Climate Media

Happer & Wrightstone: Get Real and Stop Blaming CO2

Posted on by Ron Clutz

The above interview was conducted by NTD news with CO2 Coalition founder William Happer (WH) and Executive Director Gregory Wrightstone (GW).  For those preferring to read, below is a transcript from the closed captions in italics with my bolds and added images.

NTD: The Environmental Protection Agency’s Lee Z eldin announced a proposal earlier this week to overturn a 16-year-old scientific finding from the Obama administration. It allowed three administrations to regulate greenhouse gas emissions like CO2. If successful, this would roll back climate rules on cars, undo $1 trillion in regulatory costs, and save over $54 billion each year. With the public comment period now open, here to break down what all of this means are two guests. William Happer, professor emeritus at Princeton University department of physics, and Gregory Wrightstone, geologist and executive director of the CO2 coalition. Thank you both so much for being here.

Now, first, how big of a deal would this be, repealing the 2009 endangerment finding? Who has benefited under it so far?

WH: Well, I’m not sure who you asked this question, but I will answer it and Greg can add to what I say. This is something that was long overdue. I mean, it was a ridiculous regulation that purported that carbon dioxide, which all of us breathe out, is a pollutant. I mean, I can’t think of anything dumber than that, but that’s what it was. And so finally there’s been an administration with the courage to tell the truth, that it isn’t a pollutant at all and it’s actually good for the earth to have more carbon dioxide.

NTD: What is the likely legal process of repealing this? And Gregory, this finding was the legal prerequisite used by the Obama and Biden administrations to regulate new car and engine emissions. What is the likely legal process of repealing this now?

GW: Well, this right now is just dealing with cars and light trucks and vehicles, but it’s sure to extend into the other things. Your viewers have had their freedom systematically eroded using the endangerment finding. With this endangerment finding, they’ve been able to tell you what car kind of car to drive. Look at the ceiling fan over your head, regulate that. All these electrical devices, your washer, dryer, dishwasher. the only ones you can buy today are government approved devices because of the endangerment finding. So what this does is to actually liberate Americans for freedom to choose what kind of appliances they want. If they want to buy a dishwasher that’s very efficient in terms of washing dishes, not in terms of how much electricity you use. That should be my choice and your choice and all of your viewers’ choices. So, this is really liberation day for America and restoring a lot of the freedoms that were lost based on this failed endangerment finding.

NTD: Expanding on that, William, what about the science needed to decide whether or not this will get repealed? Besides the legal angle, break down for us the science that’s needed to decide whether or not this will get repealed.

GW: Well, the science is quite clear. Understand what they did in 2009, they excluded any contrary science. By contrary science, anything that indicated that CO2 was not a pollutant. But the Supreme Court rulings in 2024 now say you have to consider all of the science. And there’s just a huge amount of of science right now that that disputes endangerment, that actually confirms carbon dioxide has hugely beneficial aspects. Greening the earth, vegetation growth, crop production is exploding. And Dr. Happer can perhaps talk about how the the greenhouse gas warming potential is not at all what they say it is.

NTD: Will CO2 cause dangerous warming? On that note, will you break down that aspect for us ?

WH: Well, as Greg said, the accusation against CO2 is that it would cause dangerous warming of the earth. And as usual there’s a grain of truth that CO2 will cause some warming, but the warming will be trivial. It will almost certainly be beneficial to most of the earth. The reason it warms is CO2 is a greenhouse gas. It lets sunlight come through and warm the surface of the earth. But it retards the cooling of the earth by infrared radiation to space. And it’s the balance of those two that determines the earth’s temperature.

But it’s a very inefficient greenhouse gas. It doesn’t much matter if you double CO2. You only change the cooling radiation into space by 1%, a tiny effect. And so, it’s amazing they’ve managed to blow up this molehill into this mountainous threat. It’s not a threat at all. It’s a benefit.

NTD: On that note, Gregory, in terms of how we got to the endangerment finding, was contradictory science a factor in that decision?

Well, actually, no. There was no contradictory science. And again, now bear in mind things are different today than they were even just two years ago. with two Supreme Court rulings last year. In Ohio vs. state farm case the US Supreme Court ruled that these regulatory agencies like the DOE, EPA, DOT, all of these alphabet soup regulatory bodies need to consider all significant science that affects their judgment which EPA in the endangerment finding did not do.

And the evidence we say is is entirely overwhelming. We see by almost every metric you look at, we find that Earth’s ecosystems are thriving and prospering, and the human conditions are improving because of increases in CO2. It’s really the greatest untold story of the 21st century, that of a thriving earth and the benefits to humanity. It’s a feel-good story, but they’ve turned this into fear-mongering where children can’t sleep at night because they’re being lied to by this the promoters we call the climate industrial complex.

Let’s get back to true science, the scientific method. Enough of this consensus science and group think. We support the scientific method and critical thinking which has been removed from many of these government agencies for 30 years or longer.

Climate models

NTD: And William, on that note, there is a big focus on climate change or climate alarm as some might say. Talk to us about some of the climate models that are used. What did these models get wrong?

WH: Well, I think the main thing the models get wrong is that they they know perfectly well that the direct effects of carbon dioxide will cause a very small warming of the earth if there are no other effects. If you double CO2 100% increase, which would take more than a century by the way, that would only warm the earth by a little less than one degree centigrade. It’s a trivial amount and we may never double it anyway.

So here’s what they’ve done. They’ve taken this trivial warming is agreed by most people who understand how this works, and they’ve multiplied it by factors three, four, five and saying that there’s these enormous positive feedbacks on the direct warming. That’s completely crazy because most feedbacks in nature are negative. With most other systems in nature, the first thing you calculate is usually too big, not too small. It’s even got a fancy name. It’s called Chatelier’s principle.

And so everything they’ve done violates Chatelier’s principle that works for everything else in nature, but it apparently doesn’t work for climate alarmists.

China

NTD: And staying with you, William, we often hear the US and Europe talking about cutting emissions, whether that’s in cars or cows even. But at the same time, the carbon brief notes that China is the world’s largest annual greenhouse gas emitter and leads in coal use. How should we look at this if the argument is global warming and not regional?

WH: Well, of course, China has built lots of very efficient new coal plants in the last 10 years. they’re ultra supercritical plants many of them. They’re really good plants and so they’ve raised the standard of living there. Part of their policy is is quite okay and the CO2 they’re emitting is good for the earth you know.

I’m not supporting any of the political things that they do but I don’t think there’s a thing wrong with releasing carbon dioxide. More power to them for that.

CO2 Coalition

NTD: On that note, Gregory, you’re the executive director of the CO2 coalition. Give us a sense of what this coalition does and how this fits in with environmental discussions.

GW: We’re 10 years old now. It was founded in 2015 by Dr. William Happer, our chair that was just on here. And we’re some 200 of the top experts and scientists in the world that don’t buy into the company line on climate change. We don’t believe that increases in human emissions of CO2 are leading to harmful warming. Rather just the opposite, we see huge benefits. Crop growth records are being broken year after year and they attribute 70% of that to increasing CO2. Crop growth and crop productivity is outpacing population growth. That’s a good thing, a really good thing.

We are in a warming trend. Yes, we are. It’s been warming for more than 300 years. But you know what that does? That means since 1900, our growing seasons in the continental United States have increased by more than two weeks. That’s a really good thing for agriculture. Your farmers will tell you they love that. So at the CO2 Coalition, our unofficial motto is: We love CO2 and so should you.

Shifting Climate Discourse

Posted on by Ron Clutz

Fun fact: Mentions of “climate crisis” in corporate media have all but imploded. Why? Because the PR propaganda campaigns aren’t needed when Democrats and their dark-money-funded NGOs aren’t pushing “green” bills or fundraising. H/T Tyler Durden

The climate crisis was merely the Democrat Party’s PR operation to siphon money from taxpayers.

Postscript on Story Counts

I don’t know the source and parameters behind the chart in Tyler Durden’s post.  Below is a chart I produced from Media Cloud based on U.S. National Online News sources.

It’s Summertime, Hottest Year Claims Ensue

Posted on by Ron Clutz

Matthew Wielicki explains the scientific malpractice in his Financial Post article Junk Science Week: The hottest year ever?.  Excerpts in italics wtih my bolds and added images

Advocates and the media claim 2024 was the hottest year ever.
Archeological data suggest it wasn’t,
while modern data suffer from biases

An image produced by NASA and used when it declared 2024 as the warmest year on record. Photo by NASA

In 2024, mainstream media and political leaders aggressively promoted the alarming narrative that Earth had just experienced its hottest year ever recorded. National Geographic dramatically proclaimed, “2024 was the hottest year ever … and the coldest year of the rest of your life,” while the Vancouver Sun declared unequivocally, “Scientists confirm 2024 was Canada’s and world’s hottest year on record.” Canadian political figures reinforced this narrative, with prime minister Justin Trudeau characterizing the year’s warmth as an urgent call for immediate climate action.

I’m an earth science professor-in-exile. Claims such as these
immediately provoke critical skepticism.

This persistent narrative, relentlessly advanced by a powerful climate-industrial complex comprising governments, activist organizations and the media, is designed not merely to inform, but to generate a state of perpetual urgency. As global greenhouse gas (GHG) emissions continue to rise despite decades of climate policy interventions, the need to claim climate conditions are increasingly severe becomes a strategic imperative, regardless of scientific accuracy or historical context. This approach not only distorts genuine scientific inquiry but fosters anxiety and despair, particularly affecting young people already inundated with predictions of catastrophe.

The answers to four fundamental questions expose the weaknesses and biases inherent in the mainstream climate narrative:

1. Can we accurately measure historical global temperatures?

Claims about unprecedented global heat depend heavily on comparing modern temperature records, which are gathered by instrument and capture annual or monthly fluctuations, to historical temperature estimates derived from proxy data such as ice cores, tree rings, sediment layers and coral reefs. But proxy data inherently smooths out short-term fluctuations, providing generalized temperature estimates spanning centuries or millennia. This mismatch between high-resolution modern data and low-resolution historical proxies inevitably exaggerates the perceived severity of contemporary warming.

For example, widely cited reconstructions and favourites of The Intergovernmental Panel on Climate Change (IPCC) explicitly acknowledge their inability to capture temperature variability occurring over periods shorter than 300 years. The rapid temperature changes of recent decades appear unprecedented when put side by side with these smoothed historical averages. This methodological flaw significantly undermines the credibility of claims asserting that current global temperatures are historically unique or alarming.

2. Was 2024 really unprecedentedly warm?

Extensive historical and geological evidence demonstrates significant natural warming vastly exceeding modern temperatures. The Holocene Thermal Maximum (five to nine thousand years ago) saw temperatures significantly warmer than today, including in Canada. Archeological evidence, such as ancient forests revealed by retreating glaciers in the Rockies, conclusively supports periods of substantial natural warmth.

During the Eemian interglacial period (115-130 thousand years ago), Greenland experienced temperatures three to five degrees C warmer than now, despite substantially lower CO₂ concentrations in the atmosphere. These scientifically documented periods confirm that Earth’s climate naturally experiences considerable variability, rendering claims of unprecedented modern warmth scientifically untenable and historically uninformed.

3. Are we measuring the effects of CO₂ or urban heat islands

Most modern temperature records fuelling alarmist headlines originate from urban areas influenced by the Urban Heat Island Effect (UHIE). UHIE results from urban infrastructure, such as concrete, asphalt and buildings, retaining and radiating heat, significantly increasing local temperatures independent of broader climate trends. Toronto’s significant infrastructure growth has noticeably raised local temperatures, heavily skewing data. Similarly, Las Vegas’ highest recorded temperatures coincided with significant expansion around Harry Reid International Airport, illustrating the dominant role of urbanization rather than atmospheric CO₂ emissions.

Recent research indicates that up to 65 per cent of urban warming is from local urbanization rather than global greenhouse gas increases. Attributing urban heat predominantly to CO₂ emissions significantly misrepresents the true dynamics of local temperature increases.

4. Do rising CO2 levels really heat the oceans?

Recent alarmist coverage in outlets like the Financial Times highlights near-record ocean temperatures, linking them directly to rising CO₂ levels. The EU’s Copernicus programme noted that May 2025 ocean temperatures were the second highest ever recorded, with scientists raising concerns about the oceans’ diminishing capacity to absorb CO₂ and excess heat.

But this narrative critically overlooks fundamental scientific facts. Oceans possess a heat capacity orders of magnitude greater than the atmosphere. The notion that atmospheric CO₂ significantly heats ocean water directly is scientifically unfounded, as infrared radiation from CO₂ penetrates mere millimetres into the ocean’s surface, not nearly deep enough to meaningfully alter ocean temperature. Ocean temperature fluctuations are primarily driven by natural phenomena such as El Niño.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

Moreover, historical data on ocean temperatures is highly uncertain, relying predominantly on sparse measurements and indirect proxies. Claiming near-record ocean temperatures without acknowledging these substantial uncertainties misleads the public about the robustness and reliability of these measurements.

Critical conclusion: One thing remains certain: it will never be “too hot” in Canada, despite alarmist rhetoric suggesting otherwise. The exaggerated claims that 2024 was “the hottest year ever” are not grounded in rigorous scientific analysis but serve primarily as political and ideological propaganda. This relentless propagation of fear fosters anxiety, despair, and nihilism, especially among young people — serious consequences largely ignored by climate alarmists.

The scientific community, policy-makers and the public at large need to insist on transparency, rigour and honesty in climate discourse. Recognizing the motivations behind alarmist claims is essential to ensuring public trust and effective policy. Climate science should strive to educate, not frighten, promoting balanced understanding rather than catastrophic narratives disconnected from historical context and scientific rigour.

Matthew Wielicki, Ph.D. in geochemistry from UCLA, publishes the Substack site Irrational Fear, which provides data-driven critiques aimed at fostering a balanced and scientifically grounded understanding of climate science.

Climate Policies to What End?

Posted on by Ron Clutz

Oren Cass writes at Commonplace Who Is Climate Policy For?  Not workers. Excerpts in italics with my bolds and added images.

I mostly stopped writing about climate change in 2018, when actual analysis lost all relevance to the increasingly unmoored claims of climate activists. The frequently cited estimates of catastrophic cost, I showed in published reports and congressional testimony, were simply nonsensical. One prominent model relied upon by the EPA predicted that heat deaths in northern cities in the year 2100 would be 50 times higher than they had been in southern cities in the year 2000, despite the northern cities never reaching the temperatures that the southern cities were already experiencing. Another study, published in Nature, predicted that warming would boost Mongolia’s GDP per capita to more than four times America’s. But no one cared; no one was held accountable.

When subsequent research flipped the claims on their head, no one even flinched. Here’s the New York Times, four years apart:

(Technically, the first chart is GDP loss, while the second is heat deaths. But as the Times explained, the main driver of GDP loss in that first chart is heat deaths: “The greatest economic impact would come from a projected increase in heat wave deaths as temperatures soared, which is why states like Alabama and Georgia would face higher risks while the cooler Northeast would not.”) [Note:  Observations actually show a “warming hole” in Southeast US, perhaps due in part to reforestation efforts.]

Discussion of solutions, meanwhile, became entirely performative. So many climate agreements were signed, none had the prospect of substantially shifting the trajectory of global emissions, which is driven overwhelmingly by growth in the developing world. The Biden administration spent four years trumpeting unprecedented investment in fighting climate change. Try to find a comment linking that action to a downward shift in future temperatures or a reduction in any of the purportedly existential harms repeated ad nauseum as the basis for the action. I’ll wait.

The climate lectures had become the equivalent of the parent telling his children to eat their vegetables, because children in Africa are starving.

So now I encounter climate change mostly in the context of discussions about how best to build a policy agenda that serves the interests of American workers, and the working class broadly. Along with the refusal to enforce immigration law and the passion for shoveling hundreds of billions of dollars into a higher education system that fails most young people, the obsession with fighting climate change is a quintessential tradeoff preferred by progressives that they are of course welcome to make, but that cannot be squared with a commitment to working-class interests.

Progressives tend not to appreciate this observation,
or the cognitive dissonance that it triggers.

As I wrote in The Once and Future Worker, “People know how they want society ordered and wish desperately for that same thing to be good for everyone else.” Our 20-year-old texter feels this strongly. Fighting the climate crisis and providing for working families are not mutually exclusive. But the belief in a mythological crisis goes forever unsubstantiated. What is the ongoing devastation of communities that Biden-style policy action will mitigate?

To be clear, when I say mythological crisis, I don’t mean that climate change is a myth. I think climate change is a very serious challenge with which the United States, and the world, must find ways to cope. I’d also like to see us pursuing aggressive public investment in next-generation nuclear technology, and in the industrial precursors to strong electric vehicle supply chains—both of which are smart industrial policy regardless of climate implications.

But in the broader scheme of a century of economic, technological,
and geopolitical changes and challenges, the gradual increase
in global temperatures does not rank high.

This is not my opinion, it is the conclusion of the climate models, the UN’s Intergovernmental Panel on Climate Change, and the analyses that attempt to translate these forecasts into economic impacts. Climate change is not one of the top challenges facing working families in America. Solving it, if we could, which we can’t, would do little to move the needle in helping them achieve middle-class security.

But what about the “Green New Deal”? It has “New Deal” right in the title, suggesting a clear commitment to improving economic opportunity! That’s true, as far as it goes. Indeed, we could launch a “Purple New Deal” dedicated to knocking down all buildings that are not purple and replacing them with purple ones, which would also have many jobs associated with it.  Unfortunately, that’s not good economic policy.

What the Green New Deal—and climate policy, generally—attempts to do is shut down the existing energy industry and much of the industrial economy that relies on cheap and reliable energy, and replace it all with new “green” jobs. This should not require saying, but apparently does: Supplanting an existing, robust energy sector and industrial economy that provides a lot of very good jobs outside of our knowledge economy and superstar cities, with a new set of industries that hopes to do the same, does not in fact deliver economic gains.

The stated goal of climate policy is to replace things we already have. Anything new it creates is an attempt to climb back out of a hole it has dug itself. And unfortunately, the new tends to be less good, economically speaking, than the old. That reality in the auto industry is what drove the UAW strike last year.

The best way to understand all this is with a simple hypothetical: Let’s say we didn’t have to worry about climate change. A neat little box sucked greenhouse gases out of the atmosphere for free; problem solved. Would anyone still propose the Green New Deal? No climate change to worry about, you need to propose an agenda to support working families, how high on the list is “spend trillions of dollars shutting down the industrial economy and attempting to replace it with a set of less efficient and unproven technologies in which the United States has a much weaker position”?

It’s nowhere on the list.
Because climate policy does not help the working class.

For whatever reason, the project of decarbonizing the economy captures the progressive mind like no other. Ezra Klein and Derek Thompson’s Abundanceopens with a paragraph about waking up in the year 2050 in a cool bedroom powered by clean energy sources—a bedroom no cooler than the one you would wake up in today. Their abundant future is, first and foremost, not a more abundant one at all—merely one whose energy system they have transformed. Discussing scarcities, they start with, “We say that we want to save the planet from climate change.” When they enthuse that “new technologies create new possibilities and allow us to solve once-impossible problems,” they are thinking first of greenhouse gas emissions. “We worry,” first, “over climate change.” And “this book is motivated in no small part by our belief that we need to decarbonize the global economy.”

In my podcast with Klein, I asked him whether combatting climate change might represent a tradeoff in his agenda, rather than item one for bringing abundance to America. “For most, certainly, liberals who think about this and have studied this,” he responded, “the decarbonization is just central to the idea of what it would mean for our descendants to live a flourishing life.” Pitched this way, it fits perfectly the ideological template of most neoliberal missteps of the past 30 years: a purported win-win that serves the priorities of highly educated, high-income elites, who then instruct everyone else that the same thing should be their priority too. Like globalization, and unrestricted immigration, and free college.

Fool me once… Climate policy imposes massive costs, and damages the industrial economy, in pursuit of a specific goal: reducing carbon dioxide emissions. And if that’s your goal, that’s fine. Fight for it! Make the case for the tradeoff. But don’t pretend there’s no tradeoff, and certainly don’t tell the people you’re trading off that you’re really doing it for them.

 

See Also 

Eco-Loons War on Productive Working Class

 

Sea Level Rise Hype from Climatists Lying by Omission Again

Posted on by Ron Clutz

From Inside Climate News comes this example, New Study Projects Climate-Driven Flooding for Thousands of New Jersey Homes.

Sea-level rise threatens coastal communities even if global emissions drop.

Of course the alarm is picked up everywhere:

As Summer Approaches, New Jersey’s Shore Towns Confront an Unrelenting Foe: Sea Level Rise Inside Climate News

US East Coast faces rising seas as crucial Atlantic current slows, New Scientist

Sea level rise creates a crisis at US coasts: What to know, USA Today

Map Shows US Cities Where Sea Level Rise Is Accelerating, Newsweek

Global sea levels are rising faster and faster. It spells catastrophe for coastal towns and cities, CNN

Etc., Etc., Etc.

Climatists Make Their Case by Omitting Facts

A previous post documented this pattern, of which we have this fresh example.  Let’s start with the tidal gauge at Atlantic City, New Jersey.

It presents a long record of steadily rising levels for more than a century.  The rate is 4.25 mm per year, or a rise of about 1 inch every six years.  The lie is in attributing all of that to sea level rising, and adding in burning of hydrocarbons as the cause.  What’s left out is the well known and documented subsidence of land along the US Eastern seaboard.

Vertical land motion (VLM) across the US Atlantic coast (a) Estimated VLM rate. The circles show the location of GNSS validation observations color-coded with their respective vertical velocities. (b) Histogram comparing GNSS vertical rates with estimated VLM rates. The standard deviation (SD) of the difference between the two datasets is 1.3 mm per year. (c) Land subsidence (representing negative VLM) across the US Atlantic Coast.

The black rectangles indicate the extent of study areas for Chesapeake Bay area and Georgia, South Carolina, and North Carolina (GA-SC-NC) area shown in Fig. 4. State Codes: ME Maine, NH New Hampshire, VT Vermont, MA Massachusetts, RI Rhode Island, NY New York, PA Pennsylvania, NJ New Jersey, WV West Virginia, OH Ohio, DE Delaware, VA Virginia, NC North Carolina, SC South Carolina, GA Georgia, and FL Florida. National, state, and great lakes boundaries in a, c are based on public domain vector data by World DataBank (https://data.worldbank.org/) generated in MATLAB.

Abstract from paper Hidden vulnerability of US Atlantic coast to sea-level rise due to vertical land motion

The vulnerability of coastal environments to sea-level rise varies spatially, particularly due to local land subsidence. However, high-resolution observations and models of coastal subsidence are scarce, hindering an accurate vulnerability assessment. We use satellite data from 2007 to 2020 to create high-resolution map of subsidence rate at mm-level accuracy for different land covers along the ~3,500 km long US Atlantic coast. Here, we show that subsidence rate exceeding 3 mm per year affects most coastal areas, including wetlands, forests, agricultural areas, and developed regions. Coastal marshes represent the dominant land cover type along the US Atlantic coast and are particularly vulnerable to subsidence. We estimate that 58 to 100% of coastal marshes are losing elevation relative to sea level and show that previous studies substantially underestimate marsh vulnerability by not fully accounting for subsidence.

A further reference to causes of land subsidence:

Land subsidence, in particular, deserves special attention because it can significantly magnify the relative sea-level rise (RSLR) to several times beyond the global average sea-level rise, which usually amounts to just a few mm/yr on its own (Shirzaei et al. 2021). Land subsidence results from various factors encompassing both natural processes and human activities that operate at local or regional scales (Ohenhen et al., 2023). Globally, groundwater extraction is the primary cause of land subsidence (Coplin and Galloway, 1999;Shastri et al., 2023).

Finally, we can observe that the Atlantic City sea level rise of 4.25 mm per year measured at the gauge is close to the subsidence rate shown in the right hand panel.  So yes, authorities in that area need to address the problem with hydro engineering and zoning laws.  But no, reducing CO2 emissions is not the solution.

See Also:

Observed vs. Imagined Sea Levels 2023 Update

Media’s at Fault for Liberals’ Climate Anxiety

Posted on by Ron Clutz

 

Linnea Lueken explains in her Climate Realism article Liberals May Be Suffering from Climate Anxiety, but if So, It’s The Media’s Fault. Excerpts in italics with my bolds and added images.

A recent article at the Washington Free Beacon, titled “Great News for Humanity: Depressed Liberals Are Increasingly Suicidal Due to ‘Climate Anxiety,’ Study Finds,” takes a humorous approach (black humor, to be sure) to discussing a study that found liberals are increasingly suffering from climate anxiety and depression, leading the climate-anxious to refrain from having children and even contemplating and, in some cases, committing suicide. The article makes light of it, but it is a widely reported trend. Since climate change does not threaten human existence or flourishing, and extreme weather is not worsening, their fears and anxiety are unjustified by the actual state of the climate. Unfortunately, climate alarm has been foisted upon people, especially on children and mentally unwell adults, despite evidence indicating climate change is not anything to be alarmed about.

The Washington Free Beacon reports:

“Negative psychological responses related to the observed and anticipated impacts of climate change, such as climate anxiety, eco-anxiety and climate-related guilt have … emerged as a potential risk factor for poor mental health and suicide-related behaviors,” the authors wrote last month in Nature Medicine. “International surveys show that concern about climate change is associated with feelings of despair, hopelessness, anger, frustration and guilt, especially among younger populations.”

The findings of this study, published in Nature, are not unique. Other research has come to similar conclusions: a study conducted by Save the Children found that 70 percent of kids they surveyed struggle with what they dubbed “climate anxiety,” as discussed in this Climate Realism post. Other surveys show similarly sad results.

Each time these results are presented, the media and the researchers involved frame the story as climate change and its impacts are causing fear and anxiety, and the lack of action is causing deep feelings of hopelessness and despair for people worried about climate change. Yet it is the false tales that the media, politicians, and green interest groups are telling about climate change motivating anxiety and mental distress, not the actual conditions of the planet.

For instance, in the media coverage of the Save the Children survey, the UK website Future Net Zero implies that without immediate societal scale action, the present generation of children “stand to inherit a deeply unequal world,” and that their terror is “warranted.”

Likewise, articles from The Hill and The Conversation discussing a study attributing adult PTSD to climate change assert that climate change is impacting people through increased wildfires and other disasters. This is false, the framing of their research is built on falsehoods.

Climate change is not causing worsening weather disasters. Data show that not only are events like wildfires not increasing, but the number of all climate-related deaths are declining because of improvements to infrastructure, healthcare, technology, and yes, better climatic conditions. (See figure below)

The real reason so many impressionable people are depressed and anxious about climate change is because the media and governments relentlessly push and promote false and alarming misinformation and fake news about extreme weather and climate change. It is no wonder that children are afraid, when their teachers are telling them that the world will end in short order unless dramatic global reforms are made. When people don’t see the supposedly climate saving reforms being made, they are left hopeless and despondent. But it is an unnecessary misery – there has never been a safer time period for humans to live in.

The Washington Free Beacon made light of the situation, but it is no laughing matter. Children in particular are being traumatized by adults in their lives over the climate issue. Climate change is not harming mental health, but climate alarmism, built on falsehoods, hysteria, and hyperbole, certainly is.

Can You Trust an AI/ML Model to Forecast?

Posted on by Ron Clutz

The latest fashion in model building is adding AI/ML (Artificial Intelligence/Machine Learning) technology to numerical models for weather forecasting.  No doubt soon there will be climate models also claiming improved capability by doing this.  A meteorological example is called Aardvark Weather and a summary is provided at Tallbloke’s Talkshop Scientists say fully AI-driven weather prediction system delivers accurate forecasts faster with less computing power.

Like all inventions there are weaknesses along with the claimed benefits.  Here’s a short list of the things that can go wrong with these new gadgets. The concerns below are listed along with some others in a paper Understanding the Weaknesses of Machine Learning: Challenges and Limitations by Oyo Jude. Excerpts in italics with my bolds.

Introduction

Machine learning (ML) has become a cornerstone of modern technological advancements, driving innovations in areas such as healthcare, finance, and autonomous systems. Despite its transformative potential, ML is not without its flaws. Understanding these weaknesses is crucial for developing more robust and reliable systems. This article delves into the various challenges and limitations faced by ML technologies, providing insights into areas where improvements are needed

Data Quality and Bias

Data Dependency

Machine learning models are highly dependent on the quality and quantity of data used for training. The performance of an ML model is only as good as the data it is trained on. Common issues related to data quality include:

Incomplete Data: Missing or incomplete data can lead to inaccurate models and predictions. Incomplete datasets may not represent the full spectrum of possible inputs, leading to biased or skewed outcomes.
Noisy Data: Noise in data refers to irrelevant or random information that can obscure the underlying patterns the model is supposed to learn. Noisy data can reduce the accuracy of ML models and complicate the learning process.

Data Bias

Bias in data can significantly impact the fairness and accuracy of ML systems. Key forms of data bias include:

Selection Bias: Occurs when the data collected is not representative of the target population. For example, if a model is trained on data from a specific demographic group, it may not perform well for individuals outside that group.
Label Bias: Arises when the labels or categories used in supervised learning are subjective or inconsistent. Label bias can skew the model’s understanding and lead to erroneous predictions.

Model Interpretability and Transparency

Complexity of Models

Many advanced ML models, such as deep neural networks, are often described as “black boxes” due to their complexity. The lack of transparency in these models presents several challenges:

Understanding Model Decisions: It can be difficult to understand how a model arrived at a specific decision or prediction, making it challenging to diagnose errors or biases in the system.
Trust and Accountability: The inability to interpret model decisions can undermine trust in ML systems, particularly in high-stakes applications such as healthcare or criminal justice. Ensuring accountability and fairness becomes challenging when the decision-making process is opaque.
Explainability:  Efforts to improve model interpretability focus on developing techniques and tools to make complex models more understandable. Techniques such as feature importance analysis, surrogate models, and visualization tools aim to provide insights into model behavior and decisions. However, achieving a balance between model performance and interpretability remains an ongoing challenge.

Generalization and Overfitting

Overfitting

Overfitting occurs when a model learns not only the underlying patterns in the training data but also the noise, resulting in poor performance on new, unseen data. This issue can be particularly problematic with complex models and limited data. Strategies to mitigate overfitting include:

Cross-Validation: Using techniques like k-fold cross-validation helps assess model performance on different subsets of the data, reducing the risk of overfitting.
Regularization: Regularization methods, such as L1 and L2 regularization, add penalties to the model’s complexity to prevent it from fitting noise in the training data.

Generalization

Generalization refers to a model’s ability to perform well on unseen data that was not part of the training set. Achieving good generalization is crucial for the practical application of ML models. Challenges related to generalization include:

Domain Shift: When the distribution of the data changes over time or across different domains, a model trained on one dataset may not generalize well to new data. Addressing domain shift requires continuous monitoring and updating of models.
Data Scarcity: In scenarios where limited data is available, models may struggle to generalize effectively. Techniques such as data augmentation and transfer learning can help address data scarcity issues.

Comment:

Many similar issues have been raised against climate models, undermining claims their outputs are valid projections of future climate states.  For example, the issue of detailed and reliable data persists.  It appears that even the AI/ML weather forecasting inventions are dependent on ERA5, which has a record of only ~40 years to use for training purposes.  I’m suspending belief in these things for now–new improved black boxes sound too much like the Sorcerer’s Apprentice.

Disney’s portrayal of the Sorcerer’s Apprentice in over his head.

It Must Be Climate Change

Posted on by Ron Clutz

Prager U video can be seen at this link: https://www.prageru.com/video/it-must-be-climate-change

Transcript is below in italics with my bolds and some added images.

Have you noticed that every extreme weather event is blamed on climate change formerly known as global warming?

Every. . . Single. . .One. 

Can you think of an exception?

Too hot — climate change.    Too cold – climate change. 

Previously, cold spells were termed “Weather” in contrast to “Global Warming.” Now it’s all “Climate Change.”

Drought – climate change.   Too much rainfall – climate change. 

And there’s always a climate scientist at some university who’s willing to make a statement blaming the current catastrophe on our profligate use of fossil fuel. 

Some years ago, on The Late Show with David Letterman, MSNBC host Rachel Maddow made the definitive statement on this issue. She said, “I think global warming probably means extreme weather events of all kinds.” Naturally, Dave agreed.

What’s behind all these confident assertions? 

As a PhD in geochemistry, former member of the University of Alabama Department of Geological Sciences and someone who has written and lectured widely on the subject of climate and geology, I can tell you that it comes down to two things: 

Obscure metrics and highly speculative models.

Mix these ingredients together and voila! You can get any result you want. The scarier, of course, the better. “Torrential rain” makes a much better headline than “heavy rain.” 

To show you how this works, let’s look at a recent example. 

Here’s the assertion:   Climate change is making air turbulence more volatile and thus air travel more dangerous. 

Scary, right?   But is it true?  No. Not if we look at the observable data; that is, hard data we can easily verify. 

Here’s a chart of the number of turbulence-related accidents in the US from 1989 to 2018. 

Despite the rise in annual US airline passengers from about 400 million in 1989 to nearly one billion by 2018, turbulence-related accidents have remained constant. If climate change were indeed making turbulence significantly worse, we would expect to see a corresponding increase in these accidents.

Yet, the data does not support this assertion. Instead, it suggests that the relationship between turbulence and climate change is either negligible or nonexistent.

In fact, the co-author of the original study cited in a BBC article admitted as much.

“When we add [data back to 2002] to the previous results, the statistical significance assigned to the…North Atlantic winter jet stream…disappears.”

This was conveniently left out of the BBC article.

This disconnect between obscure metrics and highly speculative models, and observable data is not limited to turbulence. 

The broader climate crisis narrative is built on similar shaky foundations. 

Let’s look at three more examples. 

No Increase in Extreme Weather: The number of hydrological, meteorological, and climatological disasters has remained relatively flat since 2000. If climate change were causing more extreme weather events, we would expect to see a clear increase in these numbers. Instead, the data, again, reflects no such increase.

No Increase in Loss of Life: Deaths from meteorological, hydrological, and climatological disasters have not increased. This is a critical metric because it directly reflects the human impact of these events. Despite frequent claims that climate change is making weather more deadly, the data does not bear this out.

No Increase in Costs: Global weather losses as a percent of global GDP have not risen significantly. This is another crucial metric because it accounts for the economic impact of climate-related disasters. If climate change were truly making these events more severe, we would expect to see a rising trend in economic losses relative to global GDP.

We are left with this conclusion:

The reliance on obscure metrics and highly speculative models
to support the climate crisis narrative often serves
to cloud the truth rather than illuminate it. 

By focusing on projections and models rather than observable data, environmental activists, climate scientists, attention-seeking politicians and click bait media make claims that are difficult to verify and easy to manipulate. 

The fear that fuels the “climate crisis” is simply not justified by the data. That’s why — over and over again — end-of-the-world predictions don’t pan out. 

This does not mean that we should ignore environmental issues. We live on the same planet. We all want clean air and water. 

However, it does mean that we should approach claims of climate catastrophe with a healthy dose of skepticism and demand that assertions be backed up by observable, measurable data. Given that politicians and government agencies are spending tens of billions of our tax dollars every year to “save the planet” that would seem to be the least they could do: give us some hard facts, rather than unproven assertions. 

And the hard facts are, turbulence-related accidents have not increased despite a massive rise in airline passengers. Extreme weather events, loss of life, and economic costs have not shown the dramatic increases that alarmists would have us believe. 

By focusing on observable data we can have a more grounded, rational discussion about our environmental challenges and how best to address them.

That’s the way to practical, real-world solutions.  The blame game — “it’s climate change” — gets us nowhere. 

I’m Matthew Wielicki for Prager University.

No, Grist, MSN, et al: CO2 Is Not Making Oceans Boil

Posted on by Ron Clutz

 

The Climate Crisis media network is announcing a new claim that rising CO2 is causing recent ocean warming, proving it’s dangerous and must be curtailed.  Examples in the last few days include these:

Finally, an answer to why Earth’s oceans have been on a record hot streak Grist

Ocean warming 4 times faster than in 1980s — and likely to accelerate in coming decades MSN

News spotlight: Fossil fuels behind extreme ocean temperatures, study says. Conservation International

Ocean temperature rise accelerating as greenhouse gas levels keep rising UK Natural History Museum

The surface of our oceans is now warming four times faster than it was in the late 1980s The Independent UK

Oceans Are Warming Four Times Faster as Earth Traps More Energy Bloomberg Law News

All this hype deriving from one study,
and ignoring the facts falsifying that narrative.

Fact:  Historically, ocean natural oscillations drive observed global warming.

The long record of previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1997-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles.

Fact: Recent rise in SST was driven by ENSO and N. Atlantic Anomalies.

And now in 2024 we have seen an amazing episode with a temperature spike driven by ocean warming in all regions, along with rising NH land temperatures, now dropping below its peak.

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through December 2024.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016, followed by rising temperatures in 2023 and 2024.

To enlarge, open image in new tab.

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  A small warming was driven by NH summer peaks in 2021-22, but offset by cooling in SH and the tropics, By January 2023 the global anomaly was again below the mean.

Now in 2023-24 came an event resembling 2015-16 with a Tropical spike and two NH spikes alongside, all higher than 2015-16. There was also a coinciding rise in SH, and the Global anomaly was pulled up to 1.1°C last year, ~0.3° higher than the 2015 peak.  Then NH started down autumn 2023, followed by Tropics and SH descending 2024 to the present. After 10 months of cooling in SH and the Tropics, the Global anomaly came back down, led by NH cooling the last 4 months from its peak in August. It’s now about 0.1C higher than the average for this period. Note that the Tropical anomaly has cooled from 1.29C in 2024/01 to 0.66C as of 2024/12.

Fact: Empirical measurements show ocean warms the air, not the other way around.

One can read convoluted explanations about how rising CO2 in the atmosphere can cause land surface heating which is then transported over the ocean and causes higher SST. But the interface between ocean and air is well described and measured. Not surprisingly it is the warmer ocean water sending heat into the atmosphere, and not the other way around.

The graph displays measures of heat flux in the sub-tropics during a 21-day period in November. Shortwave solar energy shown above in green labeled radiative is stored in the upper 200 meters of the ocean. The upper panel shows the rise in SST (Sea Surface Temperature) due to net incoming energy. The yellow shows latent heat cooling the ocean, (lowering SST) and transferring heat upward, driving convection. [From An Investigation of Turbulent Heat Exchange in the Subtropics by James B. Edson]

As we see in the graphs ocean circulations change sea surface temperatures which then cause global land and sea temperatures to change. Thus, oceans make climate by making temperature changes.

Fact: On all time scales, from last month’s observations to ice core datasets spanning millennia, temperature changes first and CO2 changes follow.

Previously I have demonstrated that changes in atmospheric CO2 levels follow changes in Global Mean Temperatures (GMT) as shown by satellite measurements from University of Alabama at Huntsville (UAH). That background post is included in the posting referenced later below.

My curiosity was piqued by the remarkable GMT spike starting in January 2023 and rising to a peak in April 2024, and then declining afterward.  I also became aware that UAH has recalibrated their dataset due to a satellite drift that can no longer be corrected. The values since 2020 have shifted slightly in version 6.1, as shown in my recent report  Ocean Leads Cooling UAH December 2024.

I tested the premise that temperature changes are predictive of changes in atmospheric CO2 concentrations.  The chart above shows the two monthly datasets: CO2 levels in blue reported at Mauna Loa, and Global temperature anomalies in purple reported by UAHv6.1, both through December 2024. Would such a sharp increase in temperature be reflected in rising CO2 levels, according to the successful mathematical forecasting model? Would CO2 levels decline as temperatures dropped following the peak?

The answer is yes: that temperature spike resulted
in a corresponding CO2 spike as expected.
And lower CO2 levels followed the temperature decline.

Above are UAH temperature anomalies compared to CO2 monthly changes year over year.

Changes in monthly CO2 synchronize with temperature fluctuations, which for UAH are anomalies now referenced to the 1991-2020 period. CO2 differentials are calculated for the present month by subtracting the value for the same month in the previous year (for example December 2024 minus December 2023).  Temp anomalies are calculated by comparing the present month with the baseline month. Note the recent CO2 upward spike and drop following the temperature spike and drop.

Summary

Changes in CO2 follow changes in global temperatures on all time scales, from last month’s observations to ice core datasets spanning millennia. Since CO2 is the lagging variable, it cannot logically be the cause of temperature, the leading variable. It is folly to imagine that by reducing human emissions of CO2, we can change global temperatures, which are obviously driven by other factors.

12/2024 Update–As Temperature Changes, CO2 Follows

 

 

 

 

 

 

Devious Climate Attribution Studies

Posted on by Ron Clutz

Patrick Brown raises the question Do Climate Attribution Studies Tell the Full Story? Excerpts in italics with my bolds and added images, his analysis concluding thusly:

How a cascade of selection effects bias
the collective output of extreme event attribution studies.

Weather and climate extremes—such as high temperatures, floods, droughts, tropical cyclones, extratropical cyclones, and severe thunderstorms—have always threatened both human and natural systems. Given their significant impacts, there is considerable interest in how human-caused climate change influences these extremes. This is the focus of the relatively new discipline of Extreme Event Attribution (EEA).

Over the past couple of decades, there has been an explosion in EEA studies focusing on (or, “triggered by”) some prior notable weather or climate extreme. Non-peer-reviewed reports from World Weather Attribution (e.g., here, here, and here) represent some of the most notable examples of these kinds of analyses, and many similar studies also populate the peer-reviewed literature. The Bulletin of the American Meteorological Society’s “Explaining Extreme Events From a Climate Perspective” annual series compiles such studies, as does the Sabin Center for Climate Change Law, and they are also synthesized in reports like those from the IPCC (IPCC WG1 AR6 Chapter 11.2.3) and the United States National Climate Assessment.

The collective output of these kinds of studies certainly gives the impression that human-caused climate change is drastically changing the frequency and intensity of all kinds of weather extremes. Indeed, Carbon Brief recently published an extensive summary of the science of EEA studies, which begins with the proclamation, “As global temperatures rise, extreme weather events are becoming more intense and more frequent all around the world.”

However, these numbers cannot be taken as an accurate quantification of the influence of climate change on extreme weather because they are heavily influenced by a cascade of selection biases originating from the physical climate system, as well as researcher and media incentives. Identifying and understanding these biases is a prerequisite for properly interpreting the collective output of EEA studies and, thus, what implications they hold for general scientific understanding, as well as political and legal questions.

The large apparent discrepancy between the size of the influence of human-caused climate change on extreme weather reported in EEA studies (like those compiled by Carbon Brief) compared to more comprehensive systematic analyses (like those compiled by the IPCC) can, in large part, be attributed to the many layers of Selection Biases that influence the EEA literature’s collective output.

Selection Bias is a broad term that refers to any bias that arises from a process that selects data for analysis in a way that fails to ensure that data is representative of the broader population that the study wishes to describe.

Selection biases in the context of EEA studies include those associated with the physical climate system itself, those concerning proclivities and incentives facing researchers/journals, and those concerning the proclivities and incentives facing the media. They include

Occurrence Bias is a bias introduced by the physical climate system. Since EEA studies tend to be triggered by extreme events that have actually occurred, there is reason to believe that these studies will disproportionately sample events that are more likely than average to be exacerbated by climate change because the events occurred in the first place. Essentially, extreme events that are more likely to occur under climate change—and thus more likely to be observed—are going to be overrepresented in EEA studies, and extreme events that are less likely to occur under climate change—and thus less likely to be observed—are going to be underrepresented in EEA studies.

The map below illustrates this phenomenon. It shows changes in the magnitude of extreme drought under climate change. Specifically, it shows the fractional change in the intensity of once-per-50-year droughts (as quantified by monthly soil moisture) between a preindustrial and 21st-century run (SSP2-4.5 emissions) of the highly-regarded NCAR CESM2 Climate Model. Blue areas represent locations where the model simulates that extreme droughts become less frequent and intense with enhanced greenhouse gas concentrations, and red areas represent locations where the model simulates that extreme droughts become more frequent and intense with enhanced greenhouse gas concentrations. It is notable that overall, this model simulates that warming decreases the frequency and intensity of extreme drought in more locations than it increases it (consistent with soil moistening under warming simulated by other models).

Now, here’s the kicker: The black dots show locations where once-per-50-year droughts actually occurred in the 21st-century simulation and thus represent events that would plausibly trigger EEA studies.

What do you notice about where the dots are compared to where the red is? That’s right; the simulated EEA studies overwhelmingly sample areas where droughts are getting more intense and more frequent by the very nature that those are the types of droughts that are more likely to occur in the warming climate. The result is that the EEA sample is majorly biased: warming decreased the intensity of once-per-50-year droughts by about 1% overall, but it increased their intensity within the EEA sample by 18%!

Thus, if you just relied on the EEA sample, you would come away with an
incorrect impression not only on the magnitude of change in extreme droughts
but also on the sign of the direction of change!

Choice Bias arises when researchers use prior knowledge to choose events for EEA studies that are more likely to have been made more severe by climate change. A clear example of Choice Bias pervading the Carbon Brief database is there have been 3.6 times more studies on extreme heat than there have been on extreme winter weather (205 vs. 57). Another example would be the dearth of EEA studies on extratropical cyclones (the kinds of low-pressure systems with cold and warm fronts that are responsible for most of the dramatic weather outside of the tropics). The IPCC states that the number of extratropical cyclones associated with intense surface wind speeds is expected to decrease strongly in the Northern Hemisphere with warming. Yet, it is relatively rare for EEA attribution studies to be done on these types of systems, which results in an exclusion of this good news from the EEA literature.

Publication Bias could be playing a role, too, where researchers are more likely to submit, and journals are likely to publish studies that report significant effects on salient events compared to studies that find null effects.

From Clark et al., 2023

Finally, the climate reporting media ecosystem is characterized by actors whose explicit mission is to raise awareness of the negative impacts of climate change, and thus, there will be a natural Media Coverage Bias with a tendency to selectively highlight EEA studies where climate change is found to be a larger driver than EEA studies that do not reach such a conclusion. These selection biases are apparent at the aggregate level, but there is also strong evidence of their presence in individual studies.

A more recent specific example suggestive of many of these dynamics is a study, Gilford et al. (2024), titled “Human-caused ocean warming has intensified recent hurricanes”. This study was conducted by three researchers at Climate Central, which summarizes the study’s findings with the following infographic:

From Climate Central press release on Gilford et al. (2024).

Essentially, they claim that climate change is enhancing the intensity of all hurricanes and that the enhancement is quite large: Storms today are calculated to be an entire Category stronger than they would have been in a preindustrial climate.

This is a huge effect, and thus, if it were real, it is reasonable to expect to see clear long-term trends in metrics of tropical cyclone (hurricane) intensity like the accumulated number of major (Category 3+) hurricane days or the accumulated cyclone energy from all tropical cyclones (which is proportional to the square of hurricane windspeed accumulated over their lifetimes). However, any long-term trends in such metrics are subtle at best, both globally and over the North Atlantic.

From Colorado State University Department of Atmospheric Science Tropical Meteorology Project.

So, this is a microcosm of the aforementioned apparent discrepancy between more broad quantifications of changes in extremes and their associated EEA counterparts, and again, I’d argue there are several selection biases at play affecting the production and dissemination of the EEA study.

Let’s start with Choice Bias on methodology. Human-caused warming changes the environment in some ways that work to enhance hurricanes and in other ways that diminish them. The main way that hurricanes are enhanced is via the increase in sea surface temperatures (which provides the fundamental fuel for hurricanes), and the main way that hurricanes are diminished is via changes in atmospheric wind shear and humidity.

The net result of these countervailing factors pulling in opposite directions is that we expect fewer hurricanes overall, but when hurricanes are able to form, they can be stronger than they would otherwise. These factors, though, are small relative to natural random variability, and thus, they are difficult to detect in observations.

However, the Climate Central researchers made the methodological choice
to largely exclude the influence of factors that diminish
hurricane development from the study.

Are these Choice Biases in event type and methodology an accident? There are many reasons to believe they are not.

The research paper itself spells out that the motivation of the study is to “connect the dots” between climate change and hurricanes because “landfalling hurricanes with high intensities—can act as ‘focusing events’ that draw public attention” and that “Increased attention during and in wake of storms creates opportunities for public and private discourse around climate and disaster preparedness.”

Then, there is the extensive media coverage of this study. It was picked up by 134 news outlets and ranked in the 99.95th percentile of research articles (across all journals) of similar age in terms of online attention. Further, it was immediately incorporated into seven Wikipedia articles (likely having high leverage on AI queries, which would make its findings indistinguishable from scientific “fact”). This is affected by the aforementioned Media Coverage Bias, but it is also undoubtedly directly influenced by the efforts of Climate Central, which is explicitly an advocacy organization whose self-described specialty is media placement and dissemination. 

The above sheds light on the reasons for certain choice biases in a particular study, but there is plenty of evidence that these selection biases are pervasive in the EEA field. After all, Dr. Myles Allen essentially founded the field with the motivation of answering the question, “Will it ever be possible to sue anyone for damaging the climate?”. This same motivation seems to animate many of the most high-profile scientists in the field today, like Allen’s protege, Dr. Friederike Otto (co-founder and leader of World Weather Attribution). She and her organization are frequently cited as bringing the necessary intellectual authority to credibly sue fossil fuel companies. She states the motivation of her work explicitly:

“Attributing extreme weather events to climate change, as I do
through my work as a climatologist, means we can hold
countries and companies to account for their inaction.”

Given the explicitly stated motivation of those in the EEA field, it is quite reasonable to suppose that there are major selection biases at play, and thus, it is not at all surprising that the collective output of the EEA field would look so different from more broad comprehensive assessments.