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3D static reservoir model of the Havnsø structure in Petrel™ format, v. 2020
No full text3D numerical reservoir model of the Gassum Formation in the Havnsø structure (western Zealand, Denmark) in Petrel™ format. The model is based on a simplistic facies model which at present does not reflect the complex sand/shale architecture of the Gassum Formation. The model uses two synthetic wells to reflect high and low N/G scenarios. The porosity model is converted to permeability (property PERMX) using analogue well data from the nearby Stenlille gas storage faciltiy
Validation of remotely sensed snow liquid water content on the Greenland ice sheet at the PROMICE weather station sites
No full textSurface melt on the Greenland Ice Sheet has been estimated using L-band radiometer data measured by the SMOS satellite. This data has previously been validated with the focus of correct binary detection of melt. In this thesis, the validation will extend to correct detection of the magnitude of snow liquid water content as well. It will be validated by comparing the data from the SMOS satellite to data from the PROMICE automatic weather stations along the margin of the Greenland Ice Sheet. The SMOS satellite data has contamination issues along the margin of the Ice Sheet, where land or rock is near, as the resolution of the antenna on the SMOS satellite is 40 km. The contaminated data mainly shows low values of snow liquid water content with no clear peaks or onsets of melt and has therefore been discarded. When comparing data from the PROMICE Automatic weather stations along the margin of the Greenland Ice Sheet to data the SMOS satellite further in on the Ice Sheet, the SMOS satellite data shows a later onset of melt. This is not an issue with automatic weather station less than 20 km away. Moreover, the penetration depth of the L-band is depending on the snow liquid water content. This is clear as the SMOS satellite has higher snow liquid water content values than the PROMICE automatic weather stations, when the snow liquid water content is low, and lower value when the content is high. The penetration depth is estimated to at least 1.8 m in snow with 1% snow liquid water content, and higher in dry snow. Based on this, the penetration depth is assumed 1.8 m in this thesis, though results indicate that it should be less, which is reasonable as the snow liquid water content often is higher than 1% in the ablation season
Supplementary files for: A review of oil and gas seepage in the Nuussuaq Basin, West Greenland – implications for petroleum exploration
No full textThe Nuussuaq Basin in West Greenland has an obvious exploration potential. Most of the critical elements are well documented, including structures that could form traps, reservoir rocks, seals, and oil and gas seepage that document petroleum generation. And yet, we still lack a full understanding of the petroleum systems, especially the distribution of mature source rocks in the subsurface and the vertical and lateral migration of petroleum into traps. A recently proposed anticlinal structural model could be very interesting for exploration if evidence of source rocks and migration pathways can be found. In this paper we review all existing, mostly unpublished, data on gas observations from Nuussuaq. Furthermore, we present new oil and gas seepage data from the vicinity of the anticline. Occurrence of gas within a few kilometres on both sides of the mapped anticline have a strong thermogenic fingerprint suggesting an origin from oil-prone source rocks with a relatively low thermal maturity. Petroleum was extracted from an oil-stained hyaloclastite sample collected in the Aaffarsuaq valley in 2019 close to the anticline. Biomarker analyses revealed the oil to be a variety of the previously characterised ‘Niaqornaarsuk type’, reported to be formed from Campanian-age source rocks. Our new analysis places the ‘Niaqornaarsuk type’ 10 km from previously documented occurrences and further supports the existence of Campanian age deposits developed in source rock facies in the region
Havbundssedimentkort
No full textSedimentkortet, der er opdateret i 2020, viser fordelingen af havbundssedimenter i de danske farvande. Det er et geologisk kort, der hovedsageligt er baseret på seismiske og akustiske baggrundsdata kalibreret ud fra sedimentprøver.
Der er en meget ujævn fordeling af data fra den danske havbund – nogle steder ligger data meget tæt, andre steder meget spredt. Tolkningerne er derfor baseret på interpolationer mellem datapunkterne, men den geologiske viden om dannelsesforholdene sammenholdt med præcise kort over dybdeforholdene har været anvendt til at tegne grænserne mellem sedimenttyperne. Endvidere har biologiske informationer (f.eks. udbredelsen af bundlevende alger, ålegræs og muslinger) været anvendt som supplement til de geologiske data, idet de giver indirekte indikationer om det substrat, der knytter sig til de enkelte arters tilstedeværelse. Klassifikationerne på kortet er et udtryk for et gennemsnit af havbundens sedimenter i de øverste halve meter.
Denne opdaterede 2020-version af sedimentkortet består af den tidligere 2014-version, hvor nye kortlagte områder er erstattet med ny sedimentklassifikation. De nye klassifikationer stammer fra en lang række individuelle kortlægningsprojekter, der til forskel fra det tidligere generaliserede kort også kan være baseret på fulddækkende datasæt af sidescan sonar og/eller multibeam ekkolods data. For at tilgodese detaljeringsgraden i de nye data har vi besluttet at bibeholde deres oprindelige skala og opløsning.
Sedimentkortet og de bagvedliggende klassifikationer er beskrevet i Geoviden 2014, nr. 2.
Kortet kan downloades i dansk og engelsk version som en ArcGIS Pro mpkx-fil i dansk og som en pakke til brug i QGIS
Streams, Outlets, Basins, and Discharge [k=1.0]
No full textGreenland land and ice sheet streams, outlets, basins, and discharge. Routing assumes k = 1.0 for subglacial routing algorith
Greenland Ecosystem Monitoring (GEM) discharge data used by Mankoff et al. (2020)
No full textData comes from Kirsty Langley at the Asiaq-Greenland Survey, Nuuk, Greenland, is collected as part of the Greenland Ecosystem Monitoring Programme (GEM) project. The data is available from the GEM website ( https://data.g-e-m.dk/ ) but here is collected into one CSV file and includes additional metadata, such as the station location
Greenland Ice Sheet solid ice discharge from 1986 through last month: Discharge
No full textGreenland Ice Sheet solid ice discharge from 1986 through last month
Recent update includes PROMICE Ice Velocity (200m resolution), and baseline thickness has been updated to the 2020 DEM from Winstrup et al in review see github issue: #44 and related datasets.
Before using the data you should check for any open/active issue tagged WARNING</a
Snow and Firn temperature on the Greenland’s ice sheet
No full textFirn temperatures from the Greenland ice sheet have been collected, analyzed and combined to perform results concerning selected locations and the entire ice sheet. The purpose has been to investigate whether the recent atmospheric warming observed at the Greenland ice sheet has impacted the snow and firn temperature. Factors such as depth, average snowfall and air temperature have been taken into account using linear regression models to obtain useful results. Uncertainties and lack of data points leaches the results, but both local and global indications of climate changes have been shown
Greenland ice sheet meltwater runoff from the Kangerlussuaq and Isunnguata Sermia catchments using observation-based surface energy balance modeling (2009-2019)
No full textBackground:
This readme provides limited metadata for the Greenland ice sheet meltwater runoff from the Kangerlussuaq / Watson River and Isunnguata Sermia catchments in southwest Greenland. A more complete description of this product can be found in: Van As D, Bech Mikkelsen A, Holtegaard Nielsen M, Box JE, Claesson Liljedahl L, Lindbäck K, Pitcher L and Hasholt B (2017) Hypsometric amplification and routing moderation of Greenland ice sheet meltwater release. The Cryosphere, 11, 1371-1386 (doi:10.5194/tc-11-1371-2017).
Data format:
Data are provided in ASCII format.
File naming:
The file names indicate the calculated variable "GIS (Greenland ice sheet) surface runoff", the catchment ("WR" for Kangerlussuaq / Watson River and "IS" for Isunnguata Sermia), the time period in years, and the temporal resolution of the data ("hourly" and "daily").
Column information of data files at "hourly" temporal resolution:
Column 1 - Year
Column 2 - Day of year
Column 3 - Hour of day (UTC)
Column 4 - Total of meltwater generated at the ice sheet surface within the catchment per reported time unit (units: cubic meters)
Column 5 - Total of meltwater exiting the glacier front per reported time unit, i.e. column 4 including routing delay (units: cubic meters)
Column information of data files at "daily" temporal resolution:
Identical to the file structure detailed above, but without column 3.
Meltwater calculation:
Measurements by the on-ice KAN_L, KAN_M and KAN_U weather stations interpolated into 100-m elevation bins along with calibrated MOD10A1 surface albedo data, feeding into a surface energy balance model calculating meltwater runoff. Surface albedo per elevation bin in the Isunnguata Sermia catchment is set equal to the values of the Kangerlussuaq / Watson River ice sheet catchment. Van As D, Bech Mikkelsen A, Holtegaard Nielsen M, Box JE, Claesson Liljedahl L, Lindbäck K, Pitcher L and Hasholt B (2017) Hypsometric amplification and routing moderation of Greenland ice sheet meltwater release. The Cryosphere, 11, 1371-1386 (doi:10.5194/tc-11-1371-2017).
Catchment delineation:
Based on surface and bedrock digital elevation models. Lindbäck K, Pettersson R, Hubbard AL, Doyle SH, Van As D, Mikkelsen AB and Fitzpatrick AA (2015) Subglacial water drainage, storage, and piracy beneath the Greenland Ice Sheet. Geophysical Research Letters, 42 (18), 7606-7614 (doi:10.1002/2015GL065393).
Elevation bins:
Determined using the Greenland Mapping Project (GIMP) digital elevation model vertically transformed to the EGM96 geoid.
Routing delays:
Determined as a function of ice sheet surface elevation by tuning a delay-per-elevation-bin function for optimal agreement with Watson River discharge measurements. The same delay function is applied to - but not validated for - the Isunnguata Sermia catchment for which few discharge measurements exist. Van As D, Bech Mikkelsen A, Holtegaard Nielsen M, Box JE, Claesson Liljedahl L, Lindbäck K, Pitcher L and Hasholt B (2017) Hypsometric amplification and routing moderation of Greenland ice sheet meltwater release. The Cryosphere, 11, 1371-1386 (doi:10.5194/tc-11-1371-2017).
Funding information:
The runoff data were produced for the Greenland Analogue Project (GAP) funded by SKB (2008-2020), Posiva Oy (2008-2013) and NWMO (2008-2013). The weather stations central to this calculation feed data into the Programme for Monitoring of the Greenland Ice Sheet (PROMICE).
Terms of use:
If the data are presented or used to support results of any kind, please inform us, and include the acknowledgement "Greenland ice sheet runoff was calculated for the Greenland Analogue Project (GAP) in collaboration with the Programme for Monitoring of the Greenland Ice Sheet (PROMICE)".
Contact:
The responsible PROMICE point-of-contact for queries on these data is Dirk van As ([email protected]).
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Remote sensing of Greenland ice sheet surface characteristics using Sentinel 3 satellites
No full textIn recent decades, changes of global climate have had a profound effect on the cryosphere and in particular on polar glaciers. These glaciers, such as those in Greenland, have an important role in the global climate regulation via their low albedo, drive major currents by pouring fresh water into the ocean and are a major contributor to the sea level rise. Modeling the mass loss of those glacier is an important part in quantifying all of those effects. However, glaciers present a variety of snow and ice facies, that behave very differently depending on temperature, amount of snow fall and amount of snow melt. Describing and mapping snow facies over all polar glaciers is therefore primordial. In this project, we study previous methods to use remote sensing from passive microwave and radar satellites to map these facies, propose new methods to classify them and propose new methods to assess the quality of those classifications