# Nicola Scafetta, Ph. D.

## Research Interests (#)

Earth and Planetary Science, Computational Physics, Statistical Physics, Solar Physics, Space Weather, Auroras, Climate Change, Biophysics, Environmental Physiology, Time Series analysis, Fractal Systems, Complex Systems, Non-Linear Dynamics, Econophysics.

### Research summary

• Solar Physics, Climate Change and Sun-Climate Interactions. Identifying and reconstructing solar and climate variability/oscillations, studying the physical origin of their dynamics, and their interconnection and link to the oscillations of the solar system and of the heliosphere are some of the most challenging physical problems of our days. I am developing stochastic and physical models to efficiently reconstruct and forecast both solar activity and climate change by identifying and quantifying the harmonic and non-harmonic constituents of their dynamics at multiple time scales. Go to the bottom page (# Astronomical/Solar/Climate model) for a brief presentation of my proposed astronomical/solar/climate model. Figures are added including an updated figure showing a comparison among the global surface temperature record since 2000, my proposed astronomical/climate model and the current general circulation model projection range adopted by the IPCC. The figures clearly highlight the higher accuracy of the proposed semi-empirical astronomical based climate model. Download an extended popular "invited review" about my research referring to the planetary theory of solar variation and its implications also about climate change here PDF1_E&E. A technical extended review comparing the Astronomical semi-empirical model versus all CMIP5 general circulation models used by the IPCC Fifth Assessment Report (AR5, 2013), was published on October/4/2013 in Earth-Science Reviews, PDF2_ESR.
• Statistical Physics. I have developed novel statistical techniques for studying the scaling exponents of time series analysis and their fractal/multifractal scaling properties. For example, the Diffusion Entropy Analysis, when used together with more traditional variance-based methodologies, allows the discrimination among fractal noises generated by alternative dynamics such as fractal Brownian motion and Levy-walk signals. Relevant papers: PRE2002, Chaos2003, JMS2004, JPCM2007, EPL2007; Book2011.
• Econophysics. Wealth distribution in societies and human mobility are other phenomena well-known to be characterized by scaling behavior and inverse power law distributions. I have demonstrated (QF2004) that wealth distributions can be described by a Gamma distribution (for low-medium income) plus an inverse power law Pareto tail (for high income). Wealth distributions can be modeled by coupling two mechanisms: i) a trade mechanism that moves wealth from one agent to another that statistically slightly favors the poorer agent, and a multiplicative investment mechanism that tends to favor the rich class, which is responsible for the Pareto tail of the distribution. About human mobility, I have found (Chaos2011) that the inverse power law distributions of human displacements are characterized by simple integer exponents (1, 2, and larger) depending on whether the displacements are short (for example, within a city) or long (for example, trips among cities). This surprisingly simple characteristic can be deduced from topological geometry and simple cost-decision properties.
• Environmental Fractal Physiology. During the past two decades the biomedical community has witnessed several applications of nonlinear system theory to the analysis of biomedical time series and the development of nonlinear dynamic models. The development of this area of medicine can best be described as nonlinear and fractal/multifractal physiology. These studies have been intended to develop more reliable methodologies for understanding how biological systems respond to peculiar altered conditions induced by internal stress, environment stress, drugs and/or disease. My research has shown the fractal dependency on different conditions of physiological signals such as inter-breath intervals, heart inter-beat intervals, and human stride intervals. These findings can be used for developing novel clinical monitoring methodologies and computerized machines. These topics are particularly relevant to several fields of medicine, anesthesiology and environmental physiology (for example, for improved interpretation of diving and altitude physiology). Physical stochastic models to interpret the fractal dynamical evolution of physiological signals under several conditions have been proposed. Relevant papers: PRE2002, PRE2003, ABE2004, Complexity2007, CJA2008, Chaos2009.
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## Publications (#)

### Scientific Books

1. Scafetta N., 2010. Diffusion Entropy Analysis of Time Series: Theory, concepts, applications and computer codes for studying fractal noises and Lévy walk signals. (VDM Verlag Dr. Müller).
2. West B. J. and N. Scafetta, 2010. Disrupted Networks: from physics to climate change. (World Scientific Publishing Company).
3. Idso C., S. F. Singer plus 35 contributors including N. Scafetta, 2009. Climate Change Reconsidered: The Report of the Nongovernmental International Panel on Climate Change (NIPCC). (The Heartland Insitute).

### Free Web-Booklets

1. Scafetta N., 2013. Solar and planetary oscillation control on climate change: hind-cast, forecast and a comparison with the CMIP5 GCMs. (Science and Public Policy Institute).
2. Scafetta N., 2012. Testing an astronomically based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models. (Science and Public Policy Institute).
3. Scafetta N., 2010. Empirical Evidence for a Celestial Origin of the Climate Oscillations and its Implications. (Science and Public Policy Institute).
4. Scafetta N., 2010. Climate Change and Its Causes, A Discussion About Some Key Issues. (Science and Public Policy Institute).

### Scientific papers in Journals and Books (#)

1. Scafetta N., 2014. Global temperatures and sunspot numbers. Are they related? Yes, but non linearly. A reply to Gil-Alana et al. (2014). Physica A 413, 329–342.
2. Scafetta, N., 2014. Comment on “Tiny warming of residual anthropogenic CO2”. International Journal of Modern Physics B 28, 1475001.
3. Scafetta N., 2014. Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes. Climate Dynamics 43(1-2), 175-192.
4. 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.
5. Scafetta, N., N.-A. Mörner, 2014. The giant solar flare event of January 7, 2014 in light of the planetary theory of solar variability. Pattern Recognition in Physics 2(2), 31-34.
6. Scafetta, N., 2014. The complex planetary synchronization structure of the solar system. In the Special Issue “Pattern in solar variability, their planetary origin and terrestrial impacts”, Eds: N.-A. Mörner, R. Tattersall, and J.-E. Solheim. Pattern Recognition in Physics 2, 1-19.
7. Mörner, N.-A., R. Tattersall, J.-E. Solheim, I. Charvatova, N. Scafetta, H. Jelbring, I. R. Wilson, R. Salvador, R. C. Willson, P. Hejda, W. Soon, V. M. Velasco Herrera, O. Humlum, D. Archibald, H. Yndestad, D. Easterbrook, J. Casey, G. Gregori, and G. Henriksson, 2013. General conclusions regarding the planetary–solar–terrestrial interaction. In the Special Issue “Pattern in solar variability, their planetary origin and terrestrial impacts”, Eds: N.-A. Mörner, R. Tattersall, and J.-E. Solheim. Pattern Recognition in Physics 1, 205-206.
8. Scafetta, N., and R. C. Willson, 2013. Multi-scale comparative spectral analysis of satellite total solar irradiance measurements from 2003 to 2013 reveals a non-linear planetary modulation of solar activity depending on the 11-year solar cycle. In the Special Issue “Pattern in solar variability, their planetary origin and terrestrial impacts”, Eds: N.-A. Mörner, R. Tattersall, and J.-E. Solheim. Pattern Recognition in Physics 1, 123-133.
9. Scafetta, N. 2013. Discussion on climate oscillations: CMIP5 general circulation models versus a semi-empirical harmonic model based on astronomical cycles. Earth-Science Reviews 126, 321-357.
10. Scafetta, N. 2013. Reply to Benestad’s comment on “Discussions on common errors in analyzing sea level accelerations, solar trends and global warming” by Scafetta (2013). Pattern Recognition in Physics 1, 105-106.
11. Scafetta N., and R. C. Willson, 2013. Empirical evidences for a planetary modulation of total solar irradiance and the TSI signature of the 1.09-year Earth-Jupiter conjunction cycle. Astrophysics and Space Science 348(1), 25-39.
12. Scafetta N., 2013. Solar and planetary oscillation control on climate change: hind-cast, forecast and a comparison with the CMIP5 GCMs. Energy & Environment 24(3-4), 455–496.
13. Scafetta N., 2013. "Interactive comment on `Agnotology: learning from mistakes' by R. E. Benestad et al." Earth System Dynamics - Discussion, 4, C312–C312, 2013.
14. Scafetta N., 2013. Discussion on common errors in analyzing sea level accelerations, solar trends and global warming. Pattern Recognition in Physics, 1, 37–57.
15. Scafetta N., O. Humlum, J.-E. Solheim, and K. Stordahl, 2013. Comment on “The influence of planetary attractions on the solar tachocline” by Callebaut, de Jager and Duhau. Journal of Atmospheric and Solar–Terrestrial Physics 102, 368-371.
16. Scafetta N., and R. C. Willson, 2013. Planetary harmonics in the historical Hungarian aurora record (1523–1960). Planetary and Space Science 78, 38-44.
17. Mazzarella A., A. Giuliacci and N. Scafetta, 2013. Quantifying the Multivariate ENSO Index (MEI) coupling to CO2 concentration and to the length of day variations. Theoretical and Applied Climatology 111, 601-607.
18. Manzi V., R. Gennari, S, Lugli, M. Roveri, N. Scafetta and C. Schreiber, 2012. High-frequency cyclicity in the Mediterranean Messinian evaporites: evidence for solar-lunar climate forcing. Journal of Sedimentary Research 82, 991-1005.
19. Scafetta N., 2012. Does the Sun work as a nuclear fusion amplifier of planetary tidal forcing? A proposal for a physical mechanism based on the mass-luminosity relation. Journal of Atmospheric and Solar-Terrestrial Physics 81-82, 27-40.
20. Scafetta N., 2012. Multi-scale harmonic model for solar and climate cyclical variation throughout the Holocene based on Jupiter-Saturn tidal frequencies plus the 11-year solar dynamo cycle. Journal of Atmospheric and Solar-Terrestrial Physics 80, 296-311.
21. Scafetta N., 2012. Testing an astronomically based decadal-scale empirical harmonic climate model versus the IPCC (2007) general circulation climate models. Journal of Atmospheric and Solar-Terrestrial Physics 80, 124-137.
22. Scafetta N., 2012. A shared frequency set between the historical mid-latitude aurora records and the global surface temperature. Journal of Atmospheric and Solar-Terrestrial Physics 74, 145-163.
23. Mazzarella A. and N. Scafetta, 2012. Evidences for a quasi 60-year North Atlantic Oscillation since 1700 and its meaning for global climate change. Theoretical and Applied Climatology 107, 599-609.
24. Scafetta N., 2012. Der vergessene natürliche 60-Jahres-Zyklus (The forgotten 60-year natural cycle). Chapter in Die kalte Sonne - Warum die Klimakatastrophe nicht stattfindet (The cold sun: Why the climate crisis is not happening). Edited by F. Vahrenholt and S. Lüning (Hoffmann und Campe, Germany).
25. Scafetta N., 2011. Understanding the complexity of the Lévy-walk nature of human mobility with a multi-scale cost/benefit model. Chaos: An Interdisciplinary Journal of Nonlinear Science 21, 043106.
26. Loehle C. and N. Scafetta, 2011. Climate Change Attribution Using Empirical Decomposition of Climatic Data. The Open Atmospheric Science Journal 5, 74-86.
27. Scafetta N., 2011. Total Solar Irradiance Satellite Composites and their Phenomenological Effect on Climate. In Evidence-Based Climate Science edited by Don Easterbrook (Elsevier), chap. 12, 289-316.
28. Scafetta N. and B. J, West, 2010. Comment on `Testing hypotheses about Sun-climate complexity linking'. Physical Review Letters 105, 219801.
29. Scafetta N., 2010. Empirical evidence for a celestial origin of the climate oscillations and its implications. Journal of Atmospheric and Solar-Terrestrial Physics 72, 951-970.
30. Scafetta N., 2010. I cicli climatici e le loro implicazioni (Climate cycles and their implications). Bollettino della Scuola Normale di Pisa 13(2), 6-10.
31. Scafetta N., 2010. I cambiamenti climatici sono regolati da cicli naturali di origine astronomica (Climate change is regulated by natural cycles with an astronomical orogins). Il 21mo Secolo, Scienza e Tecnologia 1, 5-10 (2010).
32. Scafetta N., 2010. I cambi climatici e le loro cause, una discussione su alcuni punti chiave (Climate Change and Its Causes, A Discussion About Some Key Issues). La Chimica e l'Industria 1, 70-75.
33. Scafetta N., 2009. Empirical analysis of the solar contribution to global mean air surface temperature change. Journal of Atmospheric and Solar-Terrestrial Physics 71, 1916-1923.
34. Scafetta N., B. J. West, B. R. Jordan, P. Duffy, B. Santer, and T. Wigley, 2009. Interpretations of climate-change data. Physics Today 11, 8-10 (2009).
35. Scafetta N., D. Marchi and B. J. West, 2009. Understanding the complexity of human gait dynamics. Chaos: An Interdisciplinary Journal of Nonlinear Science 19, 026108.
36. Scafetta N. and R. Willson, 2009. ACRIM-gap and Total Solar Irradiance (TSI) trend issue resolved using a surface magnetic flux TSI proxy model. Geophysical Research Letter 36, L05701.
37. Foukal P., D. Schmidt, W. Klaassen, J. Gulledge, A. D. Socci, W. H. Smith, J. R. Smith, R. W. Cohen, N. Scafetta, and B. J. West, 2008. Variations on Sun's role in climate change. Physics Today 10, 10-16.
38. Froehlich K. F., M. R. Graham, T. G. Buchman, L. G. Girling, N. Scafetta, B. J. West, E. K-Y. Walker, B. M. Mc Manus and W. A. C. Mutch, 2008. Physiological Noise versus White Noise to Drive a Variable Ventilator in a Porcine Model of Lung Injury. Canadian Journal of Anesthesia 55, 577-586.
39. Scafetta N., 2008. Comment on `Heat capacity, time constant, and sensitivity of Earth's climate system' by Schwartz. Journal of Geophysical Research 113, D15104.
40. Scafetta N. and B. J. West, 2008. Is climate sensitive to solar variability? Physics Today 3, 50-51.
41. Kabela E. and N. Scafetta, 2008. Solar Effect and Climate Change. Bulletin of the American Meteorological Society 89, 34-35.
42. Forkner I. F., C. A. Piantadosi, N. Scafetta, R. E. Moon, 2008. Hyperoxia-induced Decrease in Organ Blood Flow. Anesthesiology 108, 169-170.
43. Scafetta N., and B. J. West, 2007. Phenomenological reconstructions of the solar signature in the NH surface temperature records since 1600. Journal of Geophysical Research 112, D24S03.
44. Scafetta N., R. Moon, and B. J. West, 2007. Fractal Response of Physiological Signals to Stress Conditions, Environmental Changes and Neurodegenerative Diseases. Complexity 12, 12-17.
45. Forkner I. F., C. A. Piantadosi, N. Scafetta, and R. E. Moon, 2007. Hyperoxia-Induced Tissue Hypoxia: A Danger? Anesthesiology 106, 1051-1055.
46. Scafetta N. and B. J. West, 2007. Probability distributions in conservative energy exchange models of multiple interacting agents. Journal of Physics: Condensed Matter 19, 065138.
47. Scafetta N. and B. J. West, 2007. Emergence of bi-fractal time series from noise via allometric filters. European Physical Letters 79, 30003.
48. Scafetta N. and B. J. West, 2006. Phenomenological solar signature in 400 years of reconstructed Northern Hemisphere temperature record. Geophysical Research Letters 33, L17718 (2006).
49. Scafetta N. and B. J. West, 2006. Reply to comments by J. Lean on `Estimated solar contribution to the global surface warming using the ACRIM TSI satellite composite'. Geophysical Research Letters 33, L15702.
50. Scafetta N. and B. J. West, 2006. Phenomenological solar contribution to the 1900-2000 global surface warming. Geophysical Research Letters 33, L05708.
51. Scafetta N., A. Ray and B. J. West, 2006. Correlation regimes in fluctuations of fatigue crack growth. Physica A 359, 1-23.
52. Scafetta N., R. Moon, and B. J. West, 2006. Physiological signals and their fractal response to stress conditions, environmental changes and neurodegenerative diseases. In Proceedings of The 25th Army Science Conference (ASC), Orlando, Florida, November 27-30.
53. Scafetta N. and B. J. West, 2005. Estimated solar contribution to the global surface warming using the ACRIM TSI satellite composite. Geophysical Research Letters 32, L18713 (2005).
54. Scafetta N. and B. J. West, 2005. Multiscaling comparative analysis of time series and geophysical phenomena. Complexity 10, 51-56.
55. West B. J. and N. Scafetta, 2005. A Multifractal Dynamical Model of Human Gait. Fractals in Biology and Medicine, Vol. IV Book Series: Mathematics and Biosciences in Interaction, pages: 131-140.
56. Moon R. E., Eschenbacher L. E., Scafetta N., 2006. Perioperative respiratory depression and monitoring. Patient Safety and Quality Healthcare Nov/Dec Suppl, 15-20.
57. Moon R. E., L. Eschenbacher and N. Scafetta, 2005. Perioperative Respiratory Depression and Monitoring. In Pain Management and Patient-Controlled Analgesia: Improving Safety and Quality of Care, pp. 15-20. Proceedings from The Sixth Conference Center for Safety and Clinical Excellence November 17-18, 2005, San Diego, CA. P. J. Schneider, MS, FASHP, Editor.
58. Scafetta N. and B. J. West, 2004. Complexity, multiresolution, non-stationarity and entropic scaling: Teen birth thermodynamics. Journal of Mathematical Sociology 28, 229-259.
59. West B. J., N. Scafetta, W. Cooke and R. Balocchi, 2004. Influence of progressive central hypovolemia on multifractal dimension of cardiac interbeat intervals. Annals of Biomedical Engineering 32, 1077-1087.
60. Scafetta N., B. J. West and S. Picozzi, 2004. A trade-investment model for distribution of wealth. Physica D (Anomalous Distributions, Nonlinear Dynamics, and Nonextensivity) 193, 338-352.
61. Scafetta N., S. Picozzi and B. J. West, 2004. An out-of-equilibrium model of the distributions of wealth. Quantitative Finance 4, 353-364.
62. Scafetta N. and B. J. West, 2004. Multi-scaling comparative analysis of time series and a discussion on `earthquake conversations' in California. Physical Review Letters 92, 138501.
63. Scafetta N., T. Imholt, J. A. Roberts and B. J. West, 2004. An intensity-expansion method to treat non-stationary time series: an application to the distance between prime numbers. Chaos, Solitons & Fractals 20, 119-125.
64. Scafetta N. and B. J. West, 2004. Multiresolution Diffusion Entropy Analysis of time series: an application to births to teenagers in Texas. Chaos, Solitons & Fractals 20, 179-185.
65. Scafetta N., P. Grigolini, P. Hamilton and B. J. West, 2004. Non-extensive diffusion entropy analysis and teen birth phenomena. In Nonextensive Entropy: Interdisciplinary Applications, pp. 295-304. M. Gell-Mann and C. Tsallis, editors, (Oxford University Press).
66. Scafetta N., P. Grigolini, T. Imholt, J. A. Roberts and B. J. West, 2004. Solar turbulence in earth's global and regional temperature anomalies. Physical Review E 69, 026303.
67. Scafetta N., L. Griffin and B. J. West, 2003. Hölder exponent spectra for human gait. Physica A 328, 561-583.
68. Scafetta N. and B. J. West, 2003. Solar Flare Intermittency and the Earth's Temperature Anomalies. Physical Review Letters 90, 248701.
69. West B. J., and N. Scafetta, 2003. A non linear model for human gait. Physical Review E 67, 051917.
70. Scafetta N., E. Restrepo and B. J. West, 2003. Seasonality of birth and conception to teenagers in Texas. Biodemography and Social Biology 50, 1-22.
71. Allegrini P., V. Benci, P. Grigolini, P. Hamilton, M. Ignaccolo, G. Menconi, L. Palatella, G. Raffaelli, N. Scafetta, M. Virgilio and J. Yang, 2003. Compression and Diffusion: A Joint Approach to Detect Complexity. Chaos, Solitons & Fractals 15, 517-535.
72. Scafetta N., and P. Grigolini, 2002. Scaling detection in time series: diffusion entropy analysis. Physical Review E 66, 036130.
73. Scafetta N., V. Latora and P. Grigolini, 2002. Lévy Scaling: The diffusion entropy method applied to the DNA sequences. Physical Review E 66, 031906.
74. Scafetta N., V. Latora and P. Grigolini, 2002. Lévy statistics in coding and non-coding nucleotide sequences. Physics Letters A 299, 565-570.
75. Grigolini P., D. Leddon, N. Scafetta, 2002. The Diffusion entropy and waiting time statistics of hard x-ray solar flares. Physical Review E 65, 046203.
76. Aquino G., P. Grigolini, N. Scafetta, 2001. Sporadic Randomness, Maxwell's Demon and the Poincare' recurrence times. Chaos, Solitons & Fractals 12, 2023-2038.
77. Scafetta N., P. Hamilton and P. Grigolini, 2001. The Thermodynamics of Social Process: the Teen Birth Phenomenon. Fractals 9, 193-208.
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## Astronomical/Solar/Climate model (#)

My studies suggest that the climate system is characterized by a complex set of specific harmonics at the annual, decadal, secular and millennial time scales throughout the Holocene. The constituent harmonics of the climate system are found to be well correlated and, therefore, likely linked to oscillations found in the dynamics of the Sun, of the Moon and of the planets of the solar system. For example, Figure 1 shows the power spectra (black) of global surface temperature records since 1850 (Global, North, South, Land and Ocean) against a set of major harmonics deduced from the speed of the wobbling Sun relative to the barycenter of the solar system (red area), which is a convenient way to detect a possible set of the major planetary harmonics of the solar system.
Figure 1 shows that there exists a good coherence between the solar and climate power spectra at multiple frequencies. Figure 2 shows a direct comparison between the 20-year and 60-year oscillations of the speed of the wobbling sun (in black) and the equivalent 20-year and 60-year oscillations found in the global surface temperature. A similar common coherence is also found between the temperature and the aurora historical records (see JASTP2010 and JASTP2012a for details). Note that the barycenter movement of the Sun needs to be interpreted just as an approximate “proxy” for the forces and the physical mechanisms acting on the Sun and on the solar systems: no claim is made that the barycenter movement by itself is the physical cause of the observed dynamics because the sun is evidently in free-fall in it.
In particular, the 20-year and 60-year Jupiter/Saturn cycles together with a quasi-millennial cycle were even well-known in the ancient/medieval times as generated by the Trigon of the Great Conjunctions. For centuries Jupiter/Saturn conjunction cycles were believed to be related to climate changes, political/economical shifts and infectious and epidemic disease in history. A 60-year cycle was included in traditional Chinese and Indian calendars (the Brihaspati-Jupiter 60-year cycle), was known to numerous ancient civilizations and also well documented in the works of Kepler, who was trying to understand and forecast weather and climate change by looking at the Sun, the moon and the planets.
How planets may influence solar activity and/or the Earth's climate has been a deep mystery throughout history. Today, some people think that a planetary influence of the Earth is only an astrological superstition. However, also the ancient belief that the Moon was causing the ocean tides on the Earth, a theory strongly advocated by Ptolemy and Kepler upon observations and correlations, was naively opposed by even some prominent scientist such as Galileo Galilei on the mere assumption that a physical mechanism linking the Moon to the ocean tides was not known at the time (up to the 17th century): actually, Galilei dismissed the ancient theory because he claimed to have found the “tidal mechanism” - that is, the Earth orbiting the Sun - but nobody believed him, beginning from Kepler, because the lunar-based empirical tidal models, as those developed by the Northumbrian monk Bede in 725, predicted the tides very well. Therefore, the Moon was the main cause of the tides although the physical mechanism was not known yet. As today everybody knows, about 100 years later, Newton solved the physical problem in favor of Ptolemy and Kepler's empirical arguments with his law of gravity. This historical example teaches us that the development of a scientific theory begins with observations and with the discovery of phenomenological correlations between physical observables. On the contrary, the process of understanding the underlying physical linking mechanisms requires its own time, which may be long. The scientific method requires people to generate a hypothesis, make predictions, testing them and, eventually, polish the hypothesis and start the process again. As in the Middle Ages Roger Bacon understood, the scientific method is based on a repeating cycle of observation, hypothesis, experimentation, and the need for independent verification. Evidently, scientific research is time-consuming. Therefore, a present-day lack of understanding of underlying mechanisms referring to a complex phenomenon cannot be used to naively dismiss empirical evidences under the pretense that "correlation is not causation". If sufficiently good correlations are found and a empirical model based on them is shown to posses hindcast and forecast capabilities, it is perfectly legitimate to investigate the theory that hypothesizes a physical link between the two observables, and this requires its own effort and time.
In any case, I have also proposed (JASTP2012d) a physical mechanism derived from the stellar mass-luminosity relation that, if correct, would imply that planetary tidal forcings may induce a sufficiently large energy signal capable to allow the Sun to synchronize to the planetary harmonics of the solar systems. It should be noted that if the mass of all planets were added to the Sun, the luminosity of the Sun would increase by about 0.5 %. In fact, the Sun is currently on the main sequence of the Hertzsprung–Russell stellar diagram, which means that there should exist a delicate balance between the power dissipated by solar gravity and solar luminosity. Because the planetary tides add a little bit of gravitational work, which oscillates in time, to that already released by the solar gravity itself, the solar luminosity should monotonically respond to that gravitational stimulus and oscillate as well. Moreover the flux of light toward the tachocline and the surface may be modulated by the stretched plasma probably through some sound-like gravitational wave generated in the solar core. Essentially, the sun would work as a great nuclear fusion amplifier of the weak planetary gravitational tides because of its nuclear fusion active core and of its balance with the gravitational forces. Of course other mechanisms related mostly to electro-magnetic interactions may be present as well, which would be facilitated along the Parker spriral of the stellar wind, as it has been hypothesized to explain astronomical observations about stellar activity enhancement due to interactions  with  extrasolar  giant planets.
Note that major critiques against a planetary theory of solar variation are based on simplistic classical-physics arguments such as that the elongations and accelerations induced by planetary tides on the Sun appear to be too small to produce any observable effect. However, simple classical physics has evident shortcomings when attempting to explain solar physics: for example, classical physics predicts that the Sun is just about 10-40 million years old as, in the 19th century, was deduced from the power generated by the Kelvin–Helmholtz gravitational contraction. On the contrary, the Sun is 4.7-billion years old, and today it is clear that classical physics can fail to explain how the Sun works by a large factor. Today everybody knows that the solar power output and long lifetime are due to thermonuclear energy production, which is only regulated by the solar gravity, and nuclear fusion cannot be explained in classical-physical terms. Evidently, a planetary theory of solar variation requires a modern-physical approach together with the novel physics of dynamical synchronization of coupled oscillators, which deal with mechanisms capable to greatly amplify small harmonic forcings. This would also explicate why the 19th century pioneers of the planetary theory of solar variation (such as Rudolf Wolf - the father of the sun-spot number series -, R. C. Carrington and other solar/aurora experts), could not figure out a working mechanism.
Then, solar and planetary oscillations would drive equivalent oscillations in the electric and magnetic properties of the Heliosphere, which have been detected also in the aurora records (JASPT2012a). The solar and heliospheric oscillations likely force the Earth's water-vapor and cloud system through multiple mechanisms (solar irradiance, UV, modulation of the incoming flux of galactic cosmic rays, etc.), and cause equivalent oscillations in the terrestrial albedo up to a 1-3% variations (which is a realistic amplitude as deduced from available data, as I also show in my papers). Oscillations in the albedo can drive equivalent oscillations in the climate system (including atmosphere and ocean oscillations) because they determine the amount of total solar irradiance that reaches the surface and warms it. Other mechanisms may be present as well.
In brief, climate has always changed and people have always studied it, and tried to understand and forecast it since antiquity. Both astrophysical and geophysical elements contribute to climate mutations and the astrophysical elements are usually characterized by cyclical behaviors. My studies suggest that most of the decal-to-millennial variability observed in the climate system at multiple time scales throughout the last 12,000 years (the Holocene) including the Medieval Warm Period (900-1300), the Little Ice Age (1300-1800), the Modern Warm Period started in the 19th century and, in particular, the warming since 1970, can be correlated to the above identified solar/lunar/astronomical natural cycles at multiple time scales.
Also an anthropogenic global climate change effect - greenhouse gas emission (GHG) plus urban heat island (UHI) plus land use change (LUC) - is likely present, but its overall contribution to climate change, also during the last decades, appears secondary to that associated to natural cycles. It is possible that the global temperature will remain approximately steady or perhaps it will slightly cool for the next 2-3 decades, up to the 2030s, because the quasi 60-year cycle entered in its cooling phase around 2002 and the 115-year solar cycle will approach its minimum in 2030s yielding to a new grand solar minimum, which will have its own characteristics and will likely differ from the Maunder and Dalton solar grand minima. The harmonically modeled natural cooling should be strong enough to compensate the projected anthropogenic warming, which cannot be more than a third of what calculated by the current climate models adopted by the IPCC because of geometrical constrains due to the presence of natural cycles. This conclusion also derives from the fact that solar variability at multiple time scales can be approximately reconstructed and, apparently, predicted with planetary tidal cycles plus a solar dynamo cycle.
Figures 9, 10, 11 and 12 show my basic solar variation model constructed by using the two tidal cycles of Jupiter and Saturn on the Sun (periods: 9.93 and 11.86 years) plus the solar dynamo cycle (period: 10.87 years) against proxy records of the temperature and of solar activity (C14 and Be10) throughout the Holocene. The adopted three harmonics have been discovered by spectral analysis of the sunspot number record since 1749 as shown above in Figure 3. In addition, the three harmonics produce quasi 61, 115, 130 and 980 year beat cycles. Of course, many other cycles are present: for example, ocean tides are currently predicted with 30-40 harmonic constituents related to the Sun and the Moon and a similar situation would occur with the planetary tides occurring on the Sun. Therefore, my proposed three-frequency model should be understood only as the simplest working model that can reproduce the major patterns recognized in the data. To improve the precision there is the evident need to add numerous other harmonics.
As observed in the figures, the three-frequency astronomical harmonic model already well correlates to the observed solar and climatic variability at multiple time scales. The model is able to approximately hindcast known solar grand minima that occur at about 115-year intervals (some of them are known as Oort, Wolf, Sporer, Maunder and Dalton solar minima) and the great quasi-millennial cycle responsible for the Roman Warm Period, the Dark Age Cold Period, the Medieval Warm Period, the Little Ice Age and the Current Warm Period, which may last for other two centuries, and many other events in the antiquity. All these cycles are observed in both solar and climate records. For example, Figure 12 shows in red two filtered solar proxy models (Be10 and C14) and a temperature model (HSG) (taken from Bond et al., 2001) and in black the 980-year beat harmonic produced by the three-frequency astronomical model. As the figure shows, the model well captures the millennial solar/climate cycle. The complex patterns seen in the solar data are produced by interference among the constituent solar/tidal harmonics. For example, the multi-decadal grand solar minima emerge when the central 10.87-year cycle interferes destructively with the two Jupiter and Saturn tidal cycles. The finding rebuts another major critique of a planetary theory of solar variation claiming that planetary geometry does not correlate to known solar dynamics. The good correlation exists, but it emerges only if the tidal cycles are coupled with the solar dynamo cycle that likely emerges as a synchronization/resonance response of the hydrodynamics of the convective-zone solar plasma to the internal luminosity oscillations induced by the planetary harmonics. These results would also qualitatively agree with my preliminary studies showing that solar records and climate data present similar complex scaling exponents. Relevant papers: PRL2003, PRE2004, JASTP2012a, JASTP2012c, JASTP2012d.
Figure 13 shows the ACRIM total solar irradiance (TSI) satellite composite against the PMOD composite. The two records imply alternative solar dynamical histories since 1980. Figure 14 shows empirical reconstructions of the solar signature on the climate since 1600 using ACRIM and PMOD since 1980. The black and blue curves highlight how important understanding correctly solar dynamics may be for correctly interpreting climate changes. Note that ACRIM uses the TSI satellite measurements as published by the original science teams, while PMOD adopts “corrected” versions that, however, are rejected by the original satellite experiment teams. ACRIM dynamical pattern (an increase from 1980 to 2000, and a decease since 2000) would be compatible with the 61-year cycle predicted by the astronomical model (see Figure 4) and would explain a significant part of the global warming since 1980. Relevant papers: GRL2005, JGR2007, PhysicsToday2008, JGR2008, GRL2009, JASTP2009, Book2011. The issue is quite important because there may be the possibility that for their climatic simulations the current GCMs are not using sufficient physical mechanisms and are not even using appropriate solar radiative forcing records.

### Astronomical Climate model forecast vs. IPCC (#)

Magnification of Figure 6 that shows the global surface temperature (HadCRUT3): the red curve shows the original global surface temperature record published in the paper JASTP2012b and the blue curve shows the global surface temperature updated to the most current available month. The back curve within the cyan area is the full astronomical harmonic model forecast since 2000 that clearly outperforms the IPCC general circulation model projections (green area). The yellow curve is the harmonic component alone without the anthropogenic component.
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Global surface temperature records (e.g. HadCRUT4) since 1850 are characterized by climatic oscillations synchronous with specific solar, planetary and lunar harmonics superimposed on a background warming modulation. The latter is related to a long millennial solar oscillation and to changes in the chemical composition of the atmosphere (e.g. aerosol and greenhouse gases). However, current general circulation climate models, e.g. the CMIP5 GCMs, to be used in the AR5 IPCC Report in 2013, fail to reconstruct the observed climatic oscillations. As an alternate, an empirical model is proposed that uses: (1) a specific set of decadal, multidecadal, secular and millennial astronomic harmonics to simulate the observed climatic oscillations; (2) a 0.45 attenuation of the GCM ensemble mean simulations to model the anthropogenic and volcano forcing effects. The proposed empirical model outperforms the GCMs by better hind-casting the observed 1850-2012 climatic patterns. It is found that: (1) about 50-60% of the warming observed since 1850 and since 1970 was induced by natural oscillations likely resulting from harmonic astronomical forcings that are not yet included in the GCMs; (2) a 2000-2040 approximately steady projected temperature; (3) a 2000-2100 projected warming ranging between 0.3 ${}^{o}C$ and 1.6 ${}^{o}C$, which is significantly lower than the IPCC GCM ensemble mean projected warming of 1.1 ${}^{o}C$ to 4.1 ${}^{o}C$; ; (4) an equilibrium climate sensitivity to $C{O}_{2}$ doubling centered in 1.35 ${}^{o}C$ and varying between 0.9 ${}^{o}C$ and 2.0 ${}^{o}C$.