Changing surface wave conditions alter the altimeter's estimate of mean sea level. Present‐day methods for correcting this bias are solely based on wave and wind information from the altimeter. This paper tests the use of additional information to develop several sea state bias correction models using a yearlong combination of Jason‐1 data with wave field statistics generated from the WaveWatch3 ocean wave model hindcast. Each candidate model is produced in the same manner, using a nonparametric mapping between Jason‐1 sea surface height anomaly estimates and two correlatives. The first is always the significant wave height from Jason‐1 and the model differences come through choice of the second variable. Past studies dictate our selection of these second parameters and they include terms related to the local wind speed, swell energy, wave age, wave period, and wave slope. Model skills are evaluated in terms of explained variance. Several models indicate promise for wave model use in future empirical developments. For instance, results show that in the low latitudes the models developed using the swell height and mean period modestly but systematically outperform the actual operational parameterisation. This study further indicates that systematic regional error in the present sea level corrections may be improved by inclusion of wave model information.
