Aims. We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The dataset includes several low-redshift samples (z < 0.1), all three seasons from the SDSS-II (0.05 < z < 0.4), and three years from SNLS (0.2 < z < 1), and it totals 740 spectroscopically confirmed type Ia supernovae with high-quality light curves. Methods. We followed the methods and assumptions of the SNLS three-year data analysis except for the following important improvements: 1) the addition of the full SDSS-II spectroscopically-confirmed SN Ia sample in both the training of the SALT2 light-curve model and in the Hubble diagram analysis (374 SNe); 2) intercalibration of the SNLS and SDSS surveys and reduced systematic uncertainties in the photometric calibration, performed blindly with respect to the cosmology analysis; and 3) a thorough investigation of systematic errors associated with the SALT2 modeling of SN Ia light curves. Results. We produce recalibrated SN Ia light curves and associated distances for the SDSS-II and SNLS samples. The large SDSS-II sample provides an effective, independent, low-z anchor for the Hubble diagram and reduces the systematic error from calibration systematics in the low-z SN sample. For a flat ΛCDM cosmology, we find Ω m = 0.295 ± 0.034 (stat+sys), a value consistent with the most recent cosmic microwave background (CMB) measurement from the Planck and WMAP experiments. Our result is 1.8σ (stat+sys) different than the previously published result of SNLS three-year data. The change is due primarily to improvements in the SNLS photometric calibration. When combined with CMB constraints, we measure a constant dark-energy equation of state parameter w = −1.018 ± 0.057 (stat+sys) for a flat universe. Adding baryon acoustic oscillation distance measurements gives similar constraints: w = −1.027 ± 0.055. Our supernova measurements provide the most stringent constraints to date on the nature of dark energy.

Aims. We present an empirical model of type Ia supernovae spectro-photometric evolution with time. Methods. 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 Å with calculable uncertainties, including those arising from variability of spectral features.Results. 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.