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Eddies are important in climate studies because they transport heat, salt, and nutrients through the world's oceans and are vessels of biological productivity. The study of eddies in global ocean-climate models requires large-scale, high-resolution simulations. This poses a problem for timely eddy analysis, as ocean simulations generate massive amounts of data, causing a bottleneck. Future analyses at very-high spatial and temporal resolutions will be difficult with file-based workflows due to resource constraints, such as storage size and supercomputing (I/O) time. In response, we have developed an in situ eddy census workflow in MPAS-Ocean, which scales well to ten-thousand processing elements. This study demonstrates that in situ analysis has many advantages that pertain to climate model analysis tasks, as we move to higher resolutions. We report the strong- and weak-scaling performance of this workflow, along with the early science results of eddy censuses in MPAS-Ocean.