Tag Archives: Solar Activity

How we know the sun changes the climate. III: Theories

From Climate Etc.

By Javier Vinós

Part I in this series on the Sun and climate described how we know that the Sun has been responsible for some of the major climate changes that have occurred over the past 11,000 years. In Part II, we considered a range of changes that the Sun is causing in the climate today, including changes in the planet’s rotation and in the polar vortex that are changing the frequency of cold winters.

None of the evidence for the Sun’s effect on climate we reviewed is included in the IPCC reports. The role of the IPCC is to assess the risk of human-induced climate change, not to find the causes of climate change, which since its inception has been assumed to be due to our emissions.

  1. Main solar theories

Nevertheless, some scientists continue to try to explain the Sun’s effect on climate and have developed three different explanations. These three theories are not mutually exclusive. The fact that one is true does not mean that the others are false.

The first theory is based on the direct effect on climate of changes in solar radiation. Because the effect is proportional to the cause, we say it is linear.

This theory has been defended by Dr. Soon, Prof. Scafetta and 35 other scientists in a recent paper.[i] To explain the Sun’s effect on climate, these scientists make their own temperature reconstruction, based on rural stations to avoid the urban heat effect, and their own reconstruction of solar activity over the last two centuries. Figure 1 left shows their reconstruction compared to the one accepted by the IPCC on the right. The differences between the two would explain a much larger effect of the Sun on climate than that accepted by the IPCC.

Figure 1. Left graph shows in black a temperature reconstruction using only rural stations from four regions in NOAA’s GHCN dataset, and in orange a high variability solar series. Right graph shows in black a temperature reconstruction with urban and rural stations and in orange an IPCC’s AR6 recommended solar series (from Soon et al. 2023).

In the second theory, it is cosmic rays that change the climate, and the Sun’s magnetic field regulates the number of cosmic rays that reach the Earth. It is therefore an indirect effect, but also a linear one, since the change in cosmic rays would be proportional to the activity of the Sun.

This theory, proposed by Dr. Svensmark, is based on the fact that cosmic rays create ions in the atmosphere that act as cloud seeds.[ii] Part of the theory has been confirmed by experiments in a particle accelerator, but it is not yet known whether the effect is significant enough. One problem is that cosmic rays have increased while satellites show a decrease in the low cloud layer, which may actually contribute to the observed warming.

Figure 2. Percentage cloud cover anomaly (black) from EUMETSAT CM SAF dataset. Cosmic ray data (red) from the Oulu neutron monitor database.

The third theory is the one I have proposed.[iii] In it, the Sun acts indirectly on the climate, and its effect is non-linear because other factors are involved. Non-linear means that the effect is not proportional to the cause. This explains why there is no direct correlation between the Sun and surface temperatures, although the Sun’s effect is important. What is this process, capable of changing the climate in a natural way, that scientists have not properly accounted for? It is heat transport.

Figure 3. Three main types of solar theories based on the direct or indirect effect of different components of solar variability. Less developed hypotheses based on solar particles and solar wind have also been proposed.
  1. Changes in heat transport change the climate

What is heat transport?

Most of the Sun’s energy reaches the Earth in the tropics, creating a zone of excess energy that receives more energy than it emits, shown in red in Figure 4. Outside the tropics, there are two energy deficit zones, which receive less energy than they emit and whose size depends on the seasons. They are shown in blue in Figure 4, which presents the situation during winter in the Northern Hemisphere. These imbalances should result in continuous warming in the red zone and continuous cooling in the blue zones. That this does not happen is due to the transport of heat, which also transports moisture and clouds, and is very important for the climate. The climate of any region depends on insolation and the transport of heat and moisture.

Figure 4. Actual graphic of the mean top of the atmosphere net radiation by latitude for December-February, showing positive values in red and negative values in blue, placed in a cartoon showing the Earth’s tilt with respect to the Sun. The direction of heat and moisture transport is shown with purple arrows.

Heat transport is a particularly difficult climate process to study and some scientists who research it believe current theories do not satisfactorily describe it.[iv] The seasonal variation in heat transport is very important. Because of the tilt of the planet’s axis, much more heat is transported in the winter than in the summer.

In the first chapter of the 6th Assessment Report, the IPCC provides a clear explanation of climate change, defining its causes as follows: “The natural and anthropogenic factors responsible for climate change are known today as radiative ‘drivers’ or ‘forcers’. The net change in the energy budget at the top of the atmosphere, resulting from a change in one or more such drivers, is termed ‘radiative forcing’.” According to the IPCC, heat transport is not considered a radiative forcing and, therefore, not a cause of global climate change. Its effects only contribute to internal or regional variability. This perspective is reflected in the limited attention given to heat transport in the IPCC reports. In the massive 2,391-page 6th Assessment Report, heat transport is only briefly mentioned in a 5-page subsection on ocean heat content.[v] In this subsection, we learn that climate change is due to heat addition, while changes in ocean circulation cause heat redistribution.

To the IPCC, variations in heat transport have not contributed to recent climate change because they only redistribute heat within the climate system, while recent climate change is due to heat being added to the system. Therefore, heat transport cannot cause global climate change, only regional changes.

Figure 5. The first objection to changes in heat transport being a cause of climate change is incorrect because the greenhouse effect is very uneven, so emissivity is altered by poleward heat transport.

Is this true? Actually, it is not. It is rarely mentioned, but 75% of the Earth’s greenhouse effect is due to water vapor and water clouds.[vi] And their distribution by latitude is extremely uneven. The tropical atmosphere contains a lot of water, and the polar atmosphere in winter contains almost none. Therefore, the greenhouse effect in the polar regions is extremely small, and the transport of heat from the tropics to the Arctic changes the emissions. This means that the total is not constant, so heat transport has the ability to change the global climate through changes in water vapor and cloud distributions.

In the 1960s, Jacob Bjerknes stated that if the top of the atmosphere fluxes and oceanic heat storage remained relatively stable, the total heat transported through the climate system would also remain constant. This implies that changes in atmospheric or oceanic transport should be compensated by changes of the same magnitude and opposite sign in the other one. This Bjerknes compensation has not been empirically demonstrated but is present in all models despite its physical basis being unknown.[vii] If the compensation is true it should result in transport being constant and, thus, not a cause for climate change.

Figure 6. The second objection to changes in heat transport being a cause of climate change is incorrect because heat transport to the Arctic does not show the expected compensation.

But again, reality is different. Heat transport can increase in the atmosphere and also in the ocean, changing the amount of energy transported. In fact, this is logical because an important part of ocean transport is in surface currents driven by wind, which is also responsible for heat transport through the atmosphere. If the wind increases, the transport in both compartments should increase.

Figure 7. Upper graph, tropospheric winter latent energy transport across 70°N by planetary scale waves (Rydsaa et al., 2021). Lower graph ocean heat transport to the Arctic and Nordic Seas in Terawatts (Tsubouchi et al. 2021).

This is also supported by data from two studies of Arctic heat transport in recent decades.[viii] Both atmospheric and oceanic heat transport increased in the early 21st century. In the Arctic, winter temperatures have risen sharply. Obviously, that heat has to be transported there, because the Sun does not shine in the Arctic in winter, so no heat is generated. And the increase in temperature has greatly increased the emission of infrared radiation into space. Remember that the greenhouse effect is very weak in the Arctic at this time of year, and heat is not retained. Because of the warming of the Arctic caused by increased transport, the planet is losing more energy than it was losing before.

Figure 8. Upper graph, Arctic winter temperature anomaly. Data from Danish Meteorological Institute. Lower graph, 5-year November-April average outgoing longwave radiation anomaly at 70-90°N top of the atmosphere from NOAA data (black) and solar activity (sunspots, red) with a decadal Gaussian smoothing (thick line).

So, what has caused this warming of the Arctic in the 21st century? CO₂ has been rising sharply since the 1950s and its effects on radiation are instantaneous, they do not take 50 years. There’s also talk of it being a consequence of the warming that’s been going on since the mid-1970s, but why should it take two decades for the heat to reach the Arctic? We have the Sun. Arctic warming and increased outgoing radiation coincide in time with the decline in solar activity that began in the mid-1990s with solar cycle 23, which, as we have seen, was accompanied by a weakening of the polar vortex.

How do we know that the change in solar activity caused the change in transport and the warming of the Arctic? Because it has been doing so for thousands of years. A study by leading scientists looked at the relationship between solar activity and Greenland’s temperature and found that over the past 4,000 years, solar activity has been inversely correlated with Greenland’s temperature.[ix] When solar activity decreased, Greenland warmed, as it is doing now. It also says that there have been periods in those 4,000 years when Greenland was warmer than it is now, which is inconsistent with being caused by our emissions.

  1. How the Sun changes heat transport

The signal from the Sun is received in the stratospheric ozone layer, which absorbs much of the ultraviolet radiation. This is a very sensitive receiver because UV radiation changes 30 times more than total radiation (3%). But in addition, the increase in UV radiation creates more ozone, which also increases by 3%. With more ozone and more UV radiation, the ozone layer experiences a temperature increase of 1°C with solar activity, which is much more than at the surface.

The ozone response to changes in solar activity modifies the temperature and pressure gradients, and this causes the speed of the zonal winds in the stratosphere to change, as we saw earlier. When the activity is high, the gradients become larger and this causes the wind speed to increase, and when the activity is low, the gradients become smaller and the wind speed decreases. In the troposphere, atmospheric waves called planetary waves are generated, and when the wind is weak, they reach the stratosphere and hit the polar vortex, weakening it. But when the wind is strong, they do not manage to enter the stratosphere and the vortex remains strong. Changes in the vortex are transmitted to the troposphere, altering atmospheric circulation and heat transport.

Figure 9. Cartoon showing the mechanism by which solar activity regulates planetary wave activity in the stratosphere and the polar vortex strength and, through it, winter atmospheric circulation and heat transport toward the Arctic.

Planetary waves are atmospheric waves of the Rossby type. The largest storms on the planet fit into their undulations and have a huge impact on meteorology. They are responsible for some of the most extreme atmospheric phenomena, such as the heat waves in Europe in 2003 and in Russia in 2010, and the floods in Pakistan in 2010, in China in 2012, and in Europe in 2013. The amount of energy they move is staggering. Planetary waves are the largest of all, and under certain conditions can reach the stratosphere, hitting the polar vortex and weakening it.

Fifty years ago, a scientist suggested that if the Sun had an effect on climate, planetary waves were a possible candidate for the mechanism.[x] But no one investigated this possibility, and the paper was forgotten.

A 2011 study finally proved him right, showing that planetary waves in the Northern Hemisphere respond to the solar cycle.[xi] Figure 10 shows the sunspot cycle in red and the amplitude of the planetary waves in black. We observe large oscillations from one year to another because the mechanism is not exclusive to the Sun and there are other causes that affect it. This is the difficulty of studying non-linear phenomena. But the effect of the solar cycle is clear, because the highest amplitudes occur in periods of low solar activity.

Figure 10. Planetary wave amplitude index based on the averaged amplitude of wavenumbers 1–3 averaged over 55–75°N in 70–20 hPa (black, from Powell & Xu, 2011). Annual sunspot index (red, from SILSO). Purple circles indicate high wave amplitude years that coincide with low solar activity.

The effect this has on the polar vortex was discussed in Part II and is shown in Figure 11. More active solar cycles, with fewer planetary waves, have faster zonal winds and stronger vortices, while during less active solar cycles the increase in planetary waves weakens the vortex.

Figure 11. Monthly sunspot number (red), cumulative anomaly of zonal wind speed at 54.4°N, 10 hPa (blue, Lu et al. 2008), and the mean vortex geopotential height anomaly at 20 hPa (purple, NCEP, Christiansen 2010).

We have already mentioned the effect this has on the frequency of cold winters in the Northern Hemisphere, but how does this mechanism explain the change in global climate?

  1. How the Sun changes the climate

My theory is that when solar activity is high, the zonal winds are strengthened, preventing the planetary waves from entering the stratosphere and allowing the vortex to remain strong throughout the winter. By acting as a wall, the vortex reduces heat transport to the Arctic in winter, and this causes temperatures to drop, reducing the infrared emissions to space that allow heat to escape from the Earth. All of these steps have been verified by scientists. The result is that by reducing emissions, the planet conserves more energy, which can cause it to get warmer. This is the situation that occurred from the mid-1970s to the late 1990s, when the planet experienced strong warming under high solar activity.

Figure 12. Climate-changing mechanism through changes in heat transport as a result of high solar activity.

When solar activity is low, the zonal winds subside, allowing planetary waves to enter the stratosphere and hit the vortex, weakening it. As the wall weakens, heat transport to the Arctic increases, causing it to warm. This warming increases emissions to space, causing the planet to conserve less energy. The result is that the planet either warms more slowly or cools, depending on other factors. Because this mechanism regulates the amount of heat that enters the Arctic in winter, I have named my theory “The Winter Gatekeeper”.

Figure 13. Climate-changing mechanism through changes in heat transport as a result of low solar activity.

It is important to note that this is not a solar theory, although it does explain the Sun’s effect on climate. Variations in heat transport are a general cause of climate change. Perhaps the most important one. Any factor that persistently changes the amount of heat transported becomes a cause of climate change, and this includes plate tectonics and orbital variations. This theory has the ability to explain the ice age of the last 34 million years, and the growth and shrinkage of the ice sheets in glaciations and interglacials.[xii] The explanations it provides fit the evidence better than the CO₂ changes.

The solar mechanism I propose has the following features:

  • It is indirect, because what changes the climate is not the change in solar energy, but the change in heat transport.
  • It is exclusively due to changes in the Sun’s ultraviolet radiation.
  • It produces dynamic changes in the stratosphere, which is the part of the climate system whose response to the Sun is important for climate change.
  • The mechanism works by altering the propagation of planetary waves, as proposed 50 years ago.
  • Since there are multiple causes that affect this propagation, the cause-effect relationship becomes non-linear, which makes it very difficult to study because we humans think linearly.
  • It affects the polar vortex, which is responsible for transmitting what happens in the stratosphere to the troposphere, determining the position of the jet streams and the atmospheric circulation in winter.
  • In its final part, the mechanism alters the transport of heat to the Arctic in winter. This is the most visible effect of the Sun on climate. Winter temperatures in the Arctic and the frequency of cold winters in eastern North America and Eurasia reveal the Sun’s effect on climate.
  • Finally, the mechanism works because the greenhouse effect is extremely heterogeneous across the planet. It is a very thick blanket in the tropics, leaving the poles exposed. Increasing CO₂ doesn’t change that because most of the greenhouse effect is due to water, which changes much more than CO₂.

This theory explains many of the problems that the Sun’s effect on climate has always had:

Figure 14. The solar part of the Winter Gatekeeper theory provides an explanation for several questions and solar-climate related phenomena, some of them not properly explained before.
  • It explains the mismatch between the small change in solar energy and the resulting climate effect. The change in solar energy only provides the signal, like the finger pushing the button on an elevator. The energy to change the climate is provided by planetary waves, which carry very large amounts of energy and act on sensitive parts of the climate.
  • It explains the lack of cause-and-effect correlation claimed by NASA and the IPCC. It is a non-linear process that cannot be required to have a linear correlation.
  • It explains the recent warming of the Arctic, the timing of which cannot be explained by CO₂ or global warming.
  • It explains the recent increase in cold winters in the Northern Hemisphere that scientists cannot adequately explain.
  • It explains changes in the Earth’s rotation due to the Sun that no one has been able to explain. Changes in atmospheric circulation induced by the Sun are what alter the angular momentum responsible for variations in the Earth’s rotation.
  • It explains the cumulative effect of changes in solar activity on climate. Why grand solar minimums have such a large effect, proportional to their duration. Low activity alters the energy balance by increasing emissions throughout the duration of the grand minimum, progressively reducing the energy of the climate system and causing the effects to become larger and global over time.
  • It explains the greater impact of solar-induced climate change on the Northern Hemisphere, as it affects the heat transported to the Arctic. The Antarctic polar vortex is much stronger and less sensitive to solar forcing. This is why the Medieval Warm Period and the Little Ice Age, caused by solar forcing, were much more pronounced in the Northern Hemisphere.
  • It also explains a significant part of the 20th century warming. The 70 years of grand solar maximum in that century caused the planet to increase its energy and warm up.
  1. Conclusion

The Sun has a lot to say about future climate, but we are not listening. Long-term changes in solar activity are cyclical, and what adds to warming now will subtract from it in the future. This theory does not deny that changes in CO₂ affect climate, and indeed it is based on differences in emissions due to changes in the greenhouse effect, just not in time, but in space, with latitude. But it is undeniable that if the Sun has played a relevant role in the warming of the 20th century, it reduces the role our emissions have played.

This article can also be watched in a 19-minute video with English and French subtitles.

References

[i] Soon, W., et al., 2023. The detection and attribution of northern hemisphere land surface warming (1850–2018) in terms of human and natural factors: Challenges of inadequate data. Climate, 11 (9), p.179.

[ii] Svensmark, H., 1998. Influence of cosmic rays on Earth’s climate. Physical Review Letters, 81 (22), p.5027.

[iii] Vinós, J., 2022. Climate of the Past, Present and Future. A scientific debate. Critical Science Press. Madrid.

[iv] Barry, L., et al., 2002. Poleward heat transport by the atmospheric heat engine. Nature, 415 (6873), pp.774-777.

[v] Fox-Kemper, B., et al., 2021. Climate Change 2021: The Physical Science Basis. 6th AR IPCC. Ch. 9 Ocean, Cryosphere and Sea Level Change. pp.1228–1233.

[vi] Schmidt, G.A., et al., 2010. Attribution of the present‐day total greenhouse effect. Journal of Geophysical Research: Atmospheres, 115 (D20).

[vii] Outten, S., et al., 2018. Bjerknes compensation in the CMIP5 climate models. Journal of Climate, 31 (21), pp.8745-8760.

[viii] Rydsaa, J.H., et al., 2021. Changes in atmospheric latent energy transport into the Arctic: Planetary versus synoptic scales. Quarterly Journal of the Royal Meteorological Society, 147 (737), pp.2281-2292. Tsubouchi, T., et al., 2021. Increased ocean heat transport into the Nordic Seas and Arctic Ocean over the period 1993–2016. Nature Climate Change, 11 (1), pp.21-26.

[ix] Kobashi, T., et al., 2015. Modern solar maximum forced late twentieth century Greenland cooling. Geophysical Research Letters, 42 (14), pp.5992-5999.

[x] Hines, C.O., 1974. A possible mechanism for the production of sun-weather correlations. Journal of the Atmospheric Sciences, 31 (2), pp.589-591.

[xi] Powell Jr, A.M. and Xu, J., 2011. Possible solar forcing of interannual and decadal stratospheric planetary wave variability in the Northern Hemisphere: An observational study. Journal of Atmospheric and Solar-Terrestrial Physics, 73 (7-8), pp.825-838.

[xii] Vinós, J. 2023. Solving the Climate Puzzle. The Sun’s surprising role. Critical Science Press. Madrid.

How we know that the sun changes the Climate. Part I: The past

From Climate Etc.

By Javier Vinós

Part I of a three part series.

The Sun is a variable star and the amount of energy it emits varies from month to month, year to year, and century to century. One of the manifestations of these variations are sunspots, which are more common when the Sun is more active and disappear when it is less active. These spots follow a solar cycle of about 11 years, but sometimes there is a longer period, decades or centuries, when the Sun’s activity is so low that there are no spots. These periods are called grand solar minima. There are also periods of decades or centuries when the activity is higher. These are called grand solar maxima.

The Sun provides 99.9% of the energy that the climate system receives. So, there have always been scientists who thought that variations in the Sun were the cause of climate change. The problem is that they never had enough evidence to prove it. Until now.

  1. The IPCC and NASA say…

The IPCC and NASA are convinced that changes in the Sun have very little effect on climate. They rely on two arguments. The first is that changes in solar activity are very small. We measure them with satellites because they cannot be measured from the surface, and we know that the radiant energy coming from the Sun varies by only 0.1%. The magnitude of the changes is better appreciated when we use the full scale. Many scientists believe that such a small change can only produce small changes in climate.

The second argument is that the evolution of temperature does not coincide with the evolution of solar activity. Since the 1990s, solar activity has decreased while warming has continued.[i]

Actually, this argument is not valid because it does not say that the Sun does not affect temperature, but that it is not the only factor in doing so, something we already knew because temperature responds to many factors such as El Niño, volcanoes, the polar vortex, or changes in the Earth’s orbit. There are many natural causes that change the climate, and what we need to know is whether the Sun is one of the main ones.

To find out, we don’t need to care what the IPCC and NASA think, we need to ask the climate itself. It doesn’t matter how small the changes in the Sun are if it turns out that the climate responds strongly to them by causing big changes.

  1. Climate during the Holocene

And the best way to find out is to look at what has happened to the climate over the last 11,000 years, the interglacial period we call the Holocene. The advantage of doing this is that the Holocene climate changes could not have been caused by changes in CO₂. They must have been caused by something else.

To study the climate of the past, scientists use various climate proxies that they collect in different parts of the world. A major study published in Science used 73 of these proxies to reconstruct Holocene climate.[ii] I have used the same proxies, with a slight modification in the way they are mixed.

What we see, and what a large number of studies also support, is that there was a warm period of thousands of years, called the Climate Optimum, followed by a long period of cooling, called Neoglaciation.

How do we know that this reconstruction is correct? Another study reconstructed the progress of the Earth’s glaciers over the past 11,000 years.[iii] They divided the globe into 17 regions, and this graph shows the number of regions whose glaciers increased in size during each century of the Holocene.

Since glaciers grow when it is colder, we can invert their figure and compare it to the temperature reconstruction graph so that its meaning is the same. We find a high degree of agreement. The glaciers confirm what the temperature reconstruction shows. We also know that CO₂ has done the opposite of temperature, but that is a story for another day.

Note: y-axis is the Z factor, which is related to temperature anomaly.

Both graphs also show some severe cooling episodes that were accompanied by increased glacier growth. These abrupt climate events of the past have been studied and identified by paleoclimatologists. Of all of them, we will focus on four of the most important ones. The Boreal Oscillation, the 5.2 kiloyear event, the 2.8 kiloyear event, and the Little Ice Age.

The four are separated by multiples of 2,500 years and form a cycle that I have called the Bray cycle because that was the name of the scientist who discovered it in 1968.[iv]

Now that we know the climate of the past, we need to talk about the activity of the Sun in the past.

  1. Past solar activity

The Sun’s activity is recorded in the tree rings through the action of cosmic rays. A constant stream of cosmic rays from the galaxy reaches the solar system. Some interact with the atmosphere. Some collide with nitrogen in the atmosphere, converting it to carbon-14, which is heavier than normal carbon-12 and radioactive. This carbon-14 combines with oxygen to form radioactive CO₂, which is breathed by trees. The carbon is used in photosynthesis to make cellulose, which allows the tree trunk to grow in diameter. When the tree dies, the carbon-14 in the wood slowly decays over centuries and millennia. You just have to measure how much carbon-14 is left in the wood to know how much time has passed since the tree died.

Each growth ring of a tree records the carbon-14 that was in the atmosphere that year, and scientists have used millennia-old trees and preserved logs to construct a calibration curve that spans tens of thousands of years. This allows them to determine the age of any organic remains, even if it is not a tree trunk, just by knowing the carbon-14 it contains. This is known as radiocarbon dating.

The only problem is that the production of carbon-14 by cosmic rays is not constant. The Sun’s magnetic field deflects the path of cosmic rays, causing many to miss the Earth, and changes in the Sun’s activity affect its magnetic field.

As the Sun’s activity increases, fewer cosmic rays arrive, less carbon-14 is produced, and organic remains appear older because they contain less of it. When the Sun’s activity becomes weaker, more cosmic rays arrive, more carbon-14 is produced, and the organic remains look younger because they contain more of it.

This produces deviations in the calibration curve that allow us to know what the Sun’s activity was in the past.

  1. Spörer-type solar minima

When we analyze the radiocarbon curve over the last 11,000 years, we observe large deviations that indicate long periods of low solar activity. These extended periods of low solar activity are called grand solar minima and increase carbon-14 production by 2%. The most common ones last about 75 years, and there have been about twenty in the last 11,000 years. The most recent was the Maunder Minimum in the late 17th century. But there are other types of grand solar minima that are much more severe because they last twice as long, about 150 years. The last of these severe solar minima was the Spörer Minimum, which occurred in the 15th and 16th centuries.

There have been only four such Spörer-type grand minima in the entire Holocene. 2,800 years ago, there was the Homer Minimum, 5,200 years ago the Sumerian Minimum, and 10,300 years ago the Boreal Minimum. We know when they occurred thanks to tree rings.

If the dates sound familiar, it is because the four grand Spörer-type Holocene minima coincide exactly with the four major climatic events on the graph we saw earlier. We know that during each of these grand solar minima, when the Sun’s activity dropped for 150 years, the climate experienced a tremendous cooling that had a major effect on climate proxies around the globe.

We also know that low solar activity during the grand minima has had a major impact on human populations. Past human settlements and their component structures can be radiocarbon dated. When humans were doing well in the past, the population grew and they built more, and when they were doing poorly, usually because there was less food, the population decreased and they built less. Scientists have estimated the evolution of the human population of the British Isles by analyzing the radiocarbon dates of thousands and thousands of remains from hundreds of archaeological excavations.[v]

What they have found is that the population increased greatly with the advent of agriculture, but every time there was a severe deterioration in the climate, the human population suffered from diminishing resources. And the largest declines occurred when grand Spörer-type solar minima took place. Other population declines also coincide with other cooling periods, confirming our reconstruction.

This tells us that the worst climate changes in the past have been caused by changes in solar activity. It also tells us that what is bad for humanity is cooling, not warming.

Now we can respond to the IPCC and NASA. Never mind that solar irradiance changes very little, and never mind that temperature does not always do the same thing as solar activity. Clearly there are other factors at play. But we can state emphatically that changes in solar activity affect the climate because that is what the climate says. The study of past climate leaves no room for doubt. The Sun changes the climate. And if we don’t know how it does it, we should study it.

  1. The 20th century solar maximum

Since low solar activity causes cooling, it stands to reason that high activity must cause warming. Solar activity in the 20th century was very high, in the top 10% of the last 11,000 years.

If we count the number of sunspots in each solar cycle over the last 300 years and divide by the length of each cycle, we can see how much solar activity has deviated from the average. Since the Maunder Minimum, during the Little Ice Age, solar activity has been increasing and was well above average between 1933 and 1996, a period of six cycles of increased solar activity that formed the 20th century solar maximum.

Although we cannot know how much of the 20th century warming is due to this modern solar maximum, there is no denying that it is a significant part, because as we have seen, the Sun has been the cause of much of the major climate change over the past 11,000 years.

  1. Conclusions

There are two pieces of good news. The first is that solar activity cannot rise above the 20th century maximum. It is not like CO₂, which can keep going up. The Sun’s activity can stay high or go down, but it cannot go up, so the warming should not accelerate and should not be dangerous.

In 2016, I developed a model to predict solar activity in the 21st century. At the time, some scientists believed that solar activity would continue to decline until a new grand solar minimum and mini-ice age. But my model predicts that solar activity in the 21st century will be similar to that of the 20th century. It also predicted that the current solar cycle, the 25th, would have more activity than the previous one, and it was right.

The second piece of good news is that if much of the 20th century warming is due to the Sun, then there is no climate emergency. Believing that all climate change is due to our emissions is one of those errors that sometimes occur in science, like believing that the Earth is the center of the solar system, that interplanetary space is full of ether, or that stomach ulcers are caused by stress, not bacteria.

This article can also be

[i] NASA. Is the Sun causing global warming?

[ii] Marcott, S.A., et al., 2013. A reconstruction of regional and global temperature for the past 11,300 years. science, 339 (6124), pp.1198-1201.

[iii] Solomina, O.N., et al., 2015. Holocene glacier fluctuations. Quaternary Science Reviews, 111, pp.9-34.

[iv] Bray, J.R., 1968. Glaciation and solar activity since the Fifth Century BC and the solar cycle. Nature, 220 (5168).

[v] Bevan, A., et al., 2017. Holocene fluctuations in human population demonstrate repeated links to food production and climate. PNAS, 114 (49), pp.E10524-E10531.

Wrong, USA Today, More Than One Type of Solar Activity Influences the Earth’s Climate

wallup.net

From ClimateRealism

By H. Sterling Burnett

USA Today published a supposed fact check claiming solar activity is not responsible for climate change. This is misleading at best, and foolishly wrong at worst. Various types of changes in solar activity have long been associated with changes in the Earth’s temperature and climate, on short, mid-term, and longer time scales.

The USA Today article by Kate S. Petersen, “The sun is mighty, but modern climate change is caused by human activity | Fact check,” presents itself as a fact check on a popular Facebook post. Wow! Responding to somebody’s certainly Facebook post is taking on hard hitting news from a reliable source! Still, when one examines the post, and compares it to the supposed fact check, the Facebook post is closer to the truth than Petersen’s and USA Today’s story.

“The implied claim is wrong,” Petersen writes. “While the sun significantly impacts Earth’s climate, it is not responsible for modern climate change.

“While the amount of solar energy striking the Earth fluctuates on an 11-year cycle, there hasn’t been a net increase since the 1950s, according to NASA,” Petersen continues. “However, global surface temperatures have risen dramatically.”

Petersen either is unaware of or simply ignored the fact that the 11-year solar cycles during which Sol’s magnetic fields flip are just one type of solar cycle that can drive temperature and climate changes on the earth. Sunspots and solar flares happen seemingly randomly though with some consistency, and 1,000 and 1,500 year cycles, and Milankovitch cycles also occur. All of these activities and others impact the Earth’s temperatures. As discussed at Climate at a Glance: The Sun’s Impact on Climate Change, historically through the present day, solar activity correlates quite well with climate change, better than changes in CO2. (see figures 1-3, below)

Figure 1. Changes in the Sun’s energy output since 1900. The Sun’s energy output has increased since the 1600’s with its most recent increase occurring during the 20th century. Source: J. Lean, Geophysical Research Letters, Vol 27, No. 16 (2000).
Figure 2: Temperature history according to the United Nations IPCC First Assessment Report. The top graph shows temperatures during the past 1 million years. The middle graph shows temperatures during the past 12,000 years. The bottom graph shows temperatures during the past 1,000 years. Present temperatures are at the far right. Source: IPCC First Assessment Report, United Nations, p. 202.
Figure 3. Temperature changes vs. changes in the Sun’s energy output and changes in atmospheric carbon dioxide concentrations. The graph on the left shows 20th century temperature changes in blue vs. changes in the Sun’s energy output in red. The graph on the right shows 20th century changes in blue vs. changes in atmospheric carbon dioxide emissions in red. W. Soon, et al., “Solar irradiance modulation of Equator-to-Pole (Arctic) temperature gradients: Empirical evidence for climate variation on multi-decadal timescales,” Journal of Atmospheric and Solar-Terrestrial Physics, 93, 45-56.

All the myriad ways solar activity impacts the Earth are not fully understood. Changes in solar output and their impact on solar winds are plausible explanations for temperature shifts on some time scales. Scientific research also suggests another type of forcing from the sun, its impact on volume of cosmic rays entering the earth’s atmosphere, which also impacts cloud formation and rainfall.

The point is, when Petersen and the government agencies she references state that the sun can’t be a factor in current climate change, they are only looking at one type of solar activity on a single time scale. Our solar system isn’t that simple.

To buttress her claim that the sun isn’t causing or significantly contributing to present climate change Petersen quotes Josh Willis, a NASA climate scientist, who told USA Today that “the amount of warming we see matches what we expect based on the increased CO2 we’ve added. The timing of the warming matches the timing of the CO2 increase caused by people.”

Willis’s claim doesn’t match the facts. The Earth began to warm in the mid- to late 19th century, before humans began emitting large significant amounts of CO2 into the atmosphere, then after the 1940s, even as global industrialization and anthropogenic CO2 emissions were increasing at a rapid pace, the earth began cooling, leading some scientists and media outlets by the 1970s to warn that an ice age might be coming. Then, the Earth started warming in the 1980s, only to plateau or pause for 15 years beginning in the late 1990s, despite CO2’s steady increase. There has, in fact, been no good correlation between CO2 concentrations and temperature changes throughout the latter 20th and early 21st centuries.

Also, as we’ve discussed dozens of times at Climate Realism, CO2 driven temperature changes projected by climate models don’t, in fact, accurately reflect recent warming trends. Ground-level temperature measurements, weather balloon temperature measurements, and satellite temperature measurements are far lower than model projections built on the assumption that CO2 is the prime forcing factor for global warming. As a result, Willis is simply wrong when he says, “the amount of warming we see matches what we expect based on the increased CO2 we’ve added.”

The physics and factors that drive the Earth’s climate conditions are many, varied, and complex. The Earth is not the simple linear system described in climate models and presented by Petersen and USA Today. Carbon dioxide is likely one factor influencing the recent modest warming, but the sun and numerous other factors are almost certainly having an impact as well—arguably playing role greater than the increase in greenhouse gases.

More Research Affirms The Human Role In Global Warming Has Been Strongly Overestimated


From NoTricksZone

By Kenneth Richard on 4. January 2024

AGW proponents use subjective forcing models and unmeasured estimates of past solar activity to claim humans drive warming. A scientist’s (Larminat, 2023) reassessment finds the Sun can drive climate, equilibrium climate sensitivity (ECS, 2xCO2 + feedbacks) is 1.14°C, and human forcing is overestimated.

Because there have been no direct measurements of solar activity until the late 1970s, proponents of anthropogenic global warming (AGW) rely on “a high degree of (informed) subjectivity,” a “degree of belief that exists among [IPCC] lead authors,” and uncertain solar models and proxy-based assumptions to conclude the Sun has not had more than a negligible role in climate change (Larminat, 2023). This way it can be claimed that human activities, especially CO2 emissions, are predominantly or even solely responsible for modern warming.

However, because these climate models and numerical approximations are derivations of meteorological models designed to predict the weather, they are “questionable for validating the anthropogenic principle.”

When alternative estimates of past solar activity assume the Sun to have played a more substantial role in warming, and when efforts to “disappear” the Medieval Warm Period and Little Ice Age climate variations go unrealized, it can instead be shown that the anthropogenic impact on climate has been strongly overestimated (ECS = 1.14°C, not 2.5 to 4.0°C as claimed by the IPCC), and solar activity is the predominant driver of past and even modern warming.

Image Source: Larminat, 2023
from-behavioral-climate-models-and-millennial-data-to-agw-reassessmentHerunterladen

November 2023 Ocean Warmth Persists Due to Tropics

From Science Matters

By Ron Clutz

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • Major El Ninos have been the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through November 2023.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016. 

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean.

Then in 2022, another strong NH summer spike peaked in August, but this time both the Tropic and SH were countervailing, resulting in only slight Global warming, later receding to the mean.   Oct./Nov. temps dropped  in NH and the Tropics took the Global anomaly below the average for this period. After an uptick in December, temps in January 2023 dropped everywhere, strongest in NH, with the Global anomaly further below the mean since 2015.

Now comes El Nino as shown by the upward spike in the Tropics since January, the anomaly nearly tripling from 0.38C to 1.07C.  In August 2023, all regions rose, especially NH up from 0.70C to 1.37C, pulling up the global anomaly to a new high for this period. September showed a new peak for NH at 1.41, but then in October anomalies in all regions have dropped down 0.1C bringing down the Global anomaly.  In November, NH added cooling, offset by slight warming in SH.  Tropical ocean temps rose to nearly match 2015 in November, but the Global anomaly changed little and remained lower than the September peak.

Comment:

The climatists have seized on this unusual warming as proof of their Zero Carbon agenda, without addressing how impossible it would be for CO2 warming the air to raise ocean temperatures.  It is the ocean that warms the air, not the other way around.  Recently Steven Koonin had this to say about the phonomenon confirmed in the graph above:

El Nino is a phenomenon in the climate system that happens once every four or five years.  Heat builds up in the equatorial Pacific to the west of Indonesia and so on.  Then when enough of it builds up it surges across the Pacific and changes the currents and the winds.  As it surges toward South America it was discovered and named in the 19th century  It is well understood at this point that the phenomenon has nothing to do with CO2.

Now people talk about changes in that phenomena as a result of CO2 but it’s there in the climate system already and when it happens it influences weather all over the world.   We feel it when it gets rainier in Southern California for example.  So for the last 3 years we have been in the opposite of an El Nino, a La Nina, part of the reason people think the West Coast has been in drought.

It has now shifted in the last months to an El Nino condition that warms the globe and is thought to contribute to this Spike we have seen. But there are other contributions as well.  One of the most surprising ones is that back in January of 2022 an enormous underwater volcano went off in Tonga and it put up a lot of water vapor into the upper atmosphere. It increased the upper atmosphere of water vapor by about 10 percent, and that’s a warming effect, and it may be that is contributing to why the spike is so high.

A longer view of SSTs

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July. 1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino. 

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  In 2021-22 there were again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, then in October to January 2023 by deeper cooling in NH and Tropics.  

Now in 2023 the Tropics flipped from below to well above average, while NH has produced a summer peak extending into September higher than any previous year. In fact, October and now November are showing that this number is likely the crest, despite El Nino driving the Tropics anomaly close to 1998 and 2015 peaks.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

Contemporary AMO Observations

Through January 2023 I depended on the Kaplan AMO Index (not smoothed, not detrended) for N. Atlantic observations. But it is no longer being updated, and NOAA says they don’t know its future.  So I find that ERSSTv5 AMO dataset has data through October.  It differs from Kaplan, which reported average absolute temps measured in N. Atlantic.  “ERSST5 AMO  follows Trenberth and Shea (2006) proposal to use the NA region EQ-60°N, 0°-80°W and subtract the global rise of SST 60°S-60°N to obtain a measure of the internal variability, arguing that the effect of external forcing on the North Atlantic should be similar to the effect on the other oceans.”  So the values represent sst anomaly differences between the N. Atlantic and the Global ocean.

The chart above confirms what Kaplan also showed.  As August is the hottest month for the N. Atlantic, its varibility, high and low, drives the annual results for this basin.  Note also the peaks in 2010, lows after 2014, and a rise in 2021. Now in 2023 the peak is holding at 1.4C.  An annual chart below is informative:

Note the difference between blue/green years, beige/brown, and purple/red years.  2010, 2021, 2022 all peaked strongly in August or September.  1998 and 2007 were mildly warm.  2016 and 2018 were matching or cooler than the global average.  2023 started out slightly warm, then rose steadily to an  extraordinary peak in July.  August to October were only slightly lower, but now November cooled by ~0.3C.

The pattern suggests the ocean may be demonstrating a stairstep pattern like that we have also seen in HadCRUT4. 

The purple line is the average anomaly 1980-1996 inclusive, value 0.18.  The orange line the average 1980-202306, value 0.38, also for the period 1997-2012. The red line is 2013-202306, value 0.64. As noted above, these rising stages are driven by the combined warming in the Tropics and NH, including both Pacific and Atlantic basins.
Curiosity:  Solar Coincidence?

The news about our current solar cycle 25 is that the solar activity is hitting peak numbers now and higher  than expected 1-2 years in the future.  As livescience put it:  Solar maximum could hit us harder and sooner than we thought. How dangerous will the sun’s chaotic peak be?  Some charts from spaceweatherlive look familar to these sea surface temperature charts.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? And is the sun adding forcing to this process?

Space weather impacts the ionosphere in this animation. Credits: NASA/GSFC/CIL/Krystofer Kim

Footnote: Why Rely on HadSST4

HadSST is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

NYT Claims Record September Temperature Indicates Accelerated Climate Change – It Doesn’t

Just another scare story of climate scientist Zeke Hausfather because a single record warm month of data is not an indication of “evidence that global warming has accelerated.”

The post appeared first on ClimateREALISM

A guest opinion article in The New York Times by Zeke Hausfather, Ph.D, titled “I Study Climate Change. The Data Is Telling Us Something New,” suggests that a single record warm month of data is an indication of “evidence that global warming has accelerated.” The claim is false for four reasons; because a single month isn’t representative of long term climate change, the data Hausfather cites isn’t in agreement with other datasets, and it isn’t representative of the globe, but a weather anomaly in Antarctica. Finally, the year-on-year increase in atmospheric carbon dioxide, said to drive such temperatures, wasn’t enough to cause the event.

First, one month of record high temperatures has nothing to do with long-term climate change, which is defined by the World Meteorological Organization as “…the average weather conditions for a particular location and over a long period of time.” To create a climate record, 30 years of weather data is averaged to create a “normal” climate expectation for a location or region. What we experience on a day-to-day basis are weather events, not climate events. Weather is not climate and therefore one September record high temperature is not a climate change indicator. Hausfather, being a climate scientist, should know this.

However, given the emotional and unscientific opening statement made by Hausfather in the article, “Staggering. Unnerving. Mind-boggling. Absolutely gobsmackingly bananas,” it seems he is prone to emotions over fact.

One errant month of high temperature will in fact change the slope of any temperature graph upwards, but that is not an indication of acceleration, but rather an outlier data point which are known to happen. For example, in figure 1, global temperature data released by Climate.gov shows what looks to be a clear data point outlier in September.

Figure 1. September temperature compared to the 20th-century average from 1850 to 2023. September have grown warmer at a rate of nearly 1 degree Fahrenheit (0.6 degrees Celsius) per century over the modern temperature record. NOAA Climate.gov map and graph, based on data from NOAA National Centers for Environmental Information.

In statistics, an outlier is a data point that differs significantly from other observations. It happens in almost every data set, and in the case of Earth, which has chaotic weather systems, not at all surprising. Again, Hausfather should know better.

The article goes on to claim:

As global temperatures shattered records and reached dangerous new highs over and over the past few months, my climate scientist colleagues and I have just about run out of adjectives to describe what we have seen. Data from Berkeley Earth released on Wednesday shows that September was an astounding 0.5 degree Celsius (almost a full degree Fahrenheit) hotter than the prior record, and July and August were around 0.3 degree Celsius (0.5 degree Fahrenheit) hotter. 2023 is almost certain to be the hottest year since reliable global records began in the mid-1800s and probably for the past 2,000 years (and well before that).

Note that we didn’t have thermometers 2000 years ago, so this is pure speculation.

Other datasets and scientists don’t suggest that this summer or September was anything unusual, for example, climate scientist Roy Spencer, Ph.D, ran a guest essay here in Climate Realism last week, saying:

“Record warmth” in any given year is usually measured in mere fractions of a degree Fahrenheit. As global data from the National Oceanic and Atmospheric Administration suggest, for example, this summer’s “record” (averaged from June through August) warmth averaged only 0.43 degrees warmer than in 2019 and 2020, the next-warmest years.

The small difference in average temperature also comes with wide variation, which makes climate change considerably more nuanced than usually reported by the mainstream media.

Natural weather patterns, including a growing El Niño event, contributed to the warm summer and September.

Thirdly, not all of the Earth was abnormally warm. In fact, the real “spike” in temperature was limited mostly to a place that didn’t get above freezing – Antarctica. While Hausfather and excitable journalists are now telling the world how hot and terrible September was, the bottom line is that the winter temperatures in Antarctica, also a weather event, we less cold than normal. This is easily seen from two graphs provided by NASA Goddard Institute for Space Studies (GISS) that produces a GISTEMP product illustrating the issue, seen in Figure 2A and 2B below.

Figure 2A – September global temperature anomaly from NASA GISS. Note the patch of red in Antarctica.
Figure 2B – Temperature anomaly vs. global latitude. Note the big temperature spike on the left side where Antarctica is located in the Southern hemisphere.

Clearly, the “hottest” place on the planet in September was Antarctica, yet the temperature over the continent didn’t get above freezing during the Sothern Hemisphere Antarctic Winter (opposite of our summer in the Northern Hemisphere). It was just “less cold” than normal. That’s hardly a reason for concern, but the big spike in Antarctic temperature skewed the global data to make it look like the places that matter, where the world population lives was abnormally hot.

Finally as outlined in the Heartland Daily News, Hot Summer Due to Many Factors—Carbon Dioxide Emissions Are Not One of Them. there was a wide variety of other factors to consider: blocking weather patterns, solar activity, increased water vapor, El Niño, and an increasingly active sun.

According to the NOAA Global Monitoring Laboratory the amount of atmospheric carbon dioxide increase from September 2022 to September 2023 went from approximately 416 to 418 parts per million (PPM). Just 2PPM increase isn’t enough to explain the jump in temperature. In fact, according to this data graph, that’s much less than the yearly global variation of atmospheric carbon dioxide.

In summary, this end paragraph from the Heartland Daily News article says it best:

In short, there is a complex explanation for the complex weather patterns that have prevailed this summer. Multiple geologic, solar, meteorological, and atmospheric events have occurred simultaneously, resulting in unusually high summer temperatures obtaining over much of the world. Fossil fuel use does not cause volcanic eruptions, oceanic and wind current shifts, or changes in solar activity, thus climate change cannot fairly be blamed for the present pattern of heatwaves, which long-term data show have not increased.

And, as stated before, climate scientist Zeke Hausfather should know better than to write up a scare story about temperature with the adjectives “Staggering. Unnerving. Mind-boggling. Absolutely gobsmackingly bananas.“

IPCC Global Warming Reports Underestimated Role of Sun in Warming: Study

IPCC reports based on failed computer climate models underestimated the role of the Sun in global warming.

From NOT A LOT OF PEOPLE KNOW THAT

By Paul Homewood

Reports on global warming issued by the United Nations’ Intergovernmental Panel on Climate Change (IPCC) underestimate the role of the Sun in the warming process while falsely laying blame on human beings, according to a study published last month.

In 2021, Ronan Connolly, a scientist at the Center for Environmental Research and Earth Science (CERES), and his colleagues published a review raising concerns about multiple reports issued by the IPCC. The IPCC reports concluded that global warming since the mid-20th century was essentially human-driven, dismissing natural causes behind the process. The 2021 review was disputed in a 2022 article by two climate researchers who claimed that the review was “flawed,” that it “should not be treated as credible,” and that the IPCC’s decision to rule out solar activity as a major driver behind climate change “remains intact.”

In a Sept. 27 study published in IOP Science, a team of 20 climate researchers led by Mr. Connolly sought to debunk the 2022 article and reaffirm the 2021 review. It found that the IPCC may have “substantially underestimated the role of the Sun in global warming,” according to a recent post by CERES.

The 2021 review noted that the IPCC reports had two major flaws:

  • For their analysis, the IPCC reports used global surface temperature data that was “contaminated by urban warming biases,” meaning that only temperature records from urban regions were considered. Urban areas tend to be warmer than the countryside due to human activity and various structures. Though urban areas only represent a small percentage of land, these places make up the majority of thermometer records used in estimating global temperatures.
  • The IPCC reports used only a small data set from a large pool of data related to Total Solar Irradiance (TSI), which measures the radiant energy emitted by the sun falling on Earth’s atmosphere. And this small data set used by IPCC mostly came to two conclusions—there have been very few TSI changes over the past centuries or that TSI has slightly decreased since the 1950s.

By analyzing data showing a rise in temperatures in urban regions and little to no change in Total Solar Irradiance, the IPCC reports blamed human activity for global warming, dismissing the sun’s role in the process.

Full story here.

Has the Sun’s true role in global warming been miscalculated?

From Tallbloke’s Talkshop

October 6, 2023 by oldbrew

Of course the IPCC’s preferred idea is that the Sun can be ignored as a variable in climate influence, and all attention should focus on minor trace gases (mainly CO2 at 0.04%) in the atmosphere. A recent study by Spencer & Christy weighed in on a related topic: Our new climate sensitivity paper has been published, which proposes that actual observations indicate significant IPCC over-estimation of (theoretical) non-solar climate factors.
– – –
A new international study published in the scientific peer-reviewed journal, Research in Astronomy and Astrophysics, by 20 climate researchers from 12 countries suggests that the UN’s Intergovernmental Panel on Climate Change (IPCC) might have substantially underestimated the role of the Sun in global warming, says Ceres-Science.

The article began as a response to a 2022 commentary on an extensive review of the causes of climate change published in 2021.

The original review (Connolly and colleagues, 2021) had suggested that the IPCC reports had inadequately accounted for two major scientific concerns when they were evaluating the causes of global warming since the 1850s:

The global temperature estimates used in the IPCC reports are contaminated by urban warming biases.

The estimates of solar activity changes since the 1850s considered by the IPCC substantially downplayed a possible large role for the Sun.

On this basis, the 2021 review had concluded that it was not scientifically valid for the IPCC to rule out the possibility that global warming might be mostly natural.

The findings of that 2021 review were disputed in a 2022 article by two climate researchers (Dr. Mark Richardson and Dr. Rasmus Benestad) for two main reasons:

Richardson and Benestad (2022) argued that the mathematical techniques used by Connolly and colleagues (2021) were inappropriate and that a different set of mathematical techniques should have been used instead.

They also argued that many of the solar activity records considered by Connolly and colleagues (2021) were not up-to-date.

They suggested that these were the reasons why Connolly and colleagues (2021) had come to a different conclusion from the IPCC.

This new 2023 article by the authors of the 2021 review, has addressed both of these concerns and shown even more compelling evidence that the IPCC’s statements on the causes of global warming since 1850 are scientifically premature and may need to be revisited.

The authors showed that the urban component of the IPCC’s global temperature data shows a strong warming bias relative to the 98% of the planet that is unaffected by urbanization. However, they also showed that urbanized data represented most of the weather station records used.

While the IPCC only considered one estimate of solar activity for their most recent (2021) evaluation of the causes of global warming, Connolly and colleagues compiled and updated 27 different estimates that were used by the scientific community.

Several of these different solar activity estimates suggest that most of the warming observed outside urban areas (in rural areas, oceans, and glaciers) could be explained in terms of the Sun. Some estimates suggest that global warming is a mixture of human and natural factors. Other estimates agreed with the IPCC’s findings.

For this reason, the authors concluded that the scientific community is not yet in a position to establish whether the global warming since the 1850s is mostly human-caused, mostly natural or some combination of both.

The lead author of the study, Dr. Ronan Connolly, of the Center for Environmental Research and Earth Sciences (CERES-Science.com) described the implications of their findings:

“In scientific investigations, it is important to avoid beginning your analysis with your conclusions decided in advance. Otherwise you might end up with a false sense of confidence in your findings. It seems that the IPCC was too quick to jump to their conclusions.”

Full press release here.

New Study: Earth Will Cool By 1°C Over The Next Decades Due To The Upcoming Grand Solar Minimum

From NoTricksZone

By Kenneth Richard on 22. September 2023

“The first modern GSM1 [Grand Solar Minimum] occurs in 2020 – 2053 with the cycle amplitudes reduction to 80% in cycle 25, to 30% in cycle 26 and to 70% in cycle 27 from the maximum amplitude of cycle 24.” − Zharkova et al., 2023

Per a new study, Earth’s Total Solar Irradiance (TSI) has increased by about 1 to 1.5 W/m² from its depths in 1700 to its “maximum amplitude” in cycle 24 (2020). This resulted in a global temperature increase of about 1.5°C during this span.

“[T]he monthly TSI variations (case a) show the increase of TSI by about 1 – 1.3 W/m² in 2020 compared to 1700. This TSI increase found from the S-E distance ephemeris is close to the magnitude of 1 – 1.5 W/m² reported from the current TSI observations.”

But over the next 30 years (2020-2053) Earth will experience a period of significantly reduced solar activity and a consequent “mini ice age” climate that is “similar to the Maunder Minimum” (1645-1715 CE) that characterized the much-colder-than-today Little Ice Age period.

Temperatures will be reduced by about 1°C during the next few decades; Earth will then be only 0.5°C warmer than it was in 1700.

“Because solar irradiance and the terrestrial temperature already increased since the MM [Maunder Minimum] as is clearly recorded from the terrestrial temperature variations, the terrestrial temperature during the first modern GSM1 is expected to drop by about 1.0˚C to become just 0.5°C higher than it was in 1700.”

Image Source: Zharkova et al., 2023

In the study, no anthropogenic or carbon dioxide concentration contribution to terrestrial temperature change is mentioned.

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Controversy surrounding the Sun’s role in climate change

From Climate Etc.

by Dr. Willie Soon, Dr. Ronan Connolly & Dr. Michael Connolly

Gavin Schmidt at realclimate.org attempts to dismiss our recent papers, including pseudo-scientific takedowns.  This post takes a deep dive into the controversies.

In the last month, we have co-authored three papers in scientific peer-reviewed journals collectively dealing with the twin problems of (1) urbanization bias and (2) the ongoing debates over Total Solar Irradiance (TSI) datasets:

  1. Soon et al. (2023). Climate. https://doi.org/10.3390/cli11090179. (Open access)
  2. Connolly et al. (2023). Research in Astronomy and Astrophysics. https://doi.org/10.1088/1674-4527/acf18e. (Still in press, but pre-print available here)
  3. Katata, Connolly and O’Neill (2023). Journal of Applied Meteorology and Climatology. https://doi.org/10.1175/JAMC-D-22-0122.1. (Open access)

All three papers have implications for the scientifically challenging problem of the detection and attribution (D&A) of climate change. Many of our insights were overlooked by the UN’s Intergovernmental Panel on Climate Change (IPCC) in their last three Assessment Reports (AR), i.e., IPCC AR4 (2007), IPCC AR5 (2013) and IPCC AR6 (2021). This means that the IPCC’s highly influential claims in those reports that the long-term global warming since the 19th century was “mostly human-caused” and predominantly due to greenhouse gas emissions were scientifically premature and the scientific community will need to revisit them.

So far, the feedback on these papers has been very encouraging. In particular, Soon et al. (2023) seems to be generating considerable interest, with the article being viewed more than 20,000 times on the journal website in the first 10 days since it was published.

However, some scientists who have been actively promoting the IPCC’s attribution statements over the years appear to be quite upset by the interest in our new scientific papers.

This week (September 6th, 2023), a website called RealClimate.org published a blog post by one of their contributors, Dr. Gavin Schmidt, the director of the NASA Goddard Institute for Space Studies (NASA GISS). In this post, Dr. Schmidt is trying to discredit our analysis in Soon et al. (2023), one of our three new papers, using “straw-man” arguments and demonstrably false claims.

As we summarize in Connolly et al. (2023),

“A “straw man” argument is a logical fallacy where someone sets up and then disputes a position that was not actually made by the group being criticised. Instead, the group’s arguments or points are either exaggerated, misrepresented, or completely fabricated by the critics.”

In our opinion, while this rhetorical technique might be good for marketing, political campaigning, “hit pieces”, etc., it is not helpful for either science or developing informed opinions. Instead, we strive in our communications to take a “steel-manning” approach. As we point out in Connolly et al. (2023),

“Essentially, this involves addressing the best and most constructive form of someone’s argument – even if it is not the form they originally presented.”

With that in mind, we will first steel-man Dr. Schmidt’s apparent criticisms of Soon et al. (2023).

Steel-manning Dr. Schmidt’s criticisms of Soon et al. (2023)

In his latest RealClimate post, Dr. Schmidt claims the following:

  1. He asserts that one of the two Total Solar Irradiance (TSI) time series that we considered in Soon et al. (2023) is flawed, out-dated and unreliable. (As an aside, this was also one of the 27 TSI series we considered in Connolly et al. (2023) but he does not discuss this paper here)
  2. He claims that a 2005 paper by Dr. Willie Soon looking at the relationship between TSI and Arctic temperatures has been disproven by the passage of time.
  3. He argues that the “rural-only” Northern Hemisphere land surface temperature record that was one of the two temperature records we analysed in Soon et al. (2023) is not representative of rural global temperature trends or even rural Northern Hemisphere temperature trends.

Later in this post, we will respond to each of Dr. Schmidt’s claims and show how they are incorrect. But, first it may be useful to provide some background information on RealClimate.org.

How reliable is RealClimate.org?

RealClimate.org was created in 2004 as a blog to promote the scientific opinions of the website owners. It is currently run by five scientists: Dr. Gavin Schmidt, Prof. Michael Mann, Dr. Rasmus Benestad, Prof. Stefan Rahmstorf and Prof. Eric Steig.

Anybody with scientific training (or even just a careful reader) who actually reads our paper will be able to see that each of the claims in Dr. Schmidt’s recent blog-post are either false, misleading or already clearly addressed by our paper. Therefore, scientifically speaking, his post doesn’t contribute in any productive or meaningful way.

Instead, unfortunately, the goal of his post seems to be to try and stop inquiring minds from reading our paper.

If people were only to read his blog-post then they might be discouraged from even looking at our paper – and therefore wouldn’t find out that Dr. Schmidt’s alleged “criticisms” are without merit.

This type of pseudoscientific “take-down” of any studies that disagree with the RealClimate team’s scientific opinions seems to be a common pattern. For example, in November, they posted a similar “take-down” of our 2021 study that they disdainfully titled “Serious mistakes found in recent paper by Connolly et al.” That post summarized their attempted “rebuttal” of our Connolly et al. (2021) paper by Richardson & Benestad (2022).

Anybody who reads both Connolly et al. (2021) and Richardson & Benestad (2022) will quickly realize that their attempted “rebuttal” was also easily disproven. Indeed, two of our three recent papers explicitly demonstrate that Richardson & Benestad (2022)’s claims were flawed and erroneous.

Again, it seems that the goal of Richardson & Benestad (2022) and RealClimate’s accompanying post in November was NOT to further the science, but rather to discourage people from actually reading Connolly et al. (2021)!

Connolly et al. (2023) is our formal reply to Richardson & Benestad (2022)’s attempted rebuttal of our earlier Connolly et al. (2021) paper.

For anybody who is wondering what our response to Richardson & Benestad’s November 2022 RealClimate post is, we recommend reading the full papers themselves.

All three articles were published in the peer-reviewed journal, Research in Astronomy and Astrophysics (RAA for short).

  • Connolly et al. (2021): here
  • Richardson & Benestad (2022): here
  • Our reply, Connolly et al. (2023): abstract; preprint here (final version is still being typeset)

Addressing claim 1: What is the most reliable TSI time series available?

A key challenge that is the subject of considerable ongoing scientific debate and controversy is the question of how Total Solar Irradiance (TSI) has changed since the 19th century and earlier.

It was only in late 1978, during the satellite era, that it became possible to directly measure the TSI from above the Earth’s atmosphere using TSI-measuring instruments onboard satellites.

Even during the satellite era, it is still unclear exactly how TSI has changed because:

  1. Each satellite mission typically only remains active for 10-15 years.
  2. Each satellite instrument gives a different average TSI value.
  3. Each satellite implies subtly different, but significant differences in the trends between each sunspot cycle.

These problems can be seen below:

We can see from the above that, even though the data from each satellite mission are different, all of the instruments record the increases and decreases in solar activity over the roughly 11 year “solar cycle” which is observed in many solar activity indicators.

However, because the individual instruments typically only cover 10-15 years and they show different underlying trends relative to each other, it is unclear what other trends in TSI have occurred over the satellite era.

Several different research teams have developed their own satellite composites by combining the above satellite data in different ways and using different assumptions and methodologies. See this CERES-Science post for a summary.

Some of the main recent composites are:

  1. “ACRIM” – The ACRIM group finds that in addition to the 11 year solar cycle, there are important trends between each cycle. They find there was a significant increase in TSI between each solar minimum and maximum in the 1980s and 1990s, followed by a slight decrease in the early 2000s. See e.g., Scafetta et al. (2019).
  2. “PMOD” – The PMOD group applies several adjustments to the data of some of the early satellite missions and uses different methodological choices and assumptions. They find there has been a slight decrease in TSI between each of the cycles, but that it has been quite modest. See e.g., Montillet et al. (2022).
  3. “RMIB/ROB” – The ROB group (previously called RMIB) argues that there has been almost no change in TSI over the satellite era other than the 11 year solar cycle. See e.g., Dewitte & Nevens (2016).
  4. “The Community Composites” – Dudok de Wit et al. (2017) offer two different TSI composites. One using the original satellite data implies a reconstruction intermediate between the RMIB and ACRIM composites. The other using the PMOD-adjusted satellite data implies a reconstruction similar to the PMOD composite.

For the pre-satellite era, we don’t have direct measurements. Instead, researchers have to rely on “solar proxies” that they hope are accurately capturing important aspects of changing solar activity.

Some of the proxies include: sunspot numbers, group sunspot numbers, solar cycle lengths, the ratios of penumbra and umbra features of sunspots, bright spots in the sun’s photosphere (called solar faculae), cosmogenic isotope measurements, etc.

Typically, the solar proxies are calibrated against the satellite measurements during the satellite era. The calibrated solar proxies are then used to estimate the changes in TSI during the pre-satellite era.

Already you are probably thinking this is a complex and challenging problem. You are correct! Although, some scientists act as if these problems have all been fully resolved, those of us who have been actively researching these problems for many years can tell you that it is a thorny and contentious subject.

Depending on (a) which satellite composite is used; (b) which solar proxies are used; and (c) what methodologies are used, different research teams can develop very different long-term TSI reconstructions.

For example,

  1. Matthes et al. (2017) is the one IPCC AR6 used – based on the average of two other TSI reconstructions – Krivova et al. (2007)’s “SATIRE” and Coddington et al. (2016)’s “NRLTSI2”. All three match well to the PMOD composite.
  2. Dewitte et al. (2022) is a simple reconstruction based on simply rescaling the sunspot number record to match the RMIB composite.
  3. Egorova et al. (2018) developed 4 different estimates. Each shows far more variability over the last few centuries than the IPCC estimates.
  4. In a 2019 NASA study, Scafetta et al. (2019) updated the original Hoyt and Schatten (1993) TSI reconstruction using the ACRIM composite. This is a somewhat unique reconstruction because unlike most of the other reconstructions that only use one or two solar proxies, Hoyt and Schatten used five solar proxies in order to capture multiple aspects of solar variability.
  5. Penza et al. (2022) implies that TSI has changed significantly over the past century or so, but not as much as the Egorova et al. (2018) or the updated Hoyt and Schatten (1993) reconstruction.

In Connolly et al. (2023), we analysed a total of 27 TSI reconstructions, including all of the above. However, in Soon et al. (2023), for simplicity, we focused on just two of the above reconstructions – Matthes et al. (2017) and the ACRIM-updated Hoyt & Schatten reconstruction.

Dr. Schmidt clearly does not like either the ACRIM composite or Hoyt & Schatten’s original TSI composite. We can understand why! It implies a much larger role for the Sun in the climate changes since the 19th century than the RealClimate team claims exist.

However, it is worth noting that Hoyt and Schatten (1993) was used as one of the 6 TSI series considered by the CMIP3 modelling project that the IPCC used for their detection and attribution analysis in their 4th Assessment Report (2007). This can be confirmed by checking the list of “SOL” (i.e., TSI) time series on pages 11-12 of the Supplementary Material for Chapter 9 of IPCC AR4 Working Group 1.

The CMIP5 and CMIP6 modelling projects that contributed to the 2013 and 2021 AR5 and AR6 reports did not consider Hoyt and Schatten (1993) as a potential TSI series. However, this seems to partly be due the influence of Dr. Schmidt. He was the lead author of Schmidt et al. (2011), i.e., the paper recommending the climate modelling forcings to be used for the PMIP3 and CMIP5 projects.

At any rate, as we mentioned above, in Connolly et al. (2023) we considered a total of 27 different TSI reconstructions and we still reached similar conclusions to Soon et al. (2023). So, the specific choice of Hoyt and Schatten is just one way to demonstrate that the IPCC was premature in their AR6 attribution.

Addressing claim 2: Was Soon (2005) wrong?

In Soon (2005), Dr. Soon noticed a remarkable correlation between the Hoyt and Schatten (1993) TSI series and Arctic temperatures from 1875 to 2000.

In a follow-up paper, Soon (2009) repeated his analysis using (a) a newer version of the Hoyt and Schatten TSI series that had been updated to 2007 and (b) NASA GISS’ Arctic temperature record from 1880-2007.

The comparison is shown below adapted from Figure A.1 of Soon (2009):

In this week’s blog post, Dr. Schmidt conceded that the fit looked ok in 2005, but he claims it no longer holds:

“But time marches on, and what might have looked ok in 2005 (using data that only went to 2000) wasn’t looking so great in 2015.”

Dr. Schmidt then showed a plot he did in 2015 using a different TSI record from that used by Soon. His reanalysis failed to identify a compelling correlation when applied to the updated NASA GISS Arctic temperature record.

On the other hand, also in 2015, as part of our analysis of Northern Hemisphere rural temperature trends, in Soon et al. (2015) we included our own update to the original Soon (2005; 2009) analysis.

Below is Figure 27(d) of Soon et al. (2015). The blue line represents Arctic temperatures, while the dashed red line represents TSI:

Dr. Schmidt’s attempt to update Soon (2005)’s analysis to 2015, by using a different TSI record, failed.

In contrast, Soon et al. (2015)’s update’s that used the updated version of the TSI used by Soon (2005) and Soon (2009) confirmed the original findings of the earlier studies.

Addressing claim 3: Is our rural-only Northern Hemisphere temperature record representative of genuine climate change?

Dr. Schmidt appears to be confused about the rural-only Northern Hemisphere temperature record that we used as one of two comparative temperature records in Soon et al. (2023) and also as one of five comparative temperature records in Connolly et al. (2023).

We are surprised that he does not seem to have understood how these temperature records were constructed, since the construction of all five temperature records was described in detail in Connolly et al. (2021), along with a detailed discussion of the rationale for each temperature record. Details were also provided in the Soon et al. (2023) paper he was criticizing.

However, perhaps he hasn’t actually taken the time to read Connolly et al. (2021) yet. When Connolly et al. (2021) was published, Dr. Schmidt was asked to comment on the paper by a journalist for The Epoch Times. According to The Epoch Times:

“When contacted about the new paper, Gavin Schmidt, who serves as acting senior advisor on climate at NASA and the director of the Goddard Institute for Space Studies, was also blunt.

“This is total nonsense that no one sensible should waste any time on,” he told The Epoch Times.

He did not respond to a follow-up request for specific errors of fact or reasoning in the new RAA paper.”

– The Epoch Times, August 16th, 2021

One of the key problems we were highlighting in Soon et al. (2023) was the so-called “urbanization bias problem”. It is well-known that urban areas are warmer than the surrounding countryside. This is known as the “Urban Heat Island (UHI)” effect.

Because urban areas still only represent 3-4% of the global land surface, this should not substantially influence global temperatures.

However, most of the weather stations used for calculating the land component of global temperatures are located in urban or semi-urban areas. This is especially so for the stations with the longest temperature records. One reason why is because it is harder to staff and maintain a weather station in an isolated, rural location for a century or longer.

As a result, many of the longest station records used for calculating global temperature changes have probably also experienced localized urban warming over the course of their records. This urban warming is not representative of the climate changes experienced by the non-urban world.

Urban warming that gets mistakenly incorporated into the “global temperature” data is referred to as “urbanization bias”.

It is still unclear exactly how much the current global warming estimates are contaminated by urbanization bias. In their most recent report, the IPCC stated optimistically that urbanization bias probably accounted for less than 10% of the land warming. However, they did not offer a robust explanation for why they felt this was so.

Indeed, as described in Connolly et al. (2021), Soon et al. (2023) and Connolly et al. (2023), several scientific studies have suggested that urban biases accounted for more than 10% of the land warming – and possibly much more.

Brief detour: background to how and why we developed our rural-only Northern Hemisphere temperature record

In Connolly et al. (2021), we attempted to resolve the urbanization bias problem by developing a rural-only temperature record that only used temperature records from rural stations or stations that had been explicitly corrected for urbanization bias. However, we faced two major problems that we had been trying to resolve for nearly a decade:

  1. There was a severe shortage of rural stations with temperature records of a century or longer.
  2. Many weather stations with long temperature records are contaminated by other non-climatic biases, such as station moves, changes in instrumentation, etc.

When we looked at how other international groups (including Dr. Schmidt’s group at NASA GISS) were accounting for the non-climatic biases in the data, we discovered that they were not making any effort to contact the station owners for “station history metadata”, i.e., information on any changes associated with the station over its record.

Instead, most groups (including NASA GISS), were relying on automated computer programs that tried to guess when station changes might have introduced a bias. These programs used statistical algorithms that compared each station record to those of neighboring stations and applying “homogenization adjustments” to the data.

In a series of three “working papers”, two of us (Dr. Ronan Connolly and Dr. Michael Connolly) had published in 2014, we described how:

  1. There were serious flaws in the homogenization algorithms used by NOAA, the group whose homogenized data NASA GISS used for their global temperature estimates. (https://oprj.net/articles/climate-science/34)
  2. There were also serious problems with the additional “urbanization bias” adjustment computer program that NASA GISS applied to NOAA’s homogenized data (see https://oprj.net/articles/climate-science/31)
  3. All of the published studies up until at least 2013 that purported to have ruled out urbanization bias as a substantial problem had methodological flaws that meant their conclusions were invalid (see http://oprj.net/articles/climate-science/28)

In April 2015, while we were visiting New York City (along with Dr. Imelda Connolly), we offered to discuss these problems with Dr. Schmidt at the NASA GISS offices and see if possible solutions could be found. Dr. Schmidt declined the invitation explaining that he was not very familiar with how NASA GISS’ global temperature dataset was constructed. But, he kindly arranged for us to discuss the working papers with Dr. Reto Ruedy who was the lead scientist in charge of NASA GISS’ temperature dataset (called “GISTEMP”) at the time. All four of us (Dr. Reto Ruedy, Dr. Imelda Connolly, Dr. Michael Connolly and Dr. Ronan Connolly) met in the iconic “Tom’s Restaurant” right beside the NASA GISS office building.

Dr. Ruedy admitted that none of their research team had considered the various problems we had raised in our working papers. We asked him if he could see any problems with our analysis. He said that he couldn’t immediately, but he promised to e-mail us if he could see any mistakes in our analysis. Since he never e-mailed us, we assume that he couldn’t find any errors.

During our meeting with Dr. Ruedy, we warned him of a problem with NOAA’s homogenization algorithm which we call the “urban blending” problem, but others have called the “statistical aliasing problem”. Recently we have confirmed the severity of this problem in Katata et al. (2023).

We warned him that because of this problem, the urban warming biases in the data would become more deeply embedded in his global temperature estimates if he used NOAA’s homogenized version of the data.

He admitted that this was a problem, but he explained that the NASA GISS team in charge of the GISTEMP dataset were only allocated a limited number of hours per week to work on the data. So, he said that they had to trust that NOAA’s homogenization efforts were better than nothing.

We left our meeting with Dr. Ruedy quite disappointed to discover that even NASA GISS’ well-resourced research team didn’t know how to resolve these key scientific problems and were effectively just hoping that someone else was looking after the data.

We decided, if nobody else was going to try and properly resolve these problems, we would try.

At the time, NOAA provided two types of urban ratings associated with each of their Global Historical Climatology Network (GHCN) dataset – one based on local populations and the other based on the intensity of night-lights in the area. This was version 3 of the GHCN and NOAA kept it updated until late 2019. The current version of GHCN (version 4) does not include any urbanization metrics. So, for now our main analysis has focused on version 3. However, we are working on expanding our analysis in the future using version 4 – see Soon et al. (2018); O’Neill et al. (2022) and Katata et al. (2023) for more details on this later work.

We decided to sort all 7200 of the GHCN stations into three categories – “rural” stations are those rural in terms of both GHCN urban metrics; “urban” stations are those urban in terms of both metrics. All other stations we classify as “semi-urban”.

Immediately, we found several problems:

  1. Less than 25% of the GHCN stations are “rural”.
  2. Most of the rural stations had very short station records – often only covering 40-50 years or so.
  3. The few rural stations that had long records reaching back to the late-19th century or early-20th century were almost entirely in the Northern Hemisphere – and confined to a few regions: North America, Europe, East Asia and several Arctic locations.
  4. Many of the rural stations with nominally long station records often contained large data gaps and sudden shifts in the average temperature that could potentially be due to non-climatic station changes.

Most of the groups generating global temperature records from the weather station data rely on the temperature homogenization computer programs mentioned above to automatically adjust the original temperature records to remove “non-climatic biases” from the data.

If these homogenization computer programs were as reliable as many scientists have assumed, then these “automatically homogenized” temperature records should no longer be contaminated by non-climatic biases.

However, as we had discovered (and discussed with Dr. Ruedy in our 2015 meeting), these homogenization algorithms have serious statistical problems that introduce new non-climatic biases into the homogenized data.

In subsequent years, we have demonstrated the severity of these biases and statistical problems in several peer-reviewed scientific articles: Soon et al. (2018); O’Neill et al. (2022) and the recent Katata et al. (2023).

Therefore, we realised that the other groups analysing the weather station data were inadvertently making a major scientific blunder by relying uncritically on this automatically “homogenized” data.

Instead, to correct for non-climatic biases in the data, we need to start making more realistic experimentally-based corrections.

We decided to begin our analysis by identifying the areas with the longest rural records and the most information on the non-climatic biases associated with the data. We found that just four regions accounted for more than 80% of all the rural stations with data for the late-19th century/early-20th century. All four regions are in the Northern Hemisphere.

In our opinion, there was simply not enough Southern Hemisphere rural data to construct a global rural-only temperature series that would reach back to the late-19th century.

Therefore, we confined our analysis to the more data-rich Northern Hemisphere.

One region where we think we can expand our analysis in the future is for Europe (as we discuss in the papers). Currently, our European rural temperature analysis is confined to Ireland because we were able to obtain the key station history metadata for the Irish stations from the national meteorological organization (Met Éireann). However, in a recent paper, O’Neill et al. (2022), we carried out a large collaborative effort with scientists across Europe to compile the station history metadata for more than 800 weather stations in 24 European countries – see here for a summary. Most of these European stations are urbanized, but our preliminary analysis suggests that we should be able to use this metadata in the future to develop a more data-rich “rural Europe” temperature record.

How does our rural-only series compare to the standard “urban and rural” record?

The top panel shows the standard Northern Hemisphere land temperature estimates using all stations – urban as well as rural. The bottom panel shows our rural-only temperature estimate.

In Soon et al. (2023) – the paper Dr. Schmidt was complaining about – we consider both temperature estimates. We also consider two different TSI records – the Matthes et al. (2017) TSI series used for the attribution experiments in IPCC AR6 and the updated Hoyt and Schatten TSI series that we discussed earlier.

See below for a summary of some of our key findings:

Dr. Schmidt complains that our Northern Hemisphere rural-only temperature record is not reliable because,

“It’s not a good areal sample of the northern hemisphere, it’s not a good sample of rural stations – many of which exist in the rest of Europe, Australia, Southern Africa, South America etc., it’s not a good sample of long stations (again many of which exist elsewhere).”

This is a rather clever, but deceptive, misrepresentation of the data. Notice how he splits up his statement into two parts.

For the first part, he correctly says that there is “a good sample of rural stations” in other regions from those we analysed, but he neglects to explain that they are mostly stations with short records.

Indeed, if we look at the number of stations available in the year 2000, there are indeed many rural stations around the globe:

Then in the second part of his statement, he correctly says that there are many long station records outside of the regions we analysed, but he neglects to explain that they are not rural!

Below are the stations with data available in 1880. We have highlighted the three Southern Hemisphere regions he implied we should have also incorporated, i.e., Australia, Southern Africa and South America:Do you see why Dr. Schmidt’s characterization of the available data was disingenuous?

But, what about other estimates of Northern Hemisphere temperatures?

In Soon et al. (2023), we were assessing the Northern Hemisphere land surface warming (1850-2018) based on the weather station data. However, in Connolly et al. (2023), we also considered an additional three Northern Hemisphere temperature series. One was generated from the Sea Surface Temperature (SST) data. The other two were based on temperature proxy data: (a) tree-ring temperature proxies or (b) glacier-length temperature proxies.

Dr. Schmidt claimed that our rural-only temperature series was not representative of Northern Hemisphere temperature trends. If he is correct, then presumably these other temperature estimates would show very different trends. Let’s see!

What do you think?

Obviously, they are not exactly identical. However, in our opinion, all three of these alternative temperature estimates are broadly similar to our rural-only temperature record.

Therefore, we disagree with Dr. Schmidt’s claim.

Finally, if you recall from the beginning, Dr. Schmidt didn’t like the second TSI series we analysed in Soon et al. (2023). However, in Connolly et al. (2023), we analysed a total of 27 TSI series.

For each temperature record, we carried out statistical analysis in terms of the “natural” and “anthropogenic” (i.e., human-caused) climate drivers that the IPCC used for their attribution experiments. The IPCC only considered two natural drivers – TSI and volcanic eruptions. We used all of the IPCC’s climate driver records, but we repeated our analysis using each of the 27 TSI series in turn.

In both Connolly et al. (2023) and Soon et al. (2023), we adopt a similar approach to the IPCC’s attribution analysis. That is, we compare the results you get by considering:

  1. “Only natural factors” (which the IPCC defines as TSI and volcanic)
  2. “Only anthropogenic factors”.
  3. “Natural and anthropogenic factors”

If you want to see the results from all of these combinations, we recommend reading the full papers. But, for simplicity, let us just compare the first two combinations.

In Figure 6 of Connolly et al. (2023), we compared the “natural factors only” fittings using three of the best-fitting TSI series to the “anthropogenic factors only” fits. See below:

The TSI record that Dr. Schmidt was complaining about is labelled here as “H1993”. But, notice how for each temperature record, we can obtain similarly good fits using other TSI estimates.

Conclusions

In Soon et al. (2023), we reached the following key conclusions:

“(1) urbanization bias remains a substantial problem for the global land temperature data; (2) it is still unclear which (if any) of the many TSI time series in the literature are accurate estimates of past TSI; (3) the scientific community is not yet in a position to confidently establish whether the warming since 1850 is mostly human-caused, mostly natural, or some combination.”

These conclusions are consistent with our findings in another two of our papers that were also published in the last few weeks – in separate peer-reviewed scientific journals and using different independent analyses.

That is, in Katata et al. (2023), we confirmed that the IPCC’s estimate of the extent of urbanization bias in the global temperature data was much too low. Meanwhile, in Connolly et al. (2023), we concluded that it is “unclear whether the observed warming is mostly human-caused, mostly natural or some combination of both”.

Dr. Schmidt and the RealClimate team apparently do not want you to read our papers. They seem to be afraid that if you did, their claims on climate change would no longer seem so convincing.

In contrast, we are not afraid of people reading papers that disagree with us. In fact, we encourage people to read multiple scientific perspectives and form their own opinions. We agree with J.S. Mill’s quote below:

Below are links to the papers we mentioned above. We look forward to further discussion on our papers

References mentioned

  1. W. Soon, R. Connolly, M. Connolly, S.-I. Akasofu, S. Baliunas, J. Berglund, A. Bianchini, W.M. Briggs, C.J. Butler, R.G. Cionco, M. Crok, A.G. Elias, V.M. Fedorov, F. Gervais, H. Harde, G.W. Henry, D.V. Hoyt, O. Humlum, D.R. Legates, A.R. Lupo, S. Maruyama, P. Moore, M. Ogurtsov, C. ÓhAiseadha, M.J. Oliveira, S.-S. Park, S. Qiu, G. Quinn, N. Scafetta, J.-E. Solheim, J. Steele, L. Szarka, H.L. Tanaka, M.K. Taylor, F. Vahrenholt, V.M. Velasco Herrera and W. Zhang (2023). “The Detection and Attribution of Northern Hemisphere Land Surface Warming (1850–2018) in Terms of Human and Natural Factors: Challenges of Inadequate Data”, Climate, 11(9), 179; https://doi.org/10.3390/cli11090179. (Open access)R. Connolly, W. Soon, M. Connolly, S. Baliunas, J. Berglund, C.J. Butler, R.G. Cionco, A.G. Elias, V. Fedorov, H. Harde, G.W. Henry, D.V. Hoyt, O. Humlum, D.R. Legates, N. Scafetta, J.-E. Solheim, L. Szarka, V.M. Velasco Herrera, H. Yan and W.J. 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