An objectively interpolated field will of course have uncertainty. The further away you get from the original data, the worse that uncertainty gets. I've made maps of uncertainty for the NOAA stations (assuming all are reporting data, which is almost never true) for two cases: One, the summer case, where we have three open-water buoys available, and two, a winter case, where there is no data from the buoys. Here are those fields:
Things to notice: In the summer field, we do a great job in the western arm of the lake. This is good since that's where we're putting some of our more interesting instrumentation- we'll have better model results in this region because we have better forcing. There are some spots along the NE coast where the uncertainty is very high. Keep in mind that in this case, the interpolation relaxes to the mean of the available data, not to zero or some other un-useful point. So it's not as it there isn't forcing data up ther, it's just that it probably is not particularly representative of any regional variability.
In the winter, without the Central and Eastern buoys, the NE part of the lake is even more poorly covered. The Western Arm, however, still has very good coverage, even without the western buoy.
If we used a longer decorrelation scale, the coverage up north would be better. But the fields would be a lot smoother.
The apparently open-lake site to the E of the Keweenaw is Stannard Rock, a lighthouse, and operable all year round.