The solar activity cycle is weakly synchronized with the solar inertial motion

Paluš, Milan; Kurths, Jürgen; Schwarz, Udo D.; Seehafer, N.; Novotná, Dagmar; Charvátová, Ivanka

doi:10.1016/j.physleta.2007.01.039

Cited by 31 publications

(23 citation statements)

References 28 publications

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“…For instance, the period of the sunspot cycle varies between 9 and 13 years. (A histogram of the instantaneous frequencies of the sunspot cycle can be found in Palusˇet al (2007), Fig. 5b.…”

Section: Enhanced MC Ssa Detection Of Oscillatory Modes: the Resultsmentioning

confidence: 99%

Common oscillatory modes in geomagnetic activity, NAO index and surface air temperature records

Paluš

Novotná

2007

Journal of Atmospheric and Solar-Terrestrial Physics

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Section: Enhanced MC Ssa Detection Of Oscillatory Modes: the Resultsmentioning

confidence: 99%

Common oscillatory modes in geomagnetic activity, NAO index and surface air temperature records

Paluš

Novotná

2007

Journal of Atmospheric and Solar-Terrestrial Physics

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“…Moreover, these characteristics indicate former climatic conditions and variability. Consequently, variations on very different time scales are expected to be found: The orbital parameters of the Earth change on Milankovitch scales (19,23,41 and 100 thousand years); the solar output varies not only according the famous 11-years cycle, but also with periods of 22, 89, 148 and 207 years or 1800-2500 years (Sonnet et al, 1984) respectively; its modulation by the solar internal motion shows cycles on decadal scales (Palus et al, 2000); ocean and ice dynamics (Stuiver and Braziunas, 1993) is related to variability of 512 years, 1.47 kiloyears and 6 kiloyears; changes in atmospheric loading (O'Brien et al, 1995) are tied to a period of almost 3 kiloyears and climate oscillations such as the El Niño Southern Oscillation or the North Atlantic Oscillation (Sonnet et al, 1984) show variability on a (sub-)decadal time scale.…”

Section: Introductionmentioning

confidence: 99%

Holocene climate variability on millennial scales recorded in Greenland ice cores

Witt

Schumann

2005

Nonlin. Processes Geophys.

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Abstract. Climate variability is triggered by several solar and orbital cycles as well as by the intern ocean dynamics. Consequently, paleoclimate proxy records are expected to vary on very different time scales ranging from subdecadal to millennial duration. We demonstrate, that Foster's (Foster, 1996) wavelet analysis technique is an appropriate tool for investigating temporarily changing spectral properties of records characterized by awkward sampling quality, which is a typical feature of climate proxy records. By applying it to the Holocene part of different glaciochemical records of Greenland ice cores we proof evidence for a significant contribution of the 1.47 kiloyears cycle over alomst the entire Holocene.

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“…However, the cloud cover correlations could possibly be coincident with other climate indices (Laken et al 2012b) with the AMO, which not only exhibits the largest influence on regional cloud cover, but also displays significant correlations with both solar proxies and GCR proxies. Other researchers have raise the possibility that long-term solar activity may act as a chaotic attractor for the various climatological modes of the atmosphere and ocean, and that they may even exhibit chaotic synchronization at times (Palus et al 2007). Although both solar activity and GCR proxies exhibit regional correlations, specifically over marine low clouds, the AMO appears to exert the greatest control of cloud cover in the NARR domain.…”

Section: Discussionmentioning

confidence: 99%

Investigating a solar influence on cloud cover using the North American Regional Reanalysis data

Krahenbuhl

2015

J. Space Weather Space Clim.

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The controversial connection between cosmic rays, solar activity, and cloud cover is investigated using a climatological reconstructed reanalysis product: the North American Regional Reanalysis which provides high-resolution, low, mid-level, high, and total cloud cover data over a Lambert conformal conic projection permitting land/ocean discrimination. Pearson's product-moment regional correlations were obtained between monthly cloud cover data and solar variability indicators, cosmic ray neutron monitors, several climatological indices, including the Atlantic Multidecadal Oscillation (AMO), and between cloud layers. Regions of the mid-latitude oceans exhibited a positive correlation with cosmic ray flux. Additionally, this maritime low cloud cover exhibits the only failed correlation significance with other altitudes. The cross correlation reveals that cloud cover is positively correlated everywhere but for ocean low cloud cover, supporting the unique response of the marine layer. The results of this investigation suggest that with the assumption that solar forcing does impact cloud cover, measurements of solar activity exhibits a slightly higher correlation than GCRs. The only instance where GCRs exhibit a positive regional correlation with cloud cover is for maritime low clouds. The AMO exerts the greatest control of cloud cover in the NARR domain.

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The solar activity cycle is weakly synchronized with the solar inertial motion

Cited by 31 publications

References 28 publications

Common oscillatory modes in geomagnetic activity, NAO index and surface air temperature records

Common oscillatory modes in geomagnetic activity, NAO index and surface air temperature records

Holocene climate variability on millennial scales recorded in Greenland ice cores

Investigating a solar influence on cloud cover using the North American Regional Reanalysis data

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