ESA POLAR+ 4D Greenland Experimental Dataset Collection
Collection of five experimental datasets provided within the ESA POLAR+ 4D Greenland project.
Monthly basal melt discharge (2001-2019) at the five selected drainage basins on the Greenland ice sheet; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson. This is based on solid and liquid discharge estimates for each marine-terminating glacier, thus assessing the seasonal and annual export of freshwater from the land ice to the fjords. For each study site, a *.csv is available containing the total (sum of the components due to geothermal heating, frictional heating and surface water heating) monthly basal discharge rates.
Please read the README_BasalMelt.txt in the zip file and references Karlsson, Nanna B, 2021, "Greenland Ice Sheet Basal Melt", https://doi.org/10.22008/FK2/PLNUEO , GEUS Dataverse, V1, Karlsson, N.B., Solgaard, A.M., Mankoff, K.D. et al.
A first constraint on basal melt-water production of the Greenland ice sheet. Nature Communications 12, 3461 (2021). https://doi.org/10.1038/s41467-021-23739-z
Estimated volume changes of five subglacial lakes in Greenland, that are characterised by collapse basins in the ice sheet surface above the lakes. The subglacial lake volumes have been estimated by computing the collapse basin volume.
At collapse basins where CryoSat-2 Swath data is available, the CS2 heights and the DEM volumes are used to create a smoothed linear inversion to estimate the CS2 volumes as a function of time. The uncertainties of the volume estimates derived from the inversion are based on an error propagation of the CS2 depth estimates. Please read the README_SubglacialLakes.txt in the zip file.
Total melt water retention in the firn (1958-2019). It is estimated either directly from the MAR RCM output, or by forcing the DTU firn model with the climate from the RCMs. Reference of these MAR simulations: Tedesco, M. and Fettweis, X.: Unprecedented atmospheric conditions (1948–2019) drive the 2019 exceptional melting season over the Greenland ice sheet , The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, 2020.
Currently we provide two datasets in this experimental dataset:
1. The native model firn storage from MAR
MARv3.11 includes a description of water retention in the firn based on the MAR snow model (CROCUS) which simulates a fixed number of snow, ice, or firn layers of variable thickness, and transfers mass and energy between them. The model densifies the snow/firn layers as a function of the weight of the overlying mass, and through liquid water retention. Penetrating meltwater is retained in the firn by a fraction of the pore space (irreducible water saturation) and refreezing. Here, the irreducible water saturation is set to 10%, and the density at which pores are assumed to close off thereby eliminating liquid water retention is set to 900 kg/m3.
2. Offline DTU firn-model firn storage
In provisioning the test dataset for the Watson basin (CTS1) it was noted that the density at which pores are assumed to close off thereby eliminating liquid water retention (MAR: 900 kg/m3) is highly influential on the meltwater storage. Further, parameter studies within the DTU firn model have shown that it is more likely the pore close off is lower than the native 900 kg/m3. Hence, the DTU firn model provides a secondary estimate for meltwater storage in the firn assuming a percolation pore close off of 830 kg/m3.
Both datasets are provided as summed estimates for the snow/firn covered part of five drainage basins at monthly temporal resolution; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson.
Please read the README_Firn.txt in the zip file. Information for the DTU firn model can be found in Simonsen, S., Stenseng, L., Ađalgeirsdóttir, G., Fausto, R., Hvidberg, C., & Lucas-Picher, P. (2013). Assessing a multilayered dynamic firn-compaction model for Greenland with ASIRAS radar measurements. Journal of Glaciology, 59(215), 545-558. https://doi.org/10.3189/2013JoG12J158
Total run off and surface water from the upper and lower parts of the five drainage basins; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson. The estimations are directly from the MAR 3.11 RCM. Please read the README_UpperLower.txt in the zip file.
There are Four columns in each file;  (Index of estimation), Run Off [km^3] (Total basin Run Off in km^3), Surface Water [km^3] (Total amount of basin Surface Water in km^3), Year [Decimal Year] (Decimal year of estimation).
The total monthly runoff (2017-2021), both surface and basal, of five drainage basins in Greenland; NEGIS, Northern Lakes, Southern Lakes, Store, and Watson. The run off is estimated by summing the Surface Melt, Firn Retention, Supraglacial Change and Subglacial Runoff into monthly basin scale estimates.
1. Surface water was computed from the chosen RCM on a monthly basis by summing the surface melt and the liquid precipitation (rain fall).
2. Firn Retention is computed by subtracting the RCM runoff from the RCM surface melt in the snow/firn-covered part of the drainage basins
3. Supraglacial change volume estimates were determined via the following methodology by Lancaster University.
Supraglacial lake extent were delineated using RT algorithm to classify water within S2 images. Lake depths were calculated using a radiative transfer model (section 18.104.22.168 ATBD). Lake depth was determined using Sentinel 2 red band imagery (Band 4). Total lake volume was calculated by multiplying lake depths by lake area for each individual lake polygon and summing over the basin area.
Volume uncertainty was determined via comparison with ICESat-2 transects. The uncertainty is represented by the maximum percentage difference between lake depths integrated over ICESat-2 transects and the corresponding S2 derived lake depth transect. For the red band, it was found that lake volumes were being underestimated by up to 33.5%.
Some of the meltwater in the supraglacial lakes will not leave the ice sheet at the end of the melt season but remain frozen over the winter. It is very difficult to estimate how much. In this experimental dataset we assume that it is 25% of the observed September water volume that is frozen and stored during winter.
4. Subglacial meltwater flux maps were computed Greenland-wide, and integrated over the drainage basins of interest to produce monthly estimates of basal runoff.
Please read the README_TotalRunOff.txt