The rtopo2_interp function interpolates data from RTopo-2 (Schaffer et al. 2016, see reference below).
zi = rtopo2_interp(dataset,lati,loni) zi = rtopo2_interp(dataset,xi,yi) zi = rtopo2_interp(...,method)
zi = rtopo2_interp(dataset,lati,loni) returns interpolated values from any of the RTopo-2 gridded datasets, where lati and loni are georeferenced query coordinates. The dataset can be any of the following:
- 'bed' bed elevations relative to the geoid.
- 'base' ice base elevations relative to the geoid.
- 'surface' ice surface elevations relative to the geoid.
- 'wct' water column thickness taken as base-bed.
- 'mask' mask values numbered 0 through 3 as described below.
- 'sourcedraft' source of ice draft data as described below.
- 'sourcebathy' source of elevation data as described below.
zi = rtopo2_interp(dataset,xi,yi) interpolates to query coordinates specified by polar stereographic (true latitude 71 S) meters. Coordinates are automatically determined by the islatlon function.
zi = rtopo2_interp(...,method) specifies any interpolation method accepted by interp2. It's a bit silly to stress about the interpolation method here, because the difference between linear and cubic will never be as significant as the uncertainty of these datasets. Also, interpolation is performed in geocoordinates rather than polar stereographic coordinates, which could possibly introduce a weighting mechanism of its own. Default interpolation method is 'linear', except for the mask and souce datasets whose default is 'nearest'.
- 0. ocean
- 1. grounded ice
- 2. floating ice
- 3. bare land
Data source values:
- World Ocean bathymetry GEBCO_2014 (Weatherall et al., 2015)
- Southern Ocean bathymetry IBCSO (Arndt et al., 2013)
- Arctic Ocean bathymetry IBCAOv3 (Jakobsson et al., 2012)
- Antarctic ice sheet/shelf surface height Bedmap2 and thickness and bedrock topography (Fretwell et al., 2013)
- Greenland ice sheet/glacier surface height Morlighem et al. (2014) (M-2014) and thickness and bedrock topography
- Fjord and shelf bathymetry close to the Bamber et al. (2013) (B-2013) Greenland coast
- Bathymetry on Northeast Greenland Arndt et al. (2015) (NEG_DBM) continental shelf
- Bathymetry in several narrow Greenland fjords artificial, see Merging strategy and Data and on parts of the Greenland continental shelf corrections in Sect. 2.2.3 for details
- Bathymetry for Getz and western Abbot Ice ALBMAP (Le Brocq et al., 2010) Shelf cavities
- Bathymetry for Fimbulisen cavity Nøst (2004), Smedsrud et al. (2006)
- Ice thickness for Nioghalvfjerdsfjorden Glacier DTU (Seroussi et al., 2011) and Zachariæ Isstrøm Operation Icebridge (Allen et al., 2010, updated 2015) Alfred Wegener Institute (AWI) Mayer et al. (2000)
- Contour of iceberg A-23A in Weddell Sea Paul et al. (2015)
Suppose you want to know the surface elevation along a flight from the South Pole to McMurdo Station. Start by creating a straight-line path with 100 m spacing:
[lati,loni] = pspath([-90 -77.8],[0 166.7],100);
Now to get the surface elevation just call up rtopo2_interp like this:
sfz = rtopo2_interp('surface',lati,loni);
Plot the results as a function of distance traveled along the path:
d = pathdistps(lati,loni,'km'); plot(d,sfz) xlabel('distance from South Pole to McMurdo (km)') ylabel('surface elevation (m)')
Suppose you have some regularly spaced grid, let's say it's 800 km by 1000 km at 1 km resolution, centered on Shackleton Ice Shelf. That grid would look like this:
[lati,loni] = psgrid('shackleton ice shelf',[800 1000],1);
To get RTopo-2 values at those grid locations, simply use rtopo2_interp:
bed = rtopo2_interp('bed',lati,loni);
Plotting's easy now:
figure pcolorps(lati,loni,double(bed)) axis tight cb = colorbar; ylabel(cb,' bed elevation (m) ') shadem(3,[225 60]) scalebarps('location','se','color','w')
If you use this dataset and Antarctic Mapping Tools, please cite the following:
Schaffer, Janin; Timmermann, Ralph; Arndt, Jan Erik; Kristensen, Steen Savstrup; Mayer, Christoph; Morlighem, Mathieu; Steinhage, Daniel (2016): A global, high-resolution data set of ice sheet topography, cavity geometry, and ocean bathymetry. Earth System Science Data, 8(2), 543-557, doi:10.5194/essd-8-543-2016 and doi:10.1594/PANGAEA.856844
Greene, C.A., Gwyther, D.E. and Blankenship, D.D., 2016. Antarctic Mapping Tools for Matlab. Computers & Geosciences. http://dx.doi.org/10.1016/j.cageo.2016.08.003
The RTopo-2 Matlab functions and supporting documentation were written by Chad A. Greene of the University of Texas at Austin, November 2016.