Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data
M. Lockwood, M.J Owens, L. Barnard, and I.G. Usoskin

TL;DR
This paper investigates how different regression procedures affect the calibration of historic sunspot data, revealing that inappropriate methods can significantly distort sunspot cycle amplitudes.
Contribution
It demonstrates that common regression practices can lead to large errors in sunspot number calibration and advocates for the use of Q-Q plots and non-linear fits for more reliable results.
Findings
High correlation does not ensure accurate calibration.
Forcing regression through the origin can produce unreliable fits.
Non-linear regression and Q-Q plots improve calibration reliability.
Abstract
We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of are then re-scaled to the observed RGO group number using a variety of regression techniques. It is found that a very high correlation between and ( > 0.98) does not prevent large errors in the intercalibration (e.g. sunspot maximum values can be over 30% too large even for such levels of ). In generating the backbone sunspot number, Svalgaard and Schatten [2015] force regression fits to pass through the scatter plot origin which…
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