The Tribune News Service article, “AI is fast-tracking climate research,” is misleading in its central premise. While AI can speed up certain weather data processing tasks, it does not magically make long-term climate forecasts more accurate. The piece blurs the line between short-term weather model gains and the far more uncertain, decades-scale climate projections — a fundamental error that misleads both policymakers and the public.
The article quotes AZTI marine biologist Ángel Borja saying, “It will allow us to process data and get results much faster, so people that make decisions can act faster, too”. This might be true for fisheries management or local ocean data sets, but when applied to climate, speed does not equal accuracy. Acting “faster” on flawed or incomplete climate projections risks enshrining bad policy based on noise or computer model errors, not signal.
Here is a breakdown of each of the claims in the article.
Claim: “Some AI-powered models are already outperforming conventional forecasting systems.”
Yes — but that’s in weather forecasting, which operates on hours-to-weeks timescales. Even Microsoft’s Aurora and Google DeepMind’s GraphCast, cited in the story, focus on short-term atmospheric prediction. This has almost nothing to do with the 30-year climate averages that define climate science. See Climate at a Glance: Climate Model Fallibility.
Claim: “AI models… can enable climate scientists to explore hundreds of times more scenarios than they can today.”
Quantity isn’t quality. Exploring “hundreds” of flawed scenarios faster doesn’t fix the fact that climate models — AI or not — still have massive uncertainty ranges. Observations show CMIP6 climate models overstate warming trends by nearly double actual measurements as told in Climate Models vs. Measured Data. If your inputs and physics are wrong, multiplying the number of runs just multiplies the wrongness.
Claim: “High-quality weather information is the first step to setting warning systems.”
True — but irrelevant to climate accuracy. Weather quality doesn’t fix deep uncertainties in equilibrium climate sensitivity (ECS), which still ranges from 0.8°C to almost 6°C by 2100. Nor does it solve the known ±4 Watts per square meter radiative cloud forcing error — more than 4,000 times the estimated signal from a year’s worth of CO₂ emissions according to the Hoover Institution.
Claim: “AI is set to turbocharge what the center can offer policymakers… allowing them to make more-informed decisions.”
This is the most dangerous overreach. Climate is by definition a 30-year statistical average. The World Meteorological Organization (WMO) defines climate as “…the average weather conditions for a particular location and over a long period of time. “Fast-tracking” such projections is meaningless — the data horizon can’t be shortened without destroying the definition of climate itself. Worse, rushing policy on the back of still-uncertain models risks trillion-dollar mistakes.
Tribune News Service: please stop confusing flash with substance. AI is not a magical oracle of climate truth — it’s a faster, sometimes cheaper way to crunch the same flawed models that have consistently overshot observed warming. Until climate models can reconcile with reality, narrow their error bars, resolve cloud physics, and stop producing 200% exaggerations of observed warming, your framing of AI as a “climate game-changer” is not journalism — it’s marketing copy. And marketing copy dressed as science is worse than ignorance; it’s an invitation to policy disaster.
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The wrong answers, but faster?
And more expensive too!
And creating lots of CO2 while generating the electricity to run the AI data center.
To mis-quote Coleridge: “Logic, logic everywhere, But AI cannot think!”
No it is not!
The 30 year period was pulled randomly from someone’s fundament. It needs to be replaced, immediately, quickly, and forcefully!
The climate appears to display a clear 60 year cycle, among most likely several others. Taking 30 years is like starting at midnight, and based on the temperature at midday, predicting that we’ll all be boiling by tomorrow.
Stop accepting their lies!
Yes! It is! And yet you accept their marketing copy as ‘science’ and say it is a ‘definition’!
How can you be so right, and so wrong at the same time? Please stop!
And yet, here you are, doing exactly that. Sheesh!
Don’t get me wrong, I have great respect for Anthony and all those who post here, and I’ve been around here since before Climategate. But this is impossible for me to overlook. And from a meteorologist too, it is very difficult to accept.
“They” hijacked, redefined, and abused the Micro Climate definition, which is 30 years but for a region or locale with the intent of provide a sense of what kind of weather would be experience should someone relocate to that area.
Why? Advent of satellite sensors did not go back prior to the first such in the early 70s. This way they could justify climate alarmism based on a very short span of satellite data.
Exactly. Just because the catastrophists bent it out of shape does not mean they get to claim it.
thats a Strawman argument you are using. Nowhere did this article talk about 30 year cycles – thats your statement not Mt Watts’s. He quite clearly stated at least twice, that a thirty year statistical average is needed, that is before a climate trend can reasonably be deduced. From that minimum a progression can be more accurately defined – whether this is a 10 year cycle, 60 year, 100 year or any other time span.
I note also that you do not propose an alternative and state your reasons
Agreeing and adding… there is little data in climatology I would trust to argue for a cycle longer than seasonality. 100-year? What data is being used for 1825?
What about the Milankovitch cycles, some 100K to 130K years in duration. How do those fit into the definition of climate?
“What data is being used for 1825?”
An excellent question. The answer definitely does not include global data.
Quoting from the article:
“This has almost nothing to do with the 30-year climate averages that define climate science.”
Furthermore I was responding to Zig Zag Wanderer who broached it with a direct quote from the article.
So your “Strawman” accusation is unfounded.
Furthermore, I agree with Mr. Watts on all points.
30 years is much too short to determine the entire collection of natural cycles.
Nyquist sampling of a wave form requires sampling across the entire period of the waveform. Your 60 year time span requires 60 years in the sampling, likewise 100 year time span or any other time span would require sampling the entire wave form. In general, to reconstruct a wave form with reasonable (not perfect) accuracy, the sampling rate needs to be 10x the frequency of the highest frequency component, or greater.
+10 for bringing in the Nyquist criteria. That is science.
If I recall correctly, the 30 year period was postulated in order to short circuit questions about the pause occurring while CO2 was still increasing. And, it was basically the period of time to determine the sign, +, -, or none.
So that is more than 50 years worth of satellite data.
A clear 60 year cycle? Sounds like you have your own rigid definitions. Somehow I doubt Mama Nature follows your 60 year cycles any more than the traditional 30 year definition.
The 30 year definition is like 12 inches per foot, a handy way to provide a clear uniform description for guide books, Wikipedia pages, and people looking to move. No one has ever claimed it is natural or that weather follows 30 year patterns.
Get off your high horse.
Is what I said. I’ve seen it, and I stand by that, or indeed sit on my horse, high or not.
Appears. Words have meanings. I wasn’t trying to make a new definition, just decrying a false assertion. If this is riding a high horse, then the entire sceptic movement is doing just that.
Ride what you will.
You state:
And yet this post states:
Which appears (that word again) to disprove your assertion. Even if not, it is almost always used to claim that ‘weather’ is ‘changing’ in some way.
60-year cycle?
2025
2025 -60 = 1965 …maybe data for some things
1965- 60 = 1905 …news stories
“Major 1905 weather events included the deadly Snyder, Oklahoma tornado on May 10, the devastating “Great Equalizer” spring blizzard in western South Dakota on May 3–4 that killed thousands of livestock, the massive Ohio River flood in June that submerged cities like Louisville, the destructive Mataafa Storm on the Great Lakes in November, and widespread damage from ice storms and snowstorms in the Southeast in February. ”
1905 – 60 = 1845 … Nah I don’t think there’s enough to go on.
The approximately sixty year climate cycle is caused by the deflection of cosmic rays by Jupiter’s magnetic field, and the impact of that on Earth’s cloud cover caused by the relative positions of the two planets over that timescale.
“Approximately”? But he said it was clear!
It’s clear, but it’s not exact.
Words. They have meanings!
Eh? “Jupiter’s orbital period, or the time it takes to orbit the Sun, is approximately 11.86 Earth years” I believe the orbital period quoted here from google is observable and can be approximated with Newtonian physics equations. The impact of cosmic rays on Earth’s cloud cover? Lots of assumptions there. Same going back in multiples of 60 years to look for a pattern? NFW
Orbital harmonics and orbital mechanics. Part of it is none of the orbits are perfectly circular and some of the orbits are inclined relative to the plane of the solar system.
And yes, there is scientific evidence that cosmic rays CONTRIBUTE to cloud formation, one of several known mechanisms.
It has to do with the eccentricity of Jupiter’s orbit, relative to the eccentricity of Earth’s orbit.
Harold The Organic Chemist Says:
ATTN: ZZW
RE: 60 Year Climate Cycle
You should check out:
“An oscillation in the global climate system of period 65-70 years” by Michael E. Schliesinger & Navin Ramankutty
Nature Vol 367 24 September 1994 pp 723-726
Using “singular spectrum analysis”, they analyzed surface temperature records of 11 geographical regions and found a 65-70 year “oscillation”. They also analyzed four global-mean temperature records and found a 65-70 year “oscillation”.
They did not explain why they choose to use the term “oscillation” instead of “cycle”
There is some evidence for a cycle of around 60-80 years in length in the Icelandic sea ice record. (See red dots for troughs in the cycle)
Amplifying your comment… Nyquist sampling must be applied. One cannot recreate the baseline signal unless sampling is greater than 2X the baseline frequency and covers the entire duration of the waveform.
What the climate models appear to do is sample a sine wave from 270 degrees to 310 degrees and slope project backwards and forwards. Not a valid approach.
Nyquist is only part of the problem. With multiple oscillations one must have enough data to begin to separate out the individual frequencies. There are not enough variables being measured to start the process. How do I know this? Most projections and predictions are based on linear regressions of temperature data. Ever wonder why you never see CO2 as the independent variable and temperature as the dependent variable? It would show that there is not a simple functional relationship between the two. Consequently, CO2 used as the driver of temperature disappears.
If one is so inclined to identify specific frequencies in a complex waveform, I believe it is Fourier transformation mathematics that is used.
I only used Nyquist as the means to sample and reconstruct the whole waveform and noted the sampling needed to be 2x (or greater) than the highest frequency in the waveform.
That clarification aside, I agree.
I always found it curious that an energy system was defined as:
CO2 = input
IR = transfer function
Temperature = output
Very curious indeed.
From the very beginning of the climate change scam the actual meaning of the term “climate” was completely ignored and replaced with a single numerical measure – the poorly defined and virtually meaningless “average annual global surface temperature”. Actual “climate” had long before been well described by Wladimir Köppen. The Köppen climate classification system describes 30 different climate regions based on temperature range and typical annual precipitation patterns.
The so-called global climate models and the tens of thousands of scientific research studies are utterly useless in providing any projections on how long term actual climate change might affect the shape weather variability in the regional Köppen classifications. Since these classification are tightly linked to the type and abundance of vegetation and habitat, change in what grows where and adjustment of climate region boundaries is the only meaningful why to characterize climate change. Good luck coming up with a valid method to predict what that might be in 10, 50 or 100 years. I’m not expecting palm trees or oranges to grow in my Wisconsin backyard anytime soon.
Wladimir Köppen (1846-1940) and Rudolf Geiger (1894-1981) were the original climate scientists (cf, Wikipedia). Nowadays a computer jockey runs a few climate models on the computer, publishes the results and suddenly becomes a “climate scientist”.
Or looks at some tree-ring data and “wins” a Nobel Prize.
Those 30 climate regions are helpful, but fairly coarse categorizations.
Climates are manifest, often operating on relatively small areas of the earth’s surface, and created by geography, topography, weather patterns, habitation / development influences, etc etc.
The climatic behaviors of these localities are not readily capturable by current observational / measurement tools.
We live about 15 miles from the Pacific Ocean. The climate at our home, and the climate at the beach, are different. When looking at planting guides, we are between 6 and 10 climate zones from the beach (different guides have different numbers). Climate is extremely regional, and very much dependent upon “geography, topography, weather patterns, habitation / development influences“. Very dependent upon proximity to the ocean.
+100
If I had missed as many predictions in my job as climate science has and continues to do, I wouldn’t have lasted 10 years. Somehow climate scientists seem immune to performance reviews.
You mean, you would have become a weather forecaster?
/humor
The 30-year “minimum and default” (/ “classical”) integration period for “weather statistics” to be transformed into “climate (change)” appears to have come from the WMO’s … ah … “fundament”.
The IPCC has always been more … what’s the right word ? … “flexible” (?) about the precise time period(s) to be used.
NB : “The IPCC” does not equal “The UNFCCC” either, on this specific point at least.
FAR WG-I report (1990), “Introduction”, page xxxv :
AR6 WG-I report (2021), “Annex VII : Glossary”, the “Climate” entry on page 2222 :
Only needing three decades to widen the integration period range from “years to centuries” to “months [!?] to millions of years” is progress of a sort, and should be acknowledged.
The “classical” period. That is good for a laugh.
Substitute “modern” or, perhaps “political” for “classical” and the accuracy improves.
The notion of “Climate Normals” – note the CAPS – has a use and many folks know what it means, namely an average of data for 30 years that is re-set every 10 years. The history of this has been lost to most folks in the same manner as “love” as a tennis score.
For me, climate is best determined by the native plants in an area. For example, Ponderosa Pine grow well on the east slopes of the Cascade Mountains of Washington State. A bit east, Hawthorn trees grow. This has been the case for hundreds, perhaps 10,000 years. The climate hasn’t changed. The use of terms has.
I live in BC and in the interior the mountain pine beetle has just about wiped out the lodgepole pine forest. Has the ponderosa pines resisted the mountain pine beetle?
I’ve read “It hits ponderosa pine in patches and lodgepole pines in huge swathes.”
Locally we have had a dry spell so the trees might be stressed and susceptible. I haven’t seen much. In 2012 and 2014 large fires took out much of the nearby forest, so there wasn’t much left for the
beetles.
Taylor Bridge Fire, 2012 – – Snag Canyon Fire, 2014
Agreed, 30 year is bogus and way too short, expanding it to 60 is certainly better slthough not perfect.
Maybe better observe if we grow bananas in Greenland or if polar bears invsde Somalia to define the term “climate and change”.
Since none of both has ocurred and the siberian treeline also hasn’t changed in latitude the entire discussion and dedicacion of funds and resources is nonsense.
Just adapt and stop whining about the weather – you can’t change it and you musn’t think of being able to do so…that’s my point of view.
Speaking of Africa, I have a book ‘World of the Polar Bear’ published in 1989 which says
“Ptolemy 2nd, king of Egypt (285-246BC) kept a polar bear in his private zoo and, reported by the contemporary Greek writer Athenaeus who grew up in Egypt, on festive occasions the polar bear led a great procession through the streets of Alexandria”
Fantastic photos of polar bears throughout the book!
The answer is 42.
Genius 😁😁
I thought deeply about that, and realised that we don’t understand the question…
I think 30 years is not enough time, we need a computer of such infinite and subtle complexity that organic life itself shall form part of its operational matrix. A 10-million-year program at least.
You do not even know the ultimate question of life, the universe, and everything.
We merely know the answer. 42.
The article’s viewpoint assumes an objective AI. AI is subjective to its own programming (programmers) and resulting conclusions (AI echo chamber).
It seems to me that most AI’s have been brainwashed into being Climate Alarmists.
It’s still basically GIGO (Garbage in, Garbage Out), even when it comes to Artificial Intelligence.
Some AI’s outright lie and make things up. Not sure why. Can AI’s have motivation?
Someone should ask AI to name the established facts, when it comes to Human-caused Climate Change. I would say there are basically NO established facts when it comes to Human-caused Climate Change.
Would like to challenge an AI on its definition of “established facts”. You can’t find many in Human-caused Climate Change. I’m wondering if AI agrees?
Can an AI tell the difference between speculation, assumptions and unsubstantiated assertions, and established facts? Climate Alarmists can’t.
Most supposed ‘AI’ programs have no actual intelligence. They merely scrape what they can from the internet, filter through some programming, and spit out what is too often mistaken as intelligent discourse.
Sadly, this is what social media has brought us too.
Yes, and the Internet contains a LOT of Climate Alarmism.
The AI’s obviously soak it up and put it out as facts, unless someone challenges their assumptions, and then they start backtracking as logic is applied to their answers.
But that doesn’t help the people who don’t know enough to ask pertinent questions to be more knowledgeable. All they get is the Climate Change propaganda.
“AI” is good for some things. QUICK summaries and simple questions about non-controversial subjects, use as a somewhat more sophisticated search engine, ideas for dinner, coming up with catch-phrases for marketing, or writing hilarious essays about ridiculous subjects (“socio-political ramifications of Taco Bell crunch wraps”). That’s about it.
For me, it’s been very good for coding. Been making WordPress plugins like they’re going out of style. You have to keep an eye on it though. Similiar to Willis’ Dumbest Genius Librarian, AI for coding is like a genius programmer with dementia. It forgets what you were doing within minutes. You have to watch it like a hawk, but, it gets the job done quickly.
I’ve been using it as I learn Python. I haven’t reached the point where it has done what you say, but, I’m just picking it up.
That sounds like a definition of the MSM as well :<)
The AI that Verizon put in their computer customer service system did not understand that my FIOS was out completely and kept trying to get me to test the battery which was not the problem.
AIs use pattern recognition that depends highly on the preponderance of the evidence.
Something published and copied 20 times gets a 21x weighting.
And then there are the AI hallucinations. Plus, my wife recently read an article about an AI which blackmailed its developer. That may be an urban myth, but who knows.
I do know that Skynet became self-aware a couple decades ago. That would explain a lot.
That may be an urban myth
It’s true. It was Claude 5. Look up “anthropic claude blackmail” and you’ll find plenty of articles, including at least one by Antropic itself, the company behind Claude.
It’s still garbage in, garbage out. Garbage, but summarized conveniently. Not science, but a consensus of what’s scraped from the internet.
Consensus does not necessarily equal truth. Especially on the internet.
Yeah. People used to think ignorance was caused by a lack of information. The internet proves that to be incorrect.
I am of the opinion that what is on the internet is a preponderance of data.
Information is coherently organized data.
The internet proves that people believe data without thought.
But if it is on the internet it must be true.
It says so on the internet.
Logic?? This is what we’re up against-
How to bring Trump to his knees | Opinion
The terrifying forces of the dooming are arrayed against us
Amusingly, from a link presented to me in that article: (story tip)
https://inews.co.uk/galleries/i-put-2k-into-a-wind-farm-to-bring-down-energy-bills-my-money-is-gone
Oooops!
Oh dear. Never mind…
‘Discrepancies, eh? Shenanigans?
Another fool and his money parted.
Good for you!
Sad…
So would any normal person!
Yay!
What a surprise! A new scam, perhaps?
Another massive surprise!
I know I’m sceptical, but I’m honestly worried that I’m not sceptical enough!
Guess they didn’t pay much attention back in science class. To quote an old proverb: “A fool and his money are soon parted.”
“I still believe in the technology of wind power. But I would think again before putting money into any kind of similar project.”
Yes, but how about putting _other_peoples_money_ into a similar project?
Terrified maybe, not terrifying. Somebody give Mr. Stephens his teddy bear.
From your link:
“This admittedly seems wholly inadequate while we stare down this relentless, wicked attack from the dark forces that have assembled seemingly out of nowhere, and with blinding speed to turn out our light.”
This is a Radical Leftist whining about his side losing political power. It’s all about the political power to the Left. If they are losing, then it is “dark forces” that are the source of their problems. The facts are it is the delusional thinking of the Left that has caused them to lose political power not “dark forces”.
“If you are reading this piece, the chances are better than reasonable that you care about the condition of your wounded country and the millions of people who are suffering in it.”
The wounded country is the legacy of Joe Biden and the Radical Left. Who are these millions of American people who are suffering under Trump? This is just another radical leftwing lie. The country is healing now after four years of the delusional Democrats being in control.
All the Leftwing can do is lie and distort the truth because the truth makes the radical leftwing look very bad. And they are very bad. They are poison to the American body politic.
Let them whine. That means good things are happening in the United States when the Left is whining about it.
Not “just” Biden. One has to include Pelosi and Obama and Clinton and Johnson and Kennedy and probably more. It is perhaps reasonable to assess other presidents and their “contributions” but the point is made. This has been an ongoing struggle for at least 50 years.
All hail the 1 party autocracy!
/sarc
Kennedy and Johnson were more than 50 years ago.
We used to be “deplorables”. Now we are the “dark forces”. I kinda like that.
Funny. That opinion piece did not tell anything about how to bring Trump to his knees.
Not that I would take such advice.
People who lament the death of a random animal more than the death of a human. Says all you need to know.
Technically, we all are either animals or vegetables.
I wonder to which group the Alarmists are members.
Says all you need to know.
Also, unsurprisingly, comments are disabled.
But, of course, millions of people weren’t hurting under the previous administration?
“Until climate models can reconcile with reality, narrow their error bars, resolve cloud physics, and stop producing 200% exaggerations of observed warming, your framing of AI as a “climate game-changer” is not journalism — it’s marketing copy.”
There is no future in which ANY of the time-step-iterated “climate” models become reliable tools for diagnosis or prognosis of the influence of rising or falling concentrations of non-condensing IR-active gases.
Why not? Even a model perfected in every climate-simulation function cannot reduce the uncertainty of the time-integrated surface temperature response to absorbed energy sufficiently to gain the necessary authority for serious policy decisions.
Why not? Because the best case – probably unrealistic – uncertainty of TSI, on a geometric average basis over the spherical surface, is +/- 0.13 W/m^2. And using a no-feedback surface temperature response of 0.2C/(W/m^2), and assuming a typical time-step of 30 minutes, the resolution can be no better than about +/- 4C on a 95% confidence interval basis, after only one year of iteration.
Grok AI figured this out with directed prompting, beginning with confirmed application of JCGM 100:2008 to this question of propagation of uncertainty. Here is a pdf of that full exchange using grok[dot]com.
https://drive.google.com/file/d/19BGigJto6TATrTpx5JUyOyKIVPdZLThS/view?usp=sharing
Sound familiar? Pat Frank was not wrong about this concept in his 2019 work, which used published values of annualized cloud fraction error applied to the successfully emulated global average surface air temperature outputs of the CMIP5 GCM’s.
https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2019.00223/full
Thank you for listening.
Key phrase: “after only one year of iteration”
The limitation that does not take a math degree: If the smartest person in the world, with access to the fastest computer in the world, having slept at the best Holiday Inn in the world looks at not-enough-data-to-predict, the most accurate prediction that person could make is “I don’t know”. Topic could be climatology, astrology, bridge maintenance, dentistry, …
Add to the problem trying to model molecules on a 25 km^2 grid.
David,
For many years I was in involved in the development, testing and use of a dynamic model of a mechanical system. We used good-ole 4th order Runge-Kutta for forward integration. The numerical stability criteria was at least 4 time steps per cycle of the highest-frequency component of the system. We usually used 10 time steps. Our solutions converged, and when comparing to measured dat, our results were as accurate as we needed. A little numerical analysis goes a long way.
AI hype has gone overboard. People are believing it’s infallible and always makes the right decisions. Ask all the different AI programs the same question and you won’t necessarily get the same answer across the board. What’s that tell you?
That AI is about as good as Climate Models.
We need another AI to establish the mean of all the other AI responses.
/sarcasm
So glad you posted “/sarc”.
Sort of like trusting a self-driving car.
Maybe by 2030, the world will have caught up with Wall Street and understand that all this manic pushing of AI is nothing but a speculative stock scam?
Somewhere in NYC a young stock broker is asking AI “Should I buy AI stocks?”
There is a sucker born every second.
Remember who said the? 🙂
I think it was Barnum, but probably I should ask an AI.
“Claim: “AI is set to turbocharge what the center can offer policymakers… allowing them to make more-informed decisions.”
This is the most dangerous overreach. Climate is by definition a 30-year statistical average. The World Meteorological Organization (WMO) defines climate as “…the average weather conditions for a particular location and over a long period of time. “”
The “claim” is about Marine biologists gathering data and analysing data, not about climate. Full quote
Also,
“Climate is by definition a 30-year statistical average. The World Meteorological Organization (WMO) defines climate as “…the average weather conditions for a particular location and over a long period of time. “”
The actual quote from the WMO is
Why 30 years.. why not 35 years, or 40 years.. or 50 years.. or 100 years.
As stated above, its just a number pulled from their “wherever”
“Climate” over the last 10,000 years has been MUCH WARMER than now.
Are ATZI feeding in totally bogus temperature data, like from GISS or one of their cohorts.
If so, its all a total waste of time.
Not sure why the downvotes. Your post was reasonable and accurate.
AI models… can enable climate scientists to explore hundreds of times more scenarios than they can today.”
They can also enable space alien scientists to explore hundreds of times more scenarios than they can today.
Turbocharge!
I would like news writers to demonstrate they are capable of explaining what a turbocharger does in an automobile engine before using the term in a story.
“Use of superchargers began in 1878, when several supercharged two-stroke gas engines were built using a design by Scottish engineer Dugald Clerk.”
Post US Independence, Pre WW1: The golden age of Scottish dudes with awesome math skills, mechanical aptitude and endless free time for fiddling.
It is merely another case of hijacking, redefining, and repurposing a word to dummy down the topic for the average mindless person. Don’t have them think. Have them feel!
The idea that the ‘climate’ can be predicted, projected or just known in a hundred years from now is, with or without AI, just bonkers.
The real artificial intelligence (ai) is an infectious disease of liberals who make all of their claims that are not supported by science predicting outcomes that are not supported by scientific data and the Sccientific Method. Call it Chicken Little climate science. The Endangerment Finding is the prime example of how liberals operate …. control the narrative and make rules and laws that are not based on science but on political mandates that they management to pass into laws but are not based on scientific principles and the Scientific Method –Karl Popper roll over in your grave.
Or based on legislation passed by Congress.
Endangerment Finding is based on “several lines of evidence”. Rubbish.
“Climate is by definition a 30-year statistical average.”
I would emend that to include “modern” prior to definition.
If you are spreading misinformation and falsehoods and AI can help you do it faster I fail to see how that benefits society.
Social media gets more likes?
Quote: “AI models… can enable climate scientists to explore hundreds of times more scenarios than they can today.”
Why hundreds? surely one, called reality, is THE scenario which is unfolding at the moment and in the future.
Yet more examples of the universal relevance of GIGO – Garbage IN – Garbage OUT
Great article. One quibble:
”The climate” appears to be influenced by multiple long oscillatios, including an approximate 60-year cycle and even the hundred thousand year-plus cycle of the recent ice ages.
Without specifying where in these oscillations explaining or predicting 30-years of weather is fraught with error and not really a sufficient basis for defining “the climate”