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Nitrate Retentionmap DK
No full textMap showing the degree of nitrate retention in the subsurface and surface waters before they reach the coast calculated as an average for the period 1990-2010.
Development and production of the map was carried out in cooperation between GEUS and the Univerity of Aarhus during 2013-2015. The map is revised august 2015. Explanation for column contents: ID: ID15 Catchment area RedTot: Total retention of nitrate in percent from during transport form root zone within a given catchment area until it reaches the coast. RedSurf: Total retention of nitrate in percent from it reaches surface water in a given catchment until it reacehes the coast. RedGW: Reduction of nitrate in the subsurface in percent within a given catchment area until it reaches the surface water system. MinRedTot: Minimum total retention in percent from root zone to coast (RedTot - UncRedTot) MaxRedTot: Maximum total retention in percent from root zone to coast (RedTot + UncReddTot) UncRedTot: Uncertainty estimate of total reduction in percentage points. BiasReg: Bias region InModel: 1: ID15 catchment in measured area; 0: ID15 catchment in unmeasured area; -1: ID15 catchment lies outside model area; the total retention is estimated as an average of the other unmeasured catchment areas
Supplementary files for: Mudstone diagenesis and sandstone provenance in an Upper Jurassic – Lower Cretaceous evolving half-graben system, Wollaston Forland, North-East Greenland
No full textThe influence of rifting on the composition of Kimmeridgian to Barremian mudstones from northern Wollaston Forland in North-East Greenland is investigated by petrographic and mineralogical analysis, in addition to U-Pb zircon provenance analysis of nearby sandstones. The mudstone composition is found to vary systematically as a function of both the timing of the rifting progression and the position in the half-graben depositional system. Pyrite primarily precipitated in the early rift to rift climax phases. Euhedral pyrite overgrowths on framboids formed only during the rift climax phase (Lindemans Bugt Formation). Dolomite is the dominant carbonate cement, except for the sediments deposited in the early waning rift phase (Palnatokes Bjerg Formation) where calcite is dominant, and in the late waning rift phase (Stratumbjerg Formation) where siderite dominates. A diagenetic process scheme is established to summarize the main diagenetic reactions, of which the highest-temperature reactions with precipitation of illite, quartz, ankerite and barite signify sediment burial depths of >2 km prior to exhumation. Uplift-induced fracturing mainly occurred in the early rift to rift acceleration succession (Bernbjerg Formation). Mudstones in the proximal part of the half-graben (Rødryggen-1 core) include more detrital kaolinite than the distal mudstones (Brorson Halvø-1 core), which contain more mixed-layer illite/smectite and illite. Vermiculite was deposited only in the proximal part of the basin where it is found in the rift climax and waning rift successions. Chlorite was deposited both proximally and distally during the waning rift phase, though the supply began earlier in the distal part. Fine-grained sediment in the distal part of the half-graben was therefore probably supplied by axial transport from Palaeoproterozoic crystalline rocks and Meso- to Neoproterozoic metamorphic rocks located to the north and north-west
Terrænhøjder (topografi) og vanddybder (bathymetri) i det danske område
No full textKortet viser landets højde over havet og havdybden på det danske område i intervaller på 5 meter.
Højden på land stammer fra Kort og Matrikelstyrelsen (nu SDFE) kortgrundlag i 1:25 000 fra 2005.
Havdybderne er baseret på data af meget uens kvalitet: De indre danske farvande er fra Farvandsvæsnet (1:50 000 og 1:100 000). I området nord og vest for Frederikshavn stammer data fra Statens Kartverk (Norge; ca. 1:500.000). I de syd-østlige områder og mod svenskekysten stammer data fra Baltic Sea Research Institute (ca. 1:500 000). Data fra Nordsøen stammer fra GEUS (1:500.000 til 1:1 000 000). De forskellige datakilders dækning kan ses af den medfølgende shape-fil.
Datapakken fylder 193 MB
GlacioBasis Zackenberg - Level 1 data 2008 - 2022
No full textThe GlacioBasis Zackenberg glaciological monitoring programme, is a subprogram of the Greenland Ecosystem Monitoring (GEM, g-e-m.dk) at Zackenberg Research station, NE Greenland.
The data presented here is from a transect of three Automatic Ablation and Weather Stations (AAWSs) located on the A. P. Olsen ice cap (referred to here as APO or the Ice Cap), located in the hydrologocal catchment of Zackenberg River. The first two AAWSs of the APO transect were installed in April 2008 in the ablation zone, and the third AAWS was installed in August 2009 in the accumulation zone at the Ice Cap summit. These AAWSs have been running with alternating instrumentation until April 2022. In spring 2022 installation of new standardized AAWSs was initiated, these stations are similar to the PROMICE and GC-Net stations (Fausto and others, 2021). With the new standardized setup, the data from the APO transect will be handled as a PROMICE and GC-Net dataset and data processing will be done using the python package pypromice described in How and others (2023).
The continuation of this dataset from the A. P. Olsen transect can be found as part of the PROMICE and GC-Net automated weather station data in Greenland: https://doi.org/10.22008/FK2/IW73UU as well as in the GEM database: https://data.g-e-m.dk/ which is updated once a year in spring.
The variables published here are: Ice ablation, air temperature, relative humidity, air pressure, wind speed, incoming and outgoing shortwave and longwave radiation as well as AAWS tilt, snow depth and the derived variables cloud cover fraction, surface temperature and albedo.
References:
Fausto, R. S., As, D. V., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth System Science Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021.
How, P. R., Wright, P. J., Mankoff, K. D., Vandecrux, B., Fausto, R. S., and Ahlstrøm, A. P.: pypromice: A Python package for processing automated weather station data, Journal of Open Source Software, 8, 5298, https://doi.org/10.21105/joss.05298, 2023
Hydrogeological layers DK1 and DK2 (ascii)
No full textThe hydrogeological layers in DKmodel2019 for modelarea DK1 and DK2 (Sjælland and øerne) in ascii format. Description and principle sketch of the hydrostratigraphic units and calculation layers for the DK-model2019 in chapter 3, National Vandressource Model
Modelopstilling og kalibrering af DK-model 2019
SICEv3.0 Southern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)
No full text
SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023
Timespan
1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year
Description
For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/
Data Format
Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection.
Table 1, SICE v3.0 data, alphabetical
name, description
ANG, Angström parameter for atmospheric aerosol correction
AOD_550, aerosol optical depth at 550 nm from CAMS, m units
al, effective absorption length, mm units
albedo_bb_spherical_sw, albedo under isotropic radiation
albedo_bb_planar_sw, broadband albedo
albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21
diagnostic_retrieval, per pixel diagnostic info
cloud_mask,SCDA cloud mask
cloud_mask, SCDA cloud mask
cv1, quality check 1 (see ATBD)
cv2, quality check 2 (see ATBD)
factor
grain_diameter, effective optical snow grain diameter
isnow, See Table 2
lat, decimal latitude
lon, decimal longitude
O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020
r0, reflectance of a semi-infinite non-absorbing snow layer
r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21
r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21
snow_specific_surface_area, SSA
saa, solar azimuth angle
sza, solar zenith angle
vaa, viewing azimuth angle
vza, viewing zenith angle
Table 2, Diagnostic codes
Diagnostic Code, Description
0, clean snow
1, polluted snow
6, polluted snow for which r0 was calculated and not derived from observations
7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow
100, sza exceeding 75, no retrival albedo
102, TOA reflectance at band 21 less than 0.1, no retrieval
104, grain_diameter less than 0.1, no retrieval, potential cloud flag
-N, impossible to solve polluted snow albedo equation at band N
See also related information below
Reference Publications
Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022
Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045
Code
Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Acknowledgements
SICE has been supported by the following contracts to the European Space Agency (ESA):
Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB
Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE)
Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network
May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS)
Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB
and the ESA Network of Resources,
Related Information
description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1
https://snow.geus.dk/
Questions?
contact Jason Box, [email protected]
</html
SICEv3.0 Northern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)
No full text
SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023
Timespan
1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year
Description
For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/
Data Format
Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection.
Table 1, SICE v3.0 data, alphabetical
name, description
ANG, Angström parameter for atmospheric aerosol correction
AOD_550, aerosol optical depth at 550 nm from CAMS, m units
al, effective absorption length, mm units
albedo_bb_spherical_sw, albedo under isotropic radiation
albedo_bb_planar_sw, broadband albedo
albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21
diagnostic_retrieval, per pixel diagnostic info
cloud_mask,SCDA cloud mask
cloud_mask, SCDA cloud mask
cv1, quality check 1 (see ATBD)
cv2, quality check 2 (see ATBD)
factor
grain_diameter, effective optical snow grain diameter
isnow, See Table 2
lat, decimal latitude
lon, decimal longitude
O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020
r0, reflectance of a semi-infinite non-absorbing snow layer
r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21
r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21
snow_specific_surface_area, SSA
saa, solar azimuth angle
sza, solar zenith angle
vaa, viewing azimuth angle
vza, viewing zenith angle
Table 2, Diagnostic codes
Diagnostic Code, Description
0, clean snow
1, polluted snow
6, polluted snow for which r0 was calculated and not derived from observations
7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow
100, sza exceeding 75, no retrival albedo
102, TOA reflectance at band 21 less than 0.1, no retrieval
104, grain_diameter less than 0.1, no retrieval, potential cloud flag
-N, impossible to solve polluted snow albedo equation at band N
See also related information below
Reference Publications
Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022
Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045
Code
Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Acknowledgements
SICE has been supported by the following contracts to the European Space Agency (ESA):
Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB
Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE)
Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network
May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS)
Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB
and the ESA Network of Resources,
Related Information
description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1
https://snow.geus.dk/
Questions?
contact Jason Box, [email protected]
</html
SICEv2.3.2 Novaya Zemlya snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full text
SICE v2.3.2. Multi-regional 1 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023
Timespan
1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year
Description
For multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/
Data Format
Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region, area, sq km, percent of multi-regional area
Greenland, 1,744,666, 82.7
Arctic Canada North, 100,691, 4.8
Alaska and Yukon, 96,909, 4.6
Arctic Canada South, 40,970, 1.9
Norway, 34,018, 1.6
Svalbard, 32,506, 1.5
Novaya Zemlya, 21,506, 1.0
Severnaya Zemlya, 15,842, 0.8
Frans Josef Land, 12,131, 0.6
Iceland, 11,489, 0.5
Table 2, SICE v1 data
name, description
BBA_combination, broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final, cloud mask
albedo_bb_planar_sw,
diagnostic_retrieval, per pixel diagnostic info
num_scenes, number of scenes
r_TOA_01, TOA reflectance, band 1
r_TOA_06, TOA reflectance, band 6
r_TOA_17, TOA reflectance, band 17
r_TOA_21, TOA reflectance, band 21
snow_specific_surface_area, SSA
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Kokhanovsky, A., Box, J., and Vandecrux, B.: Pre-operational Sentinel-3 snow and ice (SICE) products: Algorithm theoretical basis document, https://doi.org/10.20944/preprints202009.0529.v1, 23 September 2020.
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Code
Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 2.3.2, https://doi.org/10.5281/zenodo.10036416, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
Acknowledgements
SICE has been supported by the following contracts to the European Space Agency (ESA):
Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB
Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE)
Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network
May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS)
Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB
and the ESA Network of Resources,
Related Information
description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1
https://snow.geus.dk/
Questions?
contact Jason Box, [email protected]
</html
GEUS snow and firn data in Greenland
No full textThis is a compilation of snow pit and firn core observations collected or digitized by the Department of Glaciology and Climate at the Geological Survey of Denmark and Greenland (GEUS).
They are provided in two harmonized formats:
Excel spreadsheets inspired from NASA SnowEx. Files may contain multiple profiles as separate sheets..
CSV files with 19 lines of header containing all the relevant information about the site, profile and different fields provided (also refered as NEAD files.
List of variables observed:
Snow or firn density
Snow or firn temperature
Snow or firn visual stratigraphy
For some snow pits, and in snowex format only, snow grain size, grain type and hardness
The following metadata should be available for every profile:
Site name
Date
Latitude
Longitude
Elevation
Data were collected for the following projects:
GC-Net historical (PI: K. Steffen)
GC-Net GEUS (PI: A. Ahlstrøm)
PROMICE (PI: R. Fausto)
Glaciobasis (PI: M. Citterio, S.H. Larsen)
ACT15 (PI: H. Machguth, D. van As)
FirnCover (PI: M. MacFerrin)
We are grateful to all the people that help directly or indirectly to the collection of this data:
Kirk Scanlan
Ken Mankoff
Øyvind Winston
Dirk van As
Daniel McGrath
Simon Steffen
Achim Heillig
Derek Houtz
Horst Machguth
C. Max Stevens
Mike MacFerrin
Chris Derksen
Josephine Lindsey-Clark
</ul
Ground penetrating radar data over the ONERA targets
No full textHuman-towed and robot-towed GPR lines over the ONERA targets from the 5th field campaig