Reconstruction of solar total irradiance since 1700 from the surface magnetic flux

Krivova, N. A.; Balmaceda, L. A.; Solanki, S. K.

doi:10.1051/0004-6361:20066725

Cited by 273 publications

(387 citation statements)

References 65 publications

(93 reference statements)

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“…It must always be remembered that sunspot numbers have applications only because they are an approximate proxy indicator of the total magnetic flux threading the photosphere and hence can be used to estimate and reconstruct terrestrial influences such as the received shortwave Total Solar Irradiance (TSI) and UV irradiance (Krivova, Balmaceda, and Solanki, 2007;Krivova et al, 2009, respectively), the open solar magnetic flux (Solanki, Schüssler, and Fligge, 2000;Lockwood and Owens, 2014a), and hence also the near-Earth solar-wind speed (Lockwood and Owens, 2014b), mass flux (Webb and Howard, 1994), and interplanetary magnetic-field strength (Lockwood and Owens, 2014a). Sunspot numbers also provide an indication of the occurrence frequency of transient events, in particular coronal mass ejections (Webb and Howard, 1994;Owens and Lockwood, 2012), and the phase of the decadal-scale sunspot cycle is used to quantify the tilt of the heliospheric current sheet (Altschuler and Newkirk, 1969;Owens and Lockwood, 2012) and hence the occurrence of fast solar-wind streams and co-rotating interaction regions (Smith and Wolf, 1976;Gazis, 1996).…”

Section: Definitions Of Sunspot Numbersmentioning

confidence: 99%

Tests of Sunspot Number Sequences: 1. Using Ionosonde Data

et al. 2016

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More than 70 years ago, it was recognised that ionospheric F2-layer critical frequencies [foF2] had a strong relationship to sunspot number. Using historic datasets from the Slough and Washington ionosondes, we evaluate the best statistical fits of foF2 to sunspot numbers (at each Universal Time [UT] separately) in order to search for drifts and abrupt changes in the fit residuals over Solar Cycles 17 -21. This test is carried out for the original composite of the Wolf/Zürich/International sunspot number [R], the new "backbone" group sunspot number [R BB ], and the proposed "corrected sunspot number" [R C ]. Polynomial fits are made both with and without allowance for the white-light facular area, which has been reported as being associated with cycle-to-cycle changes in the sunspot-number-foF2 relationship. Over the interval studied here, R, R BB , and R C largely differ in their allowance for the "Waldmeier discontinuity" around 1945 (the correction factor for which for R, R BB , and R C is, respectively, zero, effectively over 20 %, and explicitly 11.6 %). It is shown that for Solar Cycles 18 -21, all three sunspot data sequences perform well, but that the fit residuals are lowest and most uniform for R BB . We here use foF2 for those UTs for which R, R BB , and R C all give correlations exceeding 0.99 for intervals both before and after the Waldmeier discontinuity. The error introduced by the Waldmeier discontinuity causes R to underestimate the fitted values based on the foF2 data for 1932 -1945, but R BB overestimates them by almost the same factor, implying that the correction for the Waldmeier discontinuity inherent in R BB is too large by a factor of two. Fit residuals are smallest and most uniform for R C , and the ionospheric data support the optimum discontinuity multiplicative correction factor derived from the independent Royal Greenwich Observatory (RGO) sunspot group data for the same interval.Sunspot Number Recalibration

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Section: Definitions Of Sunspot Numbersmentioning

confidence: 99%

Tests of Sunspot Number Sequences: 1. Using Ionosonde Data

et al. 2016

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“…The use of more recent forcing reconstructions (e.g., Krivova et al 2007;Gao et al 2008;Pongratz et al 2009) or simulations and models in the Coupled Model Intercomparisons Project phase 5/Paleoclimate Modeling Intercomparison Project Phase 3 (CMIP5/PMIP3) (Taylor et al 2012) might improve the model-data comparison but would not be expected to have an impact on the validation of the reconstruction technique performed here.…”

Section: Model Description and Experimental Designmentioning

confidence: 99%

Assessing reconstruction techniques of the Atlantic Ocean circulation variability during the last millennium

et al. 2016

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the simulated variability at deep/shallow levels. Density changes responsible for the pseudo-reconstructed FCT are mainly driven by zonal temperature differences; salinity differences oppose but play a minor role. These results thus support the use of the thermal-wind relationship to reconstruct the oceanic circulation past variability, in particular at multidecadal timescales. Yet model-data comparison highlights important differences between the simulated and the proxy-based FCT variability. ECHO-G simulates a prominent weakening in the North Atlantic circulation that contrasts with the reconstructed enhancement. Our model results thus do not support the reconstructed FC minimum during the Little Ice Age. This points to a failure in the reconstruction, misrepresented processes in the model, or an important role of internal ocean dynamics.

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“…In sections 3-8 we test these hypotheses by directly comparing the Nimbus7/ERB data sets versus alternative solar data and proxy models. In this process we will study in details the TSI proxy models of Krivova et al (2007) Figure 3. In Appendix A Hoyt (the head of the NASA Nimbus7/ERB science team) explains the accuracy of the ERB record during the ACRIM Gap.…”

Section: Introductionmentioning

confidence: 99%

ACRIM total solar irradiance satellite composite validation versus TSI proxy models

Scafetta

Willson²

2014

Astrophys Space Sci

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The satellite total solar irradiance (TSI) database provides a valuable record for investigating models of solar variation used to interpret climate changes. The 35-year ACRIM total solar irradiance (TSI) satellite composite time series has been updated using corrections to ACRIMSAT/ACRIM3 results for scattering and diffraction derived from recent testing at the Laboratory for Atmospheric and Space Physics/Total solar irradiance Radiometer Facility (LASP/TRF). The corrections lower the ACRIM3 scale by about 5000 ppm, in close agreement with the scale of SORCE/TIM results (solar constant ≈ 1361 W/m 2 ) but the relative variations and trends are not changed. Differences between the ACRIM and PMOD TSI composites, particularly the decadal trending during solar cycles 21-22, are tested against a set of solar proxy models, including analysis of Nimbus7/ERB and ERBS/ERBE results available to bridge the ACRIM Gap (1989Gap ( -1992. Our findings confirm the following ACRIM TSI composite features: (1) The validity of the TSI peak in the originally published ERB results in early 1979 during solar cycle 21; (2) The correctness of originally published ACRIM1 results during the SMM spin mode (1981)(1982)(1983)(1984); (3) The upward trend of originally published ERB results during the ACRIM Gap; (4) The occurrence of a significant upward TSI trend between the minima of solar cycles 21 and 22 and (5) a decreasing trend during solar cycles 22 -23. Our findings do not support the following PMOD TSI composite features: (1) The downward corrections to originally published ERB and ACRIM1 results during solar cycle 21; (2) A step function sensitivity change in ERB results at the end-of-September 1989; (3) the validity of ERBE's downward trend during the ACRIM Gap or (4) the use of ERBE results to bridge the ACRIM Gap. Our analysis provides a first order validation of the ACRIM TSI composite approach and its 0.037%/decade upward trend during solar cycles 21-22. The implications of increasing TSI during the global warming of the last two decades of the 20th century are that solar forcing of climate change may be a significantly larger factor than represented in the CMIP5 general circulation climate models.Cite: Scafetta, N., and R. C. Willson, 2014. ACRIM total solar irradiance satellite composite validation versus TSI proxy models. Astrophysics and Space Science 350(2), 421-442.

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Reconstruction of solar total irradiance since 1700 from the surface magnetic flux

Cited by 273 publications

References 65 publications

Tests of Sunspot Number Sequences: 1. Using Ionosonde Data

Tests of Sunspot Number Sequences: 1. Using Ionosonde Data

Assessing reconstruction techniques of the Atlantic Ocean circulation variability during the last millennium

ACRIM total solar irradiance satellite composite validation versus TSI proxy models

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