  Type 1a supernova magnitudes are used to fit cosmological parameters under
the assumption the model will fit the observed redshift dependence. We test
this assumption with the Union 2.1 compilation of 580 sources. Several
independent tests find the existing model fails to account for a significant
correlation of supernova color and redshift. The correlation of magnitude
residuals relative to the $\Lambda CDM$ model and $color \times redshift$ has a
significance equivalent to 13 standard deviations, as evaluated by randomly
shuffling the data. Extending the existing $B-V$ color correction to a relation
linear in redshift improves the goodness of fit $\chi^{2}$ by more than 50
units, an equivalent 7-$\sigma$ significance, while adding only one parameter.
The $color-redshift$ correlation is quite robust, cannot be attributed to
outliers, and passes several tests of consistency. We review previous hints of
redshift dependence in color parameters found in bin-by-bin fits interpreted as
parameter bias. We show that neither the bias nor the change $\Delta \chi^{2}$
of our study can be explained by those effects. The previously known relation
that bluer supernovae have larger absolute luminosity tends to empirically
flatten out with increasing redshift. The best-fit cosmological dark energy
density parameter is revised from $ \Omega_{\Lambda} =0.71 \pm 0.02$ to $
\Omega_{\Lambda} = 0.74 \pm 0.02$ assuming a flat universe. One possible
physical interpretation is that supernovae or their environments evolve
significantly with increasing redshift.
