rap near the low point of this timeries, in mid September.
% In this example, we choose 52 evenly-spaced bins per year, which is
% approximately a weekly average:

[ice, yr, tmid] = reshapetimeseries(t, extent_N, ...
    'pivotdate', [9 15], 'bin', 52);

cla
plot(tmid, ice, 'b')
hold on


%%
% One thing to be aware of with this function is that it will add a NaN
% placeholder for any bins where no data existed in the original
% timeseries.  Most of the time this will correspond to larger gaps in your
% time