Whether the autocorrelation structure of random field $Z(u) + Y(u)$ is equal to the autocorrelation structure of $Z(u)$ plus that of $Y(u)$?

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I want to simulate a Gaussian random field (RF) with correlation structure (represented by the geostatistic tool 'semivariogram' $\gamma (h) \: +\: pure \: nugget \: effect$). I want to know whether can I do the simulation by independently simulate a Gaussian RF with correlation structure $\gamma (h)$ and another rand field with pure nugget effect, and then sum them up. ($u$ in the title denotes spatial location $(x, y)$). I do a simulation experiment in Matlab:

clear;
clc;
rng(0);
mu = 0; 
sigma2 = 1; % sill
covar_type = 3; % Spherical variogram model
range = 20; 
knn = 12; % number of neighbors to consider
xsize = 100; % number of columns
ysize = 100; % number of rows

field1 = J_Simu2DSGS(xsize, ysize, [], mu, sigma2, covar_type, range, knn);

% field 2
nugget = 0.3;
purenugget = sqrt(nugget)*randn(xsize, ysize);

% field1 + field2
comRF = field1 + purenugget;
Sampling from simulated fields:
samplesz = 500;
[xcoord, ycoord] = meshgrid(1:xsize, 1:ysize);
xycc = [xcoord(:), ycoord(:), field1(:), comRF(:)];
nbcell = xsize*ysize;
idx = randperm(nbcell, samplesz);
obsxy = xycc(idx, 1:2);
obscc = xycc(idx, 3:end);

The function used for simulation 'J_Simu2DSGS' above is equivalent to the function 'MGSimulSGS.m' here: https://github.com/GAIA-UNIL/MATLAB_Geostat_Utilities/blob/master/MATLAB_UTILS/MGSimulSGS.m

I calculate the semivariograms of the simulated RFs. The result is:

enter image description here

We can see that the correlation structure of the composite RF (variogram at lower right corner) is similar to that of the RF1 (variogram at lower left corner), in spite of a general shift on the y-axis representing the nugget effect.

But I also want to validate it mathematically. Namely:

Assuming second-order stationarity holds, if Gaussian random field $Z(u)$ has correlation structure $C_1 (h)$, Gaussian random field $Y(u)$ has correlation structure $C_2 (h)$, then $Z(u) + Y(u)$ has correlation structure $C_1 (h) + C_2 (h)$.

My math is poor, could someone help demonstrate it?

Note: $\gamma (h)$ is only associated with the separated distance in space since we make a second-order stationarity assumption. More info can be found in wiki: https://en.wikipedia.org/wiki/Variogram