Melissa,
Without knowing anything about your project, my gut feeling is that it does not seem prudent to grid your B dataset because you'll end up interpolating over long, long distances between data points. I suppose you could use triscatteredinterp or gridfit, but you'd probably want to then mask out any grid boxes that are far away from the B data points.
You can, however, get a correlation between these data sets. I'm going to make up a gridded dataset A and a point dataset B:
% Some gridded dataset A:
[lonA,latA] = meshgrid(-180:2:180,90:-1:-90);
A = peaks(181)+.1*latA;
% Some measurements B at specific points:
latB = 180*(rand(30,1)-.5);
lonB = 360*(rand(30,1)-.5);
B = .1*latB+rand(size(latB));
% Plot the points atop the gridded dataset:
pcolor(lonA,latA,A)
hold on
plot(lonB,latB,'rp','markersize',15)
shading interp
xlabel('longitude')
ylabel('latitude')
Then get A values at points B by interpolating the A dataset:
A_interp = interp2(lonA,latA,A,lonB,latB);
You can then use corrcoef to get a correlation coefficient, which for this fake data is 0.89:
R = corrcoef([A_interp B])
R =
1.0000 0.8936
0.8936 1.0000
But note that correlation coefficient depends a bit on data means and scaling. Below I'm going to use polyplot to plot the linear regression:
plot(A_interp,B,'b*')
hold on
polyplot(A_interp,B,'k-')
axis tight; box off
xlabel('dataset A')
ylabel('dataset B')
