No Evidence That Weather Extremes Becoming More Frequent or Intense: (2) Droughts

Droughts have been a continuing feature of the earth’s climate for millennia. Both short-term and long-term trends show no signs of any increase in frequency or intensity.

In fact, recent droughts have slightly declined on a global scale, as warmer oceans release more moisture into the atmosphere. This is illustrated in the figure below, in which drought conditions from 1982 to 2012 are denoted by D0 (abnormally dry); D1 (moderate); D2 (severe); D3 (extreme); and D4 (exceptional).

The next figure depicts observational data showing the percentage of the contiguous U.S. in drought from 1895 up until 2015. There’s clearly no trend over this period, apart from pronounced drought during the record heat waves of the 1930s.

A 2007 U.S. study was able to reconstruct the drought pattern in western North America over the last 1,200 years, using tree rings as a proxy. The width and color of the rings consti­tute a record of past climate, including droughts. The reconstruc­tion, illustrated in the following figure, reveals that several unprecedently long and severe “megadroughts” have occurred in North America since the year 800, droughts that the study authors re­mark have never been experienced in the modern era.

Comparison of the previous figure with the yearly data in this figure (indicated in gray; the thick black line is a 60-year mean), shows that the long-term pattern of overall drought in North America is featureless, despite global warming during both the Mediaeval Warm Period and today. A similar conclusion was reached by a 2021 study that compared the duration and sever­ity of U.S. hydrological droughts between 1475 and 1899 to those from 1900 to 2014. A hydrological drought refers to drought-induced decreases in streamflow, reservoir levels and groundwa­ter.

That some histori­cal droughts were even longer and more severe than those of today can be seen in another tree-ring reconstruction, of drought in California where I live. The next figure shows the pattern of dry and wet periods in my drought-prone state over the past 1,200 years. Although the third-driest period in the 1100s and the fifth driest period in the 1200s both occurred during the Mediaeval Warm Period, the driest (1500s) and fourth driest (800s) periods of drought occurred during rela­tively cool epochs.

Just like North America, Europe has also experienced mega­droughts over the past millennium, although in different peri­ods. The figure below illustrates a 2021 European reconstruction, again from tree ring proxies, of the drought pattern in central Europe from 1000 to 2012, with observational data from 1901 to 2018 ­superimposed. Black in the figure depicts the PDSI or Palmer Drought Severity Index that measures both dryness (negative values) and wetness (positive values); red denotes the so-called self-calibrated PDSI (scPDSI); and the blue line is the 31-year mean.

The authors of the study point out that droughts from 1400 to 1480 and from 1770 to 1840 were much longer and more severe than those of the 21st century. Their conclusions are reinforced by the results of another recent study, which failed to find any statistically significant trend in meteorological droughts in western Europe during the last 170 years. A meteorological drought describes one arising from a precipitation deficit alone.

What stands out in all these studies is the lack of any long-term trend in drought worldwide over at least a millennium. There is no evidence of the warming that began in the late 19th century, after the Little Ice Age ended, having played any role so far.

Indeed, ice cores from Antarctica demonstrate that much more dust – a sign of a dry climate – was deposited during the ice ages than during warmer interglacial periods. Even the UNDRR (UN Office for Disaster Risk Reduction), in its Special Report on Drought 2021 which drew a link between drought and global warming, acknowledged that one of the main sources of episodic droughts globally is the natural El Niño Southern Oscillation.

There are regional variations, however. A 2021 research pa­per found that, from 1901 to 2017, the risk of meteorological droughts increased in the southwestern and southeastern U.S., while it decreased in northern states. Indeed, the UNDRR report found that such regional differences in drought are not restricted to the U.S. but occur worldwide.

Although generally caused by a severe fall-off in precipitation, droughts can be aggravated by other factors such as elevated temperatures, soil erosion and overuse of available groundwater. The consequences of drought, which can be catastrophic for human and animal life, include crop failure, starvation and mass migration. A major exodus of early humans out of Af­rica about 135,000 years ago is thought to have been driven by drought.

Next: No Evidence That Weather Extremes Becoming More Frequent or Intense: (3) Floods

No Evidence That Weather Extremes Becoming More Frequent or Intense: (1) Heat Waves

Climate reporting of the last few years has routinely promoted the mistaken belief that weather extremes are worsening be­cause of climate change.

But the perception that weather extremes are increasing in frequency and intensity is false. The perception actually results from modern technology – the Internet and smart phones – which has revolutionized communication and made us much more aware of extreme weather than we were 50 or 100 years ago.

To demonstrate how extreme weather has not changed or even declined over time, this and subsequent posts will present observational evidence showing long-term trends over the past century or so for heat waves, droughts, floods, hurricanes, tornadoes and wildfires.

We’ll start with heat waves. It’s commonly argued that heat waves today are hotter than ever before. That is possible, but only because global warming has raised the baseline temperature by 1.3 degrees Celsius (2.3 degrees Fahrenheit) since preindustrial times – so we would expect heat waves to be that much hotter too.

Even so, there’s no evidence that current heat waves are hotter on average than they were in the past. The figure below shows the frequency and magnitude of heat ­waves in the U.S. from 1901 to 2018. The frequency (top panel) is defined as the annual number of calendar days the average U.S. maximum temperature exceeded the 90th percentile for 1961–1990 during at least six consecutive days, in a window centered on that calendar day; it repre­sents the average duration of all heatwaves of six days or longer in that year.

It’s clear that there were far more frequent and/or longer U.S. heat waves, and they were hotter, in the 1930s than in the present era of global warming. The average annual heat wave or warm spell duration (top panel) is seen to have dropped from 11 days during the 1930s to about 6.5 days during the 2000s. The peak heat wave index (bottom panel) in 1936 was a full three times higher than in 2012 and up to nine times higher than in many other years.

In addition, the aver­age maximum temperature during any particular U.S. heat wave has declined slightly from 38 degrees Celsius (101 degrees Fahrenheit) in the 1930s to 37 degrees Celsius (99 degrees Fahrenheit) since the 1980s. This can be seen indirectly in the next figure, which plots the average number of days per weather station with maximum temperatures above 35 degrees Celsius (95 degrees Fahrenheit) for the conterminous U.S. (bars) and regions (lines, 11-year averages).

With the exception of the Pacific southwest (dashed blue line) and the Four Corners states (Arizona, Utah, Colorado and New Mexico, dashed black line), all other regions exhibit a declining trend. The absence of any trend in the U.S. as a whole is clearly evident. 

As I’ve documented in a GWPF report, the hottest years of the 1930s in the U.S. were 1934 and 1936. In the summer of 1934, Fort Smith, Arkansas recorded an unbelievable 53 consecutive days with maximum temperatures of 38 degrees Celsius (100 degrees Fahrenheit) or higher. Topeka, Kansas, had 47 days, Oklahoma City had 45 days and Columbia, Missouri had 34 days when the mercury reached or passed that level. Approximately 800 deaths were attributed to the widespread heat wave, at a time when the U.S. population was about 60% smaller than today.

In comparison, the U.S. heat wave during July 2023, which was falsely trumpeted by the main­stream media as the hottest month in history, did not outmatch the scorching heat of 1934. El Paso, Texas did experience 44 consecutive days with maximum temperatures above 38 degrees Celsius (100 degrees Fahrenheit), somewhat shorter than Fort Smith’s 53 days in 1934 just mentioned. And Phoenix, Arizona saw the maximum there exceed 43 degrees Celsius (109 degrees Fahrenheit) – a comparable baseline for a city with a hotter climate than El Paso – but only for 31 days in a row.

Heat waves lasting a week or longer in the 1930s were not confined to North America; the Southern Hemisphere baked too. Adelaide on Australia’s south coast experienced a heat wave at least 11 days long in 1930, and Perth on the west coast saw a 10-day hot spell in 1933. Not to be outdone, 1935 saw heat waves elsewhere in the world, including India, France and Italy.

That today’s heat waves are nothing extraordinary is apparent from the following table, which depicts all-time record high tem­peratures for the seven continents. Three records date from the 1930s or before, while only Europe and Asia have set new records in the 21st century.

The record high temperatures during the deadly recent heat wave in Europe, which ranged up to 41.7 degrees Celsius (107 degrees Fahrenheit), are still lower than the continent’s all-time record in the table, set on the Italian island of Sicily five years ago. And the recent European heat wave’s duration pales in comparison with the U.S. heat waves described above.

Next: No Evidence That Weather Extremes Becoming More Frequent or Intense: (2) Droughts

The Pseudoscience behind Extreme Weather Attribution

As I wrote in a previous post, newly popular extreme event attribution studies are deeply flawed, with fundamental logical and meth­odological errors. Here I examine these failings in more detail.

To begin with, attribution studies rely on computer climate models, the weaknesses of which I’ve described multiple times in these pages (see for example here and here). The models have a dismal track record in predicting the future, or indeed of hindcasting the past. Not only do the majority of models overestimate the warming rate, but they also wrongly predict a hot spot in the upper atmosphere that isn’t there and are unable to accurately reproduce sea surface temperatures and sea-level rise.

Most importantly for attribution studies, the models are poor at hindcasting. That matters because the models are used to compare the present climate with anthropogenic CO₂ emissions to a preindustrial climate without extra CO₂.

In particular, climate models underestimate the warming during the global warming spell from 1910 to 1940, seen in the figure below. If the same deficiency applies to hindcasted temperatures before that period, including those in 1850 which is the baseline preindustrial year for attribution studies, then such studies will underestimate the magnitude of any counterfactual, comparison warming (and probably any other weather characteristic) in preindustrial times.

Another weakness of attribution method­ology is that, in the absence of CO₂, we simply do not know what the “natural” climate would have been. Although we have reliable historic mete­orological data for a few countries such as the UK and the U.S., we do not for most of the other countries on the planet. And historical data for variables such as cloud cover and wind speeds is lacking worldwide.

A further deficiency in event attribution studies is lack of attention to the uncertainty involved in temperature or other measurements, as I mentioned in the earlier post. An example of this is a Grantham Institute attribution study claiming that 2024’s Hurricane Helene that struck the U.S. was 100%, or 2 times, more likely than would have occurred in a preindustrial climate. Helene was a large Category 4 (top wind speed 250 km per hour or 156 mph) hurricane when it made landfall and caused significant damage across Florida and the southeastern U.S.

The next figure shows the path of Hurricane Helene, together with the maximum speed locations of historically observed and simulated hurricanes that followed paths within a 2° radius of Helene landfall. It also includes the attribution study’s estimates of landfall maximum wind speed as a function of “return period”; the return period is the expected interval between successive hurricanes at the same location, which is the inverse of hurricane frequency.

However, the methodology of the Hurricane Helene study is fundamentally flawed. Beyond the general limita­tions of attribution studies, hurricane behavior in particular is poorly reproduced by climate models. This contrasts with heatwaves, for which models are relatively skillful. Furthermore, very few North Atlantic hurricanes have made landfall in the same region of Florida, limiting the amount of observational data available.

The study’s solution to this problem was to include data from hurricanes that passed nearby but never actually made landfall in the same region – historic “near misses,” which are depicted in the top panel of the figure. Such practice is highly questionable at best, deceptive at worst. The blatant dishonesty is exemplified in the bottom panel, where it can be seen that the uncertainty (colored bands) associated with the partly simulated 2024 Helene curve (orange line) embraces the preindustrial curve (blue line); in other words, Helene may have been no more likely than normal.

The lack of attention to uncertainty is evident in the same data. For example, the uncertainty range (blue band) for the preindus­trial curve includes the observational data (black line) for all North Atlantic hurricanes since 1900 – suggesting that there has been nothing very different about Florida landfalling hurricanes, including Helene, over the whole period of observation.

After accounting for this uncertainty, therefore, the Helene study’s conclusions that the return period decreased from 130 years in the preindustrial era to 52 years, and the wind speed increased by 6.1 meters per second or 11%, are meaningless.

That there was indeed nothing exceptional about Hurricane Helene is reinforced by the plot of all Florida landfalling hurricanes since 1850, presented below. Neither hurricanes overall nor major hurricanes, of which Helene was the latest, exhibit any long-term trend. Taken as a whole, the conclusions of this Hurricane Helene attribution study are faulty.

Extreme event attribution studies, as currently conducted, fail to reinforce the mistaken belief that weather extremes are rising due to global warming – as I will demonstrate in subsequent posts.

Next: No Evidence That Weather Extremes Are Becoming More Frequent or Intense: (1) Heat Waves

RIP RCP8.5: A Hopeful Sign That the Attack on Science Is Letting Up

Nowhere is the attack on science more evident than in the debate over the human contribution to current global warming. But the recent publication of brand-new 2026 emissions scenarios that finally killed off the older RCP8.5 – which was behind the highly exaggerated notion of a “climate crisis” and other alarmist proclamations – raises hopes that reason may be returning to science.

The introduction of RCP8.5 in the early 2010s was probably well-intentioned. As the highest of standard low-, medium- and high-emissions pathways created by climate scientists, RCP8.5 anticipated annual CO₂ emissions roughly tripling by 2100, as seen in the figure below. Even though this was unlikely, it was included as part of an effort to capture all supposedly plausible outcomes – a worst case scenario around the 90th percentile.

But RCP8.5 quickly became adopted by climate alarmists and many in the climate science community as a “business as usual” scenario, which assumed emissions were on an ever-increasing trajectory. It ignored true science that was reflected in the lower emissions pathways.

That RCP8.5 was in fact implausible is evident in its underlying assumptions. First, the scenario predicted a five to sevenfold increase in global coal use that included fueling cars with coal-based liquids, displacing gasoline. As climate writer Roger Pielke Jr. has pointed out, the scenario extrapolated then rapidly rising coal growth rates in China and assumed that such vast amounts of coal would still be available by the end of the century, regardless of geological reality or other real-world constraints.      

The next figure shows that actual coal use started to decline as early as 2015. The dashed line depicts the erroneous, steadily increasing projection of RCP8.5, a false assumption baked into the scenario from the outset.

Another implausible assumption in RCP8.5 was massive population growth, from approximately 7 billion in 2010 to between 11 and 12 billion by 2100. Combined with purported high energy demand and slow income growth, as well as scorching heat, the assumed population gain would result in a lowering of global GDP. However, current demographic models peg the global population at under 10.4 billion by 2080, and socioeconomic trends suggest a much more prosperous world with substantial gains in GDP by then.

A third mistaken assumption behind RCP8.5 was future stagnation in improvements to non-coal technologies such as solar, wind and nuclear power, due to the dominance of coal energy. That hasn’t happened either, with major strides in all three areas.

The figure below compares CO₂ emissions and projected warming between 2000 and 2100 for three different pathways: the now obsolete RCP8.5; the mean of the baseline scenarios published by the IPCC (Intergovernmental Panel on Climate Change) in its Sixth Assessment Report; and one of the new 2026 scenarios.  As can be seen, projected 2100 global warming falls from 4.5 degrees Celsius (8.1 degrees Fahrenheit) in RCP 8.5 to 2.8 degrees Celsius (5.0 degrees Fahrenheit) in the latest representation.

The widespread adoption of RCP8.5 greatly distorted the climate change debate. Hundreds if not thousands of published research papers and government reports that assumed RCP8.5 was realistic took the underlying science in an entirely wrong direction, by coming up with results or predictions that must now be regarded with suspicion.

On the policy side, central banks used it to test whether financial institutions were prepared for the effects of climate change – effects that RCP8.5 exaggerated. Governments around the world used it for adaptation planning, and insurance companies used it to set rates. A whole host of past actions now need to be reexamined in the light of the new emissions scenarios.

But perhaps the greatest damage was to the public perception of climate change. Fed by media hype, people were persuaded that not only was global warming man-made and dangerous, but we were also in a climate crisis. The UN secretary-general was among many duped leaders, hysterically describing the IPCC’s Sixth Assessment Report as “code red for humanity” and proclaiming that “the era of global boiling has arrived.”

Some, like Roger Pielke Jr. and his colleague Justin Ritchie, were not fooled and began questioning conventional wisdom and arguing against the continued use of RCP8.5 almost 10 years ago. Yet these early voices of reason were largely dismissed until now. That’s a sad reflection on the state of science today.

But, as I said at the outset, this major body blow to climate alarmism may represent a turning point in the ongoing attack on science.

Next: The Pseudoscience behind Extreme Weather Attribution

A New Threat to Science: AI Making Up References in Research Papers

It’s not a new phenomenon. AI has been “hallucinating” – making things up – for some time, in areas ranging from law to medicine. But a new example of this affliction has recently emerged: fabricating citations in scientific research papers.

A recent article in the prestigious medical journal The Lancet reported the first systematic evaluation of reference authenticity. The audit of 2.5 million biomedical papers spanning 3 years showed that fabricated references are deeply embedded in the peer-reviewed literature. And the rate of fabrication is accelerating, as demonstrated in the figure below.

The integrity of references is fundamental to the integrity of scientific literature. Each reference implicitly asserts that a verifiable source exists and bolsters the claims being made. When references cite non-existent studies, readers, reviewers and policy makers are unable to evaluate the evidence.

Fabricated references can arise from paper mill activity and intentional deception, as well as the indiscriminate use of AI writing tools. Large language models (LLMs) are capable of generating plausible sounding but fictitious references. Previous studies have estimated that between 30% and 69% of LLM-generated references in biomedical research are fabricated, say The Lancet authors. The references are often correctly formatted, attributed to real researchers and include credible publication dates, making them difficult to detect by conventional peer review.

The authors developed an automated reference verification system by scanning PubMed Central’s Open Access subset from January 1, 2023, to February 18, 2026. That effort examined 2,471,758 papers and 125,615,773 structured references. Of the 125.6 million references, 77% carried a PubMed identifier and were verified; the remaining 23%, predominantly non-indexed references (from sources such as websites and books), were excluded.

Among the verified references, which came from 2810 papers, the authors identified 4046 fabricated citations. In 2023, approximately one in 2828 papers contained at least one fabricated reference. By 2025, this had gone up to one in 458, and in the first 7 weeks of 2026, a staggering one in 277 papers had at least one fabricated reference. As shown in the figure above, the fabrication rate increased by more than 10 times from 2023 to 2026.

It was found that 91% of affected papers contained just one or two fictitious references; 9% contained three or more. The sharp inflection in mid-2024 coincides with the expected publication lag following widespread LLM adoption, although increased paper mill activity and changes in journal indexing practices might also have contributed. LLMs became widely available in late 2022 and 2023.

The article’s authors qualify their findings by stating that the exclusion of 23% of references with no PubMed identifier could bias their estimates. Furthermore, PubMed Central’s Open Access does not cover all biomedical literature, and the early 2026 data span only 7 weeks. And, they say, their approach identifies the problem but not the underlying cause.

Nonetheless, the authors do have some recommendations for publishers. These include integrating automated reference verification into submission workflows before peer review; having indexing services add integrity metadata to article records so that users can assess the reliability of references; and retroactively screening existing publications and issuing corrections or retractions when fabricated references compromise a paper’s conclusions.

On the broader question of why such fabrication is occurring, the answer lies in the training of LLMs. A 2025 article in Science magazine argues that AIs hallucinate because they’re trained to fake answers when they don’t know how to answer a question. A team from OpenAI and the Georgia Institute of Technology is more specific:

They learn to bluff because their performance is ranked using standardized benchmarks that reward confident guesses and penalize honest uncertainty.

Although AIs could be modified to admit that “I don’t know,” this could simply turn off users, who would then seek an alternative LLM. A better solution, say several computer scientists, would be to rework benchmarks to penalize an AI for guessing incorrectly. Current benchmarks don’t penalize incorrect guesses any more than nonanswers.

The need for AI to clean up its act is especially important in medicine. In deciding on patient treatment, medical professionals are often influenced by clinical guidelines in the research literature. Doctors and practitioners have no way of knowing whether the evidence they are relying on actually exists.

In a comment accompanying The Lancet article, two pediatrics professors place the onus on manuscript authors themselves, saying that:

Authors must take responsibility and be held accountable for the entire content of a manuscript, including the references.  

The professors believe that a published manuscript in which a fabricated reference is detected should be retracted. While this may seem harsh, such a move would go a long way toward meeting the AI challenge and restoring the integrity of scientific research.

Next: RIP RCP8.5: A Hopeful Sign That the Attack on Science Is Letting Up

Sea Level Rise Dominated by Subsidence, Not Global Warming

Of all the topics I’ve covered in this blog, none have attracted as many readers as sea level rise (see for example here, here and here). And for good reason, since rising seas threaten the livelihood of tens of millions of coastal dwellers around the world.

What is not generally known is that the main culprit is land subsidence resulting from groundwater extraction and urban development that causes more sea level rise than any human-induced global warming. The importance of subsidence has been brought to light by two recent research papers: a Dutch study finding that current model-based estimates of sea levels are much too low, and a study of river delta subsidence by an international team of environmental scientists and others.

Several different processes can affect vertical motion of land. Long-term glacial rebound after melting of the last ice age’s heavy ice sheets is causing land to rise in high northern latitudes. Yet in many regions, the ground is sinking because of sediment settling and aquifer compaction caused by human activities, especially groundwater depletion resulting from rapid urbanization and population growth.

Land subsidence artificially amplifies any local rise in sea level, which can be measured by either tide gauges or satellite altimetry. Tide gauges measure the height of the sea relative to the land to which the gauge is attached, the so-called RSL (Relative Sea Level) metric. Satellite observations of absolute sea level measure the height of the sea, which is the distance of its surface to the center of the earth.

Subsidence of the land independently of sea level makes satellite-measured sea levels higher than tide gauge RSLs. That’s why the average rate of rise from 1900 to 2020 determined by tide gauges was only 1.75 mm (0.07 inches) per year, while NASA’s satellite measurements say the rate was more like 3.3 mm (0.13 inches) per year from 1993 to 2024.

But neither tide gauges nor satellites measure sea levels at all points on every coastline in the world, which is why so-called geoid models, rather than actual sea level measurements, are used to make estimates. A geoid is an equipotential surface that approximates mean sea level based on gravity and the earth’s rotation.

However, because the actual height of the sea surface is not determined only by the gravity and rotation of the earth, but also by other factors such as ocean currents, winds, tides and seawater temperature, the time-average sea-surface height can deviate strongly (up to several meters) from a geoid. The discrepancy between geoid and actual sea level has led to widespread underestimation of coastal sea level rise.

This occurs predominantly in parts of the world where the most rapid land subsidence is happening – in southeastern and eastern Asia, for example. The Dutch study examined 40 river deltas worldwide subject to severe subsidence such as the Vietnamese Mekong Delta, which is one of the most densely populated coastal landscapes exposed to rising sea levels worldwide.

The figure below shows how much land subsidence has already occurred in the 40 deltas. Yellow and red circles denote subsidence, the circle size indicating the percentage of the delta area subsiding faster than satellite-measured sea level rise, which averages about 4 mm (0.16 inches) per year globally. 

In 13 of the deltas (Brahmani, Brantas, Ceyhan, Chao Phraya, Ciliwung, Godavari, Mahanadi, Mekong, Nile, Po, Red, Vistula and Yellow River), the subsidence rate exceeds 4 mm (0.16 inches) per year. Among these, the Chao Phraya (Thailand), Brantas (Indonesia) and Yellow River (China) deltas show an average sinking rate of more than twice the current rate of global sea level rise.

Overall, more than 90% of the delta area is affected by subsidence in 19 of the 40 deltas studied, while more than 50% of the delta area is subsiding in 38 of the 40. Coastal cities in the deltas are experiencing subsidence rates even greater than the deltas themselves. In Jakarta (Ciliwung), for example, parts of the city are subsiding at alarming rates surpassing 30 mm (1.2 inches) per year, dwarfing average global sea level rise by almost an order of magnitude. 

The effect of land subsidence in river deltas on local populations is demonstrated in the next figure. The upper left panel (a) compares rates of local sea level rise and subsidence; current average subsidence rates exceed sea level rise in 18 of the 40 deltas, including the Mekong and Nile. The lower left panel (b) makes the same comparison, but only for populations living within 1 meter of sea level. Panel c on the right is a bar plot of subsidence vs sea level rise for 30 of the 40 deltas.

Of the various possible contributions to subsidence, groundwater storage has the strongest relative influence in 10 of the 40 deltas. The other drivers are sediment flux and urban expansion.

Next: A New Threat to Science: AI Making Up References in Research Papers

Uncertainty in Ocean Heat Content May Be Grossly Underestimated

According to measurements made by Argo profiling floats, the amount of heat stored in upper ocean layers has been rising rapidly over the past few decades. But a new paper casts doubt on this assertion, claiming that uncertainty in the measurements is so large that any increase in stored heat is statistically indistinguishable from zero.

Argo floats have been used since 2004 to study ocean temperatures and other properties at depths up to 2 km (1.2 miles), by means of a global array of over 4,100 robotic cylinders. As illustrated in the figure below, these free-drifting floats patrol the oceans, taking a deep dive every 10 days to probe the temperature, salinity and pressure of the watery depths, and then transmitting the data to a satellite within hours of bobbing up to the surface again. A recent map of the Argo array is shown in the second figure.

One of the principal sources of uncertainty in the float measurements is evident from the first figure above – namely, the large volume of seawater sampled during a float’s traverse to record just a single reading. That reading is an average of measurements made approximately every second during the float’s 6-to-10-hour ascent from depth to surface.

During the ascent stage, the exact horizontal position when the temperature is measured is highly uncertain because of depth-varying currents, mesoscale eddies and other turbulent motions. The study authors estimate the horizontal uncertainty to be as much as 5-50 km (3-30 miles), stating that the float’s path as it ascends is “an unknown and complex, meandering curve through a spatially and temporally varying flow field.”

Furthermore, the average reading during ascent is considered to be representative of the whole volume encountered by the float since its initial descent. The positional uncertainty in a single temperature measurement, therefore, can cause an associated uncertainty in temperature of 0.5-3 degrees Celsius (0.9-5.4 degrees Fahrenheit), say the researchers.

The uncertainty in Argo float temperature measurements leads to even more uncertainty in estimating OHC (ocean heat content), which is the mathematical integral of absolute temperature (usually expressed as an anomaly from some mean) multiplied by seawater density multiplied by ocean specific heat capacity. Density and heat capacity vary with depth and other factors such as large-scale currents.

Another major source of uncertainty is sampling error. The total global volume sampled by all Argo floats in one year is about nine orders of magnitude smaller than the volume of the upper ocean (to a 2 km depth). The associated uncertainty in OHC estimates is approximately 0.1-0.5 watts per square meter, the researchers say – a level from sampling error alone comparable to the total uncertainty in OHC of 0.2 watts per square meter cited by the IPCC (Intergovernmental Panel on Climate Change) in its 2021 AR6 (Sixth Assessment Report).

For the deep ocean, sampled by a paltry 315 Argo floats, they estimate the sampling error uncertainty to be as large as 0.35 watts per square meter from 1971 to 2018, which is half the IPCC’s actual OHC value of 0.7 watts per square meter.

The uncertainty in temperature measurement of 0.5-3 degrees Celsius (0.9-5.4 degrees Fahrenheit) results in an OHC uncertainty of up to 0.1 watts per square meter. Additional sources of uncertainty include unresolved mesoscale variability, altimetry uncertainty and baseline date range, among others.

By mesoscale variability, the researchers are referring to uncertainties in boundary currents and eddy-rich regions. Certain areas of the global ocean such as the Gulf Stream and the Antarctic Circumpolar Current exhibit intense fluctuations, on a scale of 10-200 km (6-125 miles), in temperature and salinity driven by eddies and other instabilities. The researchers estimate that these fluctuations contribute 0.6-1.2 watts per square meter of uncertainty to the OHC.

Altimetry uncertainty arises from the discrepancy between changes in sea level estimated from OHC, and changes determined by satellite altimetry. Altimetry deduces absolute sea level by measuring the height of the sea, which is the distance of its surface to the center of the earth. The much less direct OHC method relies on Argo float measurements of seawater temperature and salinity, the latter of which is related to density. The researchers assign an OHC uncertainty of 0.29-0.37 watts per square meter to this cause.

And baseline date range uncertainty refers to possible errors in the calculated OHC due to any shift in the reference period, for example from 2004-18 to 2005-19. Such a shift can obscure the influence of different phases of ocean cycles such as the PDO (Pacific Decadal Oscillation) or AMO (Atlantic Multidecadal Oscillation). This can produce an OHC uncertainty of 0.1-0.3 watts per square meter, say the paper’s authors.

Collectively, these and other sources can contribute a total uncertainty of 1 watt per square meter, which exceeds the IPCC’s estimate of 0.7 watts per square meter for the OHC itself.

Next: Sea Level Rise Dominated by Subsidence, Not Global Warming

The Evidence Shows We Are Nowhere Near a Climate Tipping Point, As Alarmists Claim

A recent paper raises the specter of the earth’s climate being on a “hothouse trajectory” – a pathway in which self-reinforcing feedbacks push the climate system past a point of no return, an irreversible disaster beyond which the planet would become unbearably hot. But a careful look at the evidence reveals this claim to be absurd, with no sign that we are currently anywhere close to such a tipping point.

This is not a new form of alarmism. In fact, the paper’s lead author published another paper over six years ago titled “World Scientists’ Warning of a Climate Emergency,” perhaps the beginning of the recent obsession with the erroneous notion of a climate crisis caused by global warming. And a new NGO (non-governmental organization), Global Tipping Points, has in 2023 and 2025 produced fearmongering reports on tipping points.

That we are approaching a tipping point, insists the new paper, is evident from an imagined surge in extreme weather that the paper claims is becoming “more frequent, intense, and costly.” However, the observational evidence shows that most forms of extreme weather are becoming neither more frequent nor more intense, as I’ve demonstrated numerous times in these pages (see Category “Weather extremes”). The increasing costs of natural disasters are simply a result of population gain and the ever-escalating value of property in harm’s way.

The NGO’s 2025 report features the following summary of supposed global-warming-enhanced tipping points faced by our earth. The vertical bars represent the range of anticipated temperature increases that would trigger various tipping points. The report’s purported nearness of tipping points is reflected in the lower limits of all the bars being in the current level of warming band.

Nevertheless, it’s not difficult to show that none of these tipping points – nor several others cited in the report – are imminent. I’ll discuss just three here: coral reefs, ice sheets, and the AMOC (Atlantic Meridional Overturning Circulation).

According to the figure above, die-off of low-latitude coral reefs has already begun, with an estimated tipping point of 1.2 degrees Celsius (2.2 degrees Fahrenheit) above preindustrial temperatures. This shortsighted claim, probably based on temporary losses in global coral cover during the recent period of elevated sea surface temperatures, is irrational.

Australian physicist and leading coral reef authority, Professor Peter Ridd has explained in a 2023 report that most corals that bleach due to higher temperatures do not die, but are capable of rapid recovery in a decade or less. This is exemplified by studies of Australia’s Great Barrier Reef, which has the most reliable long-term record of large-area coral cover. Despite four supposedly catastrophic bleaching events in the six years prior to 2022, the reef’s coral cover reached a record high in 2024, as depicted in the image on the left below.

The image on the right shows the estimated global average cover of hard coral (solid line) and its associated uncertainty (shaded areas) since the late 1970s. Note that data before the late 1990s is of little value, says Ridd, because of small sample sizes; but the data since then reveals little overall variation – certainly nothing suggestive of a tipping point, either already passed or impending.

As for likely collapse of the West Antarctic ice sheet, there’s no evidence that such a catastrophic event is just around the corner either. As I discussed in a 2025 post, the Antarctic ice sheet overall is growing, and no longer melting, for the first time in decades. This is illustrated in the figure below, which shows changes in Antarctic ice sheet mass from April 2002 to December 2023, measured in billions of tonnes (gigatonnes, Gt where 1 gigatonne = 1.102 U.S. gigatons).

Although the ice sheet does appear to be growing in East Antarctica, the ice loss there in the form of melting glaciers is partly caused by active volcanoes underneath the continent. There’s no evidence that the East Antarctica portion of the ice sheet is anywhere near collapse.

Finally, I also discussed the very unlikely slowing down, let alone collapse, of the AMOC in a very recent blog post. All claims of impending doom rely on computer climate models, which have a generally poor history of making predictions. Although some models do indeed support the existence of a weakened AMOC, such cherry picking is highly unscientific and many of the ignored models in fact simulate a strengthened AMOC.

The next figure, from the new paper, graphs the mean global temperature over past millennia, with future projections based on so-called SSPs (Shared Socioeconomic Pathways) that range from low- to high-emission scenarios. As climate writer Roger Pielke Jr. has emphasized on many occasions (see here, for example), high-emission scenarios such as SSP5-8.5 are implausibly extreme. More realistic scenarios such as SSP1-2.6 or even SSP2-4.5 will produce only modest warming in the near future, with no likelihood of triggering tipping points.

Next: Uncertainty in Ocean Heat Content May Be Grossly Underestimated

Abuse of Science: Extreme Event Attribution Studies

As its header suggests, this blog’s purpose is to combat today’s abuse and rejection of true science – the hallmarks of which are empirical evidence and logic. These two pillars are being outrageously abused in climate science by the ever-increasing use of extreme event attribution studies, which attempt to describe the extent to which specific extreme weather events are influ­enced by anthropogenic climate change.

Both the mainstream media and government reports have latched on to event attribution to fan the flames of climate alarmism and the associated narrative that we are in a climate crisis. But such studies are deeply flawed, with errors in both science and inter­pretation, having been created for legal and political rather than scientific reasons.

One of the fundamental failings of attribution studies is the logical fallacy of “begging the question.” To estimate the effect of a particular extreme event, the studies need to replicate the climate without the impact of global warming.

But this ignores the role of natural variability, which is neglected in climate models used in attribution studies on the assumption that only anthropogenic CO₂ – with no contribution from natural sources – accounts for all current warming. If natural sources play no role in warming today, then their contribution to a preindustrial climate is unknown.

Other scientific shortcomings are a lack of appropriate peer review, faulty statistics and the ignoring of important evidence. Defective methodological practices include the improper use of temperature datasets, a lack of sufficient attention to uncertainties in the data, and the neglect of historical records.

In a new GWPF report, I’ve discussed several recent attribution studies in detail. One example is a heatwave concentrated in the U.S. southwest, Mexico and Central America in May and June 2024, which generated alarmist media headlines proclaiming the event “35 times more likely” than before. The media reports were fed by an attribution study conducted by the Grantham Institute at Imperial College, London.

Apart from the general limitations of attribution studies, the absurdity of such a claim can be seen in the conclusions drawn from the temperature datasets employed. The figure below shows the May to June maximum of 5-day maximum daytime temperatures in the study region from 1950 to 2024, for all three datasets; the dashed lines are 10-year moving averages.

To begin with, the study’s estimate of the region’s 2024 heatwave being 35 times more likely than in the preindustrial past is an average estimate for all three temperature datasets. But its estimate for only the ERA5 data (the European Centre for Medium-Range Weather Forecasts 5th generation reanalysis product), which includes observations going back to 1950 rather than only 1979 in the other two datasets, is a much lower 13 times more likely.

Another reason this attribution study is in error is that it does not emphasize the uncertainty involved. It can be seen from the figure that when uncertainties in the temperature measurements are taken into account, a heatwave possibly com­parable to 2024 occurred in the early 1990s; the temperature uncertainty is indicated by the height of the boxes for each data point.

A second example is a devastating flash flood that swept through holiday camps and homes in central Texas on July 4, 2025. An attribution study conducted by ClimaMeter, a French counterpart of the UK’s Grantham Institute, concluded that “Natural variability alone cannot explain the changes in precipitation associated with this very exceptional meteorological condition.”

ClimaMeter attributed the catastrophic flooding to two factors: a purported temperature increase of up to 1.5 degrees Celsius (2.7 degrees Fahrenheit) in the flood-affected area, from the period of 1950–86 in the past to the more recent period of 1987–2023; and present-day rainfall up to 2 mm (0.08 inches) per day, or up to 7% wetter than in the past, in parts of central Texas.

But these assertions don’t stand up to scrutiny. First, the reference period of 1950–86 includes 25 of approximately 35 years of global cooling from 1940 to 1975, so that the estimated temperature increase for central Texas between 1950 and 1986 is most likely inflated.

Second, heavier rainfall does not necessarily lead to an increase in extreme flooding probability, which depends on other factors such as rainfall duration, landscape and the type of river basin. In fact, disastrous floods in Texas’ Flash Flood Alley are nothing new and have caused devastation for more than a century, as shown in the following table.

As my report discusses, extreme event attribution was developed because of the inability of the IPCC (Intergovernmental Panel on Climate Change) to achieve high or even medium confidence in the detection and attribution of most types of extreme weather events. This has been politi­cally problematic for climate activists, who have therefore pushed for rapid extreme event attribution in order to pursue climate litigation against fossil fuel companies.

The origins of this climate lawfare date back to a 2012 meeting of U.S. environmental advocates, climate scientists and others, which attempted to mimic strategies from the 1960s campaign against smoking tobacco.

More details of several studies and of the history can be found in the report itself.

Next: The Evidence Shows We Are Nowhere Near a Climate Tipping Point, As Alarmists Claim

Proxy Evidence Shows Early Holocene Was Warmer than Today

A persistent claim in the climate science literature, one that is used to bolster the narrative of catastrophic anthropogenic climate change, is that current temperatures are the highest the world has seen in the 125,000 years since the interglacial period between the last two ice ages. But a close look at the evidence reveals it was warmer than today as recently as the early Holocene – the geological epoch since the last ice age ended.

Underlying the preposterous claim is an erroneous temperature graph featured in the 2021 Sixth Assessment Report of the IPCC (Intergovernmental Panel on Climate Change). As shown in the figure below, the report displays the IPCC’s latest version of the so-called “hockey stick,” which exhibits no change or a slight decline in temperature for the past 2020 years and a sudden, rapid upturn since 1900.

The solid grey line from 1 to 2000 is a reconstruction of global surface temperature from paleoclimate proxies, while the solid black line from 1850 to 2020 represents direct observations. Both are relative to the 1850–1900 mean and averaged by decade.

Among other features missing from the spurious hockey stick are two previously well-documented aspects of our past climate: the MWP (Medieval Warm Period) around the year 1000, a time when warmer than normal conditions were reported in many parts of the world, and the cool period centered around 1650 known as the LIA (Little Ice Age).

But the IPCC report also excludes early Holocene warming by its statement “Warmest multi-century period in more than 100,000 years” in the figure above. That such warming took place is evidenced by numerous paleoclimate proxies such as tree rings, marine sediments, ice cores, boreholes and leaf fossils.

A 2009 research paper provides proxy evidence from Greenland ice cores of a period known as the Holocene Thermal Maximum that occurred from approximately 10,000 to 6,000 years ago. The researchers used the isotopic ratio of ¹⁸O to ¹⁶O, or δ¹⁸O, in ice cores from six different locations as a proxy for past surface temperatures in Greenland; the locations are indicated in the image on the left below.

The lower part of the image on the right shows the proxy temperature at two of the locations, Agassiz and Renland, over the period from the present back to 11,700 years ago. (Note that the time scale is reversed relative to the IPCC figure.) Of the six Greenland sites, only these two were suitable for analysis, because the ice cores were retrieved from icecap domes and were not influenced by ice flow that occurred at the other four sites. The existence of elevated temperatures during the Holocene Thermal Maximum is abundantly clear.

On the other side of the globe, further proxy evidence for the Holocene Thermal Maximum comes from marine sediment cores in Indonesia. A 2013 paper deduced that temperatures at both the sea surface and at intermediate depths in passages between the Pacific and Indian Oceans were higher during the early Holocene than in the past century.

The proxy in this case was the ratio of magnesium to calcium in the sediment cores, which is a measure of the seawater temperature at the time the sediment was deposited; a timeline can be established by radiocarbon dating. Temperatures dating back 16,000 years derived from well-dated sediment cores in several locations are depicted in the next figure. Part A denotes sea surface temperatures, while part B denotes sub-surface temperatures at the thermocline that divides warmer surface water from cooler water below.

Again, it can be seen that temperatures were higher during the Holocene Thermal Maximum than at present, more so at depth than at the surface. The magnitude of the Maximum relative to the 1850-80 mean was estimated to be 2.2 degrees Celsius (4.0 degrees Fahrenheit) and 1.5 degrees Celsius (2.7 degrees Fahrenheit) at depth and the surface, respectively.

Both the Greenland and Indonesian (Makassar Strait at 500 meters depth) proxy temperature data during the Holocene are displayed together in the figure below, compiled by petrophysicist Andy May. You can see that both datasets are closely matched and that the Holocene Thermal Maximum (Climatic Optimum) was more than 1 degree Celsius (1.8 degrees Fahrenheit) warmer than today.

Likewise, sea surface temperatures near the southern Australian coast are estimated to have been as much as 4.0 degrees Celsius (7.2 degrees Fahrenheit) higher during the mid-Holocene than today. This was deduced from δ¹⁸O and radiocarbon measurements in mollusc fossils, which were reported in a recent paper by Australian scientists.

It could be argued that all of the assertions I’ve made here rely on proxy, not actual data. But so does the shaft of the hockey stick. Reliable global instrumental measurements of temperature and other climate variables date back only about 150 years.

Next: Abuse of Science: Extreme Event Attribution Studies

The Atlantic “Cold Blob” – Cause for Alarm or Just a Curiosity?

In contrast to global warming, a little-known cooling trend has existed in the subpolar North Atlantic Ocean for the past century. Designated the “cold blob” or occasionally the “warming hole” (although this moniker actually refers to a different phenomenon), the trend appears on maps as a cooling blue dot surrounded by a sea of red heat, as shown in the figures below.

Even as sea surface temperatures in the Atlantic as a whole have risen considerably in recent years, the blob’s average temperature has steadily fallen by as much as 0.3 degrees Celsius (0.5 degrees Fahrenheit). Why?

The popular explanation among climate scientists is a weakening of the AMOC (Atlantic Meridional Overturning Circulation). The AMOC forms part of the ocean conveyor belt that redistributes seawater and heat around the globe. Exactly how global warming is changing the AMOC, if at all, is currently unknown. But alarmist proclamations in both the scientific literature and the mainstream media have suggested the AMOC may be slowing or even approaching a tipping point when it would shut down altogether.

However, all claims of impending doom rely on computer climate models, which have a generally poor history of making predictions. Apart from correctly predicting a 20-year pause in loss of Arctic sea ice, the models greatly exaggerate future warming, overestimate low cloud feedback, and are unable to reproduce observed sea surface temperatures and sea-level rise.

Two recent papers, published almost simultaneously in 2025, attempt to link the cold blob to a weakened AMOC using model simulations. In the first paper, two scientists from the University of California, Riverside compared long-term records of the Atlantic Ocean to various climate models. The second paper, by a team of researchers from Pennsylvania State University, focused on both atmospheric and oceanic contributions to model behavior.

Yet what’s striking about both papers is that climate models do not universally support either the existence of a cold blob in the North Atlantic or a weakened AMOC. The Pennsylvania State paper finds that of 32 CMIP6 models, only 11 exhibit long-term cooling in the subpolar North Atlantic, while 9 models actually “simulate greater warming in the subpolar basin compared to elsewhere in the North Atlantic”; the authors have no comment on the other 12 models.

The Riverside researchers observe that a majority of older CMIP5 models simulate a weakened AMOC historically, but a majority of newer CMIP6 models simulate a strengthened AMOC during the 20th century. Of 94 CMIP5/6 models that they utilized, 51 hindcasted a weakened AMOC from 1900 to 2005, while the other 43 models did just the opposite by hindcasting a strengthened AMOC.

Both papers ignore the models that don’t simulate the cold blob or a weakened AMOC in drawing their conclusions – cherry picking already dubious models in order to bolster their erroneous assertions of an AMOC slowdown.

That the cold blob actually exists is not in doubt, given the empirical evidence. The figure at the top of this post shows the changes in observed sea surface temperature from 1901 to 2022; at the blob’s center, the temperature can be seen to have dropped by more than 0.3 degrees Celsius (0.5 degrees Fahrenheit) over that time.

The figure immediately above shows the temperature trend per century over the area of the blob (blue dots) for three different temperature datasets. The trends for the HadISST, ERSSTv5 and Kaplan datasets are -0.04 degrees Celsius/century, -0.14 degrees Celsius /century, and -0.26 degrees Celsius /century, respectively.

Attempts in both recent papers to correlate the century-long trend of the mean observed sea surface temperature in the cold blob with the corresponding modeled trend in the strength of the AMOC are unimpressive. The Pennsylvania State researchers find an R² correlation of only 0.50, while the Riverside team estimates a correlation from 0.42 to 0.57.

To explain the low correlation, the Pennsylvania State authors point to atmospheric influences on the AMOC. They say that heat losses from the ocean in the subpolar North Atlantic induce cooling and drying in the lower troposphere, both of which decrease downward longwave radiation and further intensify sea surface cooling.

The figure above depicts the modeled effect of seven different physical processes, both radiative and oceanic, on the long-term temperature trend in the cold blob. The processes are, from left to right: surface albedo feedback; longwave cloud radiative forcing; shortwave cloud radiative forcing; shortwave clear-sky radiation, mostly from aerosols; longwave clear-sky radiation, which includes the effect of water vapor and other greenhouse gases; ocean heat transport; and surface latent and sensible heat fluxes.

Partial cancellation of both radiative and oceanic effects is evident, but overall the authors propose that radiative processes from the atmosphere contribute about two thirds of cold blob cooling, while oceanic processes contribute the other third.

Nevertheless, neither study should set the alarm bells ringing, given the selective choice of climate models discussed above.

Next: Proxy Evidence Shows Early Holocene Was Warmer than Today

AI Proves Its Mettle in Reconstruction of Antarctic Temperatures

In a 2025 post, I described the largely unsuccessful attempt of an AI to spearhead research in climate science. Now, however, another AI appears to have succeeded in the more technical task of accurately reconstructing surface air temperatures across Antarctica – something that standard temperature datasets have been unable to achieve. The work is reported in a recent paper by a team of Chinese researchers.

The figure below illustrates the geographical distribution of available observational data in Antarctica from 1979 to 2023. The data comes from a number of manned and automatic weather stations, together with meteorological observations over the ocean collected from ships and buoys. As can be seen, the majority of observations are in coastal or near-coastal regions, precluding full spatial coverage of the continent.

To overcome this shortfall, the limited station observations have traditionally been interpolated using various reanalyses. But it’s difficult for reanalysis datasets to capture complex spatial patterns, say the researchers, and such datasets often contain significant uncertainties. Moreover, deriving surface air temperatures from reanalysis datasets depends in part on model simulations rather than actual instrumental measurements.

In the light of these limitations to an accurate reconstruction of Antarctic temperatures, the Chinese research team has applied deep learning methods. This approach has already been utilized successfully to reconstruct Arctic temperatures.

Antarctic temperatures were reconstructed using daily surface air temperature data from the various sources depicted in the figure above. Daily average temperatures were calculated from observations made at 3-hour intervals for some sources, 1-hour intervals for others. Training data for the deep learning model was provided by surface air temperatures from the three reanalysis datasets that showed the best agreement with observed temperatures.

The training data, which covered the period from 1979 to 2005, totaled 29,211 daily temperature samples. Using reanalysis data from different time periods, such as 1995 to 2021, as the training set had little impact on the temperature reconstruction. Validation of the training data and testing of the reconstructed temperature set employed reanalysis data from 2006 to 2012 and 2013 to 2018, respectively.

Testing of the reconstructed Antarctic temperatures was conducted for three specific days in 2015: January 1, July 1 and November 1. For these days, the reconstructed temperatures were found to be highly correlated with their reanalysis counterparts, with spatial correlation coefficients >0.99. The researchers say this correlation shows that the trained deep learning model is capable of accurately reproducing Antarctic surface air temperatures, even with the limited observational data available.

Just how different the reconstructed surface temperatures are from global observational temperature datasets for Antarctica is depicted in the next figure. The figure shows linear trends in annual Antarctic surface air temperatures from 1979 to 2023, measured in degrees Celsius per decade. The datasets are: (a) this reconstruction; (b) Berkeley Earth; (c) ERA reanalysis; (d) NOAAGlobalTemp5.1; (e) GISTEMPv4; and (f) HadCRUT5.

You can see that none of the standard datasets exhibit the pronounced cooling trend in East Antarctica in (a), something that was inferred earlier from the ERA reanalysis dataset by a different group of Chinese researchers. Nevertheless, all datasets show warming in the Antarctic Peninsula (on the left of the continent in the maps above).

Differing from the annual trends is the pattern for the summer months (November to April) only, presented in the figure below for the period from 1989 to 2022. Although the cooling trend still dominates in East Antarctica, warming is no longer prominent in the Peninsula but is found in West Antarctica and the southern portion of East Antarctica.

East Antarctica actually experienced a summer heat wave in 2022, when the temperature soared to -10.1 degrees Celsius (13.8 degrees Fahrenheit) at the Concordia weather station, located at the 4 o’clock position from the South Pole, on March 18. This balmy reading was the highest recorded hourly temperature at that station since its establishment in 1996, and 20 degrees Celsius (36 degrees Fahrenheit) above the previous March record high there. Remarkably, the temperature remained above that record for three consecutive days, including nighttime.

But Antarctica is nothing if not unpredictable. Despite the 2022 heat wave, the mercury dropped to -51.2 degrees Celsius (-60.2 degrees Fahrenheit) on January 31, 2023. This marked the lowest January temperature recorded anywhere in Antarctica since the first meteorological observations there in 1956. Two days earlier on January 29, the nearby Vostok station, about 400 km (250) miles closer to the South Pole, registered a low temperature of -48.7 degrees Celsius (-55.7 degrees Fahrenheit), that location’s lowest January temperature since 1957.

Such swings from record highs to record lows remain a puzzle, but the present reconstruction at least helps to characterize long-term trends.

Next: The Atlantic “Cold Blob” – Cause for Alarm or Just a Curiosity?

Challenges to the CO2 Global Warming Hypothesis: (13) Global Warming Entirely from Declining Planetary Albedo

One of my early posts in this series on challenges to the CO₂ global warming hypothesis featured a paper claiming that the greenhouse effect doesn’t exist. Now the same authors appear to have sidestepped that claim in proposing instead that current global warming can be explained entirely by the observed decrease in planetary albedo over the last few decades.

In a new paper, U.S. research scientists Ned Nikolov and Karl Zeller compare empirical observations of albedo made by CERES (Clouds and the Earth’s Radiant Energy System) satellites to the output of a semiempirical mathematical model used in their earlier work. In their model, the radiative effects integral to the greenhouse effect are replaced by a thermodynamic relationship between air temperature, solar heating and atmospheric pressure, analogous to compression heating of the atmosphere.

Nikolov and Zeller conclude that the observed decrease of planetary albedo, together with variations of solar output or TSI (total solar irradiance), account for 100% of the global warming trend as well as 83% of the interannual variability in global surface air temperature. They find that temperature changes are driven primarily by albedo changes, with only a marginal contribution from TSI.

Albedo is a measure of the earth’s ability to reflect incoming solar radiation. Melting of light-colored snow and sea ice due to warming exposes darker surfaces such as soil, rock and seawater, which have lower albedo. The less reflective surfaces absorb more of the sun’s radiation and thus push temperatures higher.

The same effect occurs with low-level clouds, which are the majority of the planet’s cloud cover. Low-level clouds such as cumulus and stratus clouds are thick enough to reflect 30-60% of the sun’s radiation that strikes them back into space, so they act like a parasol and normally cool the earth’s surface. But less cloud cover lowers albedo and therefore results in warming.

The figure below shows CERES measurements of global albedo from 2000 to 2024, expressed as a percentage anomaly of the 2001 to 2022 mean. The albedo decrease since 2000 is approximately 0.79%, which implies an increase in absorbed shortwave solar radiation of 2.7 watts per square meter over that period. The two researchers point out that this absorption is very close to the total anthropogenic forcing of 2.72 watts per square meter from 1750 to 2019 estimated by the IPCC (Intergovernmental Panel on Climate Change) in its AR6 (Sixth Assessment Report). 

The decline in albedo corresponds to a similar reduction in low cloud cover studied by a trio of German environmental scientists, which I discussed in a 2025 post. Their data for total (red curve) and low cloud (lower black curve) cover, calculated by the study authors from two separate sets of satellite data, is presented in the next figure. The lowered cloud cover is most prominent in northern mid-latitudes and the tropics.

The next figure shows CERES measurements of absorbed shortwave radiation from 2000 to 2024 along with global surface air temperature, measured as the average of six temperature datasets (HadCRUT5, GISTEMP4, NOAA Global, BEST, RSS and NOAA STAR). The temperature anomaly tracks changes in the absorbed solar flux with an average lag of approximately 4 months. Nikolov and Zeller say this close empirical relationship suggests that temperature is directly controlled by the absorbed solar flux.

The researchers quantify the individual effects of albedo and TSI on surface temperatures by using their semiempirical mathematical model. The following figure compares modeled temperatures based on each of these two factors with observations. It’s clear that variations in TSI play only a minimal role while variations in albedo dominate the temperature trend.

This conclusion is also supported by the next figure, which depicts the modeled contribution to albedo and TSI separately going back to 1981. According to Nikolov and Zeller’s model, the low contribution from TSI variation indicates that the earth’s climate is 5.6 times more sensitive to changes in solar absorption than to TSI variations.

The estimate is in good agreement with a conclusion reached by Israeli physicist Nir Shaviv, who has investigated the effect of TSI cycles on several climatic variables. Shaviv found that total solar forcing of the earth’s climate, which includes indirect effects, is 5 to 7 times larger than that associated with direct solar warming.  Such a large amplification factor would imply that the climate is much more sensitive to the sun than to CO₂. Of the various possible indirect amplification mechanisms, Shaviv favors the influence of cosmic rays on low cloud cover.

Nonetheless, the observation of declining albedo or low cloud cover begs the chicken-and-egg question: is decreased albedo the cause or effect of current warming? While Nikolov and Zeller argue for the former, they also call for large-scale interdisciplinary research into the physical mechanisms controlling the earth’s albedo and cloud physics, in order to resolve the question.

Next: AI Proves Its Mettle in Reconstruction of Antarctic Temperatures

Southern Ocean Cooling: Climate Scientists Unable to Agree on Explanation

Contrary to the predictions of climate models, surface sea temperatures in the Southern Ocean around Antarctica have cooled for several decades. Over the last 15 months, three completely different explanations have been proposed for this global warming anomaly.

The first paper, published in November 2024 by a team of mostly Spanish researchers, postulated that the cooling comes from previously unstudied marine sulfur emissions. It’s been known for some time that sulfate aerosol particles linger in the atmosphere, reflecting incoming sunlight and also acting as condensation nuclei for the formation of reflective clouds. Both effects cause global cooling.

But what wasn’t known before is that there are two sources of marine sulfur emissions, both of which emanate from microscopic plankton that live on the ocean surface and emit aerosol-forming gaseous sulfur. The previously known sulfur source is dimethyl sulfide ((CH₃)₂S), mainly responsible for the distinctively pungent smell of seafood. Emission of the more reactive methyl sulfur hydride (CH₃SH), hitherto neglected, has been quantified for the first time by the Spanish research team.

The researchers found that emissions of CH₃SH increase the formation of sulfate aerosols in the atmosphere by 30% to 70% over the Southern Ocean; this decreases incident solar radiation in summer by between 0.3 and 1.5 watts per square meter, enhancing the expected aerosol cooling effect. The maximum effect, which occurs at 65^oS, is illustrated in the figure below, where the red line denotes the increase in total sulfate aerosol emission as a function of latitude.

The second paper, published in March 2025, takes a rather different tack in proposing that the unexpected Southern Ocean cooling results from an influx of freshwater that’s not incorporated in state-of-the-art climate models, and restricts the exchange of surface waters with deeper warmer waters.

The authors, an international team of earth scientists, found that over the period from 1990 to 2021, underestimated freshwater fluxes can explain up to 60% of the difference between observed and modeled sea surface temperatures in the Southern Ocean. The freshwater consists of both Antarctic meltwater, which is completely missing from most climate models, and underestimated rainfall over the ocean. 

To quantify the effect of freshwater on Southern Ocean sea surface temperatures, the researchers used an ensemble of 17 coupled climate and ocean models that simulate ocean density and circulation changes. Separate simulations investigated step changes in forcing caused by surface freshwater fluxes from Antarctic ice sheet melting, and from atmospheric rain combined with sea ice melting, respectively.

Some of their results are displayed in the next figure which shows estimates of the freshwater flux, measured in gigatonnes (Gt, where 1 gigatonne = 1.102 U.S. gigatons) per year, from 1990 to 2021. The steadily increasing rainfall (plus sea ice) contribution is represented by the blue line and shading; the green line represents the Antarctic meltwater contribution – seen to be diminishing with time.  

The figure to the left depicts the influence of these “missing” contributions to the rate of warming or cooling of Southern Ocean sea surface temperatures, measured in degrees Celsius per decade. The overestimated warming predicted by climate models is indicated by the gray box on the left; the calculated contributions from rainfall and meltwater by the blue and green boxes, respectively; and the combined contribution by the black box on the right. 

You can see that the combined contribution brings the climate model warming rate down to almost zero. So this research provides a much better representation of the actual cooling rate than before and helps to resolve the decades-long mismatch between predicted and observed Southern Ocean temperatures.

The third paper, published just two months ago in December 2025, attributes the inability of climate models to correctly predict Southern Ocean cooling on the models’ underestimation of Southern Ocean storm strength and thus the heat transfer from atmosphere to ocean. Storminess draws colder deepwater upward, keeping the surface cooler which enables the surface to take up more atmospheric heat.

The Swedish, South African and UK researchers employed a robotic “glider” to measure ocean temperature and salinity, together with atmospheric properties above the waves. The robotic observations were then combined with satellite and multi-year climate model data.

Their results are summarized in the figure below, showing the difference in atmosphere-ocean heat flux between the interior of summer storms and the whole ice-free Southern Ocean. LHF (latent heat flux), SHF (sensible heat flux) and LWR (longwave radiation) all contribute to ocean heat loss; SWR (shortwave radiation) results in ocean heat gain. The black line with dots indicates the net heat flux, which is seen to produce slight cooling overall – though less cooling than from weaker storms.

Each of these different explanations accounts partially for underestimated Southern Ocean cooling in climate models, so perhaps a combination of all three will resolve the discrepancy.

Next: Challenges to the CO2 Global Warming Hypothesis: (13) Global Warming Entirely from Declining Planetary Albedo

Ongoing Attacks on Livestock Methane Emissions Based on Faulty Science

Farmers around the world have become a scapegoat for global warming, based on the assumption that emissions of methane (CH₄) from ruminant animals trap far more heat than carbon dioxide (CO₂) over shorter timeframes.

However, despite the ongoing attacks on agriculture, this assumption is wrong and stems from a fundamental misunderstanding of the underlying science. Methane is indeed a potent greenhouse gas but, because its atmospheric concentration is increasing at a negligible rate compared with that of CO₂, its contribution to global warming is small in comparison.

Let me explain. As I discussed in a 2023 post, the actual warming produced by a greenhouse gas depends on its so-called “global warming potential” – a quantity determined by how efficiently the gas absorbs heat, its lifetime in the atmosphere, and its atmospheric concentration.

The conventional global warming potential (GWP) is a dimensionless metric, created by the UN’s IPCC (Intergovernmental Panel on Climate Change), in which the GWP per molecule of a particular greenhouse gas is normalized to that of CO₂; the GWP takes into account the atmospheric lifetime of the gas. The following table shows both GWP-20 and GWP-100, the warming potentials calculated over a 20-year and 100-year time horizon, respectively, for both CO₂ and CH₄.

The GWP value for CH₄ over 20 years suggests, erroneously, that CH₄is a whopping 83 times more potent than CO₂ as a greenhouse gas. It’s this number that has been used by climate alarmists to demonize farmers and their livestock.

Farmers caught something of a break when a group of physicists at the University of Oxford realized that the IPCC’s GWP can overestimate the warming effect of short-lived greenhouse gases such as CH₄, compared to longer-lived gases like CO₂. The Oxford researchers proposed replacing the GWP with a metric called GWP*, in which the CO₂-equivalence of short-lived greenhouse gas emissions is determined predominantly by changes in emission rate.

Nevertheless, even though using GWP* leads to smaller estimates of CH₄’s contribution to warming, the estimates are still too high because both the GWP and GWP* fail to account for the relative rate of concentration increase for CH₄ compared with CO₂.

The yearly abundance of CH₄ in the atmosphere since 1980, as measured by NOAA (the U.S. National Oceanic and Atmospheric Administration), is depicted in the next figure. Currently, the global average CH₄ concentration is approaching 1.95 ppm (1950 ppb), more than two orders of magnitude lower than the CO₂ level of approximately 420 ppm. The rate of increase in the CH₄ level over the last 10 years averages about 0.011 ppm (11 ppb) per year, which is approximately 225 times smaller than the average rate of increase in the CO₂ level of around 2.5 ppm per year.

Including this data in the GWP calculation means that the contribution of CH₄ to global warming is only 83/225 that of CO₂ over 20 years or 30/225 over 100 years. These values of what I’ve designated “True GWP” are shown as percentages in the table below, which is an extension of the previous table above.

So CH₄ is only 37% (0.37) as potent a greenhouse gas as CO₂ over 20 years – a far cry from the 83 times as potent number promoted by climate activists and the mainstream media.

Farmers, sensing that official pronouncements on the warming effect of CH₄ are exaggerated, even without this revelation about True GWP, have begun to push back. At the II World Congress on Sustainable Livestock in Extremadura, Spain in November 2025, an international group of livestock farmers and producers came together to highlight “the true environmental sustainability of livestock farming based on the latest climate science,” emphasizing that it has supported human civilization for millennia.

At the Congress, New Zealand farmer and former parliamentarian Owen Jennings briefly discussed the misuse of GWP and GWP*, adding that: Much of the science relating to ruminant methane emissions is plain wrong. IPCC claims have been found to be outdated and erroneous. Curtailing methane is distracting, expensive and unnecessary.

Another speaker pointed out that small farms of less than 20 hectares (50 acres) provide more than 50 % of the world’s livestock, with more than 70% in emerging and developing economies, as illustrated in the figure below. Anti-livestock journalism, based in part on a misunderstanding of ruminant CH₄’s minimal contribution to current warming, is far more of a threat to these farms than climate change itself.

Next: Southern Ocean Cooling: Climate Scientists Unable to Agree on Explanation

No U.S. Landfalling Hurricanes in 2025 Refutes Alarmist Rhetoric on Weather Extremes

It’s like a football game where one team didn’t show up.

Or champagne without the fizz.

Or Christmas without the tree.

That was the U.S. 2025 hurricane season, in which not a single Atlantic hurricane made landfall in the U.S. And this despite the steady drumbeat of articles in the mainstream media and pronouncements by climate alarmists, proclaiming that weather extremes such as hurricanes are on the rise.

The 2025 no-show is illustrated in the figure immediately below; the second figure shows the much more active 2024 season.  

The closest to landfall of the 2025 hurricanes were tropical storms Barry (2) and Chantal (3), neither of which actually qualifies as a fully fledged hurricane. Tropical storms have sustained wind speeds up to 117 km per hour (73 mph), while the weakest Category 1 hurricanes have top wind speeds from 119 to 153 km per hour (74 to 95 mph).

Although the last time no hurricanes made landfall in the continental U.S. was in 2015, the preceding 15 years from 2000 to 2014 saw the same phenomenon no less than 6 times. Before that, the decades of the 1960s, 1970s, 1980s and 1990s each saw just 2 landfalling hurricanes. Clearly there is no pattern or connection to climate change, as the globe was cooling in the 1960s and early 1970s, but has warmed since then.

The total number of all North Atlantic hurricanes or major hurricanes in 2025 and 2024 was 9 and 16, respectively. The lower number in 2025 is reflected in what is known as the Accumulated Cy­clone Energy (ACE) index for the North Atlantic Basin. The ACE index is an integrated metric combining the number of storms each year, how long they survive and how intense they be­come.

The next figure shows the ACE North Atlantic index since 1851. The highest index in the record was 259 in 1933. The 2025 no-landfall season had an ACE index of 133 (measured to December 4), which is just slightly higher than the long-term average; the index for 2024 was 162.

A comprehensive report on 2024 hurricanes by UK climate writer Paul Homewood, discussing long-term trends in North Atlantic hurricanes, found at that time no evidence for any increase in hurricane frequency, intensity or both associated with global warming. Homewood’s compilation of frequency data for North Atlantic hurricanes and major hurricanes from 1851 to 2024 is presented in the figure below.

While it may appear from the figure that hurricanes have indeed become more common since the 19th century, Homewood points out that the apparent increase “has been due to changes in observation practices over the years, rather than an actual increase” – as concluded in a 2021 study by a team of hurricane experts.  Prior to the satellite era, which dates only from the 1960s, many storms were not spotted at all.

Back then, most data on hurricane frequency in the U.S. was based on eyewitness accounts, thus excluding most hurricanes that never made landfall – as well as many landfalling ones in sparsely populated areas. And even the recording of non-landfall­ing hurricanes relied on observations made by ships at sea, which almost certainly resulted in an undercount. So it is hardly surprising that the public falsely sees today’s more complete coverage enabled by satellite technology as an uptick in hurricane occurrence.

The perception that extreme weather events are increasing in frequency and severity is primar­ily a consequence of modern technology – the Internet and smart phones – which have revo­lutionized communication and made us much more aware of such disasters than we were 50 or 100 years ago. Before 21st-century electron­ics arrived, many hurricanes and other weather extremes went unre­corded. The misperception has only been amplified by the mainstream media, eager to promote the latest climate scare.

Another aspect of hurricane measurement is maximum wind speeds. There is growing evidence, says Homewood, that wind speeds of the most powerful current hurricanes may be overestimated compared to those in the pre-satellite era, because of changing methods of measurement.

In the past, hurricane wind speeds were estimated from the central pressure of the system, which could be more readily measured. But more recently, wind speeds have been calculated from satellite and aircraft data. This has created an anomaly, because estimates of wind speeds for hurricanes now tend to be higher than past ones with similar central pressure. What this means is that wind speeds before the advent of satellite technology were underestimated in comparison with hurricanes today.

As with frequency, the data clearly reveals no evidence that hurricanes are becoming more intense, or that extremely intense ones are becoming more common, as global warming continues.

Climate Alarmism and Net Zero Strategy on the Wane

While it has been clear to rational thinkers for some time that widespread climate alarmism is losing its impact, it took a recent pronouncement by Microsoft co-founder and philanthropist Bill Gates to inject a dose of much-needed reality into the climate debate. In a memo titled “Three tough truths about climate,” Gates declared that:

Climate change is a serious problem, but it will not be the end of civilization.

and,    

Health and prosperity are the best defense against climate change.

Although as a skeptic, I disagree with Gates that global warming is largely the result of human activity, his memo is symbolic of the current move away from the highly exaggerated notion of a “climate crisis,” espoused by our leaders and the mainstream media. At the same time, the political drive toward the adoption of Net Zero policies is faltering in many countries.

Climate activists are being reined in too, at least Just Stop Oil protesters who have been jailed for disrupting UK motorways and airports, and defacing priceless pieces of art all over Europe. Their most recent efforts seem tame by comparison, such as the spraying of Stonehenge with an environmentally harmless orange powder that washes off.   

The pied-piper-like campaign sparked by former Swedish schoolgirl Greta Thunberg has all but died, as Thunberg has diverted her activism to other issues like the war in the Gaza Strip. Her 2019 speech to the UN Climate Action Summit, in which she admonished the world for having “stolen my dreams and my childhood,” and claimed we are on the verge of a mass extinction with her accusatory “How dare you!”, is but a distant memory.

Even the UN Secretary-General is toning down his previously incendiary rhetoric on climate change. Just a few years after hysterically describing the IPCC (Intergovernmental Panel on Climate Change)’s Sixth Assessment Report as “code red for humanity” and proclaiming that “the era of global boiling has arrived,” all he could muster in his speech to the latest UN climate conference was a call for the gathering to “ignite a decade of acceleration and delivery.”

Along with the falloff in climate activism, the lemming-like drive by many governments toward Net Zero – the achievement of zero net CO₂ emissions by 2050 – is losing steam. One of the reasons is the realization that surprisingly little global warming would actually be averted by adoption of Net-Zero policies. But nonscientific objections, especially the costs of implementing Net Zero, are gaining increasing attention as well.

Discussion of likely costs is most advanced in the UK, which was the first major economy to establish a legally binding Net-Zero target in 2019. Estimates of total cost vary wildly, but most are in the range of £1-10 trillion ($1.3-13 trillion), as shown in the figure below based on various scenarios. A total of £3 trillion ($3.9 trillion) would be equivalent to an unacceptable £100,000 ($130,000) per household, according to a recent report.

The enormous cost of Net Zero is reflected in the cost of electricity – a driving force in the economy and of particular concern to electricity users, both industrial and domestic. The next figure illustrates the average cost of electricity over the last 30 years in both the UK and U.S. While the U.S. cost has remained level during that period, the UK cost has soared, prompting fears of the nation committing economic suicide by bankrupting industrial users.

The marked difference can be attributed entirely to the UK’s quest for Net Zero, founded on intermittent and unreliable renewable energy which provided 51% of the country’s electricity in 2024. In the U.S., cooler heads have prevailed and only 21% of electricity generation was from renewable sources in 2023. However, the wheel may be turning as the UK and other European countries previously dedicated to Net Zero are having second thoughts.

A major concern all over the UK and EU is potential deindustrialization, the viability of industry being heavily dependent on electricity costs. The UK currently has the highest industrial electricity prices in the developed world. Numerous manufacturers of automobiles, steel and other products have already pulled up their British roots and moved to countries where electricity (and labor) is cheaper or simply gone out of business altogether. Germany, where the cost of electricity has also risen steeply, is also struggling to keep its economy afloat.   

Meanwhile, China and India – the largest and 3rd largest emitters of CO₂, respectively – are all but ignoring Net Zero. India has a Net-Zero goal of 2070, while China has not set any goal at all.

China currently leads the world in building new coal-fired power plants, construction of which reached a 10-year high in 2024; at the same time, renewables contributed 32% of the country’s electricity that year. India burns less coal than China but still relies heavily on coal for electricity generation.

Next: No U.S. Landfalling Hurricanes in 2025 Refutes Alarmist Rhetoric on Weather Extremes

Past Global Warming More Rapid than Today’s: The Younger Dryas

Skeptics of the climate change narrative often point to periods of warming in the distant past when global temperatures were far above today’s, but CO₂ levels were lower, as ruling out human emissions of CO₂ as the cause of modern global warming. But this assertion is rejected by advocates of the CO₂ narrative, who argue that current warming is happening far more rapidly than in any past episodes.

However, there are numerous examples of rapid climate change in the historical record, some as recently as the last ice age. One of the best documented is a period of climate upheaval known as the Younger Dryas, which occurred approximately 12,900 to 11,700 years ago and temporarily reversed the earth’s recovery from frigid glacial conditions.

The effect on temperature and ice accumulation in Greenland is illustrated in the figure below, but a similar phenomenon took place all over the Northern Hemisphere. The Younger Dryas is named after a wildflower, Dryas Octopetala, that thrives in very cold European climates.

As the earth slowly warmed from the ice age, the temperature (red line) suddenly took a steep upward turn – to almost present-day levels – around 15,000 years ago. This event is known as the Oldest Dryas and is clearly visible on the left of the figure. This was soon followed by the Younger Dryas, when the temperature plunged back to near-glacial conditions and which must have been devastating for early humans.

But then the Younger Dryas ended abruptly, with temperatures soaring upward again to where they would have been had the Dryas events not happened. By many accounts (see, for example, here and here), the mean annual global temperature rose by as much as 10 degrees Celsius (18 degrees Fahrenheit) in only 10 years.

That’s an increase of 1 degree Celsius (1.8 degrees Fahrenheit) in just one year – far in excess of modern global warming, in which the same 1-degree Celsius increase has taken more than 50 years.

However, the Younger Dryas is not an isolated instance of abrupt climate change in our planet’s past. As I discussed in a 2024 blog post, temperatures in Greenland rose suddenly and fell again at least 25 times during the last ice age, which spanned the period from about 115,000 to 10,000 years ago. Corresponding temperature swings occurred in Antarctica too, although they were less pronounced than those in Greenland.

The striking but fleeting bursts of heat are known as Dansgaard–Oeschger (D-O) events, named after palaeoclimatologists Willi Dansgaard and Hans Oeschger who examined ice cores obtained by deep drilling the Greenland ice sheet. They found a series of rapid climate fluctuations, when the earth warmed to near-interglacial conditions over just a few decades, and then gradually cooled back down to frigid ice-age temperatures.

The phenomenon can be seen in the next figure, depicting ice-core data from both Greenland and Antarctica; two sets of measurements, recorded at different locations, are shown for each. The isotopic ratios of ¹⁸O to ¹⁶O, or δ¹⁸O, and ²H to ¹H, or δ²H, in the cores are used as proxies for the past surface temperature in Greenland and Antarctica, respectively. The Younger Dryas is merely the last of 25 or 26 D–O events over the past 120,000 years, albeit an extra strong one.

Several hypotheses have been put forward to explain the Younger Dryas. The leading hypothesis postulates that enormous amounts of freshwater were discharged into the North Atlantic Ocean about 12,900 years ago, in the form of rapidly melting icebergs disgorged from the massive Laurentide ice sheet which covered most of Canada and the northern U.S.

This vast influx of freshwater would have disrupted the deep-ocean thermohaline circulation (shown in the figure below) by lowering ocean salinity, which in turn suppressed deepwater formation and weakened the AMOC (Atlantic Meridional Overturning Circulation). Eventually, as the meltwater flux abated, the AMOC would have strengthened again, enabling the climate to recover.

A problem with this hypothesis is the timing: a second meltwater pulse, while slightly smaller than the first one 1,200 years earlier, occurred at the end of the Younger Dryas. Yet the second pulse didn't result in a similar weakening of the AMOC.

An alternative explanation is the impact hypothesis. This involves the impact of a large extraterrestrial object that burst in the atmosphere, creating fragments which struck various areas around the world 12,900 years ago. The fragments are thought to have sparked widespread wildfires and even caused a number of extinctions.

Proponents of the hypothesis point to geological layers known as “black mats,” as well as the formation of nanodiamonds, as evidence of past fiery events. But others dismiss such claims, saying that it’s equally likely that volcanic eruptions were the cause.

Next: Climate Alarmism and Net Zero Strategy on the Wane

Vaccine Hesitancy on the Rise

Further evidence of the current attack on science is the opposition to vaccination against infectious diseases such as measles, hepatitis and polio. More and more parents are ignoring science by choosing not to vaccinate their children, even with vaccines that have a long history of extensive testing for adverse health effects. The WHO (World Health Organization), for the first time, listed so-called vaccine hesitancy as one of the top 10 global threats in 2019.

According to a new poll from health policy information nonprofit KFF, 16% of U.S. parents have skipped or delayed vaccinating their children against diseases other than COVID-19 or the flu during the 2024-25 school year. The same poll reveals that white parents, Republicans, the religious and those who homeschool their kids are more likely to avoid the shots.

Data for the MMR (measles-mumps-rubella) vaccine exemplifies vaccine hesitancy. The KFF poll found that only 92.5% of U.S. kindergarteners received the MMR vaccine in 2024-25, a significant drop from 2019-20 when the percentage was 95%.

The reason this drop is significant involves herd immunity. Herd immunity is the mass protection from an infectious disease that results when enough members of the community become immune to the disease through vaccination, just as sheer numbers protect a herd of animals from predators. Once a sufficiently large number of people have been vaccinated, viruses and bacteria can no longer spread in that community.

The threshold for herd immunity, which is the minimum percentage of the population that needs to be vaccinated for the herd effect to take hold, depends on the contagiousness of the disease, the effectiveness of the vaccine and other factors.  For highly contagious measles, herd immunity requires up to 95% of the populace to be immunized, while for polio the percentage ranges up to a slightly lower 86%.

KFF reports that 39 U.S. states had MMR vaccination rates for kindergarteners below the target rate of 95% for the 2024-25 school year, an increase from just 28 states during the 2019-20 (pre-pandemic) school year. And of the 39 states, 16 reported even lower rates of below 90% for 2024-25, compared to only 3 states in 2019-20; the particular states are shown in the figure below. (Montana and West Virginia didn’t report data for the 2024-25 school year).

MMR coverage rates among kindergarteners for the latest school year varied widely from state to state: from a low of 78.5% in Idaho to a high of 98.2% in Connecticut. In 2024-25 alone, over half the states experienced declines in vaccination rates for all state-required vaccines, including MMR, DTP (diphtheria-tetanus-pertussis), polio, and chicken pox.

One of the factors contributing to this decline in vaccination rates is exemptions from mandatory vaccination, both religious and philosophical, the latter exemption being based on strongly held personal, moral or other nonreligious beliefs. Although fewer U.S. states allow philosophical exemptions than grant religious exemptions, all 50 states provide exemptions on medical grounds.

The share of U.S. children claiming an exemption from one or more vaccinations rose from 2.5% in the 2019-20 school year to 3.6% in 2024-25. However, the increase comes from an increase in nonmedical exemptions; medical exemptions actually decreased slightly over this interval.

The uptick in exemptions is clearly visible in the next figure, which displays the number of states with exemption rates in select percentage groups by school year, for one or more vaccines. While fewer and fewer states are reporting exemption rates below 3%, the number with exemption rates above 5% is on the rise; this means that those states cannot reach the target vaccination rate of 95% for the MMR vaccine, even if all nonexempt children receive their vaccinations.

But religious and genuine philosophical exemptions constitute only a small fraction of overall objections to vaccination.  By far the greatest number of objections come from those who are fearful of side effects or do not trust vaccine safety. Vaccine hesistancy is also fueled by widespread misinformation, including misunderstandings about herd immunity.

It’s true that serious adverse reactions to a vaccine shot do occur occasionally – typically about once in every million vaccinations. But this is a minuscule risk compared with the risk of contracting the disease itself in an unvaccinated community during an epidemic.

Unvaccinated children exposed to someone infected with measles, for instance, have a 90% chance of contracting the disease, and one of 1,000 children who get the measles will develop encephalitis, an often debilitating aftereffect that can lead to seizures and mental retardation.  That’s a risk of about one in 1,100 of experiencing a serious aftereffect for a child who comes down with measles, compared with the much lower risk of one in one million following vaccination. Some children still die from measles, often after getting pneumonia.

Science tells us that it’s much more risky for a child to forgo vaccination and suffer the consequences of catching a potentially deadly disease, than to be vaccinated against it.

Next: Past Global Warming Was More Rapid than Today’s: The Younger Dryas

Scientific Fraud Growing Exponentially

Nowhere is the attack on science more evident than in the burgeoning incidence of scientific fraud, in the form of both falsification and fabrication of observational data. I first wrote about this in a blog post in 2019, since when the problem has only escalated. It’s now estimated that 1% to 2% of all scientific research papers are fraudulent – a fraud rate approaching that of industries such as healthcare and financial services.

A recent study from Northwestern University has examined scientific fraud in depth. Rather than the traditional focus on scientific misconduct by lone individuals, which is comparatively rare, the new study exposes numerous instances of large-scale fraud enabled by a far-flung network of editors and authors who cooperate to publish low-quality or fabricated research papers. This coordinated fraud combines clandestine “paper mills,” intermediary brokers, and so-called predatory journals that charge a fee without offering any services other than publication itself.

Paper mills are shady businesses that sell bogus manuscripts and authorships to researchers who need journal publications to advance their careers. The Northwestern researchers say that a 2022–23 survey of medical residents at hospitals in southwest China found that 47% of respondents had bought and sold papers, allowed other people to write their papers, or written papers for others.

A 2023 report in Nature magazine identified more than 400,000 research articles published over the previous two decades that show strong textual similarities to known studies produced by paper mills; the rising trend is illustrated in the figure below.

The new Northwestern study assembled an extensive database derived from major aggregators of the scientific literature, retracted publications, editorial records, and reports of image duplication in research papers.

A portion of the study focused on the massive online open access journal PLOS ONE, which has a higher-than-average retraction rate. The journal also lists the handling editor of every published paper. Of PLOS ONE editors who have accepted articles for publication, 22 accepted papers that were later retracted much more frequently than one would expect by chance. This number of flagged editors increased to 33 when mostly negative comments recorded by the watchdog PubPeer Foundation were considered.

Altogether, 45 PLOS ONE editors were flagged due to the anomalous rate at which they accepted eventually retracted or PubPeer commented publications, or because their submissions were handled by other flagged editors. Although these individuals edited only 1.3% of all papers published in PLOS ONE up to 2024, they edited a sizable 30% of the journal’s retracted papers. And 25 of these 45 editors themselves authored papers that were subsequently retracted.

These anomalous patterns are not restricted to PLOS ONE, say the Northwestern researchers. Across ten journals from the publisher Hindawi, which also disclose the editors of published manuscripts, they found 53 editors who accept eventually retracted articles anomalously often, and 96 who accept fast-tracked articles unusually frequently.

Apart from these examples of potentially fraudulent behavior, the study authors investigated whether certain scientific disciplines were more prone to fraud than others. It was found that the phenomenon is much more pronounced in six subfields in the area of RNA biology. As shown in the next figure, papers involving “lncRNAs” and “miRNAs, cancer” feature retraction rates that peak at around 4%, higher than even the rates of papers withdrawn due to errors.

Sadly, the authors conclude that scientific fraud is growing much faster than science as a whole. The number of retracted articles has been increasing exponentially over the last 30 years as seen in the figure below, in which the vertical scale is logarithmic and the dashed lines are projections.

The researchers note that the number of retracted articles and PubPeer commented articles have been doubling every 3.3 years and 3.6 years, respectively, while the total number of publications has doubled only every 15 years. The literature in some fields “may have already been irreparably damaged by fraud,” they say.

The Northwestern researchers go on to state:

Collectively, these findings show that the integrity of the extant scientific record and of future science is being undermined through the shortcomings in the very systems through which scientists infer the trustworthiness of each other’s work.

In the face of this onslaught, fortunately, the scientific community has not been silent. An informal network of research-integrity sleuths or paper-mill detectives now scrutinize thousands of published papers each year and frequently find evidence of manipulation and fabrication. Their detailed examinations, usually published online in PubPeer, often form the basis of subsequent retractions and misconduct investigations.

But sleuths and watchdog websites such as Retraction Watch can’t keep up with the rising tide of fraud. Lead author of the Northwestern study, Reese Richardson, is pessimistic about the future influence of AI (artificial intelligence):

If we're not prepared to deal with the fraud that's already occurring, then we're certainly not prepared to deal with what generative AI can do to scientific literature.

Next: Vaccine Hesitancy on the Rise