November 1, 2018 Sea surface height (SSH) has been used to measure the ocean currents that move heat around the globe as a critical component of Earth's climate. Its relationships with SST, salinity, tides, waves, and the atmospheric pressure loading patterns are of great interest of climate forecasters. To promote R2O activities for service improvement, the NMME project is planning to make its SSH hindcast data available to the community. In the teleconference this month, Dr. Bill Merryfield of the Canadian Centre for Climate Modelling and Analysis (CCCma) was invited to give a talk on his study of the verification of CCCma Coupled Climate Model, versions 3 and 4 (CanCM3/4) SSH hindcasts using multiple ocean reanalyses, i.e. Ocean ReAnalysis System 4 (ORAS4, ECMWF), Global Ocean Data Assimilation System (GODAS, NCEP), Cimate Forecast System Reanalysis (CFSR, NCEP) and German Estimating the Circulation and Climate of the Ocean, version 2 (GECCO2, University of Hamburg). His results showed hindcast skill of CanCM3/4 SSH was generally high (comparable to that for SST), although large differences existed depending on region and verification reanalysis product used, particularly in the Atlantic & Southern Oceans. Among the four reanalyses, the spatial mean skill was the highest for GODAS; this relationship may be at least partially attributed to the use of GODAS ocean temperatures to initialize CanCM3/4 hindcasts, as well as the lack of Arctic data in GODAS. Dr. Merryfield's study revealed skill may be the highest when using the multi-reanalysis mean for verification. Inconsistencies were found between reanalyses in global SSH trends; most of the reanalyses lack any realistic trend. Further work to improve skill by replacing global trend with observed trends are in progress.