Discussion on common errors in analyzing sea level accelerations, solar trends and global warming

Errors in applying regression models and wavelet filters used to analyze geophysical signals are discussed: (1) multidecadal natural oscillations (e.g. the quasi 60-year Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO)) need to be taken into account for properly quantifying anomalous accelerations in tide gauge records such as in New York City; (2) uncertainties and multicollinearity among climate forcing functions prevent a proper evaluation of the solar contribution to the 20th century global surface temperature warming using overloaded linear regression models during the 1900-2000 period alone; (3) when periodic wavelet filters, which require that a record is pre-processed with a reflection methodology, are improperly applied to decompose non-stationary solar and climatic time series, Gibbs boundary artifacts emerge yielding misleading physical interpretations. By correcting these errors and using optimized regression models that reduce multicollinearity artifacts, I found the following results: (1) the sea level in New York City is not accelerating in an alarming way, and may increase by about 350 mm from 2000 to 2100 instead of the previously projected values varying from 1130 mm to 1550 mm estimated using the methods proposed by Sallenger et al. (2012) and Boon (2012), respectively; (2) the solar activity increase during the 20th century contributed about 50% of the 0.8 K global warming observed during the 20th century instead of only 7-10% (IPCC, 2007; Benestad and Schmidt, 2009; Lean and Rind, 2009). These findings stress the importance of natural oscillations and of the sun to properly interpret climatic changes.Comment: 21 pages, 10 Figure

Empirical analysis of the solar contribution to global mean air surface temperature change

The solar contribution to global mean air surface temperature change is analyzed by using an empirical bi-scale climate model characterized by both fast and slow characteristic time responses to solar forcing: $\tau_1 =0.4 \pm 0.1$ yr, and $\tau_2= 8 \pm 2$ yr or $\tau_2=12 \pm 3$ yr. Since 1980 the solar contribution to climate change is uncertain because of the severe uncertainty of the total solar irradiance satellite composites. The sun may have caused from a slight cooling, if PMOD TSI composite is used, to a significant warming (up to 65% of the total observed warming) if ACRIM, or other TSI composites are used. The model is calibrated only on the empirical 11-year solar cycle signature on the instrumental global surface temperature since 1980. The model reconstructs the major temperature patterns covering 400 years of solar induced temperature changes, as shown in recent paleoclimate global temperature records.Comment: 9 pages, 6 figure

Climate Change and Its Causes, A Discussion About Some Key Issues

This article discusses the limits of the Anthropogenic Global Warming Theory advocated by the Intergovernmental Panel on Climate Change. A phenomenological theory of climate change based on the physical properties of the data themselves is proposed. At least 60% of the warming of the Earth observed since 1970 appears to be induced by natural cycles which are present in the solar system. A climatic stabilization or cooling until 2030-2040 is forecast by the phenomenological model.Comment: 26 pages, 15 figure. The full English version with the appendixes can be downloaded from http://scienceandpublicpolicy.org/originals/climate_change_causes.htm

Global temperatures and sunspot numbers. Are they related? Yes, but non linearly. A reply to Gil-Alana et al. (2014)

Gil-Alana et al. (Physica A: 396, 42-50, 2014) compared the sunspot number record and the temperature record and found that they differ: the sunspot number record is characterized by a dominant 11-year cycle while the temperature record appears to be characterized by a singularity or pole in the spectral density function at the zero frequency. Consequently, they claimed that the two records are characterized by substantially different statistical fractional models and rejected the hypothesis that sun influences significantly global temperatures. I show that: (1) the "singularity" or "pole" in the spectral density function of the global surface temperature at the "zero" frequency does not exist - it is a typical misinterpretation that discrete power spectra of non-stationary signals can suggest; (2) appropriate continuous periodograms clarify the issue and also show a signature of the 11-year solar cycle (amplitude <0.1 K), which since 1850 has an average period of about 10.4 year, and of many other natural oscillations; (3) the solar signature in the surface temperature record can be recognized only using specific techniques of analysis that take into account non-linearity and filtering of the multiple climate change contributions; (4) the post 1880-year temperature warming trend cannot be compared or studied against the sunspot record and its 11-year cycle, but requires solar proxy models showing short and long scale oscillations plus the contribution of anthropogenic forcings, as done in the literature. Multiple evidences suggest that global temperatures and sunspot numbers are quite related to each other at multiple time scales through complex and non-linear processes. Finally, I show that the prediction of a semi-empirical model for the global temperature based on astronomical oscillations and anthropogenic forcing proposed by Scafetta since 2009 has up to date been successful.Comment: 21 pages, 6 figure

Scaling Analysis on Indian Foreign Exchange Market

In this paper we investigate the scaling behavior of the average daily exchange rate returns of the Indian Rupee against four foreign currencies namely US Dollar, Euro, Great Britain Pound and Japanese Yen. Average daily exchange rate return of the Indian Rupee against US Dollar is found to exhibit a persistent scaling behavior and follow Levy stable distribution. On the contrary the average daily exchange rate returns of the other three foreign currencies do not show persistency or antipersistency and follow Gaussian distribution.Comment: Revised Final Version. In Press Physica

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

The sunspot record since 1749 is made of three major cycles (9.98, 10.9 and 11.86 yr). The side frequencies are related to the spring tidal period of Jupiter and Saturn (9.93 yr) and to the tidal sidereal period of Jupiter (11.86 yr). A simplified harmonic constituent model based on the above two planetary tidal frequencies and on the exact dates of Jupiter and Saturn planetary tidal phases, plus a theoretically deduced 10.87-year central cycle reveals complex quasi-periodic interference/beat patterns at about 115, 61 and 130 years, plus a quasi-millennial large beat cycle around 983 years. We show that equivalent synchronized cycles are found in cosmogenic records used to reconstruct solar activity and in proxy climate records throughout the Holocene. The quasi-secular beat oscillations hindcast reasonably well the known prolonged periods of low solar activity during the last millennium known as Oort, Wolf, Sporer, Maunder and Dalton minima, as well as 17 115-year long oscillations found in temperature reconstructions during the last 2000 years. The millennial three-frequency beat cycle hindcasts equivalent solar and climate cycles for 12,000 years. Prolonged solar minima in 1900-1920 and 1960-1980, the secular solar maxima around 1870-1890, 1940-1950 and 1995-2005, and a secular upward trending during the 20th century is recovered: this modulated trending agrees well with some solar proxy model, with the ACRIM TSI satellite composite and with the global surface temperature modulation since 1850. The model forecasts a new prolonged solar grand minimum during 2020-2045, which would be produced by the minima of both the 61 and 115-year reconstructed cycles. Solar and climate oscillations are linked to planetary motion and, furthermore, their timing can be reasonably hindcast and forecast for decades, centuries and millennia. The critique by Smythe and Eddy (1977) is rebutted.Comment: Journal of Atmospheric and Solar-Terrestrial Physics (2012

Solar and planetary oscillation control on climate change: hind-cast, forecast and a comparison with the CMIP5 GCMs

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 $CO_{2}$ doubling centered in 1.35 $^{o}C$ and varying between 0.9 $^{o}C$ and 2.0 $^{o}C$.Comment: 35 Pages, 18 Figures. General Review in "Mechanisms of Climate Change and the AGW Concept: a critical review

Empirical evidence for a celestial origin of the climate oscillations and its implications

We investigate whether or not the decadal and multi-decadal climate oscillations have an astronomical origin. Several global surface temperature records since 1850 and records deduced from the orbits of the planets present very similar power spectra. Eleven frequencies with period between 5 and 100 years closely correspond in the two records. Among them, large climate oscillations with peak-to-trough amplitude of about 0.1 $^oC$ and 0.25 $^oC$, and periods of about 20 and 60 years, respectively, are synchronized to the orbital periods of Jupiter and Saturn. Schwabe and Hale solar cycles are also visible in the temperature records. A 9.1-year cycle is synchronized to the Moon's orbital cycles. A phenomenological model based on these astronomical cycles can be used to well reconstruct the temperature oscillations since 1850 and to make partial forecasts for the 21$^{st}$ century. It is found that at least 60\% of the global warming observed since 1970 has been induced by the combined effect of the above natural climate oscillations. The partial forecast indicates that climate may stabilize or cool until 2030-2040. Possible physical mechanisms are qualitatively discussed with an emphasis on the phenomenon of collective synchronization of coupled oscillators.Comment: 18 pages, 15 figures, 2 table

Understanding the complexity of the L\'evy-walk nature of human mobility with a multi-scale cost/benefit model

Probability distributions of human displacements has been fit with exponentially truncated L\'evy flights or fat tailed Pareto inverse power law probability distributions. Thus, people usually stay within a given location (for example, the city of residence), but with a non-vanishing frequency they visit nearby or far locations too. Herein, we show that an important empirical distribution of human displacements (range: from 1 to 1000 km) can be well fit by three consecutive Pareto distributions with simple integer exponents equal to 1, 2 and ($\gtrapprox$) 3. These three exponents correspond to three displacement range zones of about 1 km $\lesssim \Delta r \lesssim$ 10 km, 10 km $\lesssim \Delta r \lesssim$ 300 km and 300 km $\lesssim \Delta r \lesssim$ 1000 km, respectively. These three zones can be geographically and physically well determined as displacements within a city, visits to nearby cities that may occur within just one-day trips, and visit to far locations that may require multi-days trips. The incremental integer values of the three exponents can be easily explained with a three-scale mobility cost/benefit model for human displacements based on simple geometrical constrains. Essentially, people would divide the space into three major regions (close, medium and far distances) and would assume that the travel benefits are randomly/uniformly distributed mostly only within specific urban-like areas