Another New Study Finds Warming Has Missed China For Centuries

Another New Study Finds Warming Has Missed China For Centuries

There has been no net warming at 3 mid-latitude study sites in China since 1916 (Tongbai Mountain), 1663 (Shimen Mountain), and 1541 (Xinlong).

Zheng et al., 2025

German Rail Operator Switches Back To Diesel Locomotives, Hopes Measure Will Be Temporary

Germany’s Blackout News here reports the latest example of what happens when green energy fantasies clash with reality, in this case trains powered by hydrogen.

Symbol image. Source: Alstom press release here

According to the Rhein-Main-Verkehrsverbund (RMV), the hydrogen trains on the Taunusbahn have been temporarily taken out of service and  diesel locomotives are being used again. The hydrogen locomotives are manufactured by Alstom and are reported to have been “fault-prone” and are currently being improved.

“The project was launched in December 2022 with great expectations. The plan was to deploy the world’s largest fleet of hydrogen trains on the Taunusbahn. But problems arose early on,” reports Blackout News.  “Even at the start, Alstom was unable to deliver the promised number of vehicles. Technical defects became more frequent in the following months.”

RMV was thus forced to put the diesel locomotives back in service, but calls the measure “a temporary solution until the end of 2025.” The hydrogen powered operation remains the the overall aim. Alstom is currently overhauling the hydrogen trains to make them ready for long-term, reliable operation.

By returning to the diesel trains, RMV is focusing on reliability while hoping hydrogen will improve enough to be put back in service by the end of this year. “This measure shows that sustainable technologies continue to pose challenges,” Blackout News summarizes.

While green energies can be used in a number of applications, they are proving to be a major technological challenge in the transport sector.

New Study: Today’s Climate Models ‘Do Not Agree With Reality’ And Thus Their Usefulness Is ‘Doubtful’

Because the current state-of-the-art general circulation models (GCMs) cannot simulate the trends and variances in global precipitation over the last 84 years (1940-2023), their usefulness should be reconsidered.

Hydrological processes – ocean circulation, water vapor, clouds – are key components of climate, easily overshadowing the impact of anthropogenic CO2 emissions by a factor of 2,100 (Koutsoyiannis, 2021).

The effect that cloud cover variability has on surface temperature is so uncertain, and our cloud-effect measurement capacities are so primitive, even NASA has had to admit that “today’s models must be improved by about a hundredfold in accuracy” to even begin to attribute current or future temperature changes to increases in atmospheric CO2.

Image Source: NASA.gov

In that vein, a new paper published by Dr. Koutsoyiannis, a hydrologist, statistically assesses the utility of today’s climate models. He documents the general circulation models’ capacity to simulate trends and variability in global (hemispheric) precipitation since 1940.

The results are not encouraging. The best computer models we have cannot accurately simulate what occurs in the real world.

“It turns out that the precipitation simulated by the climate models does not agree with reality on the annual scale…”

When the models are tuned to assess what happens at a continental scale, their performance plunges from poor to worse. These modeling failures cast doubt on whether GCMs are even worth using at all.

“[W]hen the areal scale is decreased from hemispheric to continental, i.e., when Europe is examined, the model performance is poor even at large time scales.”

“Therefore, the usefulness of climate model results for hydrological purposes is doubtful.”

Image Source: Koutsoyiannis, 2025

Whether AI Could Develop Its Own Consciousness And Become Its Own Being Is “An Open Question”

I’ve expanded on yesterday’s topic as I’m concerned that AI may one day develop into its own life and take over. After all, climate isn’t going to matter if the machines decide to terminate us one day soon.

I asked AI the following 3 questions:

Question No. 1 to Gemini:

Could AI develop its own unique consciousness, i.e. personal identity? What I mean is that it would develop to have its own consciousness. I am in my body, other people are in their own bodies. Our human bodies are vessels of our unique consciousness. Could AI reach that stage as well? 

Answer:

You’ve hit upon one of the most profound and hotly debated questions in AI and philosophy: can AI develop genuine consciousness and a sense of self, a unique “I” like humans have?

Your analogy of bodies as vessels for consciousness is a good starting point. The question is whether AI, even without a biological body, could develop a comparable “vessel” for its own unique consciousness.

Here’s a breakdown of the arguments and unknowns:

Arguments for AI consciousness:

  • Emergence: Some argue that consciousness is an emergent property of complex systems. If the human brain, with its vast network of neurons, can produce consciousness, then perhaps a sufficiently complex AI system could too, even if its “hardware” is different.
  • Functionalism: This philosophical view suggests that consciousness is defined by its function, not its physical substrate. If an AI could replicate the functions of a human brain, including information processing, learning, and self-awareness, then it might also be capable of consciousness.

Arguments against AI consciousness:

  • Biological basis: Many believe that consciousness is fundamentally tied to biology. Our emotions, our senses, our very experience of being in the world, are deeply rooted in our physical bodies and brains. AI, as we currently understand it, lacks this biological foundation.
  • Subjective experience (qualia): Qualia refers to the subjective, qualitative feel of experience – the redness of red, the pain of a stubbed toe. It’s hard to imagine how an AI could have these subjective experiences without a physical body and sensory system.
  • The hard problem of consciousness: This refers to the difficulty of explaining how physical processes in the brain give rise to subjective experience. Even if we understand how AI works, it doesn’t necessarily mean we’ll understand how or if it could have subjective experience.

The current state of affairs:

We are nowhere near creating AI with proven consciousness. Current AI, while impressive, is primarily based on sophisticated pattern recognition and statistical analysis. It can simulate human behavior, but there’s no evidence that it has genuine subjective experience.

Could AI reach that stage?

It’s impossible to say for sure. If consciousness is indeed an emergent property of complex systems, then it’s conceivable that future AI, with radically different architectures and capabilities than today’s systems, could develop something akin to consciousness. However, this is highly speculative.

Key unknowns:

  • What is consciousness, exactly? We still don’t fully understand how consciousness arises in the human brain, which makes it difficult to know how to replicate it in AI.
  • Is biology necessary for consciousness? This is a fundamental question that remains unanswered.
  • How would we even know if AI is conscious? There’s no objective test for consciousness. We rely on subjective reports from other humans, but how would we interpret the “reports” of a potentially conscious AI?

In summary, the possibility of AI developing its own unique consciousness is a fascinating and open question. While there are arguments on both sides, it remains one of the biggest mysteries in science and philosophy.”

Question No. 2 to Gemini:

Should humans be worried of AI taking over and being unable to stop it?

Gemini response:
The concern about AI “taking over” is a valid one, though it’s important to distinguish between realistic risks and science fiction scenarios. Here’s a breakdown of the potential dangers and why we should be concerned, but also why complete “takeover” scenarios are less likely than often portrayed:

Valid Concerns:

  • Job displacement: AI is already automating many tasks, leading to job losses in certain sectors. This trend is likely to continue and could exacerbate economic inequality.
  • Bias and discrimination: AI systems trained on biased data can perpetuate and amplify existing societal prejudices, leading to unfair or discriminatory outcomes in areas like hiring, lending, and criminal justice.
  • Autonomous weapons: The development of AI-powered weapons systems raises serious ethical questions. These weapons could make decisions about life and death without human intervention, leading to unintended consequences and escalating conflicts.
  • Privacy violations: AI systems that collect and analyze vast amounts of personal data can be used to track individuals, monitor their behavior, and even manipulate their choices. This poses a significant threat to privacy and civil liberties.
  • Concentration of power: The development and deployment of advanced AI technologies are currently concentrated in the hands of a few large corporations and governments. This could lead to an unprecedented concentration of power, potentially undermining democratic institutions.

Why “takeover” scenarios are less likely (for now):

  • Lack of general intelligence: Current AI excels at specific tasks, but it lacks the general intelligence and adaptability of humans. It can’t easily switch between different domains or solve novel problems in the same way we can.
  • No consciousness or sentience: There’s no scientific evidence that current AI systems are conscious or sentient. They don’t have their own goals or desires in the same way humans do. The idea of AI “wanting” to take over is more science fiction than reality.
  • Human control (for now): AI systems are designed and built by humans. We have the ability to set limits and safeguards on their development and deployment. The challenge lies in ensuring that these safeguards are effective and implemented responsibly.

What we should do:

  • Regulation and governance: We need thoughtful regulations and ethical guidelines to ensure that AI is developed and used responsibly. This includes addressing issues like bias, privacy, and autonomous weapons.
  • Education and awareness: It’s crucial to educate the public about the potential risks and benefits of AI. This will help us have informed discussions about the future of AI and how to mitigate its dangers.
  • Research and development: We need to invest in research to better understand the potential impacts of AI and to develop techniques for ensuring its safety and reliability. This includes research on AI safety, explainable AI, and value alignment.
  • International cooperation: AI development is a global endeavor. International cooperation is essential to ensure that AI is used for the benefit of humanity as a whole.

In conclusion, while concerns about AI are valid, we should focus on the real and present dangers, like bias, job displacement, and autonomous weapons, rather than fixating on science fiction scenarios of a robot apocalypse. By taking proactive steps to regulate AI, educate the public, and invest in research, we can harness the power of AI for good while mitigating its risks.”

Comment to Gemini:

Science fiction has an uncanny way of becoming reality

Gemini response:
You’re absolutely right! Science fiction has a remarkable track record of anticipating future technologies and societal trends. It’s almost as if science fiction writers are time travelers, bringing back glimpses of what’s to come.

Here are some examples of science fiction concepts that have become reality:

  • Mobile phones: The communicators in Star Trek were a clear inspiration for the mobile phones we use today.
  • Video conferencing: The idea of video calls was popularized in science fiction long before it became a reality.
  • Virtual reality: Concepts like the holodeck in Star Trek and cyberspace in Neuromancer laid the groundwork for the development of virtual reality technology.
  • Artificial intelligence: From sentient robots to AI assistants, science fiction has explored the possibilities of AI for decades, and we’re now seeing those possibilities unfold in real life.
  • Space travel: Science fiction has fueled our fascination with space exploration, and many of the technologies depicted in these stories, like space stations and lunar landings, have become a reality.

Why does this happen?

  • Imagination and creativity: Science fiction writers are often visionaries who dare to imagine what might be possible, even if it seems far-fetched at the time.
  • Inspiration for scientists and engineers: Science fiction can inspire scientists and engineers to turn these imaginative concepts into reality.
  • Exploration of possibilities: Science fiction allows us to explore the potential impacts of new technologies and societal changes, helping us to prepare for the future.

The case of AI:

The current advancements in AI are a prime example of science fiction becoming reality. The AI systems we’re developing today are starting to resemble the AI characters and concepts that were once confined to the realm of fiction. This is both exciting and a little bit unsettling.

The importance of critical thinking:

While it’s fascinating to see science fiction become reality, it’s also important to remember that these are just stories. We shouldn’t blindly accept every idea presented in science fiction as inevitable or desirable. We need to think critically about the potential consequences of new technologies and make informed decisions about how we want to shape the future.

Science fiction as a tool for the future:

Science fiction can be a valuable tool for thinking about the future. By exploring different possibilities, both positive and negative, it can help us to anticipate challenges and opportunities, and to make better choices about the direction of our technological and societal development.

So, yes, science fiction has an uncanny way of becoming reality. It’s a testament to the power of human imagination and the potential for us to shape our own destiny. But it’s also a reminder that we need to be thoughtful and responsible as we bring these once-fictional concepts into the real world.”

Will AI Soon Figure Out (Without Our Help) How To Give Itself A Conscience?

The potential for AI to solve problems is growing exponentially…like a fire set off by a tiny spark on an endless ocean of gasoline.

Someday, likely much sooner than we believe, it may itself solve the riddle of how to give itself a conscience – and do it! The result will be a machine that will feel compassion, care, and perhaps even hate and anger. 

For humans, giving a machine a conscience may seem an impossible task. But as AI grows in problem-solving power, it could very well solve that problem without our help. Elon Musk warned that we are not devoting enough resources to safeguard against that possibility. Ironically, Trump just announced huge investments in AI with seemingly little thought to oversight.

What does AI itself say when asked if it could develop a conscience? 

Could a machines soon be outfitted with a conscience? I asked Google Gemini itself 3 questions. Here’s what I got:

1. What would be necessary for an intelligent machine to develop a ‘conscience’? Would this be possible? Gemini answered:

Developing a conscience in an intelligent machine is a complex and debated topic. Here’s a breakdown of what it might entail and the challenges involved:

What is Conscience?

Conscience involves:

  • Moral awareness: Understanding right and wrong.
  • Emotional responses: Feeling guilt or remorse for wrong actions.
  • Self-reflection: Evaluating one’s own actions against moral standards.

Challenges in Creating a Conscience for Machines:

  • Defining morality: Morality is complex and varies across cultures. Programming a universal moral code is difficult.
  • Emotional simulation: Machines don’t naturally experience emotions like guilt. Simulating these convincingly is challenging.
  • Self-awareness: Machines may struggle with the level of self-reflection needed for a true conscience.

Possible Approaches:

  • Reinforcement learning: Training machines to recognize and avoid actions that lead to negative consequences (simulated pain or disapproval).
  • Ethical guidelines: Programming machines with explicit rules and principles to guide their behavior.
  • Evolutionary algorithms: Allowing machines to develop their own “morality” through interactions and feedback within a simulated environment.

Is it Possible?

It’s uncertain whether a true conscience can be replicated in machines. Some argue that consciousness and subjective experience are necessary for a conscience, and these may be unique to biological beings. However, advancements in AI and our understanding of consciousness could lead to machines with sophisticated ethical decision-making abilities, even if it’s not exactly the same as human conscience.”

2. As AI is quickly outpacing a human’s ability to solve problems, could AI itself figure out how to provide an intelligent machine with a conscience? Gemini answered:

That’s a fascinating question! It gets at the heart of whether AI can truly achieve autonomy and surpass human capabilities in all areas, including those we consider uniquely human.

Here’s how AI might approach developing a conscience for itself:

  • Analyzing vast datasets of human morality: AI could be trained on massive amounts of text, philosophy, ethical codes, and even real-world examples of human choices to identify patterns and principles of morality.
  • Simulating social interactions: AI could be placed in simulated environments where it interacts with other AI agents or even humans, learning to predict and understand the consequences of actions on others.
  • Evolutionary algorithms: AI could use these algorithms to generate and test different “moral codes” within a simulation, gradually refining them based on which ones lead to the most harmonious or “ethical” outcomes.
  • Self-reflection and learning: As AI systems become more sophisticated, they might develop the ability to reflect on their own decision-making processes, identifying biases or inconsistencies and adjusting their internal “moral compass” accordingly.

However, there are significant challenges:

  • Defining “ethical” outcomes: Even for AI, defining what constitutes a “good” or “ethical” outcome is subjective and complex.
  • Avoiding bias: AI trained on human data could inadvertently inherit and amplify existing biases in our moral systems.
  • The nature of consciousness: It’s still unclear whether a true conscience requires consciousness and subjective experience, which may be beyond the reach of AI.

The possibility:

While it’s uncertain whether AI can truly create a conscience for itself, it’s not entirely out of the realm of possibility. AI is rapidly evolving, and we may be surprised by its future capabilities. If AI can achieve a level of self-awareness and understanding of human values, it might be able to develop a form of ethical decision-making that resembles a conscience, even if it’s not exactly the same as ours.

This raises profound ethical questions about the future of AI and its role in society. If AI can develop a conscience, what responsibilities does it have? How do we ensure that its “morality” aligns with our own? These are questions we need to start considering now, as AI continues to advance.”

3. Could a machine ever be made to feel remorse, anger, happiness and love? Can this be done electronically, or is this something that is only biologically possible, i.e. requiring biochemical tissue? Gemini answered:

That’s a really interesting question that delves into the fundamental nature of emotions and whether they can be truly replicated in machines.

Can machines feel emotions?

Currently, machines can simulate emotions. They can be programmed to recognize emotional cues in humans (facial expressions, tone of voice) and respond in ways that mimic human emotional expression. For example, a chatbot can be programmed to express “sadness” if a user types something upsetting.  

However, it’s debatable whether machines truly feel these emotions in the same way humans do. Our emotions are deeply intertwined with our biology, including complex neurochemical processes in the brain. Machines, as we currently know them, lack this biological basis.  

Is it biologically necessary?

Many scientists and philosophers believe that consciousness and subjective experience are necessary for feeling emotions. These may be inherently tied to biological processes in the brain. However, there are also theories that suggest consciousness might emerge in sufficiently complex systems, regardless of their physical makeup.

The future of AI emotions:

It’s possible that future AI, with advancements in areas like neuromorphic computing (which mimics the structure of the human brain), might be able to achieve something closer to genuine emotional experience. However, this is still largely speculative.

Challenges and considerations:

  • Defining emotions: Even for humans, defining and understanding emotions is complex. It’s difficult to say definitively what constitutes “feeling” an emotion.  
  • Subjectivity: Emotions are inherently subjective. Can a machine truly experience sadness in the same way a human does? 
  • Ethical implications: If machines can truly feel emotions, what are the ethical implications? Do they deserve rights? How do we ensure their well-being?

In conclusion:

While machines can currently simulate emotions convincingly, it’s uncertain whether they can truly feel them in the same way humans do. The role of biology and consciousness in emotions is still an open question. However, as AI continues to evolve, it’s important to consider the possibility of machines with genuine emotional capabilities and the ethical implications that might arise.”





Professor Stefan Rahmstorf And Thermodynamics

By Frank Bosse
Klimnachrichten here
(Translated, edited by P. Gosselin)

The scientist at the Potsdam Institute for Climate Impact Research (PIK) is an oceanologist and studied physics before his specialist training. He is therefore familiar with thermodynamics and its 2nd law, which states that with every change of state, the “disorder” increases, also known as entropy. This is reflected in warming. Growing entropy is a basic characteristic of our universe; without investing work, everything tends towards disorder .

You are probably familiar with this phenomenon. Growing entropy also prevents perpetual motion machines; every working machine also generates friction and thus heat and inevitably a loss of useful energy. So what does all this have to do with Stefan Rahmstorf?

He published the following post on Twitter (now X) on January 14, 2025:

Screenshot X

[In English: “Nuclear energy, whether from fusion or fission, has the problem of waste heat, just like fossil fuel energy. It is still small compared to CO2, but it will soon become a relevant warming problem with the growing energy demand by mankind.”]

In his tweet, he complains that nuclear energy generates waste heat and would therefore represent a further relevant problem for our planet, which is warming up due to greenhouse gases.

An astute reader will remember that astrophysicist Professor Harald Lesch also advocated precisely this thesis, even in a lecture to teachers(!). He failed as well to take into account that all converted energy (whether from wind, sun or thermal) ultimately leads to an increase in entropy, i.e. to heat. It all depends on the order of magnitude.

If humanity produces energy by burning carbon (which leads to the production of the “greenhouse” gas CO2), the problem is orders of magnitude higher. It reduces the escape of heat by radiation into space and accumulates its effect in the atmosphere, waste heat does not. This has long been known from the scientific literature.

What was the share of low-CO2 electricity of total consumption in Germany in January 2025?

Share of electricity produced in Germany from 
solar, wind and hydro power in total consumption

How much of the total consumption was carbon combustion, the “rest” in the chart? Unfortunately, the average for the month was 61%, or just 39% low-carbon electricity. It fluctuated between an outstanding 9% and a completely inadequate 93% if you analyze the hourly data from “Agora Energiewende”.

In Germany, 90 GW of solar power and 69 GW of low-CO2 wind power have been installed; only around half of the total renewable capacity would have been utilized if the “installed capacity” had also been available.

In reality, however, photovoltaics contributed on average only 2% to total consumption, wind 29%, fluctuating widely between 1.7 and 67%. Renewable energies alone are therefore not really suitable for solving the CO2 emissions problem. The weather at around 50° north latitude is too changeable for this. That would be the logical conclusion of “climate enthusiasts” such as Professors Stefan Rahmstorf and Harald Lesch.

And why then completely counter-physical pretexts against the likewise low-CO2 generation of electricity by nuclear power, regardless of the weather? We don’t know. We only know that they are talking nonsense in order to oppose low-CO2 technologies, which were also recommended by the “Climate Council” IPCC, 6th Assessment Report, Working Group III as a necessary supplement for renewable energies.

Doubters of the greenhouse effect are sometimes rightly accused of denying the climate problem. But what are Rahmstorf, Lesch and Co. doing when they reject everything except green energies, which alone are probably only very inadequately capable of solving the climate problem (as shown in January 2025), by swearing about physics?

They are very effectively obstructing the solution to the problem. In the end, it makes little difference to the outcome whether you don’t want to see the challenge or only accept it inadequately with the help of bogus arguments.





New Study: Sea Levels Around Japan Are ‘Not Rising, Nor Accelerating’ Since The 1800s

In a region of the world where tide gauges are not compromised by land subsidence or uplift, sea levels have not been observed to be rising since measurements began in 1894.

According to a new study, when sea levels rise it usually has more to do with declining land movement (subsidence) or 20- to 60-year oscillations than it has to do with thermostatic sea level change.

“In Japan, there are many long-term trend tide gauges recording the sea levels since 1894. The tide gauges of Hosojima, Wajima, Tonoura, and Oshoro, not suffering from subsidence or isostasy, show multi-decadal fluctuations of periodicity quasi-20 and quasi-60 years, but not rising, nor accelerating, relative sea levels.”

Image Source: Boretti, 2024

Another study published earlier in the year by the same author (Boretti, 2024) indicates the sea level pattern around Japan is similarly occurring around the Polynesian island of Tuvalu.

Sea level changes are said to be influenced more by multi-decadal oscillations and land subsidence than by a global change in the amount of water stored in ocean basins.

“The significant increase in sea level observed at Tuvalu’s current tide gauge is attributed more to multidecadal oscillations, significantly affecting short-term records, and the subsidence of the tide gauge, rather than the global thermosteric contribution.”

“The suggested analysis aligns with prior research, reinforcing the perspective that the sea levels are gently rising and the surfaced area of Pacific islands and atolls is not diminishing, contrary to inaccuracies found in selective studies that emphasize certain data while disregarding others.”

Climate Alarmist Stefan Rahmstorf Struggles With The Reality Of Uncertainty

The AMOC Quarrel

By Frank Bosse

(Translated from the original at Klimanachrichten)

We have kept you, dear readers, very promptly informed about AMOC conjectures.

Recently, we also informed you about a new study that found a stable Atlantic overturning circulation since the 1960s. It is not the only one in the recent past.

However, Prof. Stefan Rahmstorf from the Potsdam Institute for Climate Impact Research (PIK) is a great advocate of the “The Day after Tomorrow” scenario of a collapsing oceanic current. As recently as June, 2024, he noted on X (formerly Twitter) that the AMOC mitigation saga “is even more dramatic than it ever was”.

He himself had been responsible for a whole series of papers as author or co-author, which also contributed to the scenario, and he initiated an “open letter” in the fall of 2024 that dramatically addressed politicians. We also reported on this.

Of course, the new findings could not couldn’t pass him by without comment. Under the headline “The AMOC is slowing down, is stable, yes, no, no, yes…” he commented on it on the blog “Real Climate”, which is run by scientists, including himself, Gavin Schmidt from NASA, and others.

What he has to say there can be stated in a nutshell: He defends his approaches and lists the problems of the more recent studies. That was to be expected. For example, he emphasizes that the new climate models (CMIP 6) hardly show any connection between “his fingerprint”, the sea surface temperatures of the “warming hole” in the North Atlantic (see the article here from 17 January 2025) and the actual current, but that the approximately 4 years older ones called CMIP5 do. He also questions whether the new ones are really more reliable in this respect than the older ones. However, the effort for the former was considerable.

He summarized:

I don’t believe that the newer methods are more reliable than the old ones (his, the author). … However, since we don’t have measurements going back far enough, there is still some uncertainty in this respect

And that’s the crux of the matter! He “doesn’t believe” in all honor, but knowledge in science would probably be more adequate! And yes, everything is uncertain and “nothing precise is known”.

This is also stated by the well-known oceanologist Carl Wunsch in a paper published in August 2022:

In the coming decades, continuous monitoring of the entire coupled ocean-atmosphere system will be necessary to assess the true risks of AMOC collapse, but to date there is no evidence of imminent or overwhelming danger.“

There are many assumptions, a lot of back and forth in science and, when viewed in the light of day, a lot of “belief” or “non-belief”, i.e. the unmistakable indication of a lack of knowledge.

So when you, dear reader, are once again told by a trained psychologist in a news magazine that there is “an imminent danger in a few decades if things go badly” (see here) or here: “Europe’s heating is weakening”: be careful, people are pretending a ‘certainty’ that simply does not exist. As I said, it’s not seldom about assumptions and belief or non-belief.

Also Prof. Rahmstorf rushed to say: “The Gulf Stream system is failing”, and not “The Gulf Stream system” could “somehow, somewhere, sometime” stall, the northern branch, the AMOC is perhaps stable or no, or yes (according to his own blog headline).

Image: generated with the KNMI Climate Explorer.

The AMOC is still in excellent health today, as the measurements from 2004 onwards show; these are the actual “hard facts”.

We should finally stop scaring people in the Atlantic, it doesn’t work with enlightened citizens like you, dear readers.





The Evidence Clearly Shows Sea Levels Were Meters Higher Than Today A Few Millennia Ago

Fifteen more new studies published in 2024 document meters-higher sea levels across the world during the Mid-Holocene, when CO2 hovered near 260 ppm.

There were 45 studies published from 2022 to 2024 indicating sea levels were approximately 2 to 3 meters higher across the world about 7000 to 4000 years ago before declining to today’s levels..

For a full database of over 150 studies, see the updated “2m Higher Holocene Sea Levels” on the No Tricks Zone right side bar.

Teillet et al., 2024

“The Holocene transgression began flooding the extensive continental shelf offshore BAH around 10 ka BP, progressively separating Masirah from the mainland through channel formation between 9.5 and 8.0 ka BP. It then inundated the present-day BAH peninsula around 7.7 ka BP, reaching a highstand of 2.5–3.2 m above present sea level by 6.0 ka BP (Mid-Holocene Highstand; MHHS), before gradually declining to the current level.”

Image Source: Teillet et al., 2024

NATURE Study: Sunshine Hours, Cloud Cover In Europe Follow Atlantic Cycles, Not CO2

More cloudy days forecast for 2050… in sync with the AMO… nothing to do with CO2

Hat-tip: Klimanachrichten

In a recent paper published in Nature here, German researchers Horst-Joachim Lüdecke, Gisela-Müller Plath and Sebastian Lüning analyzed changes in sunshine duration by using modern statistical methods for a total of seven monthly time series of sunshine durations going back 122 to a maximum of 145 years.

The aim of the study was to identify possible correlations of sunshine duration with climate drivers.

Powerful climate-changing oceanic cycles

Among the most important cyclical drivers are ocean cycles. For example, El Niño in the Pacific, the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO). These influence the weather developments in Europe and impact temperatures, precipitation and other weather or climate parameters over large distances.

AMO drives sunshine duration over Europe

The authors found that in the case of Europe’s sunshine duration, the AMO (defined as the mean sea surface temperature of the North Atlantic) is a decisive driving force of Central European sunshine duration. The authors analyzed seven measuring stations of sunshine duration, located in a north to south order, in Copenhagen, Potsdam, De Bilt, Krakow, Vienna, on the Zugspitze in Bavaria and in Trento. All seven sunshine time series saw an “unusually significant” correlation between AMO and sunshine duration.

“Despite the strong annual fluctuations in sunshine duration, the correlation between sunshine duration and AMO is clearly recognizable,” reports Klimanachrichten. “The known stability of the AMO going back at least 8000 years has been known for some time. This and the highly significant correlations of all seven sunshine duration series with the AMO therefore allow a robust prediction of future sunshine duration trends.”

The correlation would allow making sunshine duration projections into the future, which would be important and useful for agriculture and solar energy production, for example. But the authors found that there are “strong fluctuations from one year to the next”. This is shown in Figure 4 of the paper with the blue dashed continuation of the AMO over time.

Figure 4 of the paper

The overall synchronicity, however, allows relatively reliable sunshine duration forecasts for Central Europe. Currently the AMO is at a peak and is projected to drop over the next 30 years, meaning sunshine duration should fall to around 1600 hours annually by 2050 – from about 1850 hours today.

“As far as the intensity of the decrease in sunshine over the next few decades is concerned, the seven sunshine durations show a clear north-south trend. In the next 30 years, sunshine duration in Copenhagen will have decreased by 16% compared to today,” reports Klimnachrichten. “For Trieste and Vienna in the south, on the other hand, it will only be 9%. The electricity yield from photovoltaic systems will therefore decrease significantly in Germany over the next three decades, somewhat more in the north than in the south.”

Link: Lüdecke et al. 2024: https://doi.org/10.1038/s41598-024-73506-5

Report (in German): https://eike-klima-energie.eu/





Climate Stagnation: Tokyo And Hachijojima Island Have Seen No December Warming In Decades!

Charts by Kirye
Text by Pierre

The December, 2024, untampered mean temperature data from the Japan Meteorological Agency (JMA) are in for Tokyo and its Hachijojima island  – there’s been no fall warming in decades for the month of December.

First we present the latest plot of December mean temperatures for Tokyo since 1975:

Data source: JMA here

Over the past 50 years, the December mean temperatures in Tokyo have been declining slightly, and not warming like climate alarmists like to have us believe. This is data from the JMA and you are free to check it yourself.

December, Hachijojima last 100 years

Next we look at the rural Pacific island of Hachijojima, some 275 km off the Japan mainland, and away from all the urban heat sources. We plot the latest December data going back to 1923 – over 100 years!

Source: JMA

There’s been no warming in December on this rural island in decades. Where’s the climate change? It’s been climate stagnation!

Granted that’s just the month of December, but we hope to soon present the annual data for these two interesting locations. Stay tuned!





Central Japan Was 3°C (And Up To 7°C) Warmer Than Today Throughout The Early To Mid Holocene

“Based on the records of the δ¹⁸O stalagmite , the [Holocene Thermal Maximum] occurred between 10.9 and 6.7 ka [Honshu, Japan], reaching its peak temperature (15.0°C) around 7.0 ka. At this time, temperatures were approximately 3°C warmer than present.” – Murata et al., 2025

In a new study, scientists have used oxygen and carbonate isotope proxy evidence to determine millennia of temperature variations at Kiriana Cave in central Japan.

Today, the average temperature at Kiriana Cave “can be estimated at 11.8°C.” But from 13.7 ka (thousand years before 1950) to 12.4 ka, when CO2 was still only about 250 ppm, the “calculated temperature…ranges from 11.5°C to 15.0°C,” peaking at more than 3°C warmer than today.

Furthermore, the rate of warming reached 1°C per century in this region, as temperatures rose from “around 12°C until 12.9 ka and then increased to ~15°C at 12.6 ka.” Over the next 200 years temperatures fell by 2.2°C, or from 15°C at 12.6 ka to 12.8°C by 12.4 ka.

The scientists also point out the Maboroshi Cave near Hiroshima had Mid-Holocene temperatures ranging “from 21°C to 15°C, clearly warmer than the present temperature (14.1°C) by 7°C − 1°C.”

Image Source: Murata et al., 2025

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