Objectively analyzed fields of satellite sea surface temperature (SST, advanced very high resolution radiometer (AVHRR) Pathfinder) and sea surface height anomaly (SSHA, combined TOPEX/Poseidon--ERS-1/2) are used to characterize, statistically, the mesoscale variability about the U.S. Joint Global Ocean Flux Study (JGOFS) Bermuda Atlantic Time-Series Study (BATS) site. These results are applied to the in situ BATS time series data and a local one-dimensional (1-D) physical upper ocean model to better understand the contribution of mesoscale eddies to the time series record and the model-data mismatch. Using a low-pass spatial filter, we decompose the anomalies from the seasonal cycle into two components: the large-scale, regional climate variability and a mesoscale signal. The mesoscale SST and SSHA fields are positively cross-correlated at a statistically significant level, consistent with near-surface isotherm displacements for cyclonic and anticyclonic eddies. The results from time-lagged cross-correlation analysis show that detectable eddy signatures exist in the in situ SST data and that eddies are a noticeable (~10%) but not dominant error source for the 1-D model solution. Several factors may be at work: the 1-D model captures a more regional signal, whereas the BATS in situ data include small-scale spatial heterogeneity; the satellite data and 1-D model are indirectly coupled via the National Centers for Environmental Prediction (NCEP) reanalysis forcing data; and the satellite-based mesoscale variability estimates are also missing specific events because of the sparse space-time sampling of a polar orbiting, visible/infrared wavelength sensor. The mesoscale eddy cross-correlation signature did not show up clearly in a similar analysis conducted on the original anomaly fields, highlighting the fact that climate scale variability needs to be carefully removed to isolate the eddy signature.