SOLAR ACTIVITY:

A DOMINANT FACTOR IN CLIMATE
DYNAMICS

by

Dr Theodor
Landscheidt

Schroeter Institute for Research in
Cycles of Solar Activity

Nova Scotia, Canada

1. “Solar Constant” Variations in the 11-Year Sunspot Cycle and
Climatic Effects

Atmospheric circulation, the cause of
weather, is driven by the sun’s energy.  Climate is the integral of
weather over periods of more than a year. This integral also depends on the
flux of solar energy. The same applies to variations in the energy flux caused
by the sun’s varying activity. Satellite data show that the “solar constant”
S is variable. The solar irradiance decreased from the sunspot
maximum 1979 to the minimum 1986, increased again on the way to the next
maximum in the 11-year sunspot cycle, and decreased anew in the descending
phase. This came as a surprise as it is plausible that the dark sunspots with
their strong magnetic fields impede the free flux of energy from the sun’s
interior to the outside. Yet P. V. Foukal and J.
Lean [22] have shown
that bright faculae in the vicinity of sunspots increase even more than
sunspots when the activity grows stronger, so that an irradiance surplus is
established.

IPCC scientists hold that the
corresponding variation in the solar constant (Delta S) is
smaller than 0.1% and has no impact on climate that could count in comparison
with the greenhouse effect [94]. Yet they fail to appreciate that quotes of 0.1% in the
literature refer to the absolute amplitude of the sinusoidal variation in the
solar constant, not the whole change from minimum to maximum, or from maximum
to minimum [25, 32, 39]. Figure
1 after C. Fröhlich [25] shows this distinctly. The
data at the top of the figure, designated by `HF', represent NIMBUS-7
measurements. The smoothed curve shows the 81-day running average related to
the interval of three solar rotations of 27days. The horizontal axis indicates
the investigated period, above in years, below in days since the first day of
1980. The vertical axis measures the solar constant S in
W/m2. The scale in the middle of Figure 1
indicates the range of 0.1%. When this scale is taken to measure the variation
in the smoothed curve from the sunspot maximum 1979 to the minimum in 1986,
the result is Delta S approximately equal to -
0.22%.   IPCC scientists cannot object to this higher value on
the grounds that it is not a common practice to assess the total variation in
such a way. They proceed equally by relating the rise in global temperature to
the minimum at the end of the 19th century and not to the long-term
temperature mean.

According to satellite measurements,
the mean value of the solar constant is S = 1367
W/m2.   0.22% of this amount of
energy equals 3 W/m2 . This result may
also be read from Figure 1. The maximum of the smoothed curve is at 1374.2
W/m2 and the minimum at 1371.2 W/m2 . The variation of 0.22% does not affect climate in its
entirety. The solar constant defines the amount of energy which just reaches
the outside of the earth’s atmosphere.  30% of this energy is not
absorbed by the atmosphere, but reflected. Furthermore, it has to be taken
into account that the irradiated sectional area of the earth constitutes only
a quarter of the surface to which this thermal energy has to be distributed.
So there is only 239 W/m2 available to
heat the atmosphere. Consequently, the variation of 3 W/m2 has only a climate effect of 0.53 W/m2 . How this affects global temperature depends on
the general circulation model used to assess the climate sensitivity.
C. Fröhlich [25] proceeds from a value
between 0.3° and 1.4° C / W/m2 . When we
choose the mean value 0.85° C / W/m2 to avoid
an overestimation, the climate effect of 0.53 W/m2 yields a temperature effect of 0.45° C. The
chosen mean value lies within the range given in the literature
[19, 31, 33, 82, 87, 89, 115]. Even if a four times longer smoothing interval is chosen as in
Figure 1, the variation of the solar constant reaches 2.2 W/m2 [74] with a temperature effect of 0.33° C.

Variations in global temperature of
0.45° or 0.33° C in the course of seven years cannot be considered negligible.
This all the more so as the observed rise of temperature during the last
hundred years amounts to merely 0.4° C. From the value 0.5° C, quoted
in the literature, 0.1°C has to be subtracted because it is due to urban
warming that causes a spurious rise in global temperature [39]. Observed climate data, which
follow the rhythm of the 11-year sunspot cycle, indicate that the effect of
irradiance variations on the atmosphere is enhanced by positive feed-back
processes or stochastic resonance. This form of resonance involves the
cooperative interplay of random and periodic stimuli. Noise can improve the
response to small periodic or quasiperiodic signals so that the small input is
able to entrain large scale fluctuations [80,
116]. This effect is strongest in nonlinear
systems with a high level of noise.

The atmosphere meets these conditions.
K. Labitzke and H. van Loon [51] have discovered a
statistically significant connection between temperature-dependent 30-hP
heights in the stratosphere and extrema in the 11-year sunspot cycle, which
involves the troposphere and is strongest in special geographical regions. It
is an indication of feed-back or resonance amplification that the temperature
difference in the stratosphere between minimum and maximum of the 11-year
cycle reaches 1.8° C and in the troposphere still 0.9° C [50]. In the Subtropic troposphere this
difference even amounts to 2° C [70]. Northern and Southern Hemisphere show such sunspot related
temperature patterns in a mirror-symmetric way. The geographic distribution of
the temperature effect corroborates the hypothesis that a modulation of Hadley
cell circulation is involved [95]. Experiments with models have shown that winds in the lower
stratosphere can have an impact on circulation in the troposphere
[84]. Strong
temperature variations following the course of the 11-year sunspot cycle were
not only observed in recent decades. According to M. Stuiver, P. M. Grootes, and T. F. Braziunas [109] the GISP delta 18O climate record shows a close correlation with the
11-year sunspot cycle for hundreds of years. This data point to a regional
temperature variation of 2.6° C following the sunspot
rhythm.

2. Gleissberg
Cycle of Solar Activity and Climate Change

As to climate, seven years is a rather
short interval. A climatic effect caused by total irradiance variations
becomes more effective when its impact lasts longer. The Milankovitch theory
in its modern form shows that a change of 0.1% effective during a very
long interval can release a real ice-age [49]. So it may be expected that the
90-year Gleissberg cycle of sunspot activity, which modulates the intensity of
the 11-year cycle, possesses a considerable potential to accumulate an
effective surplus of irradiance, or to induce a steadily decreasing level of
radiant flux density, particularly since the Gleissberg cycle can reach a
length of 120 years [58]. Figure
2 after J. A. Eddy [17] shows the strong intensity
variations in the 11-year sunspot cycle. When we connect the peaks by an
enveloping curve, minima in the Gleissberg cycle emerge around the years
1670 (Maunder minimum), 1810, and 1895. They are marked
by black arrows. Each of these secular sunspot minima coincided with cool
climate in the Northern Hemisphere. The deeper the level of solar activity
fell, the deeper sank the temperatures.

In Figure 3 after
E. Friis-Christensen and K. Lassen [24] this connection becomes
quite evident. The thick curve shows the Northern Hemisphere surface
temperature (right scale), while the thin line represents the length of the
11-year sunspot cycle (left scale) covering the years 1865 to 1985.
Occasionally, this impressive synchronism is objected to on the grounds that
the length of the cycle should be of no import, as only the intensity of
sunspot activity would count in a potential climate effect. Yet the
length of the 11-year cycle is a measure of its intensity. Short cycles
generate high sunspot maxima, wheras long cycles are characterized by weaker
sunspot activity. Friis-Christensen and Lassen have shown that the close
correlation extends back to the 16th century [68]. C. J.
Butler [10]
corroborated these results when he investigated English temperature data since
1796. Together with the results elaborated by Labitzke and van Loon this is an
indication that the solar influence on climate is considerably stronger than
IPCC scientists assume.

Those scientists who spread anxiety in
the eighties by predicting climate catastrophees cannot plead that at this
time there were not any publications pointing to a relation between solar
activity and climate that had to be taken seriously. The relationship in Figure 4 was presented
at the international climate symposium “Weather and Climate Responses to
Solar Variations” in Boulder, Colorado, as early as 1982
[55]. The plot shows a
temperature time series after H. H. Lamb and C. D. Schönwiese at the bottom,
radiocarbon data after J. E. Eddy [16] — proxy data reflecting
solar activity — covering the interval 1000 to 1950 at the top, and in the
middle data I had derived from a semiquantitative model of cyclic solar
activity. S and M mark the Spoerer minimum and the Maunder minimum of sunspot
activity, while O points to the medieval climate optimum which coincided with
very strong solar activity. The synchronism of these three time series,
covering 950 years, extends the connection elaborated by Friis-Christensen and
Lassen 550 years farther back into the past and opens a possibility of
long-range forecasts, as the data in the second curve are based on
calculations that can be extended far into the future. On this basis, I
forecasted, in 1982, that we should expect declining temperatures after 1990
and probably a new Little Ice Age around 2030. In further papers I specified
this prediction [58, 59, 63]. I also expected considerably weaker sunspot activity after
1990. The slowly ascending new sunspot cycle, which started in May 1996, seems
to follow the predicted trend.

When satellite observations had
established that the solar constant is variable, phenomenological regression
models were developed which assess the variations in irradiance in past
decades and centuries. The model developed by D. V.
Hoyt and K. H. Schatten [39], shown in Figure 5, is based on
proxy data related to secular changes in the convective energy transport or
the convective velocities in the sun. They include the solar cycle length, the
equatorial solar rotation rate, and sunspot structure. This solar-irradiance
model has only two parameters: the amplitude of variations of the 11-year
cycle and the Gleissberg cycle. The thick curve in Figure 5 shows the output
of the model. The corresponding vertical axis on the left measures the
irradiance in W/m2.  The dashed curve
represents the smoothed annual mean Northern Hemisphere temperature variations
(right scale) for 1700 – 1879 from B. S. Groveman
and H. E. Landsberg [28], and for 1880 to the present from J.
E. Hansen and S. Lebedeff [30]. The two curves show a close correlation that points to a
strong link between solar activity and climate.

As direct measurements of Delta
S are not available before 1978, it is important that observations
of the surface magnetism of solar type stars have yielded variations in
irradiance up to 0.6% [84]. Variations of this order in the sun’s activity could explain
climate features like the “Little Ice Age”, especially if it is assumed that
the general magnetic network, which covers the photospheric surface even in a
sunspot minimum, vanishes during activity lulls of the Maunder minimum type.
Every fourth of the observed stars is in a state comparable to the Maunder
minimum of the sun [84]. One star — HD 3651 — was even observed just in transition
between the cyclic and the Maunder minimum phase. It showed periodic behaviour
for about 12 years and then stopped fluctuating as its surface activity
dropped to very low levels [84]. This indicates that the sun has a much stronger potential of
irradiance variation than assumed. The satellite observations since 1978 cover
only a small part of the sun’s range of variability. S. Baliunas and W. Soon [2] have shown in addition that
short star cycles produce stronger magnetic activy and irradiance than long
cycles. This confirms the results published by Gleissberg, FriisChristensen
and Lassen.

When measuring the equivalent width of
the high excitation photospheric line of C 5380 Å in the solar irradiance
spectrum since 1978, W. Livingston discovered that it increased in strength by
0.081 mÅ within 12 years. This implies a temperature increase of 4.6° K, an
order of magnitude greater than the variation observed by satellites. Since
change in the intensity of absorption lines points to change in the
irradiance, D. V. Hoyt and K. H. Schatten [39]
assume that there are components of varying irradiance beyond
sunspots, faculae, and the magnetic network which are not yet known. A
candidate could be those recently discovered huge streams of electronically
charged plasma flowing beneath the surface of the sun, which ring the solar
poles at about 75° latitude and resemble jet streams in the earth’s
atmosphere. There is also plasma flow similar to the earth’s trade winds
[104]. As these plasma
streams move about 10% faster than their surroundings, the resulting shear
induces concentrations in the magnetic fields “frozen” in the plasma which
lead to stronger magnetic activity. It is to be expected that research into
these features will result in a new index and a better explanation of solar
activity. The steady increase in the intensity of the line C 5380 Å over 12
years, observed by Livingston, is independent of the 11-year cycle. It seems
to point to a longer cycle of solar activity. Is this the Gleissberg cycle, or
a new yet unknown cycle?

3. Variations in the
Sun’s Ultraviolet Radiation and Climate Models

Change in the ultraviolet radiation of
the sun is much greater than in the range of visible radiation. The
ultraviolet range of the spectrum lies between 100 Å and 3800 Å. Wavelengths
below 1500 Å are called extreme ultraviolet (EUV). The variation in radiation
between extrema of the 11-year sunspot cycle reaches 35% in the EUV- range
[119], 20% at 1500 Å
[21], and 7% around
2500 Å [34,97]. At
wavelengths above 2500 Å, the variation reaches still 2% [21]. At the time of energetic solar
eruptions, the UV-radiation increases by 16%. At a sunspot maximum the
EUV-radiation raises the temperature in the Ionosphere by 300% in relation to
the minimum [21]. Yet
most important is that the UV-radiation below 2900 Å is completely absorbed by
ozone in the stratosphere. The resultant rise in temperature is augmented by
positive feed-back, as the UV-radiation also generates new ozone. Satellite
observations show that the ozone content grows by 2% from sunspot minimum to
maximum [113]. D. Rind
and J. Overpeck are working on a model which explains how the rising
temperature in the stratosphere influences the circulation in the troposphere.
J. D. Haigh [29] has already assessed this
effect in quantitative terms and shows that temperature in the Subtropics and
North Atlantic storm tracks are especially affected.

Variations in radiation are not the
the sun’s only way to influence climate. Between energetic solar eruptions and
galactic cosmic radiation modulated by the solar wind on the one hand and
electric parameters of the atmosphere on the other, exist couplings, the
strength of which varies by 10% in the course of days, years, and even decades
[113]. The most
important change is to be found in the downward air-earth current density,
which flows between the ionosphere and the surface. R. Markson and M. Muir [71] have shown how this affects
the thunderstorm activity, while B. A. Tinsley
[113] assumes that
electrically induced changes in the microphysics of clouds (electrofreezing)
enhance ice nucleation and formation of clouds. These approaches have the
advantage to be independent of dynamic coupling between different layers of
the atmosphere, since these variations affect the whole atmosphere. Therefore,
IPCC scientists who allege that there are not any physical explanations of a
solar impact on climate change must be unaware of the relevant literature.

4. Cosmic Radiation, Solar Wind, and Global Cloud
Coverage

The most convincing argument yet,
supporting a strong impact of the sun’s activity on climate change, is a
direct connection between cloud coverage and cosmic rays, discovered by
H. Svensmark and E. Friis-Christensen [111] in 1996. It is shown in
Figure 6. Clouds
have a hundred times stronger effect on weather and climate than carbon
dioxide in the atmosphere. Even if the atmosphere’s CO2
content doubled, its effect would be cancelled out if the cloud cover expanded
by 1%, as shown by H. E. Landsberg [53]. Svensmark’s and
Friis-Christensen’s result is therefore of great importance. The thin curve in
Figure 6 presents the monthly mean counting rates of neutrons measured by the
ground-based monitor in Climax, Colorado (right scale). This is an indirect
measure of the strength of galactic and solar cosmic rays. The thick curve
plots the 12-month running average of the global cloud cover expressed as
change in percent (left scale). It is based on homogeneous observations made
by geostationary satellites over the oceans. The two curves show a close
correlation. The correlation coefficient is
r =
0.95.

Short-range variations in the
intensity of cosmic rays, caused by energetic solar eruptions, have the same
effect, though shorter. The plot shows that strong cosmic rays go along with a
larger cloud cover, whereas weak cosmic rays shrink the cloud cover. The
global cloud coverage diminished from its peak at the end of 1986 to its
bottom in the middle of 1990 by more than 3%. According to observations
by V. Ramanathan, B. R. Barkstrom, and E. F.
Harrison [91], clouds
have a net cooling effect of -17 W/m2 .
Svensmark and Friis-Christensen [111] conclude from the
diminution of this cooling effect between 1986 and 1990 that the solar
irradiance has increased by about 1.5 W/m2 within these three and a half years. A change of
this order is quite remarkable, since the total radiative forcing by carbon
dioxide accumulated since 1750 has been estimated by the IPCC not to go beyond
1.5 W/m2 . This means that cosmic rays,
strongly modulated by solar activity, achieve an effect within three and a
half years for which the accumulation of carbon dioxide in the atmosphere
needs centuries. This shows clearly to what extent the greenhouse effect has
been overestimated in comparison with the solar contribution to climate
change, which turns out to be the most important factor.

There is also a physical explanation
of the effect: the secondary ions produced by the cosmic rays serve as
condensation nuclei with hygroscopic properties that enhance the formation of
clouds [4, 15, 23].
Meanwhile, H. Svensmark [112] has extended his
investigation that now covers the interval 1980 to 1996. As before, the
correlation between cloud cover and cosmic rays is very close. Indirect
measurements of the intensity of cosmic rays, which register myons instead of
neutrons, go back to 1937. When H. Svensmark
[112] compared these
data with global temperature in the Northern Hemisphere, he again found a
strong correlation which indicates that the connection between cosmic rays,
cloud cover, and global temperature is real.

The primary cause of the solar
modulation of cosmic rays is not the level of sunspot activity, but the
varying strength of the solar wind. This supersonic outflow of plasma
originates in the very hot corona of the sun and carries ionized particles and
magnetic field lines from the sun. While it is expanding towards the boundary
of the solar system, cosmic ray particles interacting with it lose energy.
When the solar wind blows heavily, cosmic rays are weak, and when the solar
wind is in a lull, cosmic rays become strong. The highest velocities in the
solar wind are caused by energetic solar eruptions and coronal holes. Strong
eruptions (flares and eruptive prominences) avoid sunspot maxima and even
occur close to sunspot minima. So sunspots are not a good indicator of solar
wind strength [65]. As
cosmic rays, which have such a strong impact on cloud cover, are strongly
modulated by eruptional features of the sun’s activity, the solar contribution
to climate change can no longer be considered negligible. This is all the more
so as the already described changes in irradiance have an additional
effect.

D. Rind and J. Overpeck [93] have shown that at least
half of the rise in temperature since the end of the Little Ice Age can be
attributed to the parallel rise in the sun’s irradiance. D. Hoyt and K. H. Schatten [39] judge their elaborate
results as follows: “From the record, we
believe the sun plays a major role in natural secular climatic changes on time
scales of decades to centuries.".  E. S. Posmentier, W. H. Soon, and S. L. Baliunas [88, 107] eventually derive from
a model based on the same solar factors as in the Hoyt-Schatten-model that
78% of the rise in temperature between 1885 and 1987 can be explained by
the sun’s varying irradiance. An additional statistical experiment
corroborates this result, though it omits the Svensmark effect and other
solar-terrestrial relationships which are independent from irradiance. There
is not much room left for the anthropogenic greenhouse effect. H. N. Priem [90] aptly remarks:

“Recent studies show that solar
variability rather than changing CO pressure is an important, probably the
dominant climate forcing factor ... The current and anticipated fleet of
spacecraft devoted to the study of solar and solar-terrestrial physics will
therefore pobably prove to have more bearing on the understanding and
forecasting of climate change than the orchestrated assessments by
politically motivated international panels biased towards global warming
exclusively by the enhanced greenhouse effect.”

The discovery by Svensmark and
Friis-Christensen highlights the IPCC objection (that exogenic factors are
energetically too weak to have an impact on global temperature), as pointing
in the wrong direction. Primary cosmic rays, which regulate cloud coverage,
inject a total energy into the atmosphere equal to the intensity of starlight
in the night skies [23]. J. G. Roederer [95] comes closer to reality
with his remark:

“The energy argument, however, is
not valid for highly nonlinear, complex systems such as the coupled
atmosphere-ocean-cryosphere-biosphere. It is well known that complex systems
can behave chaotically, i.e. follow very different paths after the smallest
change in initial or boundary conditions, or in response to the smallest
perturbation. In a highly nonlinear system with large reservoirs of latent
energy such as the atmosphere-ocean-biosphere, global redistributions of
energy can be triggered by very small inputs, a process that depends far
more on their spatial and temporal pattern than on their
magnitude.”

5. Failure of
Climate Predictions by IPCC Scientists

Precise forecasts that prove correct
are a sharp criterion for efficient science. The protagonists of global
warming remain empty-handed in this respect in spite of great material and
personal expense. In the eighties S. Schneider from the National Center for
Atmospheric Research in Boulder, Colorado, predicted in his book “Global
Warming” a huge jump in temperature, polar ice melting away, seas
surging across the land, famine on an epidemic scale, and ecosystem collapse.
Today this is no longer taken seriously. Yet other climatologists, too, made
forecasts in the eighties they no longer maintain. C. D. Schönwiese [99], usually critical and cautious in his statements, still
predicted in 1987 a 4.5° C rise in temperature until 2030, though only as an
upper limit. He thought that the sea level in the German Bay could rise by 1.5
m till 2040 and in the ocean around India even 2 to 3 m. A projection of his
temperature forecast yields 11.8° C for the year 2100. At the climate
conference in Villach in 1985 similar predictions were presented to the
public. The IPCC still predicted in 1990 and 1992 that global temperature
would rise 1.9° - 5.2° C until 2100 [100] and thought that a rise in sea
level by 1.10 m was possible [36].

All these predictions have turned out
to be untenable. It is accepted that global temperature has risen by 0.5°
C in the last hundred years. Yet during the last fifty years the
temperature has remained approximately at the same level, even though 70% of
the anthropgenic carbon dioxide contribution was injected into the atmosphere
during this time. From 1940 to 1970 the temperature fell, and according to
satellitite data available since 1979, which are in good accord with balloon
data [27], the trend in
the lower troposphere has remained at -0.06° C per decade. The IPCC
prediction made in 1992 proved so exaggerated that it had to be adjusted to
reality three years later by reducing the rise range to 1° - 3.5° C by 2100.
As to sea level rise, the IPCC meanwhile acknowledges (in accordance with a
consensus in the specialized literature [3]) that sea level has risen by merely
18 cm in the last hundred years. According to M. Baltuck et al. [3] it is very probable that the rising sea level is due to natural
causes and not to man’s contribution to the greenhouse
effect.

The discrepancy between IPCC forecasts
and observed data stands out very clearly as to temperatures in the polar
regions. The general circulation models, presented by the IPCC in 1990,
predict for the regions near the poles in a CO2 doubling
scenario a rise in temperature of more than 12° C [13]. If this were true, in the last 40
years with their steep increase in CO2 concentration, a
warming trend with a temperature rise of several °C should have emerged. The
opposite is true [20].
A joint investigation by American, Russian and Canadian scientists shows that
the surface temperatures in the Arctic region observed between 1950 and 1990
are going down. They fell 4.4° C in winter and 5° C in autumn
[43]. Satellite data
too, available since 1979, do not indicate rising temperatures [105]. This agrees with data published
by the world Glacier Monitoring Network in Zurich, according to which
55% of the glaciers in high latitudes are advancing compared with 5%
around 1950.

The main reason of the incompatibility of
IPCC forecasts and observed data is the lacking suitability of the general
circulation models (GCM) for the purpose of long-range climate predictions.
GCMs are an excellent tool for research into data connections, the physics of
which is just beginning to emerge. In such cases quantitative and qualitative
aspects of the data pattern may be investigated which develop when the
determining variables are changed. The point here is learning, not
predicting. The development in the immensely complex nonlinear climate
system with feed-back coupling of atmosphere, ocean, cryosphere, and biosphere
may be forecast, if at all, only for rather short intervals.

GCMs are based on the same type of
nonlinear differential equations which induced E. N. Lorenz in 1961 to
acknowledge that long-range weather predictions are impossible because of the
atmosphere’s extreme sensitivity to initial conditions. It is inconceivable
that the Butterfly Effect should disappear when the prediction interval
of a few days is extended to decades and centuries. Some climatologists
concede that there is a problem. C. D. Schönwiese
[100] remarks in this
respect:

“Consequently we should conclude
that climatic change cannot be predicted.
It is correct that the varied
and complex processes in the atmosphere cannot be predicted beyond the
theoretical limit of a month via step by step calculations in circulation
models, neither today, nor in the future. Yet there is the possibility of a
conditioned forecast. The condition is that a special factor within the
complex cause-and effect relationship is so strong in its effect that it
clearly dominates all other factors. In addition, the behaviour of that
single dominant causal factor must be predictable with certainty or a high
degree of probability.”

The dominant causal factor, meant
here, is the anthropogenic greenhouse effect. However, there is no convincing
evidence that this is an outstanding factor that clearly dominates all other
factors which could have an influence on climate. The results presented here
indicate clearly that the sun’s varying activity is at least a non-negligible
factor and probably the really dominant one. Furthermore, the greenhouse
effect is contrary to Schönwiese’s conditions in being not predictable to a
high degree of probability, as the inadequate performance of IPCC forecasts
shows. In addition, it is quite uncertain when doubling of the atmosphere’s
CO2 content will occur. In the eighties it was surmised
that doubling would happen as early as 2030. Now J.
P. Peixoto and A. H. Oort [86] expect doubling in 2200. Another contentious point is how long
CO2 will stay in the atmosphere, several hundred years,
or only five years? New results by P. Dietze and T. V. Segalstad
show that shorter residence times are much more probable than the extended
ones. Moreover, J. Barrett has shown that all the energy that can be absorbed
by the atmosphere is already being absorbed by the lower atmosphere (water,
aerosol, and CO2 ) under present conditions. Finally, it
has been assumed in the GCMs that the planet’s population, responsible for the
anthropogenic CO2 contribution, will grow to 11.5 billion
people by the end of the next century. The recent statistical survey published
by the UN, “World Population Prospects: The 1996 Revision”,
shows clearly that the growth expected by the IPCC is utopian and will have to
be revised sharply downward, thus reducing the imagined threat dramatically.
In 1950 - 1955 the global total fertility rate (the world average number of
children born per woman per lifetime) was five, explosively above the
replacement rate of 2.1 children. In 1975 - 1980 the fertility rate sank to
four. At present it has reached 2.8 and continues to sink. In Europe the rate
has fallen by 20% during the last ten years and is at 1.4 now. The same
applies for Russia and Japan. The developing countries are no exception. In
Bangladesh the fertility rate has fallen from 6.2 to 3.4 in just ten years. So
the CO2 output will be much lower than that estimated in
the GCM calculations.

When those equations that are thought
to represent the climate system are subjected to a first integration with the
anthropogenic forcing kept constant so that the result can be compared with a
second integration based on increasing CO2 forcing, the
outcome can be considered convincing only if the differential equations
represent the physics of the climate system exactly and completely. Yet this
condition is far from being fulfilled. Not only do we not know enough about a
wealth of details of complex feed-back problems [114], but there is also a fundamental
lack of data. In addition there are technical and mathematical difficulties.
J. P. Peixoto and A. H. Oort [86]
comment aptly:

“The integration of a fully coupled
model including the atmosphere, oceans, land, and cryosphere with such
different internal time scales poses almost insurmountable difficulties in
reaching a final solution, even if all interacting processes were completely
understood.”

A fatal flaw however is that tiny
deviations from the ideal initial conditions may lead to quite different
courses in the development of climate. C.
Wiin-Christensen and A. Wiin-Nielsen [117] have rightly pointed out
that the resulting limited predictability is insurmountable as it is linked to
the given nonlinearity of the differential equations.

6. Cycles in the
Sun’s Oscillation Affect Sunspots and Climate

The IPCC holds:

“Solar variability over the next 50
years will not induce a prolonged forcing significant in comparison with the
effect of increasing CO concentrations.”

However, if, contrary to the IPCC’s
attitude, the sun is taken seriously as a dominant factor in climate change,
this opens up a possibility to predict climate features correctly without any
support by supercomputers. A string of examples will be presented. The chaotic
character of weather and climate does not stand in the way of such
predictions. Sensitive dependance on initial conditions is only valid with
regard to processes within the climate system. E. N. Lorenz has stressed that
only non-periodic systems are plagued by limited predictability. External
periodic or quasiperiodic systems can positively force their rhythm on the
climate system. This is not only the case with the periodic change of day and
night and the Milankovitch cycle, but also with variations in solar energy
output as far as they are periodic or quasiperiodic. The 11-year sunspot cycle
meets these conditions, but plays no predominant role in the practice of
predictions. Most important are solar cycles which are without exception
related to the sun’s fundamental oscillation about the center of mass of the
solar system and form a fractal into which cycles of different length, but
similar function are integrated. The solar dynamo theory developed by H.
Babcock, the first still rudimental theory of sunspot activity, starts from
the premise that the dynamics of the magnetic sunspot cycle is driven by the
sun’s rotation. Yet this theory only takes into account the sun’s spin
momentum, related to its rotation on its axis, but not its orbital angular
momentum linked to its very irregular oscillation about the center of mass of
the solar system (CM).

Figure 7 shows this
fundamental motion, described by Newton [85] three centuries ago. It is
regulated by the distribution of the masses of the giant planets Jupiter,
Saturn, Uranus, and Neptune in space. The plot shows the relative ecliptic
positions of the center of mass (small circles) and the sun’s center (cross)
for the years 1945 to 1995 in a heliocentric coordinate system. The large
solid circle marks the sun’s surface. Most of the time, CM is to be found
outside of the sun’s body. Wide oscillations with distances up to 2.2 solar
radii between the two centers are followed by narrow orbits which may result
in close encounters of the centers as in 1951 and 1990. The contribution of
the sun’s orbital angular momentum to its total angular momentum is not
negligible. It can reach 25% of the spin momentum [60]. The orbital angular momentum
varies from -0.1 x 1047 to 4.3 x 1047 g cm2 s-1 , or reversely, which is more than a forty-fold
increase or decrease. Thus it is conceivable that these variations are related
to varying phenomena in the sun’s activity, especially if it is considered
that the sun’s angular momentum plays an important role in the dynamo theory
of the sun’s magnetic activity.

Variations of more than 7% in the
sun’s equatorial rotational velocity, going along with variations in solar
activity, were observed at irregular intervals [ 54,
56]. This could be explained if there were
transfer of angular momentum from the sun’s orbit to the spin on its axis. I
have been proposing such spin-orbit coupling for two decades [56, 57]. Part of the coupling could
result from the sun’s motion through its own magnetic fields. As R. H. Dicke [14] has shown, the low corona can act as a brake on the sun’s
surface. The giant planets,which regulate the sun’s motion about CM, carry
more than 99% of the angular momentum in the solar system, while the sun is
confined to less than 1%. So there is a high potential of angular momentum
that can be transferred from the outer planets to the revolving sun and
eventually to the spinning sun.

The dynamics of the sun’s motion about
the center of mass can be defined quantitatively by the change in its orbital
angular momentum. The rate of change is usually measured by derivatives. In
some respects the running variance yields more informative results. It applies
the well-known smoothing of two, three, or more consecutive readings to
variance, the square of the standard deviation. Consecutive values of the
running variance draw attention to the variation in variability and accentuate
dynamical processes [98]. Figure
8 displays the 9-year running variance of the orbital angular momentum
for the years 730 to 1075. The 9-year running variance has been chosen because
the narrow orbits with a stronger curvature have just this cycle length and
yield interesting results. Surprisingly, the pattern in Figure 8 is shaped by
a five-fold symmetry. For the sake of simplicity I call the features “big
hands” and “big fingers”. They emerge in a similar way in past and future
millenia. Their five-fold symmetry is not their only interesting quality. They
are linked to cycles which play an important part in solar-terrestrial
relations. The big hand cycle has a length of 178.8 years. P. D. Jose [41] has shown in his pioneering computer analysis of the sun’s
motion that a cycle of this length appears in the sunspot data. The strongest
cycle discovered by W. Dansgaard et al. [63] in the oxygen isotope
profile in the Camp Century ice core has a length of 181 years, close to 178.8
years. This points to a relationship with climate. It is conspicuous that the
Gleissberg cycle is just half as long as the big hand cycle. J. F. W. Negendank, A. Brauer, and B. Zolitschka [83] have found a cycle of 88
years in warves of the crater lake of Holzmaar which cover 13,000 years. The
length of the cycle of a half big hand is 89.4 years. This points again to a
connection with climate.

7. Cycles of 36
Years in Solar Activity and Climate

Cycles of big fingers have a mean
length of 35.8 years (178.8 years [big hand] / 5 = 35.76 years [big fingers]).
They are closely connected with solar activity. They coincide with maxima and
minima in the Gleissberg cycle and open up the possibility of predicting these
crucial phases many years ahead [62,
63]. As will be shown below, they also define
the length of the 22.1-year magnetic cycle of sunspot activity (Hale cycle).
As far as climatic change is concerned, cycles of a length of 36 years are not
new. Francis Bacon [102] has already pointed to a
cycle in the Netherlands with a length of 35 to 40 years with cool and wet
phases followed by warm and dry periods. E.
Brückner [7] discovered
this cycle again in 1887. He demonstrated that varied climatic phenomena in
different regions of the world show synchronized phases in a cycle of 33 to 37
years. He had already surmised in those days a connection with the sun’s
activity. H. W. Clough [11,
12] followed this suggestion and found
the Brückner cycle not only in 12 meteorological variables, but also in
sunspots and especially in variations in the length of the 11-year sunspot
cycle. D. V. Hoyt and K. H. Schatten [39] think that the reality of
the cycle is confirmed by Scandinavian tree ring data which show its rhythm
over hundreds of years. With regard to Brückner’s supposition of a connection
with the sun’s activity, they ask which index of solar activity would conform
with a 36-year cycle. The results presented here answer this
question.

Figure 9 after P. D. Jones [40] shows the time series 1850 to 1987 of the annual-mean surface
air temperature averaged over the Northern Hemisphere, expressed as departures
in °C from the reference period 1951 to 1970. The arrows mark the start phases
of big finger cycles (BFS) that fall in the data range. The triangle at the
top of the plot points to the start phase in 1933 of a big hand cycle (BHS).
BFSs 1867, 1901, and 1933 coincide with outstanding temperature maxima in the
smoothed curve. BFS 1968, however, indicates the bottom of a downtrend that
began after BHS 1933. Obviously, this is due to a phase reversal in the BFS
pattern. Contrary to statistical investigations, the semi-quantitative model
presented here can give an explanation that seems to solve the problem of
sudden phase jumps in solar-terrestrial cycles hitherto unpredictable and
unexplainable.

Experimentation with electrical and
mechanical control equipment shows that at nodal points, where the response of
the system is zero, the phase can shift by pi radians. The initial phase of a
big finger cycle is such a nodal point. Yet it is crucial that BFS 1933 is at
the same time the start of a big hand. Such nodal points higher up in the
hierarchy of the fractal of cycles derived from the sun’s motion about CM
induce phase reversals or other forms of instability in subordinate cycles.
This will be shown in a string of examples. The next BHS will be reached in
2111. So the new BFS rhythm is expected to hold for a long time. The epoch of
the coming BHS phase 2007 should go along with another bottom in the global
temperature.

Often the second harmonic of finger
cycles is as important as the fundamental. The thickness of Lake Saki varves
is related to local precipitation: the thickest warves ar linked to very wet
years and the thinnest varves to very dry years [101]. I could show that maxima in the
varve thickness are consistently correlated with cycles of half big fingers
with a mean length of 17.9 years. The analysis covers the years 700 to 1894,
nearly 12 centuries. A Monte Carlo model and Student’s t-test yielded t = 8.2
for 33 degrees of freedom. The null hypothesis of no connection between the
studied variables can be rejected at a high level of significance (P < 6
x10-7 ) [62].

BFSs represent minima of the running
variance in the sun’s orbital angular momentum. The maxima, too, have proven
relevant. I call them big finger tips (BFT). They appear in Figure 10 which shows
the Palmer Drought Index for the U.S.A. The vertical axis measures the
percentage of area covered by drought. The arrows designate consecutive epochs
of BFSs and BFTs. Prior to the big hand start 1933, indicated by an open
triangle, the starts of big fingers (S) coincided with drought maxima and the
tips (T) with minima. After BHS 1933 the correlation with the big finger
phases as such continued, but a phase reversal changed the rhythmic pattern.
Now BFTs coincided with drought peaks and BFSs with minima. The new rhythm has
been stable since 1933. There is a good chance that it will continue until the
next BHS in 2111. Farmers in the U.S.A. may expect wet climate around the next
BFS in 2007.

Yet, what is the meaning of those
black circles in Figure 10 which alternately go along with drought maxima and
minima and are also subjected to a phase reversal? They mark the Golden
section between BFSs and BFTs. The five-fold symmetry in the dynamics of the
sun’s oscillation about the center of mass of the solar system, visible in
Figure 8,
establishes a relationship between the sun’s motion and the Golden section, as
this remarkable proportion is closely related to the number 5 [45]. To show this intimate connection,
all of the corners of a regular pentagon (the fundamental geometrical
representation of the number five ) are connected by diagonals. A five-pointed
star emerges, a pentagram, the intersecting lines of which form a complex web
of Golden sections. Within this star a new pentagram appears that contains a
smaller star with further Golden section divisions, and so on, in an infinite
fractal sequence.

As illustrated in Figure 11, the Golden
section divides a frame structure like a line segment, a surface, a cycle, or
any other delimited feature so that the ratio of the whole to the larger part
(major) equals the ratio of the larger part to the smaller one (minor). Point
G represents the irrational Golden Number
G = 0.618... It divides the unit
height of the temple into major (0.618...) and minor (0.3819...). To find the
major of a line segment, a cycle etc., it has to be multiplied by 0.618.
Multiplication by 0.382 yields the minor. As the fundamental oscillation of
the sun about CM depends on the masses and the positions of the giant planets,
the relationship with the Golden section extends to the whole solar system.
A. N. Kolmogorov [47],
V. I. Arnol’d [1], and J. Moser [79] have proven theoretically,
that the stability of the solar system hinges on the Golden section. This is
crucial, as we know from publications by G. J.
Sussman and J. Wisdom [110] as well as J. Laskar [67] that the orbits of all
planets are chaotic. In my paper “The Cosmic Function of the Golden
Section” [64] I
have shown in practice how the Golden section, which stands for stability in
polar opposition to instability, keeps the chaotic planetary orbits stable.
The mean of the ratios of the perihelion distances of neighbouring planets
from Mercury to Pluto, including the mean radius vector of the planetoids,
turns out to be very close to the Golden number G. The difference between this
mean and G is as small as 0.002. Fivefold quantities have deep roots in
Nature. There are not four, but five physical forces. We merely have forgotten
that electromagnetism is composed of different forces. First Maxwell unified
electricity and magnetism and later on electromagnetism and the weak force was
unified to constitute the electro-weak force [44].

Figure 12
after R. Mogey
[78] presents a further
practical example, the Great Lake (Michigan-Huron) water levels. After BHS
1933, marked by a filled arrow, the deepest levels coincide with BFSs (S,
filled arrows) and the peak levels with BFTs (T, open arrows). A deep trough
in the data is to be expected around 2007 and a new peak level around 2025.
The flat triangles point to secondary peak levels, related to the minor 0.382
of the Golden section between BFS and BFT phases.

The Golden section has left its mark,
too, upon the 11-year sunspot cycle. Reliable data are available since 1750.
They show that the ascending part of the cycle has a mean length of 4.3 years
[73]. The mean cycle
length amounts to 11.05 years. The minor of the mean length falls at 4.2
years
(11.05 years × 0.382 = 4.22 years). This is close to 4.3 years. Thus,
the maximum of the 11-year cycle falls at the minor of the Golden section. The
descending wing of the cycle has the length of the major. This contributes to
the stabilization of solar activity which is characterized by phenomena
generated by instability.

Magnetic cycles of solar type stars
show the same structure shaped by the Golden section [64]. The histogram in Figure 13 after EOS
[18] shows the
distribution of higly energetic solar eruptions within the 11-year cycle. The
accents are set by the Golden section within the subcycles formed by the
ascending and descending part of the whole cycle. This pattern recurs in
terrestrial cycles. The three curves in Figure 14 after
H. H. Lamb [52] connect the 11-year sunspot
cycle with thunderstorm activity in central Europe. At the top of the plot,
consecutive sunspot minima and the maximum in between are marked by small
arrows. The upper curve presents for 1810 to 1934 the number of days with
thunderstorm activity in Kremsmünster, the curve in the middle for 1878 to
1934 the thunderstorm frequency in Vienna, and the curve at the bottom the
number of houses struck by lightning in Bavaria between 1833 and 1879. The
peaks in all of the curves fall at minor and major of the solar subcycles.
These Golden section phases are marked by open triangles.

The magnetic sunspot cycle of 22.1
years, also called the Hale cycle, is the true cycle of solar activity. Groups
of sunspots are usually composed of preceding and following spots with
different magnetic polarity. With the commencement of a new cycle the polarity
reverses. Thus, the original polarity is only restored every second 11-year
cycle. When the position of the major of the Golden section within a big
finger cycle is calculated, it falls just at the length of the Hale cycle
(35.76 years × 0.618 = 22.1 years). This helps to limit the instability which
is inherent in solar activity. In climate, the Hale cycle is a dominant
feature in the global record of marine air temperatures, consisting of
shipboard temperatures measured at night [9], in the detrended Central England
temperature record for 1700 to 1950 [72], and in the drought severity index
covering different areas of the Western United States [77]. The major of the Golden section
within the cycle of the big hand (178.8 years × 0.618 = 110.5 years) yields a
similar result. Japanese scientists found a cycle of just this length in
sunspots when they applied a frequency analysis to the data [120].

8. Cycles of “Small Fingers”: a Solid Basis for Predictions of
Solar Eruptions and Climate

A ubiquitous notion in present day science
is the term fractal coined by B. B. Mandelbrot. A fractal is a geometrical
shape whose complex structure is such that magnification or reduction by a
given factor reproduces the original object. Self-similarity on different
scales is a pre-eminent feature of fractals. The solar cycles derived from the
sun’s motion about the center of mass form such a fractal. The big fingers in
big hands contain small hands with small fingers (SF). This becomes apparent
by further amplification. Figure 15 shows the
3-year running variance of the sun’s orbital angular momentum. The circled
numbers at the top mark epochs of BFTs. Tips of small fingers (SFT) are
indicated by small numbers. Fat arrows and small triangles point to starts of
big and small fingers. The vertical dotted line marks the initial phase of a
big hand in 1933. The theoretical mean length of cycles of small fingers is

178.8 years / 5 / 5 = 7.2 years. Yet small fingers show a higher degree of
“morphological” anomalies. There are sometimes hands that have only three or
four fully developed fingers. There is a wider range of deviations from the
mean length of small finger cycles. However, all of these variations can be
computed and predicted.

The starts of the small finger cycle
(SFS) are of special importance. The sun’s orbital angular momentum L
reaches extrema in these phases and dL/dt becomes zero. In Figure 16 after
R. Howard [37] two such initial phases at
the end of 1967 and the beginning of 1970 are shown. They were initiated by
heliocentric conjunctions of Jupiter, by far the largest of the giant planets,
with the center of mass CM. The vertical axis measures the sun’s rotational
velocity. In both of these cases a striking jump in the sun’s rotation
occurred. In former decades this phenomenon, too, was observed [54]. As the sun’s rotation on its axis
and the sun’s activity are connected, it is not surprising that energetic
solar eruptions accumulate around SFSs, as I could show in a paper published
in 1976 [54]. This
relationship is so reliable that predictions can be based on it. My long-range
forecasts of strong solar eruptions and geomagnetic storms, covering six
years, achieved a prediction quality of 90% though such events occur at quite
irregular intervals. Out of 75 events from quantitatively defined categories,
68 occurred at the predicted time [57, 60,
61]. The outcome of the forecast experiment was
checked by the astronomers W. Gleissberg, J. Pfleiderer, and H. Wöhl as well
as the Space Environment Services Center in Boulder, Colorado. The very strong
geomagnetic storms in 1982 and around 1990 were also correctly predicted
several years before the event [56,
60].

Forecasts of energetic solar eruptions
are of importance for weather and climate too, as they enhance the solar wind
and weaken the galactic cosmic radiation, which according to Svensmark and
Friis-Christensen have a strong impact on cloud coverage. So it is no longer
inexplicable that I correctly predicted at an international climate symposium
in Boulder, three years before the event, that the Sahelian drought would end
in 1985 [55].

Figure 17
shows how closely cycles of small fingers
and energetic solar eruptions are connected. The plot presents the
distribution of all X-ray eruptions X => 6 [81], observed from 1970 to 1996,
within the normalized small finger cycle. Intense X-ray eruptions have a
stronger impact than flares categorized into classes of optical brightness.
Fat arrows mark consecutive initial phases SFS of the cycle. It is conspicuous
that the eruptions concentrate on a restricted range before and after SFS.
This is already enough to base a rough prediction on. Yet a much more
differentiated pattern emerges when the Golden section is taken into
consideration. In the plot, one half of the major of the Golden section lies
after the first SFS and the second half before the next SFS, whereas the minor
is arranged in between. The filled triangles pointing downwards after the
first SFS indicate the phases on which the eruptions concentrate. They lie
just after the first SFS, at the boundary of the first half of the major, and
at minor and major within this range. The open triangles pointing upwards just
in the middle between the filled triangles indicate lulls in eruption
activity. In the half minor range before the following SFS everything is
reversed. The patterns before and after SFS are antisymmetric. The probability
that this distribution is due to chance is P = 1.3 x 10-15 , though the sample comprises only 33 very energetic
X-ray eruptions. When 163 X-ray eruptions in the range X = 2 to X < 6
[81] are investigated
to check the pattern in Figure 17, the sceptical null hypothesis can be
rejected at the level P = 7 x 10-10.
197 X-ray eruptions in the range X = 1 to X < 2 yield P = 2.7 x
10-11 . The relationship is so manifest that
dependable predictions can be based upon it.

After the publication of this result, a
further strong eruption, an X9 flare, occured on November 6, 1997. It fell
exactly at one of the active phases in Figure 17.

The primary cause of the solar
modulation of cosmic rays, which regulates cloud coverage, is not the number
of sunspots, but the varying strength of the solar wind. This was mentioned
already. The highest velocities in the solar wind up to 2500 km/sec are
generated by energetic solar eruptions (solar flares and eruptive prominences)
which even contribute to cosmic rays. These solar cosmic rays have an impact
on the strength of the solar wind, but show fluctuations different from the
galactic cosmic rays that enter the solar system from the outside. Energetic
solar eruptions shun sunspot maxima [18] and occur even close to minima.
The number of eruptions does not depend proportionally on the intensity of
11-year sunspot maxima. Figure 18 from Solar
Geophysical Data [106]
displays the monthly numbers of observed flares in sunspot cycles No 20 to 22.
Cycle No 20 with the highest monthly sunspot number R = 106 was
much weaker than cycle No 21 (R = 165) and cycle No 22 (R = 158), but it
produced nearly as many flares as cycle No 21 and considerably more than cycle
No 22. It is surprising, too, that cycle No 22, nearly as strong as cycle No
21 as to sunspots, generated such a low number of flares in relation to its
predecessor. Solar-terrestrial connections like the Svensmark effect are much
more dependent on energetic eruptions than on sunspots. Sunspot maxima are not
predominant in this respect, but special phases in the small finger cycle, as
shown in Figure 17,
are.

A wealth of publications points to a
connection between geomagnetic storms and weather [60,
103, 113, 118]. So it is informative that there
is a close correlation, too, between the velocity of the solar wind and the Kp
index of geomagnetic activity (r = 0.74) [46]. Geomagnetic storms, on the other
hand, are closely related to solar eruptions, as satellite observations show
which follow the causal chain from outbursts of energy on the sun’s surface to
disturbances of the earth’s magnetic field. Reference for many cases of direct
connections between solar eruptions and weather phenomena is given in the
literature. A typical example are the investigations by R. Scherhag [96] and R. Reiter [92] which show that the quality
of weather forecasts deteriorates significantly at the time of solar
eruptions. The described effects are not negligible. M. Bossolasco et al. [6], for example, observed an increase in thunderstorm activity by
60% after solar eruptions. Such effects of solar eruptions, well known for
decades, should be taken seriously by the IPCC, particularly since the
Svensmark effect alone has a stronger weight than the anthropogenic greenhouse
effect.

It has been mentioned already that
Hoyt and Schatten included structural changes in sunspots when they built
their model which reflects the connection between varying solar irradiance and
global temperature on earth. Large sunspots have a clearly distinguishable
dark inner zone, the umbra, and a less dark surrounding area, the penumbra.
The ratio of the areas occupied by umbra and penumbra varies continuously. The
dynamical causes are not yet known. D. V.
Hoyt [38] connects these structural variations with the strength of
convection below the sun’s surface. Sunspots are embedded in the convective
zone. The penumbra becomes less extended when the convection increases and a
more extended penumbra indicates a weaker convection. There is a link to
climate since stronger convection enhances the sun’s irradiance. Figure 19 after
D. V. Hoyt [38] shows the ratio of the
umbra area to that of the whole spot (U/W) derived from Greenwich Observatory
data. Hoyt and Schatten [39] rightly emphasize that the
U/W curve resembles the global temperature curve shown in Figure 9.

The arrows in Figure 19 indicate
initial phases of small finger cycles in which the difference forces are
balanced just for a moment before gravitation begins to prevail. The sun’s
orbital motion about CM is governed by difference forces as well as the
planets’ course around the sun. These forces, gravitation and centrifugal
force, are balanced overall. Yet in single phases of the orbit one force or
the other can prevail. This has an effect on the sun’s activity. I have shown
that solar flares are subjected to a directional effect which is independent
of the sun’s rotation on its axis. When the sun moves away from CM after a
strong impulse of the torque in its orbital motion, two times as many flares
are observed on the sun’s side pointing away from CM than on the opposite
side. When the sun moves towards CM, the number of flares on the side pointing
to CM is significantly greater than on the other side. Yet this effect occurs
only if the strength of the respective impulse of the torque in the SFS phase
goes beyond a precisely defined quantitative threshold [54, 57, 60]. The SFSs in Figure 19,
indicated by arrows, coincide within the whole investigated interval of a
century with peaks in the U/W values. This points to a close relationship
between SFSs and the strength of solar convection. The respective SFSs beyond
the time frame of Figure 19 fall at 1983.1, 1998.3, and
2008.4.

Figure 20
shows how big and small fingers interact
with regard to climate data. The curve displays the smoothed 2-year running
variance of yearly rainfall totals covering the years 1851 to 1983 derived
from 14 German stations by F. Baur [5]. Open arrows mark epochs of
SFSs correlated with maxima in the variance, while open circles indicate
epochs of SFTs that go along with minima. Only at the secular sunspot minimum
of 1895 is the correlation weak, probably because of the lack of releasable
magnetic energy available only in large sunspot groups. In statistical tests
the sceptical null hypothesis was rejected at the level P = 3 x10-5 [60]. This result was corroborated by rainfall data from England,
Wales, U.S.A., and India as well as by similar investigations into temperature
[60]. The variance
amplitudes are modulated by starts (S) and tips (T) of big fingers, marked by
flat triangles. BFTs show a correlation with high amplitudes and BFSs with
small ones.  They indicate maxima and minima that would emerge if the
curve were smoothed. The next maxima in the curve are to be expected in 1998
with an amplitude in the medium range and in 2005 with an amplitude in the
lower range.

Figure 21
after J. T.
Houghton et al. [36]
shows the growth rate of CO2 concentrations since 1958 in
ppmv/year at the Mauna Loa, Hawaii station. I owe the result presented here to
P. Dietze who drew my attention to the fact that the CO2
data reflect the rhythm of small finger cycles in a similar way as
tropospheric temperatures measured by satellites (Figure 23). Filled
triangles in Figure 21 mark SFSs and open triangles the major 0.618 within the
SF cycles. If the length of the cycle goes beyond 8 years, the minor 0.382,
too, gets involved. It is marked by diamonds. After BHS 1968 (fat arrow and
dashed vertical line) all Golden section phases (open triangles and diamond)
coincide with outstanding maxima in the CO2 data. SFSs
(filled triangles) indicate deep minimum ranges. Just in the middle between
the marked phases (little arrows) is the location of secondary minima. Before
BHS 1968, which released a phase jump, everything is reversed. Two CO2 maxima on the right, marked by filled circles, do not match
the pattern. They lie about six months past those SFSs that coincide with
middle-range maxima in global temperature shown in Figure 23. This is a
confirmation of the result, elaborated by C. Kuo et
al. [48] and
H. Metzner [75], that warming of the
atmosphere comes first and only five to seven months later the CO2 concentration follows. Yet it can be seen in addition that
the sun’s activity is involved. The next CO2 minimum is
to be expected around 1998.3, the imminent SFS, and the next maximum around
2002.9, the Golden section phase 0.618 in the new small finger cycle. An
intermittent maximum like that at the end of 1990 could possibly develop
around the end of 1998.

The connection presented in Figure 22 after
J. T. Houghton et al. [35] solves a seemingly
intractable problem of climatology and meteorology: the prediction of El Niño.
This phenomenon represents a quasicyclic large scale atmosphere-ocean
interaction which has climatic effects throughout the Pacific region and far
beyond. It is the only true global-scale oscillation that has been identified
so far. It is also called an ENSO event because of its links with the Southern
Oscillation, a fluctuation of the intertropical atmospheric oscillation. The
curve plots the monthly sea surface and land air anomalies 1961 to 1989 for
the tropical zone extending from 20° N to 20° S. The outstanding peaks
indicate ENSO events. After BFS 1968, marked by a big open arrow, all SFSs,
indicated by open triangles, coincide with peaks in the plot. The same is true
for the major of the Golden section within cycles formed by consecutive SFSs.
These 0.618 phases are marked by filled circles. In case of small finger
cycles longer than 8 years, also the minor 0.382 goes along with peaks. It is
indicated by filled diamonds. Troughs in the time series are almost exactly
linked to midpoints in between consecutive crucial phases, marked by small
arrows.

Before the initial phase 1968 of a big
finger cycle higher up in the hierarchy of the fractal of solar cycles, the
pattern was reversed. SFSs as well as majors and minors within small finger
cycles coincided with troughs, and the midpoints between these phases went
along with peaks. A further El Niño was to be expected in 1993. It appeared
punctually. In my paper “The Cosmic Function of the Golden
Section” [64] I
extrapolated this pattern and predicted more El Niños for 1995 and 1998.
Critics were sceptical about the 1995 event so close after the 1993 El Niño.
Yet the forecast proved correct [26]. A new El Niño began to build up in 1997. At the end of 1997
the Australian Bureau of Meteorology thought that El Niño had faded away and
La Niña would reign in 1998. However, as the new year opened, El Niño charged
up again, contrary to the predictions of its early demise, and showed a strong
performance in the following months, stronger than in the months July to
December 1997.

Figure 23
shows yearly means of the global mean
temperature in the lower troposphere observed by satellites [108]. In contrast to time series of
“world temperature” constructed by IPCC scientists, these data are objective
and free from distortions by the urban heat island effect. Different from the
inhomogeneous and wide-meshed net of meteorological stations they cover the
whole globe homogeneously. As can be seen from Figure 23, the temperatures in
1995 were not higher than in 1979 at the beginning of satellite observations,
though IPCC scientists claim an unprecedented rise in global temperature in
the eighties. The trend amounts to -0.06° C per decade. The quality of the
satellite data is confirmed by radiosonde observations. For the same interval
these balloon data yield nearly the same trend of -0.07° C [27]. Both of the data series show
exactly the same course [76]. The cyclic variation in the data cannot be explained by
general circulation models in spite of the entailing great expense. There is
not even an attempt to model such complex climate details, as GCMs are too
coarse for such purposes. When K. Hasselmann (a leading greenhouse
protagonist) was asked why GCMs do not allow for the stratosphere’s warming by
the sun’s ultraviolet radation and its impact on the circulation in the
troposphere, he answered: “This aspect is too
complex to incorporate it into models”
[8]. Since there are
other solar-terrestrial relationships which are “too complex” such as, for
example, the dynamics of cloud coverage modulated by the solar wind, it is no
wonder that the predictions based on GCMs do not conform to climate
reality.

However, if the sun’s dominant role in
climate change is acknowledged, the further development of the time series in
Figure 23 can be predicted. The filled arrows mark SFSs. Consecutive SFSs form
cycles that can be subjected to the Golden section. The 0.618 phases within
the small finger cycles are indicated by open arrows. All temperature maxima
coincide with the phases marked by triangles. The midpoints between the
crucial phases, designated by flat triangles, go along with minima in the
temperature. On the basis of this pattern I predicted a middle-range minimum
in the global temperature as measured by satellites for 1997.0 and a maximum
for 1998.6 [66]. As to
the minimum, the forecast has proven correct. Record-breaking minus
temperatures were observed worldwide. The maximum prediction, too, has a good
chance to turn out to be right. El Niño will take care of it. The current ENSO
event and rising temperatures are interpreted by IPCC scientists as a case for
the human impact on climate. Yet if this were true, how could the El Niño and
the current warming be predicted by looking at cycles of solar
activity?

In spite of the successful prediction
of the middle-range temperature minimum 1997.0 it is to be expected that there
will be objections that the relationship shown in Figure 23 covers only 18
years. Satellite data that start earlier are not available. Yet it would be
possible to make use of time series of surface temperatures to check the
correlation. They reach considerably higher levels, but H. Gordon [27] has shown that satellite temperatures and surface time series
have nearly coincident phases. An even better match are balloon-borne
radiosonde data [76].
Figure
24 after J. P. Peixoto and A. H. Oort
[86] is based on such
data and extends the investigation back to 1958. The curve presents the
monthly-mean atmospheric temperature anomalies in °C averaged over the
Northern (top) and Southern (bottom) Hemispheric mass between the surface and
about 25-km height for the period May 1958 to April 1988. The range of
observation includes 22 km-height that plays an important part in the quoted
investigations by K. Labitzke and H. van Loon. The anomalies are taken with
respect to the 1963 - 1973 mean conditions. The smoothed curves show 15-month
Gaussian-type filtered values.

Data for the Southern Hemisphere are not
available before 1963. The filled triangles mark SFSs and the open triangles
the Golden section phase 0.618 within cycles formed by consecutive SFSs. When
the cycle length goes beyond 8 years, the minor phase 0.382 is indicated by
filled diamonds. The correlation between the temperature maxima and the
designated phases of small finger cycles is close. As far as there are
deviations they only amount to a few months. Northern and Southern Hemisphere
also show a good conformance. This corroboration, which extends the satellite
data result to four decades, indicates that the connection between
middle-range temperature extrema and active phases of small finger cycles is
real, particularly since it is part of a complex web of interrelations, the
components of which confirm each other.

If we bear in mind that the correct
forecasts based on the semiquantitative model of solar-terrestrial relations
presented here are thinkable only if the sun’s varying activity is a dominant
factor in climate change, it seems difficult to resist the insight that once
again an artificially constructed homocentric position is beginning to rock. A
general survey of the given results indicates that climate variations are
governed by the sun, not mankind.

References

[1] Arnol’d, V. I.: Small
denominators and problems of stability of motion in classical and celestial
mechanics. Russ. Math. Surv. 18 (1963), 85.

[2] Baliunas, S. & Soon, W.: Are
variations in the length of the activity cycle related to changes in
brightness in solar-type stars? Astrophys. J. 450 (1995), 896.

[3] Baltuck, M., Dickey, J., Dixon,
T. & Harrison, C. G. A.: New approaches raise questions about future sea
level change. EOS, 1. Oktober 1996, 385, 388.

[4] Barlow, A. K. & Latham, J.:
A laboratory study of the scavenging of submicro aerosol by charged raindrops.
Quart. J. R. Met. Soc. 109 (1983), 763.

[5] Baur, F.: Abweichungen der
Monatsmittel der Temperatur Mitteleuropas & des Niederschlags in
Deutschland. Beilage zur Berliner Wetterkarte des Instituts für Meteorologie
der Freien Universität Berlin vom 24. 6. 1975.

[6] Bossolasco, M., Dagnino, I.,
Elena, A. & Flocchini, G.: Thunderstorm activity and interplanetary
magnetic field. Riv. Italiana Geofis. 22 (1973), 293.

[7] Brückner, E.: Klimaschwankungen
seit 1700. Geographische Abhandlungen 14 (1890), 325.

[8] Bührke, T.: Die Flecken der
Sterne. Süddeutsche Zeitung vom 30. 10. 1997, 41.

[9] Burroughs, W. J.: Weather cycles
- real or imaginary? Cambridge University Press,1992, 38, 128, 149.

[10] Butler, C. J.: A two-century
comparison of sunspot cycle length and temperature change - the evidence from
Northern Ireland. In: Emsley, J., Hsg.: The global warming debate. The report
of the European Science and Environment Forum (ESEF). London, ESEF, 1996,
215.

[11] Clough, H. W.: Synchronous
variations in solar and terrestrial phenomena. Astrophys. J. 22 (1905),
42.

[12] Clough, H. W.: The 11-year
sunspot period, secular periods of solar activity, and synchronous variations
of terrestrial phenomena. Monthly Weather Rev. 60 (1933), 99.

[13] Courtney, R. S.: Die Risiken
des global warming. In: H. Metzner, Hsg.: Treibhaus-Kontroverse &
Ozon-Problem. Tübingen, Europäische Akademie für Umweltfragen, 1996,
159.

[14] Dicke, R. H.: The sun’s
rotation and relativity. Nature 202 (1964), 432.

[15] Dickinson, R. E.: Solar
variability and the lower atmosphere. Bull. Am. Meteorol. Soc. 56 (1975),
1240.

[16] Eddy, J. A.: Historical
evidence for the existence of the solar cycle. In: White, O. R.: The solar
output and its variation. Boulder, Colorado Associated University Press, 1977,
67.

[17] Eddy, J. A.: A new sun. The
solar results from skylab. Washington, D. C., NASA, 1979, 12.

[18] EOS, Trans. Amer. Geophys.
Union, 18. Oktober 1988, 1.

[19] Fichefet, T.: Solar radiation
and global climate change: some experiments with a two-dimensional climate
model. In: B. Frenzel, Hsg.: Solar output and climate during the Holocene.
Stuttgart-Jena-New York, Gustav Fischer Verlag, 1995, 169.

[20] Flohn, H.: Jüngste
Klimaänderungen: Treibhauseffekt oder Beschleunigung des Wasserkreislaufs. In:
Metzner, H., Hsg.: Globale Erwärmung - Tatsache oder Behauptung? Tübingen,
Europäische Akademie für Umweltfragen, 1993, 91.

[21] Foukal, P. V.: The variable
sun. Scient. American, Februar 1990, 39.

[22] Foukal, P. & Lean, J.: An
empirical model of total solar irradiance between 1874 and 1988. Science 247
(1990), 556- 558.

[23] Franke, H.: Lexikon der Physik.
Stuttgart, Francksche Verlagshandlung, 1969, 845, 1603.

[24] Friis-Christensen, E. &
Lassen, K.: Length of the solar cycle: an indicator of solar activity closely
associated with climate. Science 254 (1991), 698.

[25] Fröhlich, C.: Variations in
total solar irradiance. In: B. Frenzel, Hsg.: Solar output and climate during
the Holocene. StuttgartJena-New York, Gustav Fischer Verlag, 1995, 125, 126,
127.

[26] Fu, L.L, Koblinsky, C. J.,
Minster, J. F. & Picaut, J.: Reflecting on the first three years of
TOPEX/POSEIDON. EOS 77 (1996), Nr. 12, 19. März 1996, 109,111, 117.

[27] Gordon, A. H.: Bias in measured
data. In: Bate, R., Hsg.: Global Warming. The continuing debate. Cambridge,
The European Science and Environment Forum (ESEF), Cambridge, 1998,
55.

[28] Groveman, B. S. &
Landsberg, H. E.: Simulated northern hemisphere temperature departures
1579-1880. Geophysical Research Letters, 6 (1979), 767.

[29] Haigh, J.: On the impact of
solar variability on climate. Science 272 (1996),981.

[30] Hansen, J. E. & Lebedeff,
S.: Global surface air temperatures. Update through 1987. Geophysical Research
Letters 15 (1988), 323.

[31] Hansen, J., Lacis, A., Rind,
D., Russell, G., Stone, P., Fung, I., Ruedy, R. & Lerner, J.: Climate
sensitivity: analysis of feedback mechanisms. In: J. E. Hansen & T.
Takahashi, Hsg.: Climate processes and climate sensitivity. Geophys. Series
29. Washington, D. C., Am. Geophys. Union (AGU),1990, 130.

[32] Hansen, J. E., Lacis, A. A.,
& Ruedy, R. A.: Comparison of solar and other influences on long-term
climate. In: K. H. Schatten & A. Arking, Hsg.: Climate impact of solar
variability. Greenbelt, NASA, 1990, 142.

[33] Harvey, L. D. D.: On the role
of high latitude ice, snow, and vegetation feedbacks in the climatic response
to external forcing changes. Climatic Change 13 (1988), 191.

[34] Hood, L. L. & Jirikowic, J.
L.: A mechanism involving solar ultraviolet variations for modulating the
interannual climatology of the middle atmosphere. In: K. H. Schatten & A.
Arking, Hsg.: Climate impact of solar variability. Greenbelt, NASA, 1990,
165.

[35] Houghton, J. T., Jenkins, G. J.
& Ephraums, J.J.: Climatic change. The IPCC scientific assessment.
Cambridge University Press, 1990.

[36] Houghton, J. T., Meira Filho,
L. G., Callander, B. A., Harris, N., Kattenberg, A. & Maskell, K: Climate
Change 1995. Cambridge, 1996, 81, 366, 381.

[37] Howard, R.: The rotation of the
sun. Scient. American 232 (1975), 106.

[38] Hoyt, D. V.: Using the boundary
conditions of sunspots as a technique for monitoring solar luminosity
variations. In: K. H. Schatten & A. Arking, Hsg.: Climate impact of solar
variability. Greenbelt, NASA, 1990, 44.

[39] Hoyt, D. V. & Schatten, K.
H.: The role of the sun in climate change. New York-Oxford, Oxford University
Press, 1997, 61, 70, 86, 184,188,194, 214.

[40] Jones, P. D.: Hemispheric
surface air temperature variations. Recent trend and an update to 1987. J.
Climate 1 (1988), 645.

[41] Jose, P. D.: Sun’s motion and
sunspots. Astron. J. 70 (1964), 195.

[42] Joselyn, J. A.: SESC methods
for short-term geomagnetic predictions. In: Simon, P. A., Heckman, G. &
Shea, M. A.: Solar-terretrial predictions. Proceedings of a workshop at
Meudon, 18.-22. Juni 1984. Boulder, National Oceanic and Atmospheric
Administration, 1986, 404.

[43] Kahl, J. D., Charlevoix, D. J.,
Zaitseva, N. A., Schnell, R. C. & Serreze, M. C.: Absence of evidence for
greenhouse warming over the Arctic Ocean in the past 40 years. Nature 361
(1993), 335.

[44] Kaku, M.: Quantum field theory.
Oxford University Press, 1993, 14.

[45] Kapfraff, J.: Connections. The
geometry bridge between art and science. New York, McGraw Hill, 1991, 85, 89,
308, 313.

[46] Kertz, W.: Einführung in die
Geophysik. Mannheim, Bibliographisches Institut, 1971, 376-377.

[47] Kolmogorov, A. N.: Preservation
of conditionally periodic movements with small change in the Hamiltonian
function. Lecture Notes in Physics 93 (1979), 51.

[48] Kuo, C., Lindberg, C. &
Thomson, D. J.: Coherence established between atmospheric carbon dioxide and
global temperature. Nature 343 (1990), 709.

[49] Labitzke, K, & van Loon,
H.: Sonnenflecken & Wetter. Gibt es doch einen Zusammenhang? Die
Geowissenschaften 8 (1990), 1.

[50] Labitzke, K. & van Loon, H:
Some recent studies of probable connection between solar and atmospheric
variability. Ann. Geophysicae 11 (1993), 1084.

[51] Labitzke, K, & van Loon,
H.: Associations between the 11-year sunspot cycle, the quasi-biennial
oscillation, and the atmosphere. Philosophical Transactions of the Royal
Society of London, A, 330 (1990), 577.

[52] Lamb, H. H.: Climate: Present,
past, and future. Bd. 1. London, Methuen,1972, 186, 456.

[53] Landsberg, H. E.: Man-made
climatic changes. In: Proceedings of the symposium on physical and dynamic
climatology of the World Meteorological Organization 347 (1974),
262.

[54] Landscheidt, T.: Beziehungen
zwischen der Sonnenaktivität & dem Massenzentrum des Sonnensystems.
Nachrichten der Olbers-Gesellschaft 100 (1976), 12, 14-15.

[55] Landscheidt, T.: Solar
oscillations, sunspot cycles, and climatic change. In: McCormac, B. M., Hsg.:
Weather and climate responses to solar variations. Boulder, Associated
University Press, 1983, 301, 302, 304.

[56] Landscheidt, T.: Cycles of
solar flares and weather. In: Moerner, N.A. & Karlén, W., Hsg.: Climatic
changes on a yearly to millenial basis. Dordrecht, D. Reidel, 1984, 475,
476.

[57] Landscheidt, T.: Long-range
forecast of energetic x-ray bursts based on cycles of flares. In: Simon, P.
A., Heckman, G. & Shea, M. A.: Solar-terretrial predictions. Proceedings
of a workshop at Meudon, 18.-22. Juni 1984. Boulder, National Oceanic and
Atmospheric Administration, 1986, 85, 86, 87-88.

[58] Landscheidt, T.: Long-range
forecast of sunspot cycles. In: Simon, P. A., Heckman, G. & Shea, M. A.:
Solar-terretrial predictions. Proceedings of a workshop at Meudon, 18.-22.
Juni 1984. Boulder, National Oceanic and Atmospheric Administration, 1986,
53-55.

[59] Landscheidt, T.: Long-range
forecasts of solar cycles and climate change. In: Rampino, M. R., Sanders, J.
E., Newman, W. S. & Königsson, L. K.: Climate. History, Periodicity, and
predictability. New York, van Nostrand Reinhold, 1987, 433-438.

[60] Landscheidt, T.: Solar
rotation, impulses of the torque in the sun’s motion, and climatic variation.
Climatic Change 12 (1988), 267-268, 270, 277, 278-280, 283,
286-290.

[61] Landscheidt, T. & Wöhl, H.:
Solares Aktivitätsminimum erst 1989/90? Sterne & Weltraum, November 1986,
584.

[62] Landscheidt, T.: Relationship
between rainfall in the northern hemisphere and impulses of the torque in the
sun’s motion. In: K. H. Schatten & A. Arking, Hsg.: Climate impact of
solar variability. Greenbelt, NASA, 1990, 260.

[63] Landscheidt, T.: Global warming
or Little Ice Age? In: Finkl, C. W., Hsg.: Holocene cycles. A Jubilee volume
in celebration of the 80th birthday of Rhodes W. Fairbridge. Fort Lauderdale,
The Coastal Education and Research Foundation (CERF), 1995, 372, 373,
374-375.

[64] Landscheidt, T.: Die kosmische
Funktion des Goldenen Schnitts. In: P. H. Richter, Hsg.: Sterne, Mond &
Kometen. Bremen & die Astronomie. Bremen, Verlag H. M. Hauschild, 1995,
240-276.

[65] Landscheidt, T.:
Klimavorhersage mit astronomischen Mitteln? Fusion 18 (1997), Nr. 1,
58.

[66] Landscheidt, T.: Forecast of
global temperature, El Niño, and cloud coverage by astronomical means.
In:Bate, R., Hsg.: Global Warming. The continuing debate. Cambridge, The
European Science and Environment Forum (ESEF), 1998, 172.

[67] Laskar, J.: A numerical
experiment on the chaotic behaviour of the solar system. Nature 338 (1989),
237.

[68] Lassen, K. &
Friis-Christensen, E.: Variability of the solar cycle length during the past
five centuries and the apparent association with terrestrial climate. Journ.
of Atmos. Terr. Phys. 57 (1995), 835.

[69] Livingston, W. C.: Secular
change in equivalent width of C 5380, 1978-1990. In: K. H. Schatten & A.
Arking, Hsg.: Climate impact of solar variability. Greenbelt, NASA, 1990,
336.

[70] van Loon, H. & Labitzke,
K.: The 10-12-year atmospheric oscillation. Meteorol. Zeitschrift 3 (1994),
259.

[71] Markson, R. & Muir, M.:
Solar wind control of the earth’s electric field. Science 208 (1980), 979.

[72] Mason, B. I.: Towards the
understanding and prediction of climatic variations. Quart. J. Roy. Soc. 102
(1976), 478.

[73] McKinnon, J. A. : Sunspot
numbers 1610-1985. Boulder, World Data Center A for Solar Terrestrial Physics,
1987.

[74] Mecherikunnel, A. T. &
Kyle, H. L: Solar constant data from Earth Radiation Budget measurements. In:
K. H. Schatten & A. Arking, Hsg.: Climate impact of solar variability.
Greenbelt, NASA, 1990, 316.

[75] Metzner, H.: Gibt es einen CO
-induzierten Treibhaus-Effekt? In: H. Metzner, Hsg.: Treibhaus-Kontroverse
& Ozon- 2 Problem. Tübingen, Europäische Akademie für Umweltfragen, 1996,
89.

[76] Michaels, P. J. &
Knappenberger, P. C.: The United Nations Intergovernmental Panel on Climatic
Change and the scientific “consensus” on global warming. In: Emsley, J., Hsg.:
The global warming debate. The report of the European Science and Environment
Forum. London 1996, 166.

[77] Mitchell, J. M., Stockton, C.
W. & Meko, D. M.: Evidence of a 22-year rhythm of drought in the Western
United States related to the Hale solar cycle since the 17th century. In: B.
M. McCormac & T. A. Seliga, Hsg.: Solar- terrestrial influences on weather
and climate. Dordrecht,Reidel, 1979, 125.

[78] Mogey, R.: The cycles in
inflation. Cycles 44 (1993), 102.

[79] Moser, J.: Stable and random
motions in dynamical systems. Princeton University Press, 1973.

[80] Moss, F. & Wiesenfeld, K.:
The benefits of background noise. Scient. American, August 1995,
66.

[81] National Geophysical Data
Center, Boulder: X-ray flares. SOLRAD (1968-1974), GOES
(1975-present).

[82] Neeman, B. U., Ohring, G. &
Joseph, J. H.: The Milankocich theory and climate sensitivity. Part I:
Equilibrium climate model solution for the present surface conditions. J.
Geophys. Res. 93 (1988), 11153.

[83] Negendank, J. F. W., Brauer, A.
& Zolitschka, B.: Die Eifelmaare als erdgeschichtliche Fallen &
Quellen zur Rekonstruktion des Paläoenvironments. Mainzer geowiss. Mitt. 19
(1990), 235.

[84] Nesme-Ribes, E., Baliunas, S.
L. & Sokoloff, D.: The stellar dynamo. Scient. American August 1996,
51-52.

[85] Newton, I.: Mathematische
Prinzipien der Naturlehre. Darmstadt, Wissenschaftliche Buchgesellschaft,
1963, 532.

[86] Peixoto, J. P. & Oort, A.
H.: Physics of climate. New York, American Institute of Physics, 1992,
466.

[87] Peng, L., Chou, M. D. &
Arking, A.: Climate studies with a multi-layer energy balance mode. Part I:
Model description and sensitivity to the solar constant. J. Atmosph. Sci. 39
(1987), 5505.

[88] Posmentier, E. S., Soon, W. H.
& Baliunas, S. L.: Relative impacts of solar irradiance variations and
greenhouse changes on climate, 1880-1993. In: Bate, R., Hsg.: Global Warming.
The continuing debate. Cambridge, The European Science and Environment Forum
(ESEF), Cambridge, 1998, 159.

[89] Potter, G. L. & Cess, R.
D.: Background tropospheric aerosols: incorporation within a statistical
dynamical climate model. J. Geophys. Res. 89 (1984), 9521.

[90] Priem, H. N. A.: CO and
climate: a geologist’s view. Space Science Reviews 81 (1997), 193.
2

[91] Ramanathan, V., Barkstrom, B.
R. & Harrison, E. F.: Climate and the earth’s radiation budget. Physics
Today, Mai 1989, 22.

[92] Reiter, R.: Influences of solar
activity on the electric potential between the ionosphere and the earth. In:
B. M. McCormac & T. A. Seliga, Hsg.: Solar-terrestrial influences on
weather and climate. Dordrecht, Reidel, 1979, 251.

[93] Rind, D. & Overpeck, J. T.:
Hypothesized causes of decadal-to-century-scale climate variability - climate
model results. Quat. Sci. Rev. 12 (1993), 357.

[94] Robock, A: Solar, volcanic, and
anthropogenic influences on climate for the past 500 years. Klimakonferenz
“Klimaveränderungen - Ursachen & Auswirkungen”, 10. -11. November in
Bonn.

[95] Roederer, J. G.: Solar
variability effects on climate. In: In: B. Frenzel, Hsg.: Solar output and
climate during the Holocene. Stuttgart-Jena-New York, Gustav Fischer Verlag,
1995, 3, 17.

[96] Scherhag, R.: Die
explosionsartigen Stratosphärenerwärmungen des Spätwinters 1951/52. Berichte
des Deutschen Wetterdienstes der US-Zone Nr. 38 (1952), 51.

[97] Schlesinger, B. M., Cebula, R.
P., Heath, D.F., DeLand, M. T & Hudson, R. D.: Ten years of solar change
as monitored by SBUV and SBUV2. In: K. H. Schatten & A. Arking, Hsg.:
Climate impact of solar variability. Greenbelt, NASA, 1990, 341.

[98] Schönwiese, C. D.: Northern
hemisphere temperature statistics and forcing. Part B: 1579-1980. Arch. Met.
Geoph. Biocl., Ser. B 35, 164.

[99] Schönwiese, C. D.: Der
Treibhauseffekt: Weltweit wird das Wasser steigen. Bild der Wissenschaft,
September 1987, 97, 98.

[100] Schönwiese, C. D.: Klima im
Wandel. Hamburg, 1994, 99, 161.

[101] Schostakovitsch, W. B.:
Bodenablagerungen der Seen & periodische Schwankungen der
Naturerscheinungen. Mémoires de l’Institut Hydrologique 13 (1934),
95.

[102] Schriever, K. H. & Schuh,
F.: Enzyklopädie Naturwissenschaft & Technik. Weinheim, Zweiburgen Verlag,
1980, 2227.

[103] Schuurmans, C. J. E.: Effects
of solar flares on the atmospheric circulation. In: B. M. McCormac & T. A.
Seliga, Hsg.: Solar-terrestrial influences on weather and climate. Dordrecht,
Reidel, 1979, 105.

[104] Showstack, R.: Rivers of
sunlight, EOS, 9. September 1997, 382.

[105] Singer F.: Globale Erwärmung.
In: H. Metzner, Hsg.: Treibhaus-Kontroverse & Ozon-Problem. Tübingen,
Europäische Akademie für Umweltfragen, 1996, 31.

[106] Solar Geophysical Data -
comprehensive reports: Monthly counts of grouped solar flares Jan 1965 - Mar
1997. Number 637, September 1997, 7.

[107] Soon, W. H., Posmentier, E. S.
& Baliunas, S. L.: Inference of solar irradiance variability from
terrestrial temperature changes, 1880-1993. An astrophysical application of
the sun-climate connection. The Astrophys. J. 472 (1996), 891.

[108] Spencer, R. W., Christy, J. R.
& Grody, N. C.: Global atmospheric temperature monitoring with satellite
microwave measurements: method and results 1979-1984. J. Climate 3 (1990),
1111.

[109] Stuiver, M., Grootes, P.
M. & Braziunas, T. F.: The GISP delta 18O climate record of the past 16,500 years
and the role of 18 the sun, ocean, and volcanoes. Quat. Res. 44(1995),
341.

[110] Sussman, G. J. & Wisdom,
J.: Chaotic evolution of the solar system. Science 257 (1992), 56.

[111] Svensmark, H. &
Friis-Christensen, E.: Variation of cosmic ray flux and global cloud coverage
- a missing link in solarclimate relationships. J. Atm. Sol. Terr. Phys. 59
(1997), 1225.

[112] Svensmark, H.: Possible
mechanisms of solar activity modulation of the earth’s climate. Klimakonferenz
“Klimaveränderungen - Ursachen & Auswirkungen”, 10. -11. November in
Bonn.

[113] Tinsley, B. A.: Do effects of
global atmospheric electricity on clouds cause climatic changes? EOS, 19.
August 1997, 341, 344, 349.

[114] Weber, G.-R.: Smudged
fingerprint: The elusive search for a human impact on the climate system. In:
Bate, R., Hsg.: Global Warming. The continuing debate. Cambridge, The European
Science and Environment Forum (ESEF), Cambridge, 1998, 63.

[115] Wetherald, R. T. & Manabe,
S.: The effects of changing the solar constant on the climate of a general
circulation model. J. Atmosph. Sci. 32 (1975), 2044.

[116] Wiesenfeld, K.: An
introduction to stochastic resonance. In: J. R. Buchler & H. E. Kandrup:
Stochastic processes in astrophysics. New York, New York Academy of Sciences,
1993, 13.

[117] Wiin-Christensen, C. &
Wiin-Nielsen, A.: Limited predictability and the estimated greenhouse effect.
In: Bate, R., Hsg.: Global Warming. The continuing debate. Cambridge, The
European Science and Environment Forum (ESEF), Cambridge, 1998, 41.

[118] Wilcox, J. M.: Solar activity
and the weather. J. Atmosph. Terr. Phys. 37 (1975), 237.

[119] Wolff, C. L. & Hoegy, W.
R.: Solar irradiance observed from PVO and inferred solar rotation. In: K. H.
Schatten & A. Arking, Hsg.: Climate impact of solar variability.
Greenbelt, NASA, 1990, 58.

[120] Yoshimura, H.: The 110-year
periodic modulations of solar magnetic cycle and solar total irradiance and
luminosity. STEP GBRSC News, 5 (1995), No.2, 7.

A German language version of the above paper

Return to the "Climate Change
Guests Debate" Page

Return to "Still Waiting For
Greenhouse" Main
Page