Solar activity in the sixteenth and seventeenth centuries (a revision)

Letfus, V.

doi:10.1007/bf00690663

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…Since the pioneering work of Eddy, there has been a concerted international effort to recover "lost" sunspot observations prior to and during the Maunder Minima [Letfus, 1993[Letfus, , 1999Hoyt and Schatten, 1995a, 1995b. There has been a rcnormalization of these early observations into the criteria for the international sunspot number [Hoyt and Shatten, 1992, 1995c, 1995d, 1998a, 1998b, and these are the sunspot numbers plotted in the figures in this paper.…”

Section: End Of the Maunder Minimummentioning

confidence: 99%

Solar cosmic ray events for the period 1561–1994: 2. The Gleissberg periodicity

McCracken¹,

Dreschhoff²,

Smart³

et al. 2001

J. Geophys. Res.

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Section: End Of the Maunder Minimummentioning

confidence: 99%

Solar cosmic ray events for the period 1561–1994: 2. The Gleissberg periodicity

McCracken¹,

Dreschhoff²,

Smart³

et al. 2001

J. Geophys. Res.

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“…Most of those studies focused on specific time intervals or on single base observers. Those valuable efforts led to proposed revisions of specific segments of the SN record (Kopecky et al 1980, Letfus 1993, Lockwood et al 2014 and to the still ongoing debate about a missing short cycle between cycles 4 and 5 (Usoskin et al 2001, Arlt 2009, Zolotova and Ponyavin 2007. Overall, all those proposed corrections were mostly local in time and were dispersed over multiple publications.…”

mentioning

confidence: 99%

Revisiting the Sunspot Number

et al. 2014

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Abstract:Our knowledge of the long-term evolution of solar activity and of its primary modulation, the 11-year cycle, largely depends on a single direct observational record: the visual sunspot counts that retrace the last 4 centuries, since the invention of the astronomical telescope. Currently, this activity index is available in two main forms: the International Sunspot Number initiated by R. Wolf in 1849 and the Group Number constructed more recently by Hoyt and Schatten (1998a,b). Unfortunately, those two series do not match by various aspects, inducing confusions and contradictions when used in crucial contemporary studies of the solar dynamo or of the solar forcing on the Earth climate. Recently, new efforts have been undertaken to diagnose and correct flaws and biases affecting both sunspot series, in the framework of a series of dedicated Sunspot Number Workshops. Here, we present a global overview of our current understanding of the sunspot number calibration.After retracing the construction of those two composite series, we present the new concepts and methods used to self-consistently re-calibrate the original sunspot series. While the early part of the sunspot record before 1800 is still characterized by large uncertainties due to poorly observed periods, the more recent sunspot numbers are mainly affected by three main inhomogeneities: in 1880-1915 for the Group Number and in 1947 and 1980-2014 for the Sunspot Number.After establishing those new corrections, we then consider the implications on our knowledge of solar activity over the last 400 years. The newly corrected series clearly indicates a progressive decline of solar activity before the onset of the Maunder Minimum, while the slowly rising trend of the activity after the Maunder Minimum is strongly reduced, suggesting that by the mid 18 th century, solar activity had already returned to levels equivalent to those observed in recent solar cycles in the 20 th century. We finally conclude with future prospects opened by this epochal revision of the Sunspot Number, the first one since Wolf himself, and its reconciliation with the Group Number, a long-awaited modernization that will feed solar cycle research into the 21 st century.

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“…7 shows the prediction error between the observed and outputs of our model for the whole data. The maximum amplitude of the sunspot number of 23 rd cycle is predicted 132 as shown in Figure 6 Kopecky, 1991 Wilson, 1992Letfus, 1993 Schattenetal,1996 Thompson,1996Kane,1999 Lantos,2000 …”

Section: Simulation Resultsmentioning

confidence: 99%

“…Numerous numerical techniques have been arduously developed to predict the amplitude and the phases of activity of solar cycles, before the sunspot cycle minimum. Among these suggested method: The method which depends on the even/odd behavior method 11,14,27,16 , mixed methods applied 26, 6, 7, and 15 and the Spectral technique 3 . The more reliable indicator to the activity is the precursor technique; especially the geomagnetic precursor which based on the records of geomagnetic storms 12,19, and 10 published a summary of the scientific panel recruited by Space Environment Center (SCE) with support of NASA to assess prediction of cycle 23 rd .…”

Section: Introductionmentioning

confidence: 99%

A genetic-based neuro-fuzzy approach for prediction of solar activity

2004

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This paper presents an application of the neuro-fuzzy modeling to analyze the time series of solar activity, as measured through the relative Wolf number. The neuro-fuzzy structure will be optimized based on the linear adapted genetic algorithm with controlling population size (LAGA-POP). First, the dimension of the time series characteristic attractor is obtained based on the smallest Regularity Criterion (RC) and the neuro-fuzzy modeling. Second, after describing the neuro-fuzzy structure and optimizing its parameters based on LAGA-POP, the performance of the present approach in forecasting yearly sunspot numbers is favorably compared to that of other published methods. Finally, the comparison predictions for the remaining part of the 22 nd and the whole 23 rd cycle of solar activity are presented.

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Solar activity in the sixteenth and seventeenth centuries (a revision)

Cited by 6 publications

References 3 publications

Solar cosmic ray events for the period 1561–1994: 2. The Gleissberg periodicity

Solar cosmic ray events for the period 1561–1994: 2. The Gleissberg periodicity

Revisiting the Sunspot Number

A genetic-based neuro-fuzzy approach for prediction of solar activity

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