On Mar 12, 5:33 am, "00BNZ" <00...@[EMAIL PROTECTED]
> wrote:
> Up To 69% Of Global Warming Due To Solar Variability
>
> Nicola Scafetta, Bruce J. West
>
> Physics Today
>
> March 2008
>
> http://www.fel.duke.edu/~scafetta/pdf/opinion0308.pdf
>
> QUOTE: "In particular, since 2002 the temperature
>
> data present a global cooling, not a
>
> warming! This cooling seems to have
>
> been induced by decreased solar activity
>
> from the 2001 maximum to the 2007
>
> minimum as depicted in two distinct
>
> TSI reconstructions."
>
> Nicola Scafetta is a research associate in the Duke University physics
> department. Bruce West is chief scientist in the mathematical and
> information science directorate, US Army Research Office, in Research
> Triangle Park, North Carolina.
>
> The causes of global warming-the
>
> increase of approximately 0.8=B10.1 =B0C in
>
> the average global temperature near
>
> Earth's surface since 1900-are not as
>
> apparent as some recent scientific publications
>
> and the popular media indicate.
>
> We contend that the changes in
>
> Earth's average surface temperature are
>
> directly linked to two distinctly different
>
> aspects of the Sun's dynamics: the
>
> short-term statistical fluctuations in the
>
> Sun's irradiance and the longer-term
>
> solar cycles. This argument for directly
>
> linking the Sun's dynamics to the response
>
> of Earth's climate is based on
>
> our research and augments the interpretation
>
> of the causes of global warming
>
> presented in the United Nations
>
> 2007 Intergovernmental Panel on Climate
>
> Change (IPCC) re****t.1
>
> The most debated issue in contem****ary
>
> science is the cause or causes of
>
> global warming, with the popular
>
> media contending that the issue has
>
> been resolved and that the majority of
>
> scientists concur. The "majority opinion"
>
> is based on the analysis of global
>
> warming done using large-scale computer
>
> codes that incor****ate all identified
>
> physical and chemical mechanisms
>
> into global circulation models (GCMs)
>
> in an attempt to recreate and understand
>
> the variability in Earth's average
>
> temperature. The IPCC re****t1 concludes
>
> that the contribution of solar
>
> variability to global warming is negligible,
>
> to a certainty of 95%. It is re****ted
>
> that the "majority" believes the average
>
> warming observed since the beginning
>
> of the industrial era is due to the increase
>
> in anthropogenic greenhouse gas
>
> concentrations in the atmosphere.
>
> Modeling TSI variability
>
> Earth's atmosphere, landm*****, and
>
> oceans absorb and redistribute the total
>
> solar irradiance (TSI) by means of coupled
>
> nonlinear hydrothermal, geochemical,
>
> and radiative dynamic processes
>
> that produce Earth's globally averaged
>
> temperature at a given time. Versions of
>
> those physical mechanisms are included
>
> in the GCMs, but what is not addressed
>
> in the simulations are the statistics
>
> of the time series. Those series
>
> consist of the monthly values of temperature
>
> anomalies. The statistical variability
>
> in Earth's average temperature is
>
> interpreted as noise; the temperature
>
> fluctuations are thought to contain no
>
> useful information and are consequently
>
> smoothed to emphasize the
>
> presumably more im****tant long-time
>
> changes in the average global temperature,
>
> typically on the order of years. According
>
> to the central limit theorem, the
>
> statistics of the fluctuations in such
>
> large-dimensional networks ought to be
>
> Gaussian.2 The fact that they are not remains
>
> unexplained. The non-Gaussian
>
> behavior prompted us to study temperature
>
> fluctuations as a problem in nonequilibrium
>
> statistical physics wherein
>
> statistical fluctuations often provide
>
> useful information about the trans****t
>
> properties of complex phenomena. An
>
> example would be the fluctuation-
>
> dissipation theorem, in which the response
>
> of a network to a perturbation is
>
> determined by the network's unperturbed
>
> autocorrelation function.
>
> The variations in TSI are indicative
>
> of the Sun's turbulent dynamics, as evidenced
>
> by changes in the number, duration,
>
> and intensity of solar flares and
>
> sunspots, and by the intermittency in
>
> the time intervals between dark spots
>
> and bright faculae. That time variation
>
> in TSI induces similar changes in
>
> Earth's average temperature and produces
>
> trends that move the global temperature
>
> up and down for tens or even
>
> hundreds of years. Our conclusions depart
>
> from those of the GCM simulations.
>
> We maintain that the variations in
>
> Earth's temperature are not noise, but
>
> contain substantial information about
>
> the source of variability, in particular
>
> the variations in TSI. Establi****ng this
>
> direct connection between the complex
>
> dynamics of the Sun and Earth requires
>
> a new kind of linking-one associated
>
> with the transfer of information between
>
> complex networks, even when
>
> the linking is extremely weak, as it is in
>
> the Sun-Earth network.
>
> We showed that the stochastic properties
>
> of the average global temperature
>
> are linked to the statistics of TSI.2 It is the
>
> linking of the complexity of Earth to the
>
> complexity of the Sun that forces Earth's
>
> temperature anomalies to adopt the TSI
>
> statistics. Consequently, both the fluctuations
>
> in TSI, using the solar flare time
>
> series as a surrogate, and Earth's average
>
> temperature time series are observed
>
> to have inverse power-law statistical
>
> distributions. Specifically, if t is
>
> the time between events, where an event
>
> is a solar flare or a fluctuation in Earth's
>
> temperature, the distribution of time intervals
>
> between events P(t) is an inverse
>
> power law; that is, P(t) ? A/t?, where A
>
> is a normalization constant. The inverse
>
> power-law index ? turns out to be the
>
> same for both the solar flare and temperature
>
> anomaly time series, even
>
> though the cross-correlation of the two
>
> vanishes except at the lowest frequencies,
>
> where quasi-periodic solar cycles
>
> dominate the dynamics.
>
> The scaling of the statistical distribution
>
> of the TSI time series was tested by
>
> randomly changing the order of the data
>
> points. If the time series were internally
>
> correlated, the resulting distribution
>
> would have changed from the original,
>
> but that did not happen. The invariance
>
> of the distribution under shuffling indicates
>
> that the statistics of the time series
>
> is non-Poisson and renewal-meaning
>
> that with the generation of each new
>
> event, the process is renewed. The same
>
> was determined to be true of the global
>
> temperature time series.
>
> Complexity matching
>
> The statistics of solar flares, which we
>
> used as a surrogate for the fluctuations
>
> in TSI, are described by a non-Gaussian
>
> distribution. The behavior of such limit
>
> distributions requires a generalization
>
> of the central limit theorem to the case
>
> in which the second moment of the variate
>
> diverges. Such processes were studied
>
> by Paul L=E9vy before World War II,
>
> www.physicstoday.orgMarch 2008 Physics Today 51
>
> and now bear his name. The solar flare
>
> statistics were shown to be describable
>
> by such a L=E9vy distribution and we assumed
>
> that intermittent solar flares perturb
>
> the intrinsic fluctuations in Earth's
>
> average temperature. The end result of
>
> this perturbation is that the statistics of
>
> the temperature anomalies inherit the
>
> statistical structure that was evident in
>
> the intermittency of the solar flare data.2
>
> The inverse power-law index ? for solar
>
> flares was determined to be 2.14,
>
> whereas ? for the air temperature was
>
> 2.11 globally, 2.20 for the Northern
>
> Hemisphere, 2.09 for the Southern
>
> Hemisphere, 2.21 over land, and 2.06
>
> over the ocean. The near equivalence in
>
> indices occurs because of a newly identified
>
> phenomenon, the complexitymatching
>
> effect,3 described below, and
>
> suggests the presence of a subtle but
>
> persistent solar signature in climate
>
> fluctuations on short time scales. Note
>
> that this climate response to complexity
>
> is separate and distinct from the response
>
> to solar cycles.
>
> Thus, the Sun's influence on Earth's
>
> temperature is subtle because it is not
>
> just an energy trans****t process but
>
> also an information transfer. According
>
> to linear response theory in statistical
>
> physics, a network S responds to a perturbation
>
> P by means of a linear transfer
>
> equation, whose kernel, the response
>
> function, is determined by the
>
> fluctuation-dissipation theorem given
>
> that the perturbation is sufficiently
>
> weak. When S and P are non-Poisson
>
> renewal processes, the response of S is
>
> maximal when the complexity of the
>
> two networks, as measured by the inverse
>
> power-law indices, is matched.3
>
> For the Sun-Earth one-way linking, S is
>
> the Earth and P is the Sun. The
>
> complexity-matching effect in the
>
> Sun-Earth network is evident in the
>
> equality of the inverse power-law
>
> indices.
>
> Solar cycles
>
> Incor****ating the influence of solar cycles
>
> into this thermodynamically closed
>
> climate modeling strategy reveals coordinated
>
> variability over even longer
>
> time scales. Recent heuristic studies indicate
>
> that the climate time response
>
> parameter ?, analogous to the Onsager
>
> relaxation time in statistical physics,
>
> might be 5-10 years.4,5 By using a climate
>
> time response ? of 7.5 years and
>
> the phenomenological 0.1 =B0C amplitude
>
> of the 11-year solar cycle (see reference
>
> 1, page 674, for details) as constraints on
>
> a simple two-parameter model in the
>
> tradition of the earliest climate models,
>
> we recently showed that it is possible to
>
> reconstruct a phenomenological solar
>
> signature (PSS) of climate for the last
>
> four centuries.5 In the figure, the interval
>
> from 1950 to 2010 is displayed with
>
> two such PSS reconstructions derived
>
> from two alternative TSI inputs. The
>
> figure shows excellent agreement between
>
> the 11-year PSS cycles and the cycles
>
> observed in the smoothed average
>
> global temperature data; a 22-year cycle
>
> component in the temperature also
>
> matches the 22-year PSS cycle very well.
>
> In particular, since 2002 the temperature
>
> data present a global cooling, not a
>
> warming! This cooling seems to have
>
> been induced by decreased solar activity
>
> from the 2001 maximum to the 2007
>
> minimum as depicted in two distinct
>
> TSI reconstructions.
>
> Thus the average global temperature
>
> record presents secular patterns of 22-
>
> and 11-year cycles and a short timescale
>
> fluctuation signature (with apparent
>
> inverse power-law statistics), both
>
> of which appear to be induced by solar
>
> dynamics. The same patterns are poorly
>
> reproduced by present-day GCMs and
>
> are dismissively interpreted as internal
>
> variability (noise) of climate. The nonequilibrium
>
> thermodynamic models
>
> we used suggest that the Sun is influencing
>
> climate significantly more than
>
> the IPCC re****t claims. If climate is as
>
> sensitive to solar changes as the above
>
> phenomenological findings suggest,
>
> the current anthropogenic contribution
>
> to global warming is significantly overestimated.
>
> We estimate that the Sun
>
> could account for as much as 69% of the
>
> increase in Earth's average temperature,
>
> depending on the TSI reconstruction
>
> used.5 Furthermore, if the Sun does
>
> cool off, as some solar forecasts predict
>
> will happen over the next few decades,
>
> that cooling could stabilize Earth's climate
>
> and avoid the catastrophic consequences
>
> predicted in the IPCC re****t.
>
> The authors thank the Army Research Office
>
> for research sup****t and for grant W911NF-
>
> 06-1-0323.
>
> References
>
> 1. Intergovernmental Panel on Climate
>
> Change, Climate Change 2007: The Physical
>
> Science Basis, Cambridge U. Press, New
>
> York (2007). Available athttp://ipccwg1.
>
> ucar.edu/wg1/wg1-re****t.html.
>
> 2. N. Scafetta, B. J. West, Phys. Rev. Lett. 90,
>
> 248701 (2003).
>
> 3. P. Allegrini, M. Bologna, P. Grigolini, B. J.
>
> West, Phys. Rev. Lett. 99, 010603 (2007); G.
>
> Aquino, P. Grigolini, B. J. West, Europhys.
>
> Lett. 80, 10002 (2007).
>
> 4. S. E. Schwartz, J. Geophs. Res. 112, D24S05
>
> (2007).
>
> 5. N. Scafetta, B. J. West, J. Geophys. Res. 112,
>
> D24S03 (2007).
>
> www.physicstoday.org
They claim that El Nina is causing all the cooling
They claim that CO2 is rising faster than ever
but the official CO2 data stops in 2004. Is that because
the CO2 hasn't risen as fast as it theoretically should ?
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