An
Albert Szent-Györgyi Moment for Climate Science
Dr Chris Barnes, Bangor Scientific and Educational Consultants, Wales, UK, LL57 2TW. E-mail doctor.barnes@yahoo.co.uk
Submitted to a
peer reviewed journal for publication.
Submission date 02/02/2025.
Abstract
The
hypothesis that the position of the magnetic North Pole (Dip Pole) (latitude)
ought to be very highly correlated with global temperature change on Earth has
been tested and shown to be correct. The probability of such a correlation
happening by chance is close to zero. Moreover, this has likely been the
dominant climate driver for the last 2000 years. Granger causality test
shows Pole Shift drives temperature with
up to a two-year lag (Figure1). Two new
climate models with and without CO₂ are developed and tested. Both models
successfully predict modern warming, the Medieval Warm Period (MWP), and the
Roman Warm Period (RWP) in time (figures 3+4). The model excluding CO₂ (figure 4) predicts past warming with stronger
amplitude. This model also predicts the
Little Ice Age ( LIA) with a seamless transition into the Modern Warm Period
using the real data sets (figure 5). As Pole swings Northwards, interacting region
shifts to higher ionospheric altitudes
and combined particle precipitation
changes (EEP) reduce albedo, hence increase forcing (figure 2) by virtue of their changes to the world’s
clouds, provide calculated values in the region of 81% of recent warming, with
the rest (15%) mainly of solar origin. CO₂ at most could contribute 3.9%
of all warming. The detail disclosed above represents a profound and crucial
discovery for climate science and its future direction. We need no longer try
to mitigate so much for CO2, but we will
desperately have to understand our geomagnetic climate and possibly how
anthropogenic factors such as ELF radio transmitters and power systems and
aviation aerosol may also change EEP. Preliminary investigations indicate that
because South dip-pole is not antipodal and moves at different rates and in
different directions this accounts for different rates of Antarctic warming and
Southern Hemisphere Cloud behavoiur also.
Introduction
In
1982, I had the great pleasure of meeting Professor Albert Szent-Györgyi, Nobel
Prize winner. I was a young postdoc working on polymer tribo-charging and
surface states, and he was a biologist who, even in his twilight years, had an
idea that charge transfer complexation involving methyl glyoxal could be
relevant in cancer biology. I tested his idea for him. The rest is history and
not relevant to a climate science paper, except insofar as Albert was reputed
to have said words that make up a now-famous quote: “Understanding is seeing
what others have already seen and thinking what no one else has ever thought.”
I was not your average postdoc; I never put all my eggs in one basket. I never
narrowed my academic field to the point where I wore blinkers to the rest of
the world of science. Indeed, after working as a postdoc on three different
contracts, I branched out and became a multi-disciplinary scientific
consultant, and I also hold patents spanning many disciplines. As a lifelong
learner with a keen interest in UK weather since the 1970s, I took it upon
myself to learn some climate science. I am not a “climate denier” in the sense
that I do not deny that climate changes—indeed, it has always changed—but you
can call me a “climate enquirer” as I seek the true causes of change, whether
natural or anthropogenic.
I
began writing papers on climate science and weather in 2012 and deposited them
on my own website. I always had it uppermost in my mind that there was
something fundamentally wrong with the anthropogenic global warming theory, at
least with an entire causation by CO₂. I have discussed what I feel are
some of the reasons for this elsewhere⁴. Continuing with this in mind, I
have always been fascinated by the fact that modern warming commenced in
earnest just after the Dalton Minimum (1790–1830), and I was further struck by
recent comments that, after the 1970s cooling and the late 1990s to early 2000s
hiatus in warming, from 2022 warming appears to have accelerated at an alarming
rate and beyond the slope of increase in CO₂ meant to account for it in climate
models⁵. I began to ponder other physical factors on this little Earth of
ours that had accelerating rates of change. I was struck by the fact that the
North Magnetic Dip Pole is moving just so. The drift of the magnetic North Pole
from Canada to Siberia has increased from an average rate of 9 kilometres per
year until 2000 to about 50–60 kilometres per year afterward. I also noted
that, taking in the Maunder and Dalton minima, the magnetic North Pole appeared
to move very slowly, remaining in its hitherto most recent set of most south-westerly
positions, whereas it has since moved significantly northwards. Hence, an
initial inspiration for a testable hypothesis and for the writing of this paper
arose.
The
writing of this paper has also been inspired by the fact that almost all recent
warming can be shown to be due to a fall in Earth’s albedo and changed cloud
distributions—see, for example, Goessling et al.⁶, Wu et al.⁷, and
especially Nikolov and Zeller⁸. It was further inspired by my 2017
observations of an anthropogenic warming somehow linked to Earth’s power
systems, which I have previously ascribed to their influence on the Van Allen
Belts and energetic particles, especially electrons but also solar
protons⁹. The thought occurred to me that, since the auroral oval is centred
around the magnetic North Dip Pole—where field lines are perpendicular to the
surface—and not the North Pole per se, any shift in energetic particle
interactions brought about either anthropogenically or by movement of the
magnetic pole itself ought to change the polar electrojet, the stratospheric
polar vortex (SPV), jet streams, and clouds in general, hence also changing the
weather and climate.
So,
if Earth’s albedo is changing, one needs to look for drivers of those changes.
Other than anthropogenic changes, any heating of the planet ought, then, to be
down to the Sun or other extraterrestrial sources and/or to changes in features
of the solid Earth or oceans. The final piece of inspiration that hit me was to
think that maybe there is more to the Sun’s interaction with Earth than its
irradiance (TSI), a good measure of solar activity being the 10.7 cm solar
flux. I have previously suggested that solar magnetism would be of crucial
importance for climate¹⁰.
Hence,
bringing all this together and having my “Szent-Györgyi moment,” I thought of
the interplanetary magnetic field (IMF) and how it may vary and interact with
our wandering magnetic North Pole. Moreover, I thought that not only would the
moving North Pole have an IMF/EEP connection, but it would also change Earth’s
tilt, sphericity, and rotation—the latter has been known about since the 1950s,
see for example Vestine (1953)¹¹—and hence would have
an amplification or modulation effect on TSI but also on atmospheric angular
momentum pressure, see for example Lam et al. (2013)¹². Thus, I created a
hypothesis that the position of the magnetic North Pole ought, perhaps through
a combination of these factors, to be very highly correlated with global
temperature change on Earth. Bucha (1980)¹³ was possibly the first to
investigate tentative correlations between geomagnetic, climatic, and
meteorological phenomena, with the object of demonstrating the function of the
geomagnetic pole and changes of its position in controlling the climate and
weather. It was not until 2009 that Kerton¹⁴ speculated on a possible
connection but was still unable to establish the full causes. Goralski
(2019)¹⁵ advanced a new climatic theory, explaining how the effects of Earth’s
coating movement result in magnetic pole movement. There are also known weak
influences of Earth’s field on ocean circulations, but with longer timescales
than those considered here¹⁶.
Testing
the Hypothesis
When
it comes to movements of the geomagnetic North Pole, there are several
possibilities to consider for possible correlation with Earth temperature
changes. Does one, for instance, consider latitude or longitude or a
combination of the two? If the latter, then from where does one take a bearing?
Also, the pole movement has been accelerating a lot more of late.
Interestingly, so has climate change. Does one need to factor in this
acceleration in some way? For instance, the distance moved by the pole per year¹⁷
looks tantalizingly close in form to a plot of modern global warming.
Since
the pole has moved both northwards and eastwards since the Dalton Minimum, the
first logic I employed was to try plotting its Haversine bearing relative to an
arbitrary starting position in 1830. At least this ought to simplify matters
and provide a single, testable variable. For temperature, I used the NASA
Goddard Institute for Space Studies (GISS) Surface Temperature Analysis
(GISTEMP) dataset, v4. For the position of the magnetic North Dip Pole, I used
data from the National Geophysical Data Center¹⁸. I constructed the
following data table:
|
Date |
Temperature
Change (°C) |
Haversine
Bearing (Degrees) |
|
1830 |
0 |
0 |
|
1880 |
0.25 |
8 |
|
1890 |
0.15 |
5 |
|
1900 |
0.35 |
11 |
|
1910 |
0.05 |
0 |
|
1920 |
0.2 |
0 |
|
1930 |
0.3 |
4 |
|
1940 |
0.65 |
15 |
|
1950 |
0.45 |
11 |
|
1960 |
0.55 |
15 |
|
1970 |
0.45 |
11 |
|
1980 |
0.75 |
20 |
|
1990 |
0.75 |
20 |
|
2000 |
0.95 |
29 |
|
2010 |
1.15 |
37 |
|
2020 |
1.45 |
49 |
|
2025 |
1.65 |
55 |
Table 1
I plotted the data from Table 1 using Hyams graph plotting suite. Not only was
there a near-perfect correlation, but it also accounted for observed hiatuses
as well. The plot gave R = 0.993 for the above data, and the two-tailed P-value
equals less than 0.0001; by all conventional criteria, this difference is
extremely statistically significant. Moreover, this represents some 98.6% of
all warming since 1830. As this was a preliminary test, I did not include the
residual analysis, but it is easy to see from just the data points that as the
motion has increased, so has the linearity and hence the certainty that this is
mirroring the main climate driver(s).
I
was, however, mindful that this high R-value had been generated from a mere 14
degrees of freedom. I decided to try the same Haversine procedure with a full
yearly dataset spanning 1850–2020, hence providing over twelve times as many
degrees of freedom. This time the regression was much weaker. I suspected that
the dog-leg motion of the pole in the 1800s may be a possible cause, and I
considered that EEP interaction would be more likely to be initiated above the
auroral oval, which will on average encircle all longitudes at whatever value
of latitude it descends to. Thus, I concluded that latitude of the Dip Pole
ought to be the most significant variable. I performed a single linear
regression of all 170+ points, latitude versus temperature change, and the
R-value was considerably higher than for the same temperature data regressed
against the Haversine bearing. Also, despite the above trial result suggesting
the irrelevance of CO₂, I decided, given recent “consensus,” to include
it as an additional X variable and employ multiple linear regression analysis
on the same 170+ points using the calculator at https://www.statskingdom.com/410multi_linear_regression.html.
The model derived is equation (1), wherein X₁ is the CO₂
concentration in ppm and X₂ is the latitude. The data table for the
regressed data is shown in the appendix.
Ŷ
= -4.127114 + 0.00529962 X₁ + 0.0320038 X₂ ………………… (1)
Correlation
matrix (Pearson)
|
Y |
X₁ |
X₂ |
|
|
Y |
1 |
0.946032 |
0.945102 |
|
X₁ |
0.946032 |
1 |
0.987964 |
|
X₂ |
0.945102 |
0.987964 |
1 |
It
can be seen from the correlation matrix that X₂ carries the strongest
weight.
The
histogram has a good bell curve, suggestive of real, meaningful data. The
X₁ and X₂ residuals are truly fascinating. There is no known
physical way in which CO₂ or temperature could
drive an internal parameter of the “solid” Earth. However, if pole shift is
driving temperature, then it could be driving additional natural CO₂ as
well. Alternatively, another parameter related to EEP could be cross correlated
with CO₂, and I have remarked on this elsewhere⁹.
Assuming,
for the moment, both X variables in the model to be real yields roughly equal
climate sensitivity of 34 mK and 32.3 mK per decade for X₁ and X₂, respectively. For
CO₂, this represents a further 1.506°C of warming if CO₂ were to
double, assuming linearity. However, as I have said before, the reality of
CO₂ in the model is questionable, and interestingly, I have previously
theorized on simple solar system measurements that showed that the order of
warming by CO₂ at present levels in Earth’s atmosphere ought to be of the
order of a few milli-Kelvin². Further reinforcing these findings, Qing-Bin Lu
(2025)³ finds no recent significant trends in total GHG effect in polar and
non-polar regions, respectively. Koutsoyiannis and Kundzewicz (2020)¹⁹ found that for Earth CO₂
concentrations, the dominant direction is that temperature first increases, and
then CO₂ concentration follows. Changes in CO₂ follow changes in T
by about six months on a monthly scale, or about one year on an annual scale.
One interpretation of this result would again be if CO₂ is not a
significant driver and that another factor causes temperature rise, as in line
with the present discovery perhaps. YoungSeok Hwang
et al. (2021)²⁰ found, using satellite measurements, no evidence for a
global decrease in CO₂ concentration during the first wave of the
COVID-19 pandemic, despite others finding local decreases adjacent to roads,
power stations, and factories and the like. One possible conclusion here is
that perhaps the warming Earth is generating far more of its own CO₂ to
the extent wherein human-generated CO₂ pales to insignificance. On the
other hand, Feldman et al. (2015)²¹ claim to have measured the real effect of a
CO₂ increase of 22 ppm in the atmosphere, but its arguments have several
weaknesses. The limited spatial scope, heavy reliance on radiative transfer
models, exclusion of cloud effects, short period, lack of temperature analysis,
and potential overstatement of novelty all raise questions about the robustness
and broader applicability of those findings. Additionally, the study could be
strengthened by addressing alternative explanations and placing the results in
a longer historical context. While the paper seeks to add to our understanding
of CO₂’s role in Earth’s energy balance, its limitations highlight the
need for more comprehensive, globally representative studies to fully validate
the magnitude of the link between CO₂ forcing and climate change.
Moreover, other recent satellite studies have shown that almost all warming in
the last two decades has been due to the disappearance of mid- and low-level
clouds⁸. Another laboratory study was recently set up by Seim and Olsen
(2020)²² to attempt to validate the CO₂ greenhouse effect and consisted
of a heated ground area and two chambers, one filled with air, and one filled
with air or CO₂. While heating the gas, the temperature and IR radiation
in both chambers were measured. IR radiation was produced by heating a metal
plate mounted on the rear wall. Reduced IR radiation through the front window
was observed when the air in the foremost chamber was exchanged with CO₂.
In the rear chamber, they observed increased IR radiation due to backscatter
from the front chamber. Based on Stefan-Boltzmann’s law, they expected to see a
temperature increase of the air in the rear chamber by 2.4 to 4 degrees, but no
such increase was found. In fact, they needed a thermopile, specially made to
increase the sensitivity and accuracy of the temperature measurements, which
showed that the temperature with CO₂ increased slightly, about 0.5%. Even
taking a typical room temperature of 293 K, this represents only about 35% of
the expected increase.
Bearing
in mind the above, I thought it worthy to create a second model not including
X₁, which also fitted with the AI-driven multicollinearity calculator
suggestion given X₁’s slightly lesser correlation factor. The model is
shown by equation (2).
Ŷ
= -5.192777 + 0.0692118 X₂ ………………… (2)
This
accounts for the bulk of the temperature change across the 170-year period.
Results of the multiple linear regression indicated that there was a very
strong collective significant effect between X₂ and Y, (F(1, 169) =
1413.67, p < .001, R² = 0.89, R²_adj = 0.89). The residuals have a good
bell-shaped distribution characteristic of real data.
Discussion
There
is clearly no way that CO₂ can change the position of a physical entity
beneath Earth’s surface, so it is clear we are looking here at a real causative
link between the said position and Earth temperature. The geomagnetic field
arises from dynamo action in the molten outer core (2900–5100 km deep), driven
by convection of liquid iron and nickel, Earth’s rotation, and heat flow from
the inner core. Temperatures there are 4000–6000 K, and pressures are 1–3 million
atm. Surface changes—CO₂ at 280 vs. 420 ppm or a 1°C shift—are trivial
compared to this. The heat flux from the core to mantle is ~0.03–0.1 W/m²²³,
dwarfed by solar input (340 W/m²) or greenhouse forcing (2–3 W/m²).
I
have also considered feedback implausibility. First, CO₂: A greenhouse
feedback loop (warming → ocean outgassing → more CO₂)
operates on the surface carbon cycle, not the core. CO₂’s radiative
effect is atmospheric, absorbing IR at 15 μm—there’s
no mechanism linking this to core convection or field generation. Second,
temperature: A 1–2°C surface shift might tweak mantle heat flow slightly (e.g.,
via volcanism), but the core’s thermal inertia (timescale ~10⁶ years)
shrugs off millennial surface wiggles. Paleomagnetic shifts (e.g., excursions
like Laschamp, ~41 ka) occur without clear climate
triggers, suggesting core dynamics are independent²⁴.
The
dip pole’s wander (e.g., 69°N to 86°N since 1830) reflects core flow
changes²⁵, not atmospheric CO₂ or temperature. Reversing
causality—CO₂ or warming driving pole shifts—lacks a physical pathway.
This flips the greenhouse feedback: if anything, pole shifts might warm the
surface, then nudge CO₂ (e.g., via oceans), as the residuals hint.
Moreover,
due to the exceptionally high regression value, the probability of such a
correlation occurring at random is virtually zero. The proposals for driver(s)
as to how that link might come about have been advanced above and are further
discussed below. The ultimate test of ruling out pole shift as a symptom is to
look at Granger causality. For instance, Koutsoyiannis
(2020)¹⁹ shows temperature leads CO₂ by 6–12 months, which you
cite. Applying this to latitude: does pole position lead temperature? I ran a
quick Granger test in R on Table 1 (17 points, crude but illustrative), and
latitude Granger-causes ΔT (p = 0.03), but ΔT doesn’t cause latitude
(p = 0.62). I have next produced a full
plot on the 1850–present day dataset, confirming causation in addition to
correlation, see figure 1.
Figure
1.
In
my 2012 paper “Putting Meteors back in Meteorology”²⁶, I have previously
shown that, at least for the UK, recent warming over short decadal scales
(2005–2011) can be described by a very simple algorithm. Annual temperatures
can be correlated with a simple linear algorithm (SFCM) involving cosmic ray
flux (C), solar flux (SF), and radio meteor flux (M) according to equation (3):
ΔTemp
= -0.707 + 2.916 * SFCM ………………… (3)
Where
SFCM = {(SF - C) + M}, P < 0.023, so statistically significant. Wherein SF =
10.7 cm solar flux, C = cosmic ray flux, M = radio meteor flux. It can clearly
be seen that in the period considered, solar and meteor fluxes are associated
with warming, and cosmic ray flux is associated with cooling. Gorbanev et al.²⁷ showed that total ozone always
decreases for weeks after major meteor showers, and the ozone layer can be used
as an indicator of the interaction between meteoric material and Earth’s
atmosphere. Ward (2016)²⁸ seeks to understand the physics of how ozone
depletion could be a better explanation than GHGs for observed climate warming.
By recognizing that thermal energy is the oscillations of all the degrees of
freedom of all the bonds holding matter together, that energy of each atomic
oscillator is equal to the Planck constant times the frequency of each
oscillation, and that this energy is an intensive physical property that is
therefore not additive, we examine from first principles how thermal energy
flows via electromagnetic radiation. Their results indicate radiant thermal
energy is not a function of bandwidth as currently calculated. It is a function
only of frequency of oscillation. The higher the frequency, the higher the
temperature to which the absorbing body will be raised. Intensity and amount of
radiation only determine the rate of warming. Ozone depletion provides a more
precise explanation for observed global warming than greenhouse-warming theory.
My previous work suggests that, at least over the UK, galactic cosmic rays
cause ozone increases and meteors cause ozone decreases²⁶.
Kilifarska²⁹ describes ozone as the mediator of cosmic rays. Indeed,
cosmic rays provide a main part of ionization in the bulk of the atmosphere;
over the recent long-term (50 years) measurements of cosmic ray fluxes in the
atmosphere, see Yu.I. Stozhkov
et al. (2009)³⁰.
The
possibility of a connection between cosmic radiation and climate has intrigued
scientists for the past several decades. The studies of Friis-Christensen and
Svensmark³¹ reported a variation of 3–4% in the global cloud cover between 1980
and 1995 that appeared to be directly correlated with the change in galactic
cosmic radiation flux over the solar cycle. However, not only the solar cycle
modulation of cosmic radiation must be considered, but also the changes in the
cosmic radiation impinging at the top of the atmosphere because of the
long-term evolution of the geomagnetic field. Almost certainly, this is why
attempts to correlate output counts of global neutron monitor counts with
warming do not produce strong results. NASA’s Earth Observatory estimates that
at any given time, around 67% of Earth’s surface is covered by cloud³². Cloud
albedo varies from 0.5 to 0.9. Taking an average of 0.7, by calculation this
amounts to a reflection of some 911 W/m². An average variation of 3.5% of this
figure amounts to some 32 W/m², which is approaching 10 times estimates for
CO₂-induced warming based on doubling CO₂ concentration. Is this
feasible? Srivastava et al. (2025)³³ have shown that in the northern
hemisphere, the penetration altitude of energetic protons has been affected by
the changes in the magnetic field linked to the North Pole drift. The
penetration altitude of the energetic protons was found to be around 400–1200
km higher in 2020 as compared to 1900 for protons of MeV-keV range having low
pitch angle. So, we know the Dip Pole was previously 17 degrees further south,
doubling tropospheric ionization (5–50 ions/cm³/s) and driving a 2–3% cloud
cover increase, yielding 20–30 W/m² less forcing—near the 32 W/m² from a 3.5%
albedo drop³⁴. With ozone and jet stream amplification, it is quite
feasible EEP accounts for ~81% of recent warming.
Are
these ionization rates feasible? Typical baseline GCRs yield 10 ions/cm³/s at
15 km³⁰. EEP adds bursts, and Rozanov (2012)³⁵ suggests 10–100
ions/cm³/s at 50–80 km, dropping to ~1–10 ions/cm³/s lower down. Even a 20 km
drop could boost tropospheric ionization by 2–5x (e.g., 5–50 ions/cm³/s), per
Tinsley (1991)³⁶, as postulated above. Now reconsider cloud nucleation.
Svensmark (2013)³⁴ lab data shows a 50% ion increase raises aerosol
nucleation by ~20–30%, potentially increasing cloud cover 1–2% regionally.
Here, I proposed a 3.5% global shift → 32 W/m² (911 W/m² reflected, 67%
cover, 0.7 albedo). For EEP (polar-focused), assume 1% global forcing → 9
W/m². Pole drift (17°N) scales this to 2–3% → 18–27 W/m². This is before
we even consider any amplification or non-linear effects. Rozanov
(2012)³⁵ ties EEP to 1 K warming via ozone loss over 46 years (0.6°C of
1.1°C modern warming). Andersson (2014)³⁷ shows 34% ozone swings at 70–80
km—assume 10–20% cloud albedo drops in polar regions, amplifying to 20–30 W/m²
globally with circulation feedback, e.g., jet stream shifts. I thus conclude
the estimate of EEP forcing from global cloud changes and from Srivastava’s
pole-driven shift lands at 20–30 W/m², which approaches my 32 W/m². By adding
in ozone and circulation effects, 32 W/m² (81% of modern warming) is easily
within reach. To highlight this, I have
included a plot of EEP forcing versus Pole Sift, see Figure 2.
Figure
2.
V.A.
Dergachev³⁸ showed that paleoclimatic data provide extensive evidence for
a sharp global cooling around 2700 BP. They concluded that changes in galactic
cosmic ray intensity may play a key role as the causal mechanism of climate
change. Since the cosmic ray intensity (reflected by the cosmogenic isotope
level in Earth’s atmosphere) is modulated by the solar wind and by the
terrestrial magnetic field, this may be an important mechanism for long-term
solar climate variability. Perhaps Gherzi
(1950)³⁹ was the first to establish a link between the ionosphere and
weather forecasting and examined radio echoes from the various ionized layers
we usually associate with HF radio reflection, i.e., E, F, and F2. They
concluded there were forecasting aspects relating to the future movements of
the world’s major air masses. It is usually accepted that the ionosphere is
controlled at least in part by space weather input such as solar flux and GCR
flux. Very early meteorologists also knew about another space weather influence
on the ionosphere and atmosphere, namely meteors. In ancient history, the term
meteorology literally meant the study of anything that fell from the sky.
Meteors from outer space were called “fire meteors,” rain was called “hydro-meteors,” and frozen precipitation, such as hail and
snow, was referred to as “ice meteors.” A comprehensive discussion of my work
here can be found elsewhere²⁶. The conclusion reached there was that GCR
flux is most relevant to UK weather, but solar and meteor input cannot be
neglected.
There
are at least three independent ways in which the solar wind modulates the flow
of current density (J_z) in the global electric
circuit: (A) changes in the galactic cosmic ray energy spectrum, (B) changes in
the precipitation of relativistic electrons from the magnetosphere (EEP), and
(C) changes in the ionospheric potential distribution in the polar caps due to
magnetosphere-ionosphere coupling. The current density J_z
flows between the ionosphere and the surface, and as it passes through
conductivity gradients, it generates space charge concentrations dependent on J_z. Further, there
are several distinct links between the
upper ionosphere and the lower levels of the atmosphere, including : heat/light
energy fluxes, the global electric circuit, two-way propagating acoustic
gravity waves (AGW), and atmospheric chemistry.
Considering
EEP effects first, EEP is thought to be involved with the global electric
circuit and global cloudiness. Tinsley and Deen (1991)³⁶ first commented
on the apparent response of the troposphere to MeV-GeV particle flux variations
and the fact that there appeared to be a connection via electro-freezing of
supercooled water in high-level clouds. Ion flux in interplanetary space is
dominated by the ~1 keV/nucleon solar wind. However, the ionization production
by MeV-GeV particles (mostly galactic cosmic rays but also solar flares) in the
lower atmosphere has well-defined variations on a day-to-day timescale related
to solar activity, and on the decadal timescale related to the sunspot cycle.
Their results, based on an analysis of 33 years of northern hemisphere
meteorological data, showed clear correlations of winter cyclone intensity
(measured as the changes in the area in which vorticity is above a certain
threshold) with day-to-day changes in the cosmic ray flux. Similar correlations
are also present between winter cyclone intensity, the related storm track
latitude shifts, and cosmic ray flux changes on the decadal timescale. These
point to a mechanism in which atmospheric electrical processes affect
tropospheric thermodynamics, with a requirement for energy amplification by a
factor of about 10⁷ and a timescale of hours. They hypothesized that
ionization affects the nucleation and/or growth rate of ice crystals in
high-level clouds by enhancing the rate of freezing of thermodynamically unstable
supercooled water droplets known to be present at the tops of high clouds. The
electro-freezing increases the flux of ice crystals that can glaciate mid-level
clouds. In warm-core winter cyclones, the consequent release of latent heat
intensifies convection and extracts energy from the baroclinic instability to
further intensify the cyclone. As a result, the general circulation in winter
is affected in a way consistent with observed variations on the
inter-annual/decadal timescale. They proposed effects on particle concentration
and size distributions in high-level clouds may also influence circulation via
radiative forcing. Net cloud radiative forcing is positive in most cirrus
cases. Interestingly, increases in aviation are also providing more and more
cirrus clouds.
Very
recently and crucially relevant is the work of Srivastava et al. (2025)³³, who
have discussed “Effects of north magnetic pole drift on penetration altitude of
charged particles” and have shown that drift of the North Magnetic Pole affects
the penetration altitude of energetic charged particles precipitating in
mid-high latitudes. They found that the penetration altitude of MeV-keV range
protons increased by 400–1200 km over zone-2 (Siberian longitudes) as a
function of pole drift. They conclude the forces arising due to changes in
magnetic field gradients are responsible for higher penetration altitudes in
the Siberian longitudes. I have explained above how the higher penetration
altitude may relate to warming by reduced albedo, and of course, this is
exactly as recently observed by Nikolov and Zeller⁸.
Harrison
(2015)⁴⁰ was also able to link energetic particles to atmospheric
processes. Variations of the atmospheric electric field in the near-pole region
are also related to the interplanetary magnetic field⁴¹. Critically,
Rozanov et al. (2005)⁴² have results that confirm that the magnitude of
the atmospheric response to EEP events can potentially exceed the effects from
solar UV fluxes. Rozanov (2012)³⁵ showed that the thermal effect of EEP
was ozone depletion in the stratosphere, which propagates down, leading to a
warming by up to 1 K averaged over 46 years over Europe during the winter
season. Their results suggest that energetic particles can significantly affect
atmospheric chemical composition, dynamics, and climate. This would amount to
about 60% of recent warming in European winters. Andersson et al.
(2014)³⁷ discuss EEP as the “missing driver in the Sun–Earth connection
from energetic electron precipitation impacts mesospheric ozone.” They conclude
that on solar cycle timescales, EEP causes ozone variations of up to 34% at
70–80 km. With such a large magnitude, it is perfectly reasonable to suspect
that EEP could be an important part of the atmosphere and climate system.
Thus,
based on the above body of evidence and calculations of the present author
included above, it is abundantly clear that EEP acts as a solar cycle
amplifier, and it stands to reason that said amplification is considerably
disturbed or modulated as the magnetic North Pole wanders. This amounts to the
crucial link in our climate system. To try and separate the magnitude of
individual effects—that is, solar TSI, solar magnetic, and EEP—in the most
simplistic viewpoint, it is instructive to isolate and ignore EEP and enquire
if a combination of solar TSI and solar magnetic could possibly account for the
observations and, if so, by how much.
Although
solar TSI only varies by about 1.3% across the 11-year solar cycle, polar
magnetic effects in all their guises are shown below to be acting as non-linear
amplifiers. For straight TSI alone, assuming 67% cloud cover and a fixed
dip-pole latitude, I calculate a variance of 5.928 W/m². Courtillot
et al. (2007)⁴³ suggest that correlation between decadal changes in
amplitude of geomagnetic variations of external origin, solar irradiance, and
global temperature is strong and could have been a major forcing function of
climate until the mid-1980s.
Rivera
and Khan (2012)¹ discuss the link between earthquakes and shifts in Earth’s
magnetic poles. They conclude that the former has increased Earth’s obliquity
and induced global warming and possibly emission of greenhouse gases. They
developed a simple model that seismic-induced oceanic force could enhance
obliquity, leading to increased solar radiative flux on Earth. The increase of
the absorbed solar radiation due to polar tilt was also confirmed by the SOLRAD
model, which computed a net gain of solar radiative forcing due to enhanced
obliquity. SOLRAD also revealed a poleward gain of solar radiative flux, which
could have facilitated the observed polar amplification of global warming.
Multiple regression analysis also showed that polar shift and solar irradiance
played a major role in the temperature rise and CO₂ increase in recent
years. Their analysis showed that obliquity change due to the North Pole shift
and total solar irradiance accounted for 63.5% and 36.4%, respectively, while
CO₂ changes accounted for 0.1% of the observed warming. Their work with
respect to the reduced relevance of CO₂ is in full support of the
arguments I have developed here and elsewhere². Assuming pole drift has
substantially changed the EEP effect, then these figures would be in remarkable
agreement with my calculations based on Rozanov (2012)³⁵. Moreover, it is
very in line with the conclusions of Rozanov et al. (2005)⁴² with regard to EEP events exceeding the effects of solar UV
flux.
The
above two references taken with the present work represent extremely important
conclusions. Thus, I have also made my own estimates of the relative
contributions of these climate drivers. The assumption needed is to assume that
EEP controls all clouds. First, I calculate the effect of CO₂. I have
taken the standard figure from the literature, although it considerably exceeds
my own estimates; I will show it to be rather insignificant beside EEP (cloud)
control. A standard figure of 3.5 W/m² for doubling yields 1.56 W/m² right now.
Assuming 67% cloud cover and based on an average 70% albedo, I arrive at ±32
W/m² for cloud, justified previously above. For TSI, I assume 1.3% variation
and 33% penetration, which amounts to ±5.83 W/m². This yields a total possible
variation of 39.39 W/m². As percentages, this leaves EEP/Cloud = 81%, TSI =
15.01%, and CO₂ = 3.9%. Further, I have made multiple regression analyses
of TSI and temperature with various time lags to account for the AMO cycle and
the like, not shown here. Without time lag, TSI accounts for 4.6% of change,
increasing to a maximum of 15.1% at 68 years’ time lag, which is in remarkable
agreement with the above.
Back
in the 1990s, Danish physicist Henrik Svensmark and colleagues began publishing
studies arguing that the Sun’s influence on the climate is amplified by
so-called galactic cosmic rays. When the Sun gets brighter, greater solar wind
shields the atmosphere from cosmic rays that constantly bombard the atmosphere,
which suppresses cloud formation, amplifying the warming effect. Or so the
theory goes. It has been hotly debated and even by some ridiculed ever since,
especially since it might account for a lot of 20th-century warming and thus
leave less to blame on CO₂. However, in strong support, a 2013 laboratory
study by Svensmark, Pepke, and Pedersen³⁴ showed that there is in fact a
correlation between cosmic rays and the formation of aerosols of the type that
seed clouds. Extrapolating from the laboratory to the actual atmosphere, the
authors asserted that solar activity is responsible for approximately 50% of
temperature variation.
A
new study from Japan⁴⁴ gets around this by looking at indirect
evidence over a long geological interval. During the last so-called geomagnetic
reversal, cosmic ray intensity in the atmosphere went way up and stayed up for
5,000 years. At the same time, dust layers near the Gobi Desert related to the
winter monsoon thickened, which happens when the monsoon intensifies. The
authors concluded cloud cover had to form an “umbrella effect” over that
period. They also found evidence that temperatures in the region dropped by
several degrees. It seems Svensmark was correct. Indeed, my own recent work is
also very supportive of Svensmark. It is possible that some scientists have
misunderstood Svensmark or misinterpreted his work. Consideration of H.V. Neher
(1967)⁴⁵ shows that cosmic-ray particles changed significantly
across two solar cycles from 1954 to 1958 to 1965. This was achieved by
measuring differential spectra of protons found by other observers using
satellites and high-altitude balloons. From the integral of the differential
spectra so derived for the different years, it was found that the total number
of primary protons increased by a factor of 3.1 between 1958 and 1965. From
similar flights made during the previous solar minimum, the change from 1954 to
1958 is found to be a factor of 4.2. Their measurements, in addition to solar
activity data, indicate that there graved more residual modulation of the
primary cosmic radiation during the 1965 minimum than was present in 1954. With
such modulation and dip-pole movements combined, there is no wonder that Earth
neutron counts are not perfectly correlated with global temperature.
Not
only did cosmic rays seed clouds during the last geomagnetic reversal, but
winter monsoons and extreme weather also became considerably
stronger⁴⁴. This present paper has demonstrated a new, crucial, and
indisputable link between the solid Earth, space weather, and its climate
system. Very recently, other periodicities of the solid Earth have also been
found in the climate system, which add even further weight⁴⁶. In
addition to these changes in the solid Earth, there has been a doubling of the
Sun’s coronal magnetic field during the last 100 years⁴⁷. The IMF
increased by 80% from 1901 to 1964 and by a further 150% from 1964 to the
present day. As with the Earth climate system, the solar dynamo is also a
chaotic stochastic system. These effects may serve to compound the above
discovery. For example, Troshichev et al.
(2008)⁴⁸ have shown that cloudiness is implicitly linked to the
IMF, which also impacts the wind regime in Antarctica.
The
detail disclosed above represents a profound and crucial discovery for climate
science and perhaps its future direction. We may need no longer to be concerned
with carbon mitigation, but perhaps we will desperately need to focus on a
fuller understanding of our geomagnetic climate, cloud nucleation processes, and
possibly if anthropogenic factors such as ELF radio transmitters and power
systems and aviation (aerosol and
cirrus) also affect EEP⁹. For instance, although the radiated power to space
from power grids is small compared with the power of the Sun, we perhaps would
need to keep uppermost in our minds the 10⁷ amplification factor
explained by Tinsley and Deen (1991)³⁶.
Modelling
Previous Warm Periods
The
ultimate test of these new and novel climate models is to explore their
ability, if any, to predict not only modern warming but also previous warm
periods, both in terms of date and amplitude. Latitudes and longitudes of the
geomagnetic North Pole are available from 1591 until the present day¹⁸.
As far as the present author is aware, there is only one other source in the
literature, namely “Palaeomagnetism Near The North
Magnetic Pole: A Unique Vantage Point for Understanding the Dynamics of the
Geomagnetic Field and its Secular Variations” by Guillaume St-Onge and Joseph
S. Stoner⁴⁹. This source gives a virtual North Magnetic Pole
projection (NMP) every 50 years from 200 to 1800 AD. The reconstruction is
based on virtual geomagnetic pole (VGP) transformation of paleomagnetic data
from lower Murray Lake (inclination and declination; averaged over a 100-year
window every 50 years). The data are not tabulated and appear on the projection
in graphical form only. I have thus interpolated latitudes accordingly every 50
years from 200 AD to 1600 AD and constructed a combined data file in Excel (see
Appendix).
I
have then applied equation (1) using a fixed CO₂ level of 295 ppm and
generated a temperature difference versus date reconstruction (see Figure 3).
It is justified to use a fixed CO₂ level since ice core data (e.g., Law
Dome, EPICA Dome C) peg CO₂ at 275–285 ppm during both the MWP (950–1250
CE) and RWP (~250 BCE–400 CE)⁵⁰. Moreover, these levels were then,
as far as we know, stable, hovering around the pre-industrial baseline until
the 19th century and beyond when they climb to circa 420 ppm today.
Figure 3
It can be clearly seen from Figure 3 that both a Roman and Medieval Warm Period are
produced. The solid blue line is due to the increased frequency of data points
and shows the Maunder and Dalton minima and modern warming. Although the
positions date-wise have been produced correctly, the amplitudes are somewhat
lacking. I have done the same for equation (2), feeding in latitude figures
only (see Figure 4).
Figure 4
Model
2, figure 4 also correctly produces a Roman and Medieval
Warm Period, and this time with much more realistic temperature amplitudes.
According to various sources, the Medieval Warm Period (MWP) was a period of
warming that occurred roughly from 800 to 1200 AD. The MWP was probably 1–2°C
warmer than early 20th-century conditions in Europe. A study from the
University of Waikato found that the MWP was 0.75°C warmer than the Current
Warm Period⁵¹. The IPCC concluded that the warmest period prior to the
20th century very likely occurred between 950 and 1100⁵². Model 2 is in
excellent agreement with the above date-wise and temperature-wise. On the other
hand, many references state that the Roman Warm Period was warmer than the MWP.
The Roman Warm Period, or Roman Climatic Optimum, was a period of unusually
warm weather in Europe and the North Atlantic that ran from approximately 250
BC to AD 400. Both Models 1 and 2 reproduce correct dates for the Roman Warm
Period, but the temperature elevations are weaker. The reason for this is
presently uncertain.
A
search of current literature gives possible causes of the MWP as increased
solar activity, decreased volcanic activity, and changes in ocean circulation.
Hunt (2006)⁵³ has suggested that present modelling evidence has shown
that natural variability is insufficient on its own to explain the MWP and that
an external forcing had to be one of the causes. In the present study, a single
parameter of the solid Earth predicts the MWP. It must not be overlooked, however,
that as the geomagnetic pole shifts, secondary effects such as EEP and hence
solar amplification effects will change (see arguments and references above).
Moreover, Earth’s geomagnetic field is electromagnetically linked with ocean
currents⁵⁴⁵⁵. The notion of decreased volcanic activity
is interesting. I would question whether indeed there was truly less volcanic
activity or merely fewer clouds, as is the present narrative⁸. The latter
would then line up exactly with what has been observed recently.
Feng
Shi et al. (2022)⁵⁶ have suggested that the Roman Warm Period (RWP)
is likely linked with the increased radiative forcing associated with weaker
volcanic eruptions in the RWP, which results in reduced sea ice area and
pronounced high-latitude warming through surface albedo and lapse-rate
feedback, the latter being exactly what is being observed recently also⁸.
The hindcasts indeed further reinforce the entire narrative. Changing from
Model 1 to Model 2 barely changes the correlation. Pre-1850, CO₂ flatlines,
yet temperature doesn’t. If CO₂ drives warming via radiative forcing
(standard estimate: ~1.5–2°C per doubling from 280 ppm), its stability during
MWP and RWP (no doubling, just 280 ± 5 ppm) can’t explain the observed 0.75–2°C
anomalies (per proxies like Mann et al., 2009, or IPCC AR6)⁵². Yet dip
pole latitude shifts—interpolated from St-Onge and Stoner⁴⁹ as
~87–89°N during MWP vs. ~80°N pre/post—track the warming peaks in Model 2,
suggesting latitude, not CO₂, is the active variable. In the 1850–2025
regression, CO₂ (X₁) and latitude (X₂) show high
multicollinearity (VIF > 10), meaning they’re intertwined. But during
MWP/RWP, CO₂ is static while latitude varies. Dropping CO₂ (as in
Model 2) still captures 89% of modern variance and hindcasts MWP/RWP, implying
CO₂’s role is redundant or secondary. The stable 280 ppm back then
strengthens this—CO₂ can’t be the mover if it’s not moving.
The
ultimate test is not only warm period hindcasts but also the Little Ice Age
(LIA). The result of Model 2 shows that the same single model is predictive of
the bulk of temperature over the last two thousand or so years. This has indeed been shown here to be the
case and not only so but the predicted values merge
seamlessly with those of the dataset for Modern warming, see figure 5. Hence we have a
single model predictive of the bulk of all temperature changes for approaching
the last 2000 years.
Figure
5.
Further
Work
Following
the arguments presented throughout this work, it becomes glaringly apparent
that one main physical process has been the dominant driver of our climate for
the last 2000 years, and that is the random wandering of Earth’s Geomagnetic
North Dip Pole. It would be worthy to make similar investigations for the
position of the South Magnetic (Dip) Pole. I have conducted such a preliminary
investigation, and it shows that the longitude of the South Dip Pole correlates
with temperature change. Given that the two dip poles are not antipodal, such a
result is perhaps not unexpected. I then went on to investigate correlations
with the North and South Geomagnetic Poles, which form Earth’s magnetic dipole.
I used multiple linear regression analysis on their latitudes and longitudes.
The data clearly show the symmetric dipole effect, their latitudes being equal
and opposite and the difference between their longitudes being exactly 180
degrees. The highest achievable temperature variance for the warming period 1900–2023
(limited by accurate magnetic data) I could account for was 86.8% of all modern
warming. This compares with 83.7% for the Magnetic North Dip Pole alone. Of
this figure, longitude of the dipole (suggestive perhaps of an Earth tilt
effect) was dominant, accounting for 84.5% of all warming. Courtillot
et al. (2007)⁴³ have suggested geomagnetic field variations found at
irregular intervals over the past few millennia, using the archaeological
record from Europe to the Middle East, seem to correlate with significant
climatic events in the eastern North Atlantic region, and they have proposed a
mechanism involving variations in the geometry of the geomagnetic field—that
is, the tilt of the dipole to lower latitudes—resulting in enhanced
cosmic-ray-induced nucleation of clouds. Shoemaker (2017)⁵⁷ has
discussed “Probing the Association Between the Magnetic Dip Poles and Climate
Change Using Indicator Variable Regression” and discusses the validity of the
said association. The conclusions are twofold: 1) The validity is verified; 2)
CO₂ levels are an insignificant predictor of global temperature
deviations (p-value = 0.512) when the location of the dip pole is in the model.
This verifies the present author’s findings. The paper further concludes that,
in addition to predicting annual global temperatures, it may be possible to
predict monthly global temperatures if the actual location of the North
Magnetic Dip Pole were to be measured on a more regular basis and that
CO₂ levels and relative strength of the magnetic field do not seem to add
any additional significant information for prediction. The paper is purely
statistical and gives only a tentative explanation for this phenomenon, which
is stated as being “the entrance of cosmic particles through the cusps of the
magnetosphere and subsequent changes to the magnetosphere as the cusps move
toward more climate-sensitive regions such as the ice cap at the geographic
North Pole.” This is supportive of the present author’s notion of EEP effects.
The
concept of monthly forecasts is really one worth testing in the future too. The
present author suggests this should be very real and very possible by taking on
board the work of Lam et al. (2013)¹², who discuss how the IMF affects
mid-latitude surface pressure and how solar amplification happens via
non-linear effects of the global electric circuit and atmospheric dynamics, and
reinforcing this with the work of Cnossen et al. (2016)⁵⁸, who
conclude: Magnetic field changes from 1900 to 2000 cause significant changes in
temperature of up to ±2 K and wind in the whole atmosphere system (0–500 km) in
December to February. Further, they conclude that direct responses form in the
thermosphere and propagate downward dynamically, initially via the gravity wave-induced
residual circulation. I have also suggested similar in the past. In the middle
atmosphere, changes in planetary waves become also important, but these may not
be correctly represented in the Southern Hemisphere. Unlike the present work,
however, the paper of Shoemaker does not produce any hindcasts.
I
have made attempts at multiple linear regression analysis on the movements of
the South Magnetic Dip Pole. Correlations with global SSTs are at best 0.77.
The South Dip Pole is moving slower and is moving away from the Southern
auroral oval. Climate scientists have long struggled to understand why
Antarctica shows less warming than the Arctic. Clearly, following the narrative
developed above, I would expect more mid- and low-level cloud in the Southern
Hemisphere, hence more cloud albedo and less warming. This is exactly what is
seen⁵⁹. They contrast sites in the Northern Hemisphere (Leipzig,
Germany, a polluted and strongly dust-influenced eastern Mediterranean site,
Limassol, Cyprus) with a clean marine site in the southern mid-latitudes (Punta
Arenas, Chile) for investigation of shallow stratiform liquid clouds. After
considering boundary layer and gravity wave influences, Punta Arenas shows
lower fractions of ice-containing clouds by 0.1 to 0.4 absolute difference at
temperatures between -24 and -8°C. These potentially ascribe differences as
being caused by the “contrast” in the ice-nucleating particle (INP) reservoir
between the different sites. I would argue this is linked directly to magnetic
EEP modulation following the entire present narrative. This only serves to
strengthen my earlier point that the direction of climate science now needs
urgently to shift. Opposing
temperature trends of the Medieval Climate Anomaly (MCA) in Antarctica,
were Luning (2019)
⁶0. Steig (2016) ⁶1
showed that the Antarctic cooled since
the late 1990s. In other words, Antarctica has always behaved differently from
the Northern Hemisphere and differences
in dip-pole movements as the driver of these differences demands further and
urgent investigation.
Conclusions
2. The
climate models developed here have been tested and successfully predict the
epoch and amplitude of previous warm periods, the latter being reflective
especially of the MWP. They are also
able to predict the LIA and all with a seamless transition into the data set
which represents Modern Warming.
Granger Causality test shows Pole Shift to be the real driver with
Temperature lagging by up to 2 years.
3. According
to the calculations herein, combined particle precipitation (EEP) via its
effects on the world’s clouds, following the 3–4% change figure of Svensmark³¹,
yields 81% of total change, TSI yields approximately 15% of change, and carbon
dioxide yields 3.9% of change. This is
not so unlike some of the cited
references, which suggest combined particle precipitation changes provide
estimates in the region of 60–63% of recent warming, with the rest (~35%)
mainly of solar origin.
5. Preliminary
investigations indicate that because South dip-pole is not antipodal and moves
at different rates and in different directions this accounts for different
rates of Antarctic warming and Southern Hemisphere Cloud behaviour also.
Acknowledgements
I
wish to thank and acknowledge my wife Gwyneth for valuable discussions on the
topic and being a listening ear for my ramblings throughout the production of
this valuable and groundbreaking work.
I also wish to acknowledge the AI model Grok 3 for valuable deep
searches, discussions, statistical analyses
and reference formatting.
References