<p>Long-term deep ocean temperature monitoring is crucial for understanding the ocean’s role in climate variability and storage of heat in the deep ocean. Observation of the ocean surface is relatively accessible via both <i>in-situ</i> and remote sensing; however, continuous, high-temporal resolution, decade-long temperature records from abyssal depths face the technical challenges of sustained deep ocean deployments. The addition of calibrated, internally-recording temperature sensors to deep-ocean moorings not far from the sea floor provides a means of making high temporal resolution temperature observations. Quality controlling and merging records from successive mooring deployments results in a decade-long time series. Our work has been to optimize approaches for ensuring data quality and continuity in multi-year deep ocean temperature datasets. Here we show a comprehensive processing framework that yields 13 years (2012 to 2025) of continuous temperature measurements at approximately 4200 to 4500 meters depth from the Stratus Ocean Reference Station near 22 °S, 85 °W, 1500 km off the coast of Chile in the Southeast Pacific. Our framework incorporates timing checks, automated spike detection, systematic multi-sensor validation, statistical validation, human-in-the-loop quality control, and merging protocols. This framework establishes reproducible standards for processing long term oceanographic observations from multiple deployments. For the Stratus data set, the result is a unique, decade-long abyssal temperature record with quantified uncertainties that constitutes a benchmark time series for evaluating the realism of deep ocean temperature in models.</p>