melt_interp_adusumilli documentation

melt_interp_adusumilli interpolates ice shelf melt rate data from Adusumilli et al., 2020.

Contents

Syntax

mi = melt_interp_adusumilli(lati,loni)
mi = melt_interp_adusumilli(xi,yi)
mi = melt_interp_adusumilli(...,'antialias',wavelength)

Description

mi = melt_interp_adusumilli(lati,loni) interpolates the composite melt rates (representing the years 2010-2018) at the geographic locations lati,loni.

mi = melt_interp_adusumilli(xi,yi) as above, but for the query points xi,yi in south polar stereographic meters.

mi = melt_interp_adusumilli(...,'antialias',wavelength) performs spatial antialiasing before interpolation. This option is provided because the raw data is distributed at 500 m resolution, but you may be interpolating to a coarser resolution grid. For antialiasing, a decent rule of thumb is to lowpass filter to a wavelength of twice the resolution of the query grid. In other words, if you are interpolating to a 3 km grid, use 6000 as the wavelength value to meet Nyquist. The antialiasing option uses the filt2 function from Climate Data Toolbox, and may take a couple seconds to compute.

Requirements

Example 1a: A grid

Suppose you want a 5 km resolution grid of melt rates for Getz Ice Shelf. We'll start by defining a 600 km wide grid, at 5 km resolution, with the psgrid function rom Antarctic Mapping Tools.

% Define a grid:
[lat,lon] = psgrid('Getz Ice Shelf',600,5);

% Interpolate:
m = melt_interp_adusumilli(lat,lon);

% Map it:
figure
pcolorps(lat,lon,m)
axis tight off
bedmachine % draws a coastline for context
modismoaps('contrast','white') % background image
cb = colorbar;
caxis([-1 1]*10)
cmocean bal
scalebarps('color','w')

Example 1b: Antialiased grid

Now do the same as above, but apply a 10 km lowpass filter to antialias before interpolating from the 500 m grid to the 5 km grid. The antialiasing filter takes about 10 seconds on my laptop.

% Interpolate:
ma = melt_interp_adusumilli(lat,lon,'antialias',10e3);

% Map it:
figure
pcolorps(lat,lon,ma)
axis tight off
bedmachine % draws a coastline for context
modismoaps('contrast','white') % background image
cb = colorbar;
caxis([-1 1]*10)
cmocean bal
scalebarps('color','w')

The antialiased map above looks very similar to the aliased version, albeit with a tiny bit less noise. My personal take is that the proper way to interpolate from a high-resolution grid to a low-resolution grid is to perform antialiasing; however, if my results change dramatically with versus without antialiasing, my findings probably aren't that meaningful.

Example 2: Melt rates along a profile

Let's look at the melt rate along a flowline of Pine Island Glacier. Start with this map for context:

figure
mapzoomps 'pine island glacier'
itslive_imagesc % plots ice speed

After plotting the map above, I used the coord function to get the coordinates (-1581526,-196704) of a grounded spot in the main trunk of PIG. I'll use that as a starting point to make a flowline:

[xi,yi,di] = itslive_flowline(-1581526,-196704);

hold on
plot(xi,yi,'r','linewidth',2)
figure
bedmachine_profile(xi,yi)
axis([900 995 -1400 300])
% Get basal meltrates along the flowline
mi = melt_interp_adusumilli(xi,yi);

bi = bedmachine_interp('base',xi,yi);

hold on
scatter(di{1},bi,30,mi,'filled')
cb = colorbar;
ylabel(cb,'melt rate (m/yr)')
cmocean thermal % colormap

Citing this data

Please cite Susheel's dataset if you use this data! Also, this function does operate on the data, so if you don't mind, please also cite Antarctic Mapping Tools.

Adusumilli, Susheel; Fricker, Helen A.; Medley, Brooke C.; Padman, Laurie; Siegfried, Matthew R. (2020). Data from: Interannual variations in meltwater input to the Southern Ocean from Antarctic ice shelves. UC San Diego Library Digital Collections. https://doi.org/10.6075/J04Q7SHT

Greene, C. A., Gwyther, D. E., & Blankenship, D. D. Antarctic Mapping Tools for Matlab. Computers & Geosciences. 104 (2017) pp.151-157. http://dx.doi.org/10.1016/j.cageo.2016.08.003

Author Info

This function and supporting documentation were written by Chad A. Greene of NASA Jet P,,ropulsion Laboratory, October 2020.