To advance predictive skill, ocean forecast systems must exploit local high resolution observations. The recent Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) provides an opportunity to examine the data assimilation issues that can limit predictive skill. A unique swarm control system guided nine ocean gliders accounting for all satellite and in situ data to provide high resolution observations for three ocean forecast experiments: 1) no glider data assimilated, 2) assimilation with glider data through a previous assimilation approach, and 3) adaptive assimilation of the glider data in which smaller scales are corrected in the vicinity of the local high resolution observations. The assimilation adaptation used a spatially varying horizontal decorrelation scale enabling corrections at smaller scales where high resolution in situ data are concentrated. When measured by spatial scales along the glider paths, skill in temperature advances from scales larger than about 220 km wavelength when utilizing the glider data with prior assimilation down to scales larger than 80 km wavelength with the adaptive assimilation. Skill in salinity advances from scales of approximately 300 km to scales of 200 km, and skill in steric height advances from 140 km to 63 km. Additionally, conductivity, temperature, and depth observations from an EcoCTD instrument provide independent data for confirmation. The results imply that as ocean observing systems advance, ocean forecast systems must adapt to use local high resolution observations.