The plotting question is pretty easy, you just need to arrange your xT and yExp values so that they correspond to the shape of pMat. The meshgrid function does great for this:
xT = [10,20,30];
yExp = [100,500,1000,5000,10000];
pMat = [5000,7000,9000,11000,13000; 7000,9000,11000,13000,15000; 9000,11000,13000,15000,17000] ;
[yExpi, xTi]=meshgrid(yExp, xT); % note that meshgrid was called with y, x - if you call it with x,y you'll need to transpose to plot
surf(xTi, yExpi, pMat);
% or a scatter if you want, just turn all the previous matrices into
% vectors with (:)
figure
scatter3(xTi(:), yExpi(:), pMat(:))
For curve fitting, it's not clear exactly what curve (surface) you want to fit...but you have x and y values and an f(x,y), so you can apply whatever math you have to predict f(x,y) based on your observed x,y. For interpolation, you might consider uysing scatteredInterpolant which is really simple to use:
s=scatteredInterpolant(xTi(:), yExpi(:), pMat(:));
s([15 25], [5000 6000]) % interpolated values where (xT, yExp) are (15, 5000) and (25, 6000)
You could also use interp2 here pretty easily, you'll just need to transpose your pMat matrix:
interp2(xT,yExp,pMat',[15 25],[5000 6000])
Note that (linear) interpolation is just finding the points that lie on the planes in the above surf, i.e. looking at the neighbors and drawing lines in between them:
[xi,yi]=meshgrid(linspace(10,30),linspace(0,10000));
zi=interp2(xT,yExp,pMat',xi,yi);
figure;
scatter3(xi(:),yi(:),zi(:),[],zi(:),'filled');
