/1_5-72; PS122/1_5-73; PS122/1_5-74; PS122/1_5-75; PS122/1_5-79; PS122/1_5-80; PS122/1_6-112; PS122/1_6-113; PS122/1_6-114; PS122/1_6-115; PS122/1_6-12; PS122/1_6-125; PS122/1_6-126; PS122/1_6-13; PS122/1_6-14; PS122/1_6-15; PS122/1_6-24; PS122/1_6-25; PS122/1_6-26; PS122/1_6-27; PS122/1_6-3; PS122/1_6-4; PS122/1_6-53; PS122/1_6-54; PS122/1_6-55; PS122/1_6-56; PS122/1_6-71; PS122/1_6-72; PS122/1_6-73; PS122/1_6-74; PS122/1_6-82; PS122/1_6-83; PS122/1_6-84; PS122/1_6-85; PS122/1_7-100; PS122/1_7-101; PS122/1_7-102; PS122/1_7-107; PS122/1_7-108; PS122/1_7-109; PS122/1_7-110; PS122/1_7-113; PS122/1_7-114; PS122/1_7-13; PS122/1_7-14; PS122/1_7-26; PS122/1_7-27; PS122/1_7-28; PS122/1_7-29; PS122/1_7-30; PS122/1_7-43; PS122/1_7-44; PS122/1_7-45; PS122/1_7-46; PS122/1_7-63; PS122/1_7-64; PS122/1_7-65; PS122/1_7-66; PS122/1_7-83; PS122/1_7-84; PS122/1_7-85; PS122/1_7-86; PS122/1_7-99; PS122/1_8-101; PS122/1_8-11; PS122/1_8-115; PS122/1_8-116; PS122/1_8-117; PS122/1_8-118; PS122/1_8-12; PS122/1_8-120; PS122/1_8-121; PS122/1_8-13; PS122/1_8-14; PS122/1_8-39; PS122/1_8-40; PS122/1_8-41; PS122/1_8-42; PS122/1_8-5; PS122/1_8-6; PS122/1_8-63; PS122/1_8-64; PS122/1_8-65; PS122/1_8-66; PS122/1_8-80; PS122/1_8-81; PS122/1_8-82; PS122/1_8-83; PS122/1_8-95; PS122/1_8-96; PS122/1_8-97; PS122/1_9-101; PS122/1_9-102; PS122/1_9-105; PS122/1_9-106; PS122/1_9-13; PS122/1_9-14; PS122/1_9-18; PS122/1_9-19; PS122/1_9-20; PS122/1_9-21; PS122/1_9-41; PS122/1_9-42; PS122/1_9-43; PS122/1_9-44; PS122/1_9-57; PS122/1_9-58; PS122/1_9-59; PS122/1_9-60; PS122/1_9-77; PS122/1_9-78; PS122/1_9-79; PS122/1_9-80; PS122/1_9-88; PS122/1_9-89; PS122/1_9-90; PS122/1_9-91; PS122/1_99-46; PS122/1_99-47; PS122/1_9-99; PS122/2; PS122/2_14-119; PS122/2_14-13; PS122/2_14-14; PS122/2_15-1; PS122/2_15-13; PS122/2_15-2; PS122/2_15-3; PS122/2_15-4; PS122/2_15-5; PS122/2_15-7; PS122/2_16-10; PS122/2_16-11; PS122/2_16-13; PS122/2_16-16; PS122/2_16-17; PS122/2_16-18; PS122/2_16-19; PS122/2_16-2; PS122/2_16-20; PS122/2_16-3; PS122/2_16-30; PS122/2_16-31; PS122/2_16-32; PS122/2_16-33; PS122/2_16-4; PS122/2_16-40; PS122/2_16-41; PS122/2_16-42; PS122/2_16-43; PS122/2_16-5; PS122/2_16-57; PS122/2_16-58; PS122/2_16-59; PS122/2_16-6; PS122/2_16-60; PS122/2_16-67; PS122/2_16-68; PS122/2_16-69; PS122/2_16-7; PS122/2_16-70; PS122/2_16-76; PS122/2_17-10; PS122/2_17-102; PS122/2_17-103; PS122/2_17-104; PS122/2_17-105; PS122/2_17-11; PS122/2_17-110; PS122/2_17-12; PS122/2_17-21; PS122/2_17-22; PS122/2_17-23; PS122/2_17-24; PS122/2_17-35; PS122/2_17-36; PS122/2_17-37; PS122/2_17-38; PS122/2_17-55; PS122/2_17-56; PS122/2_17-57; PS122/2_17-58; PS122/2_17-71; PS122/2_17-72; PS122/2_17-73; PS122/2_17-74; PS122/2_17-92; PS122/2_17-93; PS122/2_17-94; PS122/2_17-95; PS122/2_18-100; PS122/2_18-11; PS122/2_18-12; PS122/2_18-13; PS122/2_18-20; PS122/2_18-21; PS122/2_18-22; PS122/2_18-27; PS122/2_18-29; PS122/2_18-30; PS122/2_18-31; PS122/2_18-48; PS122/2_18-49; PS122/2_18-50; PS122/2_18-51; PS122/2_18-67; PS122/2_18-68; PS122/2_18-69; PS122/2_18-70; PS122/2_18-85; PS122/2_18-86; PS122/2_18-87; PS122/2_18-88; PS122/2_18-94; PS122/2_18-95; PS122/2_18-96; PS122/2_18-97; PS122/2_19-10; PS122/2_19-100; PS122/2_19-11; PS122/2_19-12; PS122/2_19-124; PS122/2_19-125; PS122/2_19-126; PS122/2_19-127; PS122/2_19-143; PS122/2_19-22; PS122/2_19-23; PS122/2_19-24; PS122/2_19-25; PS122/2_19-47; PS122/2_19-48; PS122/2_19-49; PS122/2_19-50; PS122/2_19-71; PS122/2_19-72; PS122/2_19-73; PS122/2_19-74; PS122/2_19-84; PS122/2_19-85; PS122/2_19-86; PS122/2_19-87; PS122/2_19-97; PS122/2_19-98; PS122/2_19-99; PS122/2_20-10; PS122/2_20-103; PS122/2_20-104; PS122/2_20-105; PS122/2_20-106; PS122/2_20-119; PS122/2_20-120; PS122/2_20-121; PS122/2_20-122; PS122/2_20-135; PS122/2_20-19; PS122/2_20-20; PS122/2_20-21; PS122/2_20-22; PS122/2_20-37; PS122/2_20-38; PS122/2_20-39; PS122/2_20-40; PS122/2_20-66; PS122/2_20-67; PS122/2_20-68; PS122/2_20-69; PS122/2_20-8; PS122/2_20-84; PS122/2_20-85; PS122/2_20-86; PS122/2_20-87; PS122/2_20-9; PS122/2_21-106; PS122/2_21-107; PS122/2_21-108; PS122/2_21-109; PS122/2_21-115; PS122/2_21-116; PS122/2_21-117; PS122/2_21-118; PS122/2_21-132; PS122/2_21-133; PS122/2_21-134; PS122/2_21-135; PS122/2_21-136; PS122/2_21-21; PS122/2_21-22; PS122/2_21-23; PS122/2_21-37; PS122/2_21-38; PS122/2_21-39; PS122/2_21-40; PS122/2_21-57; PS122/2_21-58; PS122/2_21-59; PS122/2_21-60; PS122/2_21-79; PS122/2_21-80; PS122/2_21-81; PS122/2_21-82; PS122/2_22-10; PS122/2_22-102; PS122/2_22-103; PS122/2_22-104; PS122/2_22-105; PS122/2_22-11; PS122/2_22-111; PS122/2_22-20; PS122/2_22-21; PS122/2_22-22; PS122/2_22-23; PS122/2_22-38; PS122/2_22-39; PS122/2_22-40; PS122/2_22-41; PS122/2_22-57; PS122/2_22-58; PS122/2_22-59; PS122/2_22-60; PS122/2_22-78; PS122/2_22-79; PS122/2_22-80; PS122/2_22-81; PS122/2_22-87; PS122/2_22-88; PS122/2_22-89; PS122/2_22-9; PS122/2_23-101; PS122/2_23-102; PS122/2_23-103; PS122/2_23-104; PS122/2_23-117; PS122/2_23-118; PS122/2_23-119; PS122/2_23-120; PS122/2_23-129; PS122/2_23-22; PS122/2_23-23; PS122/2_23-24; PS122/2_23-25; PS122/2_23-41; PS122/2_23-42; PS122/2_23-43; PS122/2_23-44; PS122/2_23-54; PS122/2_23-55; PS122/2_23-56; PS122/2_23-57; PS122/2_23-6; PS122/2_23-7; PS122/2_23-8; PS122/2_23-80; PS122/2_23-81; PS122/
    Type: Dataset
    Format: application/x-hdf, 440 kBytes
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2022-11-02
    Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉Over a five-month time window between March and July 2020, scientists deployed two small uncrewed aircraft systems (sUAS) to the central Arctic Ocean as part of legs three and four of the MOSAiC expedition. These sUAS were flown to measure the thermodynamic and kinematic state of the lower atmosphere, including collecting information on temperature, pressure, humidity and winds between the surface and 1 km, as well as to document ice properties, including albedo, melt pond fraction, and open water amounts. The atmospheric state flights were primarily conducted by the DataHawk2 sUAS, which was operated primarily in a profiling manner, while the surface property flights were conducted using the HELiX sUAS, which flew grid patterns, profiles, and hover flights. In total, over 120 flights were conducted and over 48 flight hours of data were collected, sampling conditions that included temperatures as low as −35 °C and as warm as 15 °C, spanning the summer melt season.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2022-11-02
    Description: Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm-2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.
    Description: Published
    Description: 6379
    Description: 5A. Ricerche polari e paleoclima
    Description: JCR Journal
    Keywords: Arctic climate ; vegetation type ; surface energy budget
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Quinn, P. K., Thompson, E. J., Coffman, D. J., Baidar, S., Bariteau, L., Bates, T. S., Bigorre, S., Brewer, A., de Boer, G., de Szoeke, S. P., Drushka, K., Foltz, G. R., Intrieri, J., Iyer, S., Fairall, C. W., Gaston, C. J., Jansen, F., Johnson, J. E., Krueger, O. O., Marchbanks, R. D., Moran, K. P., Noone, D., Pezoa, S., Pincus, R., Plueddemann, A. J., Poehlker, M. L., Poeschl, U., Melendez, E. Q., Royer, H. M., Szczodrak, M., Thomson, J., Upchurch, L. M., Zhang, C., Zhang, D., & Zuidema, P. Measurements from the RV Ronald H. Brown and related platforms as part of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). Earth System Science Data, 13(4), (2021): 1759-1790, https://doi.org/10.5194/essd-13-1759-2021.
    Description: The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020, last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein.
    Description: NOAA's Climate Variability and Predictability Program provided funding under NOAA CVP NA19OAR4310379, GC19-301, and GC19-305. The Joint Institute for the Study of the Atmosphere and Ocean (JISAO) supported this study under NOAA cooperative agreement NA15OAR4320063. Additional support was provided by the NOAA's Uncrewed Aircraft Systems (UAS) Program Office, NOAA's Physical Sciences Laboratory, and NOAA AOML's Physical Oceanography Division. The NTAS project is funded by the NOAA's Global Ocean Monitoring and Observing Program (CPO FundRef number 100007298), through the Cooperative Institute for the North Atlantic Region (CINAR) under cooperative agreement NA14OAR4320158.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Stevens, B., Bony, S., Farrell, D., Ament, F., Blyth, A., Fairall, C., Karstensen, J., Quinn, P. K., Speich, S., Acquistapace, C., Aemisegger, F., Albright, A. L., Bellenger, H., Bodenschatz, E., Caesar, K.-A., Chewitt-Lucas, R., de Boer, G., Delanoë, J., Denby, L., Ewald, F., Fildier, B., Forde, M., George, G., Gross, S., Hagen, M., Hausold, A., Heywood, K. J., Hirsch, L., Jacob, M., Jansen, F., Kinne, S., Klocke, D., Kölling, T., Konow, H., Lothon, M., Mohr, W., Naumann, A. K., Nuijens, L., Olivier, L., Pincus, R., Pöhlker, M., Reverdin, G., Roberts, G., Schnitt, S., Schulz, H., Siebesma, A. P., Stephan, C. C., Sullivan, P., Touzé-Peiffer, L., Vial, J., Vogel, R., Zuidema, P., Alexander, N., Alves, L., Arixi, S., Asmath, H., Bagheri, G., Baier, K., Bailey, A., Baranowski, D., Baron, A., Barrau, S., Barrett, P. A., Batier, F., Behrendt, A., Bendinger, A., Beucher, F., Bigorre, S., Blades, E., Blossey, P., Bock, O., Böing, S., Bosser, P., Bourras, D., Bouruet-Aubertot, P., Bower, K., Branellec, P., Branger, H., Brennek, M., Brewer, A., Brilouet , P.-E., Brügmann, B., Buehler, S. A., Burke, E., Burton, R., Calmer, R., Canonici, J.-C., Carton, X., Cato Jr., G., Charles, J. A., Chazette, P., Chen, Y., Chilinski, M. T., Choularton, T., Chuang, P., Clarke, S., Coe, H., Cornet, C., Coutris, P., Couvreux, F., Crewell, S., Cronin, T., Cui, Z., Cuypers, Y., Daley, A., Damerell, G. M., Dauhut, T., Deneke, H., Desbios, J.-P., Dörner, S., Donner, S., Douet, V., Drushka, K., Dütsch, M., Ehrlich, A., Emanuel, K., Emmanouilidis, A., Etienne, J.-C., Etienne-Leblanc, S., Faure, G., Feingold, G., Ferrero, L., Fix, A., Flamant, C., Flatau, P. J., Foltz, G. R., Forster, L., Furtuna, I., Gadian, A., Galewsky, J., Gallagher, M., Gallimore, P., Gaston, C., Gentemann, C., Geyskens, N., Giez, A., Gollop, J., Gouirand, I., Gourbeyre, C., de Graaf, D., de Groot, G. E., Grosz, R., Güttler, J., Gutleben, M., Hall, K., Harris, G., Helfer, K. C., Henze, D., Herbert, C., Holanda, B., Ibanez-Landeta, A., Intrieri, J., Iyer, S., Julien, F., Kalesse, H., Kazil, J., Kellman, A., Kidane, A. T., Kirchner, U., Klingebiel, M., Körner, M., Kremper, L. A., Kretzschmar, J., Krüger, O., Kumala, W., Kurz, A., L'Hégaret, P., Labaste, M., Lachlan-Cope, T., Laing, A., Landschützer, P., Lang, T., Lange, D., Lange, I., Laplace, C., Lavik, G., Laxenaire, R., Le Bihan, C., Leandro, M., Lefevre, N., Lena, M., Lenschow, D., Li, Q., Lloyd, G., Los, S., Losi, N., Lovell, O., Luneau, C., Makuch, P., Malinowski, S., Manta, G., Marinou, E., Marsden, N., Masson, S., Maury, N., Mayer, B., Mayers-Als, M., Mazel, C., McGeary, W., McWilliams, J. C., Mech, M., Mehlmann, M., Meroni, A. N., Mieslinger, T., Minikin, A., Minnett, P., Möller, G., Morfa Avalos, Y., Muller, C., Musat, I., Napoli, A., Neuberger, A., Noisel, C., Noone, D., Nordsiek, F., Nowak, J. L., Oswald, L., Parker, D. J., Peck, C., Person, R., Philippi, M., Plueddemann, A., Pöhlker, C., Pörtge, V., Pöschl, U., Pologne, L., Posyniak, M., Prange, M., Quiñones Meléndez, E., Radtke, J., Ramage, K., Reimann, J., Renault, L., Reus, K., Reyes, A., Ribbe, J., Ringel, M., Ritschel, M., Rocha, C. B., Rochetin, N., Röttenbacher, J., Rollo, C., Royer, H., Sadoulet, P., Saffin, L., Sandiford, S., Sandu, I., Schäfer, M., Schemann, V., Schirmacher, I., Schlenczek, O., Schmidt, J., Schröder, M., Schwarzenboeck, A., Sealy, A., Senff, C. J., Serikov, I., Shohan, S., Siddle, E., Smirnov, A., Späth, F., Spooner, B., Stolla, M. K., Szkółka, W., de Szoeke, S. P., Tarot, S., Tetoni, E., Thompson, E., Thomson, J., Tomassini, L., Totems, J., Ubele, A. A., Villiger, L., von Arx, J., Wagner, T., Walther, A., Webber, B., Wendisch, M., Whitehall, S., Wiltshire, A., Wing, A. A., Wirth, M., Wiskandt, J., Wolf, K., Worbes, L., Wright, E., Wulfmeyer, V., Young, S., Zhang, C., Zhang, D., Ziemen, F., Zinner, T., and Zöger, M.: EUREC4A. Earth System Science Data, 13(8), (2021): 4067–4119, https://doi.org/10.5194/essd-13-4067-2021.
    Description: The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.
    Description: This research has been supported by the people and government of Barbados; the Max Planck Society and its supporting members; the German Research Foundation (DFG) and the German Federal Ministry of Education and Research (grant nos. GPF18-1_69 and GPF18-2_50); the European Research Council (ERC) advanced grant EUREC4A (grant agreement no. 694768) under the European Union’s Horizon 2020 research and innovation program (H2020), with additional support from CNES (the French National Centre for Space Studies) through the EECLAT proposal, Météo-France, the CONSTRAIN H2020 project (grant agreement no. 820829), and the French AERIS Research Infrastructure; the Natural Environment Research Council (NE/S015868/1, NE/S015752/1, and NE/S015779/1); ERC under the European Union’s H2020 program (COMPASS, advanced grant agreement no. 74110); the French national program LEFE INSU, by IFREMER, the French research fleet, CNES, the French research infrastructures AERIS and ODATIS, IPSL, the Chaire Chanel program of the Geosciences Department at ENS, and the European Union's Horizon 2020 research and innovation program under grant agreement no. 817578 TRIATLAS; NOAA’s Climate Variability and Prediction Program within the Climate Program Office (grant nos. GC19-305 and GC19-301); NOAA cooperative agreement NA15OAR4320063; NOAA's Climate Program Office and base funds to NOAA/AOML's Physical Oceanography Division; Swiss National Science Foundation grant no. 188731; the UAS Program Office, Climate Program Office, and Physical Sciences Laboratory and by the US National Science Foundation (NSF) through grant AGS-1938108; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2037 “CLICCS – Climate, Climatic Change, and Society” – project no. 390683824; and Poland’s National Science Centre grant no. UMO-2018/30/M/ST10/00674 and Foundation for Polish Science grant no. POIR.04.04.00-00-3FD6/17-02.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...