The ocean plays an important role in modulating the mass balance of the polar
ice sheets by interacting with the ice shelves in Antarctica and with the
marine-terminating outlet glaciers in Greenland. Given that the flux of warm
water onto the continental shelf and into the sub-ice cavities is steered by
complex bathymetry, a detailed topography data set is an essential ingredient
for models that address ice–ocean interaction. We followed the spirit of the
global RTopo-1 data set and compiled consistent maps of global ocean
bathymetry, upper and lower ice surface topographies, and global surface
height on a spherical grid with now 30 arcsec grid spacing. For this new
data set, called RTopo-2, we used the General Bathymetric Chart of the Oceans
(GEBCO_2014) as the backbone and added the International Bathymetric Chart
of the Arctic Ocean version 3 (IBCAOv3) and the International Bathymetric
Chart of the Southern Ocean (IBCSO) version 1. While RTopo-1 primarily aimed
at a good and consistent representation of the Antarctic ice sheet, ice
shelves, and sub-ice cavities, RTopo-2 now also contains ice topographies of
the Greenland ice sheet and outlet glaciers. In particular, we aimed at a
good representation of the fjord and shelf bathymetry surrounding the
Greenland continent. We modified data from earlier gridded products in the
areas of Petermann Glacier, Hagen Bræ, and Sermilik Fjord, assuming that
sub-ice and fjord bathymetries roughly follow plausible Last Glacial Maximum
ice flow patterns. For the continental shelf off Northeast Greenland and the
floating ice tongue of Nioghalvfjerdsfjorden Glacier at about 79
Mass loss from the Greenland ice sheet presently accounts for about 10 % of
the observed global mean sea-level rise
Around Antarctica, research into ocean–cryosphere interaction has been an
established field of science for several decades. Many aspects of water mass
modification in the Southern Ocean's marginal seas can only be understood if
the fluxes of heat and freshwater at the base of the ice shelves surrounding
the Antarctic continent are considered
The Refined Topography data set
The aim of this paper is to present the newly compiled global topography data set RTopo-2, which provides a detailed bathymetry for the continental shelf around Greenland and contains ice and bedrock surface topographies for Greenland and Antarctica as part of a global, self-consistent data set with a horizontal grid spacing of 30 arcsec. In the following sections, we introduce the data used, the processing applied to each data set and the strategies followed for merging the data sets in a self-consistent way. We demonstrate the improvements achieved in RTopo-2 compared to previous products and discuss the most relevant caveats.
We followed the spirit of RTopo-1 and compiled global fields for
bedrock topography (ocean bathymetry, surface topography of continents, bedrock topography under grounded or floating
ice); surface elevation (upper ice surface height for Antarctic and Greenland ice sheets/ice shelves, bedrock elevation for ice-free continent, zero for
ocean); ice base topography for the Antarctic and Greenland ice sheets/ice shelves (ice draft for ice shelves and floating glaciers, zero in absence of
ice); a surface type mask that indicates open ocean, grounded ice (ice sheets), floating ice (ice shelves/floating glaciers), and bare land
surface; positions of coastlines and ice shelf/floating glacier front lines.
The bedrock topography is identical to the surface elevation for ice-free
land surface and identical to the ice base topography for grounded ice
(Fig.
RTopo-2 has been compiled by combining various gridded data sets
(Table
Sketch of a 2-D vertical section along a floating glacier tongue/ice shelf with grounded and floating ice (white), sub-ice bedrock/ocean seafloor (brown), and water in a subglacial cavity and the open ocean (blue). Lines indicate the bedrock topography (brown), the surface elevation (dark blue), and the ice base topography (black).
Data sources for the ocean bathymetry in RTopo-2. Black areas denote
transition zones between the data sets (source flag 20). Further explanations
are given in Table
Data sources for individual regions merged in RTopo-2. The index numbers correspond to the source flags in Fig.
For each of the newly incorporated regional grids, we had to ensure or
enforce consistency with the existing topographies. The necessity for this
step is quite obvious when independent data sets are combined; interpolation
of discontinuous fields (an obvious example here is the discontinuity at ice
shelf fronts) is another source for the creation of local inconsistencies
that need to be cured. For RTopo-2, the term ice thickness water column thickness water column thickness is zero, i.e. lower ice and bedrock topographies are identical, for grounded
ice; lower ice topography is negative (below sea level) and surface height is positive (above sea level) for ice
shelves; ice draft and thickness are zero outside ice-covered regions; bedrock topography is below sea level in the ocean; there are no enclosed gaps (“holes”) in the ice sheet/ice shelves other than those associated with rock
outcrops; there are no water areas south of the coastline of Antarctica.
These points may all seem trivial, but they are in fact not universally
ensured in the gridded data sets available to date. Note that the surface type
mask plays a key role in our algorithm; instead of being a merely diagnostic
property, the surface type determines the conditions to which consistency is
enforced. Choices that needed to be made include deciding which of the
topographies should be trusted more – e.g. whether bedrock from one source or
lower ice topography from another source is more reliable. These decisions
were not always straightforward and are somewhat subjective; we give some of
the reasoning in the sections discussing specific regional data sets below.
In general, consistency and continuity have been valued higher than an exact
rendition of the source data sets in RTopo-2.
As the nucleus of RTopo-2 we used an updated version of the General
Bathymetric Chart of the Oceans (GEBCO) 30 arcsec data set
GEBCO_2014 includes the International Bathymetric Chart of the Southern
Ocean (IBCSO) Version 1.0
The bathymetry of the continental shelf along the Greenland coast is crucial
to ice–ocean studies in this region and thus there is a rising interest in a
good representation of these areas. Nevertheless, away from the commonly used
ship routes and especially in ice-covered areas, the depth of the sea floor
is only weakly constrained. Data coverage maps of IBCAOv3 show that many
shelf and fjord areas around the coast of Greenland are not covered by
soundings
Coastal and shelf region in the west of Greenland, including
Jakobshavn Isbræ. Maps show the ocean bathymetry/surface elevation in
IBCAOv3
Based on surface elevation maps from the Greenland Iceland Mapping Project
(GIMP,
In addition to the airborne ice thickness survey data and the surface
elevation obtained from GIMP
To benefit from the best parts of each data set, we used
the bedrock elevation from M-2014 for all locations with grounded ice (see below), the bedrock elevation from B-2013 within the fjords and in a narrow band of about 25 km width along the Greenland
coast, and the bathymetry from IBCAOv3 further away from the coast, with transition zones of 10 km width.
Consequently, the large areas of continental shelf around Greenland are mainly
determined by IBCAOv3 data while the fjord topographies are given by the
B-2013 bedrock (e.g. Fig.
Before merging the B-2013 bathymetry with the M-2014 bedrock elevation, we
smoothed the B-2013 data set by using an unweighted moving average with a
1 km footprint. Smoothing was necessary to avoid artefacts arising from
differing grid spacings and/or from steep unrealistic gradients in the B-2013
bedrock (see above). In regions where the GIMP coastline demands ocean but
B-2013 gives land values, we prescribed small patches with negative
topography values (source flag 8, e.g. Fig.
Maps of the ocean bathymetry/bedrock elevation in B-2013
Three sectors turned out to be particularly difficult to handle:
the region around Petermann and Ryder glaciers (North Greenland), the North Greenland fjords system off Hagen Bræ and Marie Sophie and Academy glaciers, and the Sermilik Fjord in front of Helheim, Fenris and Midgaard glaciers, and Køge Bugt (Southeast Greenland).
Observations at the front of Petermann Glacier's floating ice tongue imply
that the subglacial fjord is about 900 m deep
Further to the east, the B-2013 representation of the continental shelf area
in front of Ryder Glacier features a very steep gradient and a deep trough
close to the coast, which appears unrealistic. We replaced some of the
interpolated deep and adjacent shallow parts with a smooth deep fjord/shelf
bathymetry (Fig.
Ice thickness maps of the floating ice tongue of
Nioghalvfjerdsfjorden Glacier. The maps show the coverage of ice thickness
measurements from radar and seismic soundings
For the fjord system in front of the Hagen Bræ, Marie Sophie, and Academy
glaciers, we defined small patches of artificial topography (with depth
values ranging between 50 and 250 m) to achieve a smooth transition between
the subglacial bedrock and the fjord bathymetry at the glacier fronts. We
connected the under-ice bathymetry with the ocean bathymetry following
plausible Last Glacial Maximum (LGM) ice flow patterns. The LGM ice sheet
margin was approximately located at the continental shelf break in this
region
For the Sermilik Fjord off Helheim Glacier and for Køge Bugt, the
bathymetry data from B-2013 show very deep troughs and steep gradients on the
continental shelf (Fig.
All regions with inserted artificial values were marked with the data source flag 8.
Bottom topography on the continental shelf northeast of Greenland is poorly
resolved and contains a number of artefacts in IBCAOv3. Reprocessing and
combining multi- and single-beam echo sounding data from more than 2 decades
resulted in a significantly improved digital bathymetry model (NEG_DBM)
We included the NEG_DBM bedrock elevation in the continental shelf area
between the Greenland coast in the west and the continental shelf break
(600 m depth contour) in the east, from 75 to about
80.5
As discussed in Sect.
We use M-2014 as the backbone representation of the Greenland ice sheet
geometry and as the basis for the ice/land/sea mask within the perimeter of
the Greenland continent. These are based on ocean and ice masks from GIMP,
while the ice shelves were added by using InSAR mapping (differential
satellite radar interferometry) following
Given that the floating ice tongue of Nioghalvfjerdsfjorden Glacier is one of
the very few places in the Arctic where ice and ocean interact at an ice
shelf base that covers more than just a very small area, this is a region of
particular scientific interest. We therefore decided to enhance the ice
thickness data in this area by using recently obtained airborne radar data as
well as seismic soundings
Assuming hydrostatic equilibrium, we calculated the surface height (
We combined the newly gridded glacier topographies with the surrounding surface height and ice draft maps with a transition zone of 2 km width. Corrections needed to be applied in areas where the newly gridded ice thickness exceeded the water depth. In regions where the surface type mask derived from M-2014 proposes the existence of floating ice, bedrock topography was corrected by applying a minimum water column thickness of 1 m. This procedure is justified by the fact that ice thickness observations for the floating ice tongues are much more densely spaced than the very sparse sub-ice bathymetry measurements obtained from seismics.
In comparison, the RTopo-2 ice thickness map derived from measurements
deviates from M-2014 mostly towards the glacier front (Fig.
For the sub-ice cavity of Nioghalvfjerdsfjorden Glacier, the NEG_DBM
provides a bathymetry grid that has been interpolated from seismic
observations of
Bathymetry for Getz Ice Shelf cavity and its surrounding
in Bedmap2
As discussed in Sect.
Where the coastline of the Antarctic continent is formed by a transition from grounded ice or bare land to open ocean, we join the Bedmap2 and IBCSO topographies in a narrow band directly at the coast. Along the grounding lines of sub-ice cavities, the transition between the IBCSO and Bedmap2 topographies is in a roughly 8 km wide band 10 km off the grounding line (i.e. within the sub-ice cavity). In any case, a smooth transition between the IBCSO and Bedmap2 grids is easy to ensure due to the fact that Bedmap2 bedrock topography data have been incorporated in the generation of IBCSO. Small inconsistencies that still arise from the interpolation (mainly due to the discontinuity of ice draft along the ice front) were cured by enforcing grounded ice bottom topography to be identical to bedrock topography.
Given that the IBCSO data set incorporates not only bedrock relief but also ice surface topography from Bedmap2, it may seem better to use the IBCSO products throughout Antarctica and thus avoid the stitching between the two grids along the Antarctic continent. We decided not to follow this approach because IBCSO does not provide information about the thickness of floating ice shelves. Given that the compilation of RTopo-2 has been targeted towards studies of ice dynamics and ice–ocean interaction at the interfaces between ice sheets and ocean, we decided that discontinuities of ice thickness across the grounding lines are to be avoided as far as possible. Therefore, ice surface and bottom topographies for grounded and floating ice are to be adopted from one self-consistent data set, which is possible only with Bedmap2. Similar consistency arguments apply to the bedrock relief under grounded ice; again we decided to use the original Bedmap2 product here to avoid introducing inconsistencies.
For Filchner-Ronne Ice Shelf and the ice streams in its catchment basin, as
well as for the ice topographies in many other regions, the benefit of a
largely improved data coverage and grid spacing in Bedmap2 is very obvious
and quite substantial. However, with regard to the representation of sub-ice
cavity bathymetry, the transition from RTopo-1 to Bedmap2 does not
universally yield an improvement. Although Fig. 6 in
According to
A similar case can be made for Abbot Ice Shelf. For the eastern part of Abbot
Ice Shelf, sub-ice bathymetry in Bedmap2 is derived from the
For Larsen C Ice Shelf cavity, Fig. 6 in
Bedmap2 bathymetry under the floating Fimbulisen is claimed to be derived
from RTopo-1 but in fact deviates from the latter substantially.
Specifically, the deep troughs between the islands (ice rises) in the eastern
part of the cavity (i.e. between 1 and 5
In August 1986, three giant icebergs (A-22, A-23, and A-24), each one between
3000 and 4000 km
To enable high-resolution modelers to do the model-to-data comparison in a
more consistent way – especially given that data coverage is about to
improve considerably in the framework of ongoing and planned field activities
in the area – and to achieve a more realistic representation of the local
ocean currents in hindcast simulations, we decided to include the signature
of A-23A in RTopo-2. The area covered by the iceberg was picked from a
composite of 2013 MODIS images
Note that the original bathymetry grid under the iceberg is fully preserved so that the whole feature can be removed without any loss of information in case this seems desirable in any particular application of the data set.
Global surface type mask (compare with Fig. 7 in
In addition to the maps of the bedrock and ice topographies we provide a
global mask which distinguishes between open ocean, bare land, grounded ice,
and floating ice (Fig.
On the polar continents, the mask largely follows M-2014 for Greenland and Bedmap2 for Antarctica. Ice caps not connected to the Antarctic ice sheet or Greenland mainland have been removed from the mask and classified as bare land. Ice surface height in these cases has been adopted as bedrock surface height. In contrast to RTopo-1, the surface type mask in RTopo-2 contains information about rock outcrops (surface type “bare land”) in Antarctica.
Lakes and enclosed seas outside Antarctica and Greenland are marked as bare land in the mask but are still present in the bathymetry data set adopted from GEBCO_2014. This was done to avoid the tedious procedure of manually removing features with a topography below sea level and no connection to the world ocean when setting up an ocean general circulation model.
For the Northeast Greenland continental shelf, the NEG_DBM bathymetry map
provides bedrock elevation with a very high data coverage. We used this data
set to adjust the surface type mask: grid points with an elevation
In the transition corridors between different data sets and in regions where values have been inferred from consistency arguments, errors are hard to quantify. Here we can only give an overview on error estimates provided by the authors of some of our source data sets.
In GEBCO_2014 approximately 18 % of the non-land grid cells are
constrained by bathymetric control data, which consist of echo sounding data
as well as pre-prepared bathymetric grids that may contain interpolated areas
In general, the accuracy of echo sounding systems can be expected to be about one percent of the water depth. However, in the areas between the sounding tracks uncertainties can be much higher.
For ice surface heights of Greenland the overall root-mean-square deviation
between the GIMP digital elevation model and ICESat elevation is
The technical error of ice thicknesses derived from radio echo sounding depends mainly on the sampling interval and transmitted signal length, both of which vary from system to system. The vertical resolution in ice thickness of the various employed RES systems varies between 5.05 and 8.45 m; the sampling precision is higher, usually in the order of 1 m. Thus an uncertainty of about 15 to 35 m for the ice thickness is realistic. However, complex geometries and steep topography confining the investigated glaciers and ice tongues can cause side and multiple reflections which mask the subglacial reflections, especially in airborne measurements.
Ice thickness and ice draft mapped by
Ice thickness maps derived from the available observations for
Nioghalvfjerdsfjorden Glacier and Zachariæ Isstrøm reveal distinct
differences between data sets from different years. All data across
Zachariæ Isstrøm are based on radar data from 2010 to 2014 (obtained
from Operation Icebridge and AWI flights). Based on Landsat optical imagery,
Ice thickness data covering Nioghalvfjerdsfjorden Glacier include
additionally a large number of radar tracks and seismic data obtained 10
years earlier in 1997/98 (DTU/
Next to the uncertainties related to data interpretation and processing, the
representation of the firn layer (“firn correction”) is an issue that
requires serious attention. While in B-2013 a firn layer thickness of 10 m
in all ablation regions around Greenland is assumed, there is no firn
correction applied in M-2014. Snow depth varies strongly over the Greenland
ice sheet and within the seasonal cycle
We compiled a global 30 arcsec data set for World Ocean bathymetry and
Greenland/Antarctic ice sheet/shelf topography. High-resolution data from
Greenland floating glaciers and of bathymetry on the Northeast Greenland
continental shelf were compiled into a synthesis of gridded bathymetry
products including the
This new data set provides enough local detail for a wide range of global or regional studies. Our main target group are ocean modelers who aim at a realistic representation of ice–ocean interaction in an ocean general circulation or climate model. In the current version, particular attention has been paid to the floating glaciers and the continental shelf in the Northeast Greenland sector. Other Greenland fjord regions are of similar interest but suffer from a lack of data. We encourage users who are specifically interested in one of those fjords to carefully review the data using information unused by us as a benchmark. Additional contributions of (gridded or ungridded) fjord/shelf bathymetry and/or glacier/ice shelf/cavity geometry are welcome and will be used to update the data set as soon as possible.
The RTopo-2 data set has been published by The complete global 30 arcsec data set has been split into four files:
RTopo-2.0.1_30sec_bedrock_topography.nc (3.7 GB), RTopo-2.0.1_30sec_ice_base_topography.nc (3.7 GB), RTopo-2.0.1_30sec_surface_elevation.nc (3.7 GB), and RTopo-2.0.1_30sec_aux.nc (2.8 GB), which contains auxiliary maps for data sources and the surface type mask. A regional 30 arcsec subset that covers all variables around Greenland in the interval 80 A regional 30 arcsec subset for the Antarctic region south of 50 RTopo-2.0.1_30sec_Antarctica_data.nc (2.5 GB) contains bedrock topography, ice base topography, and surface
elevation. RTopo-2.0.1_30sec_Antarctica_aux.nc (0.6 GB) contains auxiliary maps for data sources and the surface type mask. A complete global 1 arcmin data set that has been split into two files:
RTopo-2.0.1_1min_data.nc (2.8 GB) contains maps of bedrock topography, ice bottom topography, and surface
elevation. RTopo-2.0.1_1min_aux.nc (0.7 GB) contains auxiliary maps for data sources and the surface type mask.
Data sets for the location of coastlines (RTopo-2.0.1_coast.asc, 50 MB) and
the ice shelf/floating glacier front lines (RTopo-2.0.1_isf.asc, 1.4 MB)
have been prepared in ASCII format. Grounding lines are represented as parts
of the coastline. To enable communication in case of errors or updates, we
would appreciate a notification from users of our data set.
R. Timmermann (Southern Hemisphere) and J. Schaffer (Northern Hemisphere) designed the merging strategies and processed the RTopo-2 data sets. J. E. Arndt and M. Morlighem provided the latest versions of bathymetry and ice thickness maps for Greenland and the continental shelf in its vicinity. S. S. Kristensen, C. Mayer, and D. Steinhage provided pre-processed ice thickness data for Nioghalvfjerdsfjorden Glacier. J. Schaffer prepared the manuscript with contributions from all co-authors.
The authors would like to thank S. Paul and R. Zentek for extracting the
iceberg position from the MODIS data, X. Asay-Davis, S. Coers,
B. K. Galton-Fenzi, H. Gudmundsson, H. H. Hellmer, D. Jansen, L. Padman, and
D. Martin for helpful discussions, and W. Cohrs, H. Liegmahl-Pieper, and
C. Wübber for providing excellent computing facilities at AWI. GEBCO_2014
Grid (version 20150318) data were obtained from