  We present an empirical model of Type Ia supernovae spectro-photometric
evolution with time. The model is built using a large data set including
light-curves and spectra of both nearby and distant supernovae, the latter
being observed by the SNLS collaboration. We derive the average spectral
sequence of Type Ia supernovae and their main variability components including
a color variation law. The model allows us to measure distance moduli in the
spectral range 2500-8000 A with calculable uncertainties, including those
arising from variability of spectral features. Thanks to the use of
high-redshift SNe to model the rest-frame UV spectral energy distribution, we
are able to derive improved distance estimates for SNe Ia in the redshift range
0.8<z<1.1. The model can also be used to improve spectroscopic identification
algorithms, and derive photometric redshifts of distant Type Ia supernovae.
