A Recount of Sunspot Groups on Staudach’s Drawings

Svalgaard, Leif

doi:10.1007/s11207-016-1023-x

Cited by 28 publications

(23 citation statements)

References 5 publications

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“…Accumulating the light, telescopes could help a little to make out dark-dark bluish plasma tail in the night sky. However, early telescopes likely suffered from spherical and chromatic aberration (Svalgaard, 2017). Therefore, the first hint of plasma tail we figured out only for Great comet C/1769 P1.…”

Section: Discussionmentioning

confidence: 94%

Indirect Solar Wind Measurements Using Archival Cometary Tail Observations

et al. 2018

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The paper addressed to the problem of the solar wind behaviour during the Maunder Minimum. Records on plasma tails of comets would allow to shed light on the physical parameters of the solar wind in the past. We analyse descriptions and drawings of comets to the eighteenth century. To differentiate dust and plasma tails, we address to their color, shape and orientation. Basing on the calculations made by F.A. Bredikhin, we found that deviation of cometary tails from the antisolar direction on average exceeded 10 • , that is typical for dust tails. Catalogues of Hevelius and Lubieniecki are also examined. The first indication of plasma tail was revealed only for Great comet C/1769 P1.

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Section: Discussionmentioning

confidence: 94%

Indirect Solar Wind Measurements Using Archival Cometary Tail Observations

et al. 2018

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“…While in earlier parts of the series physical closeness of spots was considered a sufficient criterion, since the mid-twentieth century evolutionary information is also taken into account, sometimes resulting in the division into several groups of what would have been considered as a single group by early observers. Svalgaard et al (2017) estimate that this effect may have inflated Waldmeier's sunspot numbers by 4-5% relative to earlier counts, while the effect on the late eighteenth century sunspot reconstruction of the SSN by Wolf based on the drawings of Staudacher may be even larger, reaching 25% (Svalgaard 2017). On the other hand, Izenman (1983) notes that Waldmeier's authoritative 1965 edition of the R Z series does contain slight corrections also to the data published previously, in 1925 by Wolfer.…”

Section: Revisionmentioning

confidence: 96%

Solar cycle prediction

Petrovay

2020

Living Rev Sol Phys

195

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A review of solar cycle prediction methods and their performance is given, including early forecasts for Cycle 25. The review focuses on those aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is further restricted to the issue of predicting the amplitude (and optionally the epoch) of an upcoming solar maximum no later than right after the start of the given cycle. Prediction methods form three main groups. Precursor methods rely on the value of some measure of solar activity or magnetism at a specified time to predict the amplitude of the following solar maximum. The choice of a good precursor often implies considerable physical insight: indeed, it has become increasingly clear that the transition from purely empirical precursors to model-based methods is continuous. Model-based approaches can be further divided into two groups: predictions based on surface flux transport models and on consistent dynamo models. The implicit assumption of precursor methods is that each numbered solar cycle is a consistent unit in itself, while solar activity seems to consist of a series of much less tightly intercorrelated individual cycles. Extrapolation methods, in contrast, are based on the premise that the physical process giving rise to the sunspot number record is statistically homogeneous, i.e., the mathematical regularities underlying its variations are the same at any point of time, and therefore it lends itself to analysis and forecasting by time series methods. In their overall performance during the course of the last few solar cycles, precursor methods have clearly been superior to extrapolation methods. One method that has This article is a revised version of

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“…Svalgaard (2016) has shown that modern group-splitting will increase Staudacher's counts (made by Wolf in the 19th century from Staudacher's drawings and subsequently used by Hoyt and Schatten) by an additional 25% (or 30%; Usoskin et al 2016a), yielding a net scaling (k 0 ) (or correction) factor of~2 relative to a modern reference observer.…”

Section: Long-term Behavior Of the K 0 Seriesmentioning

confidence: 99%

Sunspot number recalibration: The ~1840–1920 anomaly in the observer normalization factors of the group sunspot number

Cliver¹

2017

J. Space Weather Space Clim.

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We analyze the normalization factors (k 0 -factors) used to scale secondary observers to the Royal Greenwich Observatory (RGO) reference series of the Hoyt & Schatten (1998a, 1998b group sunspot number (GSN). A time series of these k 0 -factors exhibits an anomaly from 1841 to 1920, viz., the average k 0 -factor for all observers who began reporting groups from 1841 to 1883 is 1.075 vs. 1.431 for those who began from 1884 to 1920, with a progressive rise, on average, during the latter period. The 1883-1884 break between the two subintervals occurs precisely at the point where Hoyt and Schatten began to use a complex daisy-chaining method to scale observers to RGO. The 1841-1920 anomaly implies, implausibly, that the average sunspot observer who began from 1841 to 1883 was nearly as proficient at counting groups as mid-20th century RGO (for which k 0 = 1.0 by definition) while observers beginning during the 1884-1920 period regressed in group counting capability relative to those from the earlier interval. Instead, as shown elsewhere and substantiated here, RGO group counts increased relative to those of other long-term observers from 1874 to~1915. This apparent inhomogeneity in the RGO group count series is primarily responsible for the increase in k 0 -factors from 1884 to 1920 and the suppression, by 44% on average, of the Hoyt and Schatten GSN relative to the original Wolf sunspot number (WSN) before~1885. Correcting for the early ''learning curve'' in the RGO reference series and minimizing the use of daisy-chaining rectifies the anomalous behavior of the k 0 -factor series. The resultant GSN time series (designated GSN*) is in reasonable agreement with the revised WSN (S N *; Clette & Lefèvre 2016) and the backbone-based group sunspot number (R GS ; Svalgaard & Schatten 2016) but significantly higher than other recent reconstructions (Friedli, personal communication, 2016;Lockwood et al. 2014aLockwood et al. , 2014bUsoskin et al. 2016a). This result is substantiated by a ''correction-factor'' (CF) time series defined as the ratio of annual group counts of the Hoyt & Schatten (1998a, 1998b series to the average raw (unscaled) group counts of all observers, as well as by a comparison of the GSN and GSN* time series with a recent reconstruction of solar wind B from 1845 to the present. The~1840-1920 k 0 -factor anomaly and its impact on the Hoyt and Schatten GSN are discussed in the context of the ongoing effort to recalibrate the sunspot number time series.

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A Recount of Sunspot Groups on Staudach’s Drawings

Cited by 28 publications

References 5 publications

Indirect Solar Wind Measurements Using Archival Cometary Tail Observations

Indirect Solar Wind Measurements Using Archival Cometary Tail Observations

Solar cycle prediction

Sunspot number recalibration: The ~1840–1920 anomaly in the observer normalization factors of the group sunspot number

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