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Helheim Glacier AWS data from 2007 and 2008
No full textAutomatic weather station data collected during the summers of 2007 and 2008 from a on-ice site on Helheim Glacier, a major outlet glacier from the Greenland Ice Sheet in Southeast Greenland near the town Tasiilaq
Snow and ice broadband albedo from Sentinel-3 OLCI measurements and empirical regression
No full textThis dataset contains:
snow and ice broadband albedo mosaics over Greenland for years 2018 and 2019 computed from a simple empirical approach (Wehrlé et al, 2021).
This approach consists of a fit between 4729 hourly PROMICE albedo measurements and the nearest in time and space OLCI Top of Atmosphere (TOA) reflectances spanning 3 years (2017–2019). We then defined the broadband albedo from a fit to the average of four OLCI TOA reflectances:
A = α (R400 nm+ R560 nm+ R865 nm + R1020 nm) / 4+ β
where α corresponds to the slope of the linear regression between OLCI TOA and PROMICE albedo measurements (1.003), and β is its intercept (0.058).
Clouds were detected and thereafter masked in Sentinel-3 imagery using the Simple Cloud Detection Algorithm (SCDA) version 2.0 (Metsämäki et al. 2015; Wehrlé & Box 2021). This algorithm consists of up to six tests on Sea and Land Surface Temperature Radiometer (SLSTR) TOA reflectances (550 and 1600 nm) and brightness temperatures (3.7, 11 and 12 μm).
Processing scripts:
https://github.com/AdrienWehrle/SICE_tools
Related studies:
- Wehrlé A.; Box J.E.; Niwano M.; Anesio A.M.; Fausto R.S., Greenland bare ice
albedo from PROMICE automatic weather station measurements and
Sentinel-3 satellite observations, GEUS bulletin, in press 2021
- Wehrlé, A. & Box, J., SICE implementation of the Simple Cloud Detection Algorithm (SCDA) v2.0, GEUS Dataverse, 2021 https://doi.org/10.22008/FK2/N0XWSJ
- Metsämäki, S.; Pulliainen, J.; Salminen, M.; Luojus, K.; Wiesmann, A.; Solberg, R.; Böttcher, K.; Hiltunen, M.;Ripper E, Introduction to globSnow snow extent products with considerations for accuracy assessment. Remote Sensing of Environment, 2015
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SICE 1 km broadband albedo monthly averages and visualisations
No full textSICE 1 km broadband albedo monthly averages and visualisation
Sediment in calved ice
No full textThis dataset contains information of the sediment concentration in calved ice
Camp Century: Simulations of firn evolution 1966-2100
No full textThis dataset contains the meteorological forcing, calculated surface energy and mass balance and simulated firn evolution at Camp Century during 1966-2100.
Contact:
Baptiste Vandecrux ([email protected])
Please cite the following study when using these data:
Vandecrux, B., Colgan, W., Solgaard, A.M., Steffensen, J.P., and Karlsson, N.B.(2021). Firn evolution at Camp Century, Greenland: 1966-2100, Frontiers in Earth Science, https://doi.org/10.3389/feart.2021.578978, 202
Gridded European Evapotranspiration Climatologies
No full textSpatial patterns in long-term evapotranspiration (ET) represent a unique source of information for evaluating the spatial pattern performance of distributed hydrological models at river basin to continental scale. This kind of model evaluation is getting increased attention, acknowledging the shortcomings of traditional aggregated or timeseries based evaluations. A variety of satellite remote sensing (RS) based ET estimates exists covering a range of methods and resolutions. There is therefore a need to evaluate these estimates, not only in terms of temporal performance and similarity, but also in terms of long-term spatial patterns. The current study evaluates four RS-ET(MODIS16, TSEB, PML_V2 and PT-JPL) estimates at moderate resolution with respect to spatial patterns in comparison to two alternative continental scale gridded ET estimates (Water balance -ET and Budyko). To increase comparability, an empirical correction factor between clear sky and all-weather ET, based on eddy covariance data is derived, which could be suitable for simple corrections of clear sky estimates.
The datasets contains the four RS-ET (MODIS16, TSEB, PML_V2 and PT-JPL) datasets at 1 km and 25 km spatial resolution and two alternative ET datasets (Water balance -ET and Budyko) at 25 km spatial resolution (ETRS_1989_LAEA; EPSG:3035). All data present long-term average annual ET for the period of 2002 to 2014, with units in mm/year
Supplementary files for: Estimating pesticides in public drinking water at the household-level in Denmark
No full textPesticide pollution has raised public concern in Denmark due to potential negative health impacts, and frequent findings of new substances after a recent expansion of the groundwater monitoring programme. Danish drinking water comes entirely from groundwater. Both raw groundwater and the treated drinking water are regularly monitored, and the chemical analyses are reported to a publicly available national database (Jupiter). Based on these data, in this study we (1) provide a status of pesticide content in drinking water supplied by public waterworks in Denmark and (2) assess the proportion of Danish households exposed to pesticides from drinking water. “Pesticides” here refers also to their metabolites, degradation and reaction products. The cleaned dataset represents 3004 public waterworks distributed throughout the country and includes 39 798 samples of treated drinking water analysed for 449 pesticides (971 723 analyses total) for the period 2002–2019. Of all these chemical analyses, 0.5% (n = 4925) contained a quantified pesticide (>0.03 µg/l). Pesticides were found at least once in the treated drinking water at 29% of all sampled public waterworks for the period 2002–2019, and at 21% of the waterworks for the recent period 2015–2019. We estimate that 56% of all Danish households were potentially exposed at least once to pesticides in drinking water at concentrations of 0.03–4.00 µg/l between 2002 and 2019. However, in 2015–2019, the proportion of the Danish households exposed to pesticides (0.03–4.00 µg/l) was 41%. The proportion of Danish households potentially exposed at least once to pesticides above the maximum allowed concentration (0.1 µg/l) according to the EU Drinking Water Directive (and the Danish drinking water standard) was 19% for 2002–2019 and 11% for 2015–2019. However, the maximum concentrations were lower than the World Health Organization compound-specific guidelines. Lastly, we explore data complexity and discuss the limitations imposed by data heterogeneity to facilitate future epidemiological studies
Greenland Ice Sheet Basal Melt
No full textThis dataset contains basal melt rates as published in Karlsson et al., (2021).
The data can be accessed in three formats NetCDF, ascii and Matlab.
The data contain basal melt rates in metres per year from three different heat sources: geothermal flux, friction heat and viscous heat from surface meltwater.
The data also contain the total basal melt rates in metres per year (the sum of the three terms).
Uncertainties for each term is named X_unc. Note that the geothermal flux has an asymetrical uncertainty. The uncertainty for the total melt rates are found by root squared sum of uncertainties.
See README.txt for more information
Supplementary files for: Episodic burial and exhumation in North-East Greenland before and after opening of the North-East Atlantic
No full textThe geology of North-East Greenland (70–78°N) exposes unique evidence of the basin development between the Devonian collapse of the Caledonian Orogen and the extrusion of volcanics at the Paleocene–Eocene transition during break-up of the North-East Atlantic. Here we pay special attention to unconformities in the stratigraphic record – do they represent periods of stability and non-deposition or periods of subsidence and accumulation of rocks followed by episodes of uplift and erosion? To answer that and other questions, we used apatite fission-track analysis and vitrinite reflectance data together with stratigraphic landscape analysis and observations from the stratigraphic record to study the thermo-tectonic history of North-East Greenland. Our analysis reveals eight regional stages of post-Caledonian development: (1) Late Carboniferous uplift and erosion led to formation of a sub-Permian peneplain covered by coarse siliciclastic deposits. (2) Middle Triassic exhumation led to removal of a thick cover including a considerable thickness of upper Carboniferous – Middle Triassic rocks and produced thick siliciclastic deposits in the rift system. (3) Denudation at the transition between the Early and Middle Jurassic affected most of the study area outside the Jameson Land Basin and produced a weathered surface above which Middle–Upper Jurassic sediments accumulated. (4) Earliest Cretaceous uplift and erosion along the rifted margin and further inland accompanied the Mesozoic rift climax and produced coarse-grained sedimentary infill of the rift basins. (5) Mid-Cretaceous uplift and erosion initiated removal of Cretaceous post-rift sediments that had accumulated above the Mesozoic rifts and their hinterland, leading to cooling of Mesozoic sediments from maximum palaeotemperatures. (6) End-Eocene uplift was accompanied by faulting and intrusion of magmatic bodies and resulted in extensive mass wasting on the East Greenland shelf. This event initiated the removal of a thick post-rift succession that had accumulated after break-up and produced a peneplain near sea level, the Upper Planation Surface. (7) Late Miocene uplift and erosion, evidenced by massive progradation on the shelf, resulted in the formation of the Lower Planation Surface by incision below the uplifted Upper Planation Surface. (8) Early Pliocene uplift raised the Upper and the Lower Planation Surfaces to their present elevations of about 2 and 1 km above sea level, respectively, and initiated the formation of the present-day landscape through fluvial and glacial erosion. Additional cooling episodes of more local extent, related to igneous activity in the early Eocene and in the early Miocene, primarily affected parts of northern Jameson Land. The three earliest episodes had a profound impact beyond Greenland and accompanied the fragmentation of Pangaea. Younger episodes were controlled by plate-tectonic processes, possibly including dynamic support from the Iceland Plume. Our results emphasise that gaps in the stratigraphic record often reflect episodes of kilometre-scale vertical movements that may result from both lithospheric and sub-lithospheric processes
Greenland SMB, D and TMB annual time series 1840-2012
No full text
<body lang=en-DK link=blue vlink="#954F72" style='tab-interval:36.0pt;
word-wrap:break-word'>
All-Greenland
Surface and Total Mass Balance annual time series after
<li class=MsoNormal style='color:black;mso-list:l2 level1 lfo3;tab-stops:list 36.0pt;
vertical-align:baseline'>Kjeldsen
et al (2015) <span
style='color:#1155CC'>https://doi.org/10.1038/nature16183
<li class=MsoNormal style='color:black;mso-list:l2 level1 lfo3;tab-stops:list 36.0pt;
vertical-align:baseline'>Box
(2013) SMB <span
style='color:#1155CC'>https://doi.org/10.1175/JCLI-D-12-00518.1
<li class=MsoNormal style='color:black;mso-list:l2 level1 lfo3;tab-stops:list 36.0pt;
vertical-align:baseline'>Box
and Colgan (2013) TMB <span
style='color:#1155CC'>https://doi.org/10.1175/jcli-d-12-00546.1
<li class=MsoNormal style='color:black;margin-bottom:4.0pt;mso-list:l2 level1 lfo3;
tab-stops:list 36.0pt;vertical-align:baseline'><span style='mso-fareast-font-family:
"Times New Roman"'>Box et al. (2013) Accumulation <a
href="https://doi.org/10.1175/JCLI-D-12-00373.1">https://doi.org/10.1175/JCLI-D-12-00373.1
Data
file
and notes
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>Greenland_mass_balance_totals_1840-2012_ver_20141130_with_uncert_via_Kjeldsen_et_al_2015.csv
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>Column headers:
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>year
accumulation accumulation 1sigma melt melt
1sigma
retention retention
1sigma runoff runoff 1sigma
discharge from 6 year lagged average runoff discharge
1sigma TMB TMB
1sigma
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>1840 645.43
65.82 277.70 64.34 143.07 48.72 173.56
46.15 406.08 36.65 65.79
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>Units: Gt per year, temperature
in deg. C
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>Column description: “1sigma”
refers to uncertainty; “accumulation” is snow accumulation equivalent with tp
minus vapor lsos; “melt” is snow or ice converted to liquid; “retention” is nternal
accumulation; “runoff” is liquid melt water exiting ice sheet; “SMB” is surface
mass balance; “TMB” is total mass balance
<p class=MsoNormal style='margin-top:0cm;margin-right:0cm;margin-bottom:4.0pt;
margin-left:36.0pt'>From these data SMB can be
computed as: accumulation - runoff - discharge
Time
series visualization code and data: <a
href="https://github.com/jasonebox/TMB_Greenland_1840-2012"><span
style='font-family:"Calibri",sans-serif;color:#1155CC'>https://github.com/jasonebox/TMB_Greenland_1840-2012
Issues:
<a
href="https://github.com/jasonebox/TMB_Greenland_1840-2012/issues"><span
style='font-family:"Calibri",sans-serif;color:#1155CC'>https://github.com/jasonebox/TMB_Greenland_1840-2012/issues
Description
The Box<span
lang=EN-US style='color:black;mso-ansi-language:EN-US'> (<span
style='color:black'>2013) 171 year (1840-2010) surface mass balance
reconstruction is developed from linear regression parameters that describe the
correlation between a.) spatially discontinuous in-situ monthly air temperature
records (Cappelen, 2011; Cappelen et al., 2001, 2006; Vinther et al., 2006) or
firn/ice cores (Box et al., 2013) and b.) spatially continuous outputs from
regional climate model RACMO version 2.1 (Ettema et al., 2010). A 43-year
overlap period 1960–2012 with RACMO2.1 is used to determine regression
parameters on a 5 km grid cell basis. Then the predictor (air temperature and
firn/ice core) data span 1840 to 2012. A fundamental assumption is that the
calibration factors, regression slope and offset for the calibration period
1960–2012 are stationary over time. See “part I” of Box et al. (2013) for a
description of the method, which includes a formal approach to estimate
uncertainty.
The Box<span
lang=EN-US style='color:black;mso-ansi-language:EN-US'> (<span
style='color:black'>2013) 171 year (1840-2010) SMB reconstruction is refined in
(Kjeldsen et al., 2015) to incorporate: including peripheral ice masses in
addition to the ice sheet; a more sophisticated meltwater retention scheme
(Pfeffer et al., 1991); multiple in-situ records are weighted in their
contribution to the estimated value; the annual accumulation rates from ice
cores are dispersed <span
style='color:black'>into a monthly temporal resolution by weighting the monthly
(based on the 1960–2012 RACMO2.1 data) fraction of the annual total for each
grid cell in the domain and the revised surface mass balance data end with year
2012.
The 173
year (1840-2012) reconstruction of annual total mass balance (TMB) is after
(Box and Colgan, 2013) improved in (Kjeldsen et al., 2015). Annual solid ice
discharge<span
style='color:black'> (<span lang=EN-US style='color:black;mso-ansi-language:
EN-US'>D) was estimated via a fit of
unsmoothed solid ice discharge data (Rignot et al., 2008, 2011) with Box<span
lang=EN-US style='color:black;mso-ansi-language:EN-US'> (<span
style='color:black'>2013) runoff data having a 6-year trailing average in Kjeldsen
et al. (<span
style='color:black'>2015). The physical basis for the SID parameterization
using runoff is described in (Box and Colgan, 2013).
Works
Cited
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Box,
J. E.: Greenland Ice Sheet Mass Balance Reconstruction. Part II: Surface Mass
Balance (1840–2010), J. Clim., 26(18), 6974–6989, 2013.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Box, J. E. and Colgan, W.: Greenland Ice Sheet
Mass Balance Reconstruction. Part III: Marine Ice Loss and Total Mass Balance
(1840–2010), J. Clim., 26(18), 6990–7002, 2013.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Box, J. E., Cressie, N., Bromwich, D. H., Jung,
J.-H., van den Broeke, M., van Angelen, J. H., Forster, R. R., Miège, C.,
Mosley-Thompson, E., Vinther, B. and McConnell, J. R.: Greenland Ice Sheet Mass
Balance Reconstruction. Part I: Net Snow Accumulation (1600–2009), J. Clim.,
26(11), 3919–3934, 2013.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Cappelen, J.: DMI monthly climate data
collection 1768– 2010, Denmark, the Faroe Islands and Greenland, Danish
Meteorological Institute., 2011.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Cappelen, J., Jørgensen, B. V., Laursen, E. V.,
Stannius, L. S. and Thomsen, R. S.: The observed climate of Greenland, 1958–99
with climatological standard normals, Danish Meteorological Institute.,
Technical Report 00-18, 151 pp., 2001.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Cappelen, J., Laursen, E. V., Jørgensen, P. V.
and Kern-Hansen, C.: DMI monthly climate data collection 1768–2005, Denmark,
the Faroe Islands and Greenland, Danish Meteorological Institute., 2006.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Ettema, J., van den Broeke, M. R., van
Meijgaard, E., van de Berg, W. J., Box, J. E. and Steffen, K.: Climate of the
Greenland ice sheet using a high-resolution climate model – Part 1: Evaluation,
The Cryosphere, 4(4), 511–527, 2010.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Kjeldsen, K. K., Korsgaard, N. J., Bjørk, A. A.,
Khan, S. A., Box, J. E., Funder, S., Larsen, N. K., Bamber, J. L., Colgan, W.,
van den Broeke, M., Siggaard-Andersen, M.-L., Nuth, C., Schomacker, A.,
Andresen, C. S., Willerslev, E. and Kjær, K. H.: Spatial and temporal
distribution of mass loss from the Greenland Ice Sheet since AD 1900, Nature,
528(7582), 396–400, 2015.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
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Pfeffer, W. T., Meier, M. F. and Illangasekare,
T. H.: Retention of Greenland runoff by refreezing: Implications for projected
future sea level change, J. Geophys. Res., 96, 22,117, 1991.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol'>·
Rignot, E., Box, J. E., Burgess, E. and Hanna,
E.: Mass balance of the Greenland ice sheet from 1958 to 2007, Geophysical
Research Letters, 35(20), doi:10.1029/2008gl035417, 2008.
<span
style='font-family:Symbol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
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Rignot, E., Velicogna, I., van den Broeke, M.
R., Monaghan, A. and Lenaerts, J. T. M.: Acceleration of the contribution of the
Greenland and Antarctic ice sheets to sea level rise, Geophys. Res. Lett.,
38(5), doi:10.1029/2011gl046583, 2011.
<span
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Vinther, B. M., Andersen, K. K., Jones, P. D.,
Briffa, K. R. and Cappelen, J.: Extending Greenland temperature records into
the late eighteenth century, J. Geophys. Res., 111(D11),
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