by E. Calvin Beisner
By now practically everyone who follows news and commentary about climate change has seen graphs of global warming over the past century or more. The National Oceanic and Atmospheric Administration (NOAA) produced this one in 2017, covering 1880–2016.
Ever since it first appeared, it’s been one of the most commonly used, whether in scholarly journals or government websites or news media or blogs or social media. More recent data generally are communicated similarly—and it’s not hard to understand why.
Here, solid bars, one for each year, depict the change in global average temperature (depicted as anomalies, i.e., departures, from the 20th-century average), and the psychological impact is predictable: fear.
How? Bars in the early years, below the average, are a comforting blue; later bars, above average, are an alarming red. If all the bars were the same color, the psychological impact of the different colors would be lost.
But the color choices aren’t all. They’re just the most obvious. Another choice is less obvious, and readers unfamiliar with how to interpret graphic representations (or misrepresentations) of data are likely not to notice it.
Ominously, the longest blue bars reach almost to the bottom of the graph, and the longest red ones almost to the top. Why? Because the vertical axis chosen (and note that word—it’s a definite choice) covers only from -0.5°C to +1.0°C (-0.9°F to +1.8°F). A grand total of 1.5°C (2.7°F).
On the one hand, this is quite defensible. Enter the raw numbers into common spreadsheet software, tell it to produce a bar graph, and that, or something very close to it, is what you’ll get. And why not? After all, it accommodates all the numbers, lowest to highest. What more can we ask?
On the other hand—if your intent is to help people think reasonably about changing global temperature, it’s utterly indefensible.
Why? Because it makes a temperature variation of under 1.5°C (2.7°F) look, to the unpracticed eye, far more significant than it is. After all, most people hardly notice if a room’s temperature rises or falls that much. But on this vertical scale, the longest red bars reach almost to the top, as if to say, “We’re about to reach the maximum!” True, the longest blue bars also reach almost to the bottom, which could be interpreted, “Whew! We just barely missed freezing!” (And since cold snaps kill, on average, 10 to 20 times as many people per day as heat waves, that should be really comforting—but I digress.)
But remember, blue’s a comforting color; red routinely means “danger!” That, after all, is why United Nations Secretary-General António Guterrez called the first volume of the Intergovernmental Panel on Climate Change’s Sixth Assessment Report “code red for humanity,” not “code blue” (though, admittedly, in a hospital “code blue” denotes a critical status of a patient—but that’s not common lingo).
And since most people read from left to right, the graph subtly communicates that, whatever risks might have come with those low temperatures, we’ve left them far behind. No need to worry about them now. It’s those high temperatures, marching inexorably upward, that we need to worry about.
Back in the early 1990s, when I was managing editor of the book The State of Humanity, its general editor, the late economist and statistician Julian L. Simon, legendary for his antipathy to misleading statistical graphs, insisted that all graphs of the data provided by the 58 authors (including 8 Nobel Prize winners) use a realistic, objective scale.
For example, graphs of data expressed as percent should have a vertical scale of a full 100 points—otherwise, the result could be highly deceptive. After all, if the vertical scale only went from 80% to 90%, a data point of 86% could appear to depict a quantity twice as high as 83%, when in reality it’s only 3.6% higher.
Another example: Graphs of data that don’t depict percents should have a zero baseline. Or, if they depict both negative and positive data, the vertical axis should stretch equally far below and above zero, so the relative magnitudes would be quickly and easily comprehensible. Or, if they depict data so enormously different that low numbers just disappear, they should be drawn with exponential scales—and that fact should be communicated prominently—or with clearly marked discontinuities along the vertical axis.
There are other examples, but you get the point. One of the basic principles is that the vertical axis should cover a truly significant range.
That’s the bigger problem with NOAA’s famous graph. As we saw above, it makes a very small change in temperature appear much larger and more significant.
A more appropriate, less misleading, way to graph the same temperature data is to use a vertical range that’s fairly typical of the weather people commonly experience. That’s a scale they’ll understand.
In the United States, except when air currents rapidly move a much warmer (or cooler) air mass from one locale to another, diurnal (daytime high to nighttime low) temperature range is typically around 5.6°C (10°F) in humid locales but around 22.2°C to 27.8°C (40°F to 50°F) in arid to semi-arid locales. In other words, people are accustomed to those temperature ranges.
It would seem reasonable, then, to depict global temperature anomaly data on a vertical scale of, say, halfway between the low and high ranges, i.e., 16.7°C (30°F). And, to complete our avoidance of psychological scare tactics, we’ll jettison the color scheme and use a neutral color.
How would NOAA’s data for 1880 to 2016 look depicted that way? Like this:
Remember, this depicts exactly the same data depicted in NOAA’s graph. Does it look scary? No, but it’s a much more honest, objective, non-manipulative depiction of the data. So, now you’re equipped not to be manipulated—and to enlighten your friends and neighbors.
Defenders of the scary way to depict the data could respond, “But the fact is that this apparently slight change in global average temperature will, if it continues at scale, cause devastating changes in weather, sea level, crop production, and other measures—changes that will impoverish humanity and possibly even bring about its extinction. So scary depiction of scary facts is just what we need.”
But the Intergovernmental Panel on Climate Change disagrees—firmly and adamantly. Its 2018 Special Report on Global Warming of 1.8°C concludes that if we do nothing to slow greenhouse gas-induced warming, the warming will make gross world product (GWP) in 2100 will be 2.6 percent lower it otherwise would be.
What would it otherwise be? The Center for Global Development says economic growth through the remainder of this century is most likely to be about 3 percent per year. After factoring in change in population, the result would be GWP per capita 8.8 times what it was in 2018.
When poverty is a far greater threat to human health and life than anything related to climate and weather, can anyone think that’s a catastrophic result?
If you spend much time at all on social media sites on which people often post text or pictures meant to make points about controversial issues, you’re bound to have seen “fact checks” stating that a post conveyed “false or misleading information” because it was “missing context.” (That’s a judgment that’s often subjective and driven by the “fact checker’s” ideology, but we can ignore that for now). What you now know is that, when it comes to “missing context” about climate change, official government agencies can be among the worst offenders, not just on social media but also on agency websites—from which their products, like the NOAA graph evaluated here, regularly make their way into scientific journals and mainstream media.
A Google image search July 11, 2024, found NOAA’s graph at about 100 sites. Where are those “fact checkers” when we need them?
E. Calvin Beisner, Ph.D., is President of The Cornwall Alliance for the Stewardship of Creation, a Christian think tank addressing environmental stewardship and economic development for the poor. He is also co-editor, with David R. Legates, Ph.D., of Climate and Energy: The Case for Realism, an Amazon bestseller.
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If the intent is to deceive, it is lying.
I have no idea if the intent of folks at NOAA was to deceive. However, the output of “common spreadsheet software” often is used without much thought. For example, one chart on the WEB shows R2 as 0.9688940092. Another about “Longevity vs Smoking” proclaims the intercept (years) as 85.72042. That decimal fraction computes to 263.1334 days.
One only has to search a little to find these ridiculous numbers. I call these folks “lazy” reporters.
Significant figures is a concept that is foreign to most reporters.
And many “scientists”!
I’m not upset that you lied to me, I’m upset that from now on I can’t believe you. Friedrich Nietzsche
(Is appropriate!)
As you say. This makes them prevaricators:
prevaricate /prĭ-văr′ĭ-kāt″/
intransitive verb
A Lie by any other name, is still a Lie.
Red indicates warm, blue indicates cool, so red bars are warmer than the baseline, blue bars are cooler than the baseline. This is both perfectly accurate and visually quite helpful. But this is just NOAA’s convention, it isn’t universal. NASA, for instance, uses a single color line on a scatterplot:
Your remarks on the axis are whining – you yourself note it is common (dare I say universal) convention to choose graph axes that closely bracket the maximum and minimum values you are graphing. The point is to be able to see the pattern of change, and zooming way out just makes that harder to do, for no gain whatsoever. It just seems that you want to flatten the change out to make it harder to see, which is the opposite of the purpose of a data visual. You could just as easily argue that the annual ticks on the x-axis are highly misleading, because humans don’t experience the passage of time in years, but in milliseconds, so we need to stretch the x-axis out til it’s ten miles long. That would really obscure the warming.
1909 had an apparent Post Industrial anomaly of -.5°C (which was already warmer than pre industrial 1770) and 2023 has a Post Industrial anomaly of +1.2°C which places Post Industrial Anomaly increase at +1.7°C from 1909 to 2023 (113 years). 1.5°C has been breached so where’s the Thermogeddon? It IS after all the “Global Anomaly” per the graphic.
The thing to keep in mind is the NOAA/NASA Hockey Stick charts do not represent reality. They are generated in a computer in an effort to sell the Human-caused Climate Change narrative.
Here is the real temperature profile of the globe, represented by the U.S. regional chart (Hansen 1999):
Compare the U.S. chart to the NOAA chart. Both show the period of the 1910’s to be the coolest period since the Little Ice Age ended (around 1850).
Then remember that in the late 1970’s, concern was being voiced that the world was cooling into another Ice Age.
Why would this be a concern?
If you go by the NOAA bastardized temperature chart, you would wonder why any concern would be expressed about a new Ice Age coming in the late 1970;s, since the NOAA chart shows the 1970’s to be much warmer than the period of the 1910’s. Nothing to see here.
But if you look at the U.S. regional chart you see that it was cold in the 1910’s, then it warmed up nicely into the 1930’s (the Dust Bowl period), and then it cooled down through the 1970’s, and notice that the cooling of the 1970’s is equal to the cooling of the 1910’s, which was the coolest period since the Little Ice Age ended.
So, it is obvious why climate scientists were looking at the late 1970’s with concern. If temperatures got much cooler, we might very well be entering a new ice age. Happily, as happened in the 1910’s, the temperatures did not continue to cool, but instead warmed up nicely to the same magnitude today as the warming in the 1930’s.
So the fears of a new Ice Age coming had a legitimate basis if a legitimate temperature chart is used.
This proves the Bogus, Bastardized Hockey Stick global charts are exactly that: Bogus, and Bastardized.
And here are 600 other unmodified, regional temperature charts, from around the world, that show a similar temperature profile to the U.S. regional chart. None of them have a “hotter and hotter and hotter” temperature profile like the bogus, bastardized Hockey Stick charts.
Hockey Stick charts are Climate Alarmist Propaganda.
https://notrickszone.com/600-non-warming-graphs-1/
AnalJ pops up with his usual garbage hockey stick featuring the impossibly small “error bars”.
Karlomonte popping in to make his favorite freudian slip about me and to expose his distaste for reading. The error bars are not impossibly small, as anyone who had cared to examine the literature would know quite well.
How does “THE literature” define a poofteenth?
(clue – a poofteenth carries no meaningful error bars. Just as global average temperatures constructs are presented in variations of poofteenths.)
You think we can get an uncertainty interval of just 0.15°C for the late 19th and early 20th centuries? Just take a look at the map attached. Most of the data are from the U.S., with a few scattered across Canada, Europe, and Australia.
Africa, Asia, South America, Russia, and the oceans? Virtually absent. Who in their right mind believes that such sparse coverage could possibly provide even a semblance of an authentic global average temperature?
Because this map shows land stations. And yes, reduced coverage is why the uncertainty grows as you can further back in time.
The uncertainty of the operational temperature measurement instruments pre-1980 were ALL +/- .5 deg. except for NIST calibrated laboratory thermometers supplied with correction sheets. Start there and add the reduced coverage factor to that.
10mK uncertainty increasing to 200mK is a BIG growth in AlanJ-World.
Of course it must be pointed out (again) that he, and climate science in general, do not understand that uncertainty is not error. Or much of anything about metrology and uncertainty.
Show us where Oceans were measured from 1891-1920.
I bet you can’t.
Even in 1950, the ocean coverage of the SH oceans was basically NIL..
… and the NH oceans probably less than 10%
Combine that with basically ZERO coverage for MOST of the land area…
… and the whole mess is just FABRICATED GARBAGE…
.. with zero probability of being even a remotely accurate estimate of anything !
To present it as anything but a complete fantasy is the very depths of DISHONESTY and DECEIT.
Exactly what we have come to expect from AlanJ.
I’ve been searching Heller’s website for a global station coverage map for the years 1930-1950, similar to the one I posted. I’ve been unsuccessful thus far.
Here is a map from GHCN covering the period 1921-1950, encompassing the period you reference:
Thank you very much.
And what of these few stations? Are they infallible as well?
The uncertainly level described in the literature are total mathematical hogwash.
That’s because they are a sampling uncertainty of the mean and not the measurement uncertainty of the mean.
Press AJ and he will admit that his basic meme is that all measurement uncertainty is random, Gaussian, and cancels. Thus there is o measurement uncertainty leaving only the sampling uncertainty to calculate. Meaning the more samples you have the smaller the sampling uncertainty gets.
BUT, and this is a BIG but, it doesn’t matter how small you make the sampling uncertainty if the accuracy of the data itself is poor. A very precisely calculated mean of inaccurate data is guaranteed to be inaccurate as well. How inaccurate is shown using measurement uncertainty.
It’s educational to know that in ASOS stations the temperatures are recorded to the nearest 1F. That means you have a basic, inbuilt measurement uncertainty of +/- 0.5F when using the data. Trying to get +/- 0.001 measurement uncertainty from data with +/- 0.5F is impossible. Especially when each measurement is of different things using different devices. Assuming all this uncertainty cancels is just plain ridiculous.
Idiot ruler monkey.
Just because something is published in the climate pseudoscience literature does not preclude it from being bullshit.
Quite the reverse. Since so much of what is “published” these days gets published *because* it supports the AGW paradigm means it is MORE LIKELY THAN NOT bullshit.
It is circular reasoning at its acme.
Not only that , but most of the more recent land data is hopelessly contaminated by urban, airport and data manipulation
The final graph is totally meaningless as a representation of anything.
Absolutely correct, but it is all they have, so they push it over and over.
They KNOW it is totally bogus.
That means they are deliberately pushing bogus data.
Deliberately LYING !!
Big question is… WHY ??
The above graph is based on sand, first of all read the heading “Global Mean Estimates Based on Land and Ocean Data.” First of all it an estimate(not real only a guess or not unqualifiable to any degree of certainty.) Global Mean is another number produce by pure guess work. Then there is “Land and Ocean Data” calling the collection of dissimilar measurements “data” is a sad joke. Even worse there are no error bars, in my business which I was trained in electronics at least when you buy a component how close said component to what is marked on it might be to its real measure value, is clearly marked plus or minus 20% 10% 5% 2% or true precision component 1%. In my estimation(guess) so called “climate science” it is all smoke and mirrors. To claim precision in any measurement when the data is know to have large errors and the measurement are dissimilar over a host of methods over the years. To claim precision of hundredth of degree is pure junk science or a con game.
Instead were are now talking how bad data should best be presented as if it resembles something that real! The only thing about climate is it changing and how much and what way and what such changes mean is far from being answered and I doubt even after 1000 years of the present haphazard method we now measure temperature we will ever know within 1 to 5 degrees F of what going on, let alone a few hundredths. If weren’t for the fact such junk science is demanding world wide changes on how humans live and the cost of such and the whole con game the simple its a giant waste of money that coming out of my pockets and from a lot of people who can’t afford it. I would careless what so called educated idiots though.
Actually, what it often does is amplify the subjective influence of what is essentially noise. Also, the scale that is used for numeric analysis is not the best for conveying patterns. Additionally, as the author points out, unthinkingly using a temperature scale that ignores physiological responses is tantamount to ignoring the ever important “context.”
You can easily see in both graphs that the variability is lower than the scale of the graph. But if that were not the case, and the climate of the past century were indeed dominated by random variability with no long term trend, that would be important to be able to see.
Why?
Humans don’t “feel” the global climate, but the difference between major climate states is only a couple of degrees. You might as well argue that people have never handled trillions of dollars, so a graph of the global GDP should only be shown with units of single dollars and should be 10 miles tall. Again it’s all part of a silly effort to pretend like global warming isn’t happening by, quite literally, trying to obscure it from view.
“You can easily see in both graphs that the variability is lower than the scale of the graph”
No I can’t
There’s an obvious warming trend apparent in the series from beginning to end, this trend is what dominates the overall range, not short term random variability. Try looking again to see if you can spot it.
Whether I see a trend or noise depends on how long “short term random variability” should last. If I’m looking at a short window of a much longer time series any apparent trend might disappear if I saw a wider view. How long would the complete series run? What is short term” in that context?
You can perform tests of statistical significance to determine if the observed change could likely arise in a series comprised of only random noise.
You can’t do anything scientific or mathematical with garbage data.
IT IS FAKED NUMBERS from GARBAGE DATA..
… TOTALLY MEANINGLESS.
It is a garbage fabrication, based on sparse irregular, tainted garbage data.
It is meaningless.
And very DISHONEST to keep pretending otherwise.
Then why bother using a scale that shows the “short term random variability?” A heavily-smoothed graph, perhaps with a regression line, should be sufficient to “see the pattern of change.” Not only “sufficient,” but probably superior.
NASA does provide a smoothed curve with the variability reduced. See above.
What a load of mindless gibberish… pertaining to absolutely nothing.
Pretending that a trash, agenda-driven fabrication from heavily tainted urban and airport sites represents anything global or remotely real..
… that is the absolute in DISHONESTY.
There is no “the global climate” — this is yet another lie of the catastrophe cabal.
No, that is exactly the opposite of what I’m arguing! When looking at the GDP, worrying about the pennies is a distraction. Any more than two or three significant figures is an obscuration.
So there goes the “we should always graph things with axes scaled to common human experience” argument, rather than graphing them with the most sensible scale for the data being visualized. Glad we’ve found some alignment.
Are you Nick Stokes using a different name?
I think there are a number reasons to object to the red blue bar charts, but it’s strange I never hear any objection when UAH does it.
The chart has more informative labels. It is a better presentation of 100 years less data.
What additional information is on the UAH one than NOAA’s? The complaint in this article isn’t about the labels, it’s about the colors.
You can see the long periods of basically no warming
You can see the sudden changes at NATURAL El Ninos.
What you can’t see is any human causation.
You can see bnice completely missing the point.
No muppet… you are missing the point
What you can’t see is any human causation.
What you can’t see is any human causation.
Yawn…. Still awaiting a rational scientific response.
bellcurveman the ruler monkey chucks in for the rescue!
Random insult generator, what exactly is your point? Are you disagreeing with something I’ve just said? Or is it just again you refusing to engage in rational discourse, whilst wanting to appear to be relevant?
Bellboy = random garbage generator.
See what random garbage you can come up to answer this question.
Where is the human causation?
Or you could continue to run around like a headless chook, proving that you know the slight beneficial warming is TOTALLY NATURAL.
Your monomania about “human causation” is so telling. You clearly worry deep down that humans are causing warming, and your only way of coping with this is to deny it at every possible opportunity – even when no-ones mentioned human causation.
The causation is irrelevant to the argument about whether this is a good or bad graph.
“but it’s strange I never hear any objection when UAH does it.”
UAH began in 1979, and appears to capture the global temperature correctly since that time.
The problem is not the temperature record since 1979, the problem is the bogus, bastardized temperature record before 1979, which erroneously depicts a climate getting hotter and hottter and hotter, for decade after decade and is now the hottest time in human history.
This is a Blatant Lie, debunked by actual, written, historic temperature records from around the globe, which show it was just as warm in the recent past, as it is today, and shows there is no unprecedented warmth today, which means CO2 has had no discernable effect on the temperatures.
Climate Alarmists don’t want us to know this, so they get their computer and bastardize the temperature record to make it look very scary.
There is a special place in Hell for Climate Alarmists who deliberately lie to the public about the future. And I would hope there is a special place in hell, here on Earth, for Climate Alarmsts before they go off to be judged by God. They have caused incalculable damage to economies and psyches with their lies about the Earth’s climate and CO2. They deserve to get what they gave.
“UAH began in 1979, and appears to capture the global temperature correctly since that time.”
Your evidence for this is?
“The problem is not the temperature record since 1979, the problem is the bogus, bastardized temperature record before 1979…”
That is your problem, not the one being discussed here. The claim in this article is that bar graphs using red for above average temperatures and blue for below average temperatures, is designed to spread “fear”.
The fact that no-one here wants to mention that, and instead keep jumping on their hobby horses suggest they don’t think it’s a very strong argument.
“Your evidence for this is?”
And your evidence for the accuracy of the NOAA and NASA global charts is?
I think the stronger evidence that NOAA is producing propaganda comes from their plot of CO2 concentrations vs the temperature plot shown above
https://www.climate.gov/media/13840
To understand how this is propaganda one has to first understand that the change in temperature is supposedly proportional to the natural log of CO2 concentrations. However, if they had plotted ln([CO2)], the effect would have not have been so dramatic. Also the scaling of the two plots has been chosen, not for best fit, but for the most drama. The CO2 plot skims across the brief temperature spikes to both emphasis the spikes and to draw the eye upwards. There was no attempt to match the temperatures prior to 1980, only the minimum near 1910.
This plot has obviously been designed, not to convey science, or even to be studied at length, it is simply meant to draw an immediate emotional response from shallow thinkers with short attention spans. When I first saw this plot I lost a lot of respect that I’d had for NOAA,.
While the data in the plot may be factual, the presentation is pure propaganda.
You can convert CO2 concentration to forcing via the relationship:
Doing so yields:
Which seems to be consistent with the climate.gov graphic.
Not really, the y-scale for the CO2 in the NOAA plot is in PPM.
Also AlanJ, I can predict global temperature more accurately using nothing more than a simple linear filter and sunspot data.
Alan, I am assuming you know that the forcing value assumes all of the photons that excite CO2 are reemitted as photons. This is a very bad assumption as we know that 99.99% of radiate energy absorbed by CO2 is converted into kinetic energy through collusion. You do not have a very good grasp of the physics..
Also, the temperature data has been adjusted in order to introduce a high correlation to CO2 concentrations that doesn’t exist in the raw data. You seem complete unaware of the science and the data. .
The forcing value makes no such assumption. The forcing represents the change in TOA net energy balance.
I’m well aware of the science and the data, and have never seen this claim proven.
Science does not prove anything. Since you think it does per your statement above, you can’t be aware of anything that it actually does, because you are waiting for science to perform magic.
This is not a question of science, it is an allegation of misconduct. It is either something that is happening or not.
Misconduct that you whole-heartedly endorse.
“This is not a question of science,”
True.. “climate science” is not a question of science.
Very little to do with real science.
The fact that you continually use data that you know to be massively contaminated and meaningless, proves that.
Real science doesn’t use known contaminated data.
AlanJ, there is evidence to support UHI bias in the temperature data. That said, the more serious flaw in the CO2 theory is the fact that CO2 concentrations lag temperature by six months except for periods of 1.3 years and 1 year, where the lag is less than 2 months. The causality is in the wrong direction for CO2-induced climate change. I was able to show this by computing the coherent frequency response between CO2 concentrations and temperature.
This pot shows that the lag relationship holds even over 10-year periods (delay is represented as slope in the phase plot). For 10-year periods, the net sensitivity (top plot) is that CO2 concentrations increase by 4.9ppm/°C. If CO2 dominated temperature-induced changes, the phase slope would be positive; it never goes positive for periods longer than 1 year.
I’ve spent quite a bit of time on this and I could not find any evidence in more than 60 years of instrumentation data that CO2 induced temperature changes were ever large enough to overcome temperature induced changes in CO2 concentrations. So it might be more appropriate to use your plot to show how CO2 concentrations follow temperature, though I’m not making any claim that all of the changes in [CO2] are driven by temperature.
As you can see from one of my sunspot models (shown above), it’s far more likely that the sun is driving global temperature, which in turn influences CO2 concentrations.
If I’m reading the above correctly, you’ve detrended temperature and CO2 prior to running your models, which means you’re observing nothing more than the seasonal relationship between temperature and CO2 that results from the annual growing season. No one is claiming that CO2 causes seasonal temperature variability, the claim that is made is that CO2 is driving the long term (multi-decadal) rise in temperatures, which your analysis cannot get at by design (because you’ve removed it).
AlanJ, you are correct, there was a linear detrend of both datasets. I wouldn’t describe the frequency response calculation as a model any more than I would a cross-correlation. You can’t generally determine causality between two linear trends with different units. So don’t be too quick the throw out the baby with the bathwater.
The advantage of the frequency response analysis is that it’s possible to separate process by their periods, so no, I’m not talking about seasonal variations those all land at a frequency of 1 yr^-1. There is some other process, with a frequency of 0.75 year^-1 that also has a shorter delay, but is still showing that [CO2] follows temperature. I’ve also analyzed ENSO influence (not shown), and [CO2] followed those longer term events as well.
The thing to keep in mind is while there are weather events that influence [CO2] there are also documented fluctuations in anthropogenic greenhouse gas emissions over the last 66 years. These are supposed to influence temperature. We’re told the effect is quite large. My use of coherent averaging reinforces signals that are common between [CO2] and temperature, no matter the direction of causality. So if [CO2] was driving temperature, it would appear as a positive phase somewhere below a frequency of 1 year^-1.
I won’t go into all of the different techniques I used to look at the data but I will show two more plots which better address the long-term trends. In these plots seasonal variations are attenuated with a 1-year moving average.
This first plot compares a logarithmic detrend of CO2 concentrations with a a linear detrend of temperature. This makes it easy to see the residuals over 66 years (upper, right plot), which is much longer than ENSO variations. In the residuals the ln() detrend is not a good fit to to the temperature residuals over the long term.
Next I performed a 2nd order detrend on [CO2], keeping the first-order detrend on temperature
The residuals are quite low now, and while the interpretation is more subjective than the frequency response analysis, there is no evidence that [CO2] leads temperature over any long periods. The delay from ENSO fluctuations is now quite easy to observe.
Here’s why I believe the causality of the trends is in the direction of temperature driving [CO2]
In the frequency response analysis, the sensitivity falls with frequency. It was 4.9ppm/°C. for 10-year periods and 2.8ppm/°C for 5-year periods. This decrease with frequency is very close to 6dB/octave which is consistent with the frequency response of an integrator, or single-pole low-pass filter. This in turn is consistent with the CO2 response having a better fit to a 2nd order polynomial when the temperature is 1st order. In other words, integrate x and you get something proportional to x^2.
Based on my analysis, I believe that the forcing function you used produces nothing more than a false correlation with temperature. By analyzing the shorter term trends which are impacted by both weather and fluctuations in anthropogenic emissions, I’ve concluded temperature is driving CO2 concentrations, and at least some of the CO2 is accumulating over time. This does not preclude anthropogenic emissions from contributing to [CO2] but there’s no evidence that I can find that those emissions influence temperature.
Well, this is a problem, because that trend, the thing you’ve removed from both datasets, is the thing that CO2 is supposed to be driving. You’ve very much thrown the baby out with the bathwater, here. No one is claiming that CO2 drives annual, interannual, or even 5-yr to decadal variability in temperature, they claim it is driving the long term trend in climate over the 20th century, and you’ve removed that from your analysis.
And this kind of analysis can’t get at the underlying physical mechanisms, anyway. CO2 is a powerful greenhouse gas, and we are emitting enormous quantities of it into the atmosphere over time, and a lot of that is hanging around in the air, causing a long term rise in atmospheric concentration. Why is that increase in a powerful greenhouse gas not causing warming, assuming your analysis were correct (and let me be clear – it is not)? At some point you have to start addressing the physics of it all, statistical analysis won’t get you there.
AlanJ, “No one is claiming that CO2 drives annual, interannual, or even 5-yr to decadal variability in temperature, they claim it is driving the long term trend in climate over the 20th century, and you’ve removed that from your analysis.”
Anthropogenic emissions have not been constant over the last 66 years. They have subdecadal variations which are not always monotonic.
https://www.researchgate.net/figure/Global-Anthropogenic-Carbon-Emissions-Source-Carbon-Dioxide-Information-Analysis-Center_fig2_260417969
Sorry, but I don’t buy the argument that a powerful forcing function with subdecadal variations can only be detected through centennial trends. One has to avoid “the physics” to reach that conclusion. This is especially true given that you are arguing that the greenhouse effect is photonic. There shouldn’t be any significant delays in global temperature if it truly is reacting to global variations in CO2 concentrations.
Also, I didn’t remove the long term trends from all of my analysis, only from the FFT-based frequency response analysis. I took the time to included my long-term trend analysis separately for your benefit. I’m not sure you’ve taken the time to review it.
The total emissions have not varied greatly, and the growth in atmospheric concentration has varied even less (the oceans take up a huge fraction of our emissions).
And you have to buy the argument, like it or not, because the climate contains numerous modes of forced and internal variability on decadal timescales, so you can’t necessarily identify the underlying long term trend over short time spans. And you can be absolutely certain that there is a temperature > CO2 relationship on those same short timescales that will confound any effort to produce a lead-lag analysis without accounting for the short term variance.
So far as I can discern, in the first analysis you’ve detrended CO2 using a linear function, and in the second analysis, you’ve detrended CO2 using a second order polynomial, both will have almost the same effect of removing the long term trend over the timescale under consideration.
And I’ll repeat again, even if you successfully demonstrate that the 20th century rise in CO2 was precluded by a rise in temperature, you are still stuck with the problem of explaining how this powerful greenhouse gas did not produce significant warming of the climate (and, I suppose incidentally, how on earth this temperature rise simultaneously produced mass quantities of CO2 in the atmosphere while perfectly accounting for anthropogenic emissions). And this is a problem you can’t solve with statistical analysis. And, of course, you have to explain what caused the temperature to increase anyway if it wasn’t greenhouse gas emissions.
Well, AlanJ. Thanks for the exchange, but I think we’ve reached the end. I did explain what caused the temperature variations. I’ve shown an empirical model which accurately predicts temperature from sunspots. This is not a spurious correlation, I now know how solar activity is encoded in the sunspot signal.
Here’s a spreadsheet if you want to explore the model.
https://localartist.org/media/SunspotPredictionExcel.xlsx
I’ve also shown you conclusive results that temperature drives [CO2] and you somehow think that there’s a sudden transition point where temperature stops driving CO2, even though I’ve shown that the sensitivity is increasing with longer periods. I’ve also shown that the long-term trend relationship between temperature and [CO2] is quadratic, not logarithmic, which is consistent with temperature forcing of CO2.
I didn’t mention this before but with the integrator-like response the ~5ppm/°C sensitivity over 10-year periods would imply 50ppm/°C over 100-year periods, accounting for half of the observed increase in CO2 concentrations — assuming the integrator has a long time constant.
You haven’t offered any direct evidence or convincing arguments in return. So, good luck with pushing your “magic molecule” as someone else on this forum referred to CO2.
I think you meant sensitivity is decreasing with longer periods.
No, what I said is correct. 4.9ppm/°C. for 10-year periods and 2.8ppm/°C for 5-year periods. Sensitivity is decreasing with frequency, or increasing with period.
“ the claim that is made is that CO2 is driving the long term rise in temperatures”
Which you know is a totally BOGUS claim.
You can’t even produce any empirical evidence that CO2 causes any warming whatsoever.
Poor red thumb… FAILED again! sadly pathetic. !
You can’t even produce any empirical evidence that CO2 causes any warming whatsoever.
Keeps FAILING to produce any evidence of human causation.
Seems there really isn’t any “A” in
AGW, after all !!Seems there really isn’t any “A” in
AGW, after all !!Do you have any evidence there is ??
A mindless void so far.
“You can’t even produce any empirical evidence that CO2 causes any warming whatsoever.”
Empty response, Proving me correct… Thanks. 🙂
Poor red-thumb just can’t face the reality.
“the fact that CO2 concentrations lag temperature by six months”
That is because you only tested for the lag. But CO2 fuctuations are dominated by seasonal periodicity. Six months lag is the same as six months lead. Try testing that.
It’s useless, of cause, because these fluctuations have nothing to do with global warming. No-one expects the annual fluctuation of a few ppm CO2 to have a detectable effect o T. What does have an effect is a 100+ rise in PPM sustained over decades.
And you know this, how exactly?
From bogus air temperature averaging gyrations of Fake Data?
Try presenting some evidence that CO2 causes any warming at all.
You have failed completely so far.
No Nick, I did not only test for lag. The technique I used would have shown CO2 leading temperature as a positive phase, or phase ramp.
The seasonal delays have a period of 1 year, and a frequency of 1 year^-1. At that point on the results the delay is not six months but is less than 2 months. The six month delay for most of the other periods likely reflects how long it takes for CO2 to distribute throughout the atmosphere.
I forgot to mention, your example of a six-month lag being the same as a six-month lead is only true at a frequency of 1 yr^-1. In the phase plot this ambiguity shows up as phase wrapping, which in these results only happens at some frequencies higher than 1 yr^-1. There is no ambiguity for a six-month delay over a 10-year interval.
We know you are well aware the temperature data is from totally contaminated urban and airport site, and has been strongly mal-adjusted to match the fake CO2 warming.
You would be here pushing this garbage otherwise.
Fake surface data from massively contaminated urban and airport sites.
Not remotely representative of anything global.
No counter… just a red thumb..
… so you accept what I said as true, just don’t like it….. oh dearie me, you poor thing.
Still no counter.. diddums
That’s another time series, Alan. The fit is reasonable only after about 1965.
Try charting temperature anomalies vs ln(CO2) or forcing. It’s quite interesting.
That would make sense, since CO2 has been the primary driver of the ongoing warming trend since the mid-20th century.
If you chart temperature vs ln(CO2) or forcing, you will see some really odd behaviour between 280 ppm and 320 ppm.
There is a pronounced spike centred around approximately 310 ppm.
Evidence needed, climate pseudoscientist.
CO2 has not been a “driver” of anything apart from enhanced plant growth.
You are yapping mindless anti-science AGW mantra BS, as usual.
Still no empirical scientific evidence that CO2 causes warming..
You FAILED again
Bullshit. CO2 is not a “temperature source”, nor is it a source of heat that can be quantified with units of hear. This is the nadir of thermodynamics for climate pseudoscience.
No, it’s actually pretty poor before early-mid 1960s.
CO2 forcing was quite low then, so it is not surprising that it was not dominating the trend.
It’s actually labelled correctly as “Earth’s surface temperature and atmospheric carbon dioxide (1850-2023)”, but the name of the graphic file is incorrect as global_temp_vs_carbon_dioxide_2023update.png
The chart as presented is a time series showing temperature on the left Y axis and CO2 on the right Y axis.
Global temperature vs CO2 would have the temperature as the Y axis and CO2 as the X axis.
NASA ignores the 1878 spike in temperature, and every month they adjust hundreds of individual monthly entries. In other words, they ignore and rewrite historical data. So far in 2024 their Land Ocean Temperature Index shows the following number of changes since January:
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
544 321 322 394 354 430
This goes on month after month, year after year.
AlanJ Nothing about the graph is accurate. There is no ocean temperature data worth using prior to WWII. The land data has been adjusted, adding a huge warming bias
Another great way to minimise the visual impact of the warming would be to use the kelvin (K) scale. This starts at absolute zero; so I wonder sometimes why these cretins don’t just use that!
They never use this argument for other worked examples; from the perspective of human body temperature, for example.
This ranges from 36.5 to 37.5 C (or 309.5 – 310.5 K, for the absolutists).
On the K, or even the C scale, a fraction over or under this and you’re dead.
Small differences can have big consequences, whether on human or global temperatures.
A drop from the current tepid global temperatures would indeed cause a lot of problems, destroy crop production , cause famine etc etc
But the planet has been quite a bit warmer for most of the last 10,000 years, as mankind developed.
A large proportion of the people living on the globe have to rug up and use heating for a significant part of the year, just to survive.
You and your marxist comrades are nothing but stupid chicken-little idiots cackling about a bit of beneficial natural warming.
“Another great way to minimise the visual impact of the warming would be to use the kelvin (K) scale. This starts at absolute zero; so I wonder sometimes why these cretins don’t just use that!“
Oh, they do Alan.
you underestimate their “Cretin-ness”
https://wattsupwiththat.com/2023/03/12/new-wuwt-global-temperature-feature-anomaly-vs-real-world-temperature/
And the irony is it was first done by an advocate of science (can’t remember who) posting on here over a decade ago as a way of showing the stupidly of reducing the y-axis to hide the information contained.
No-one underestimates how much of a moronic cretin you are A Badonned.
Cretinism oozes like slime from your every post.
The “consequences” of a warmer climate are all completely beneficial. That’s why the warmest climate during the current epoch, the Holocene, was dubbed The Holocene CLIMATE OPTIMUM.
So the small change in climate from the “pre-industrial” times to today has been hugely beneficial. Was that your point??
Yet, Alan, the whole point of the graph, colors and all, is an absurdity. We know that coming out of the LIA, temps would be warming. As time progresses, the graph must move from blue to red. This graph thus is logically and empirically tosh, piffle, useless, absurd. That is the conclusion one must draw even before reading Calvin’s helpful article.
Moreover, even if somewhat pedantic, a non-stationary series cannot have a mean against which to compare annual temps. It doesn’t exist — precisely because it is an absurdity.
Why do we know this? Surely it can only be known from a knowledge of the various forcing driving the climate state.
Only “forcing” is solar. and maybe some geothermal.
There is no measured evidence that CO2 forces anything except enhanced plant growth.
Exactly.
I am not sure that is the case. What makes you think that tendentiousness (a sociologically driven state) is and can only be the result of ‘knowledge of the various forcing[s] driving the climate’? Indeed one may not be able to define “forcings,” but one knows that leaving the LIA will only be brought about by warming.
This is a truism – the LIA ended because it warmed. Why did it warm? Why didn’t it continue cooling? Or stay relatively stable? Those are the questions we want to pursue. The observed warming trend is only a given in hindsight.
Well, sure, in 1851 or 1863, one might be justified in his skepticism. But by 1980, when warmism was blossoming forth, and absurd data began being vomited out by the hard left, we did know, didn’t we?
My point, Alan, is that these charts are bollocks. The underlying stats just can’t support it. Yet, otherwise articulate and stout fellows like yourself continue to step out on that ice.
Why are you so scared of some NATURAL warming from the coldest period in 10,000 years ????
WHY are you supporting a scam that is being used to destroy western society.????
The warming trend in GISS is meaningless as a measure of anything global..
You know that, but you keep pushing THE LIE.
WHY do that ???
What’s dishonest is claiming that CO2 is causing a Climate Crisis.
While this is true today, with the advent of forced ruinable generation adoption and removal of reliable generation grid sourced energy, the shortages of tomorrow will cause power outages during blocking high induced hot summers and eliminate A/C cooling attributing to a mass increase in heat related deaths. Heat related deaths driven by a lack of energy created by CC policies and ruinable mandates
That will also cause many more cold weather deaths. Bitter cold, still and cloudy weather means wind and solar will face plant when needed the most, especially in states dumb enough to require electric heating equipment.
“How would NOAA’s data for 1880 to 2016 look depicted that way? Like this:”
I don;t know why people here keep worrying about a return to 19th century temperatures given this graph. It would only mean cooling of around 1cm.
” 1cm “
My house cooled by 1cm last night and I had to put a wool sweater over my goose-down robe. 🙂
You do have a good feel for how followers think.
Cooling would cause a lot of problems with crop production.. That is how close the world is to being too cold.
This happened during the LIA, and the human population struggled, and many were lucky if they survived.
Most people on the planet still have to use heating and put on protective warm clothing for significant parts of the year.
On the warm side, most the last 10,000 years has been at least a few degrees warmer.. and populations flourished.
Good. So you agree with me that the “nobody notices a change of 1.5°C” is spurious. Average global temperatures are not comparable to the temperatures you feel in your room.
NOAA up until recently was claiming one recent year was hotter than another one. This was based on the assertion of 0.01 C hotter. When you look at their data the error margin was +/- 0.05 C. That is far worse than just deception
That trick only works 4 more times. Then the charts need adjustment.
Yes, NOAA and NASA both claimed that something like 10 years between the year 2000 and 2016, were the “hottest year evah!” (compared to the 1998 highpoint). NOAA and NASA managed to mannipulate each successive year as 0.01C warmer than the previous year, so they were screaming “hottest year evah!, year after year. The better to scare you with, my dear! It was all Climate Alarmist propaganda.
If you look at the UAH chart for the years from 2000 to 2015, you will find that UAH shows NO years in that time period that were warmer than 1998, and none of them could be proclaimed to be the “hottest year evah!”. The UAH chart debunks the “hottest year evah!” narrative of NOAA and NASA.
NOAA and NASA are lying to the public with their computers.
Any comment, Bellman?
Not sure what you want me to comment on. You just assume that if one data set shows less warming than the others, it must be true and all the others are fraudulent.
Number of warmest years isn’t a good metric for how much warming there has been. The mean difference between UAH and the surface data sets is that it shows a slightly slower rate of warming since 2000, but also much bigger spikes for El Niños and La Niños. This is very noticeable in 1998, which is why it took some time for UAH to beat that record.
Here are the three data sets you mentioned, adjusted tot he 1981 – 2010 base period.
“Not sure what you want me to comment on”
I want you to comment on the discrepancy between the UAH data and the NOAA/NASA data, for the years from 2000 to 2015.
The UAH data shows NO years between 2000 and 2015 that could be described as “the hottest year evah!”.
Whereas, the NOAA and NASA data shows about 10 years between the year 2000 and 2015 as being the “hottest year evah!”, and on top of that Lie, NOAA and NASA managed to massage their data so that each consecutive year is warmer (0.01C) than the previous year, so they can make it appear that the warming is relentless and going higher every year. The better to scare you with, my dear.
Very convenient if you have a Climate Alarmist agenda where you want to scare people into thinking the Earth is getting hotter and hotter and hotter and we are now at the hottest time in human history.
One could not make that argument using the UAH data because none of those years is warmer than 1998.
So NOAA and NASA are mannipulating the data to sell their Human-caused Climate Change narrative.
I want you to admit that is the case. How can you deny it? One would have to be pretty naive to think NOAA and NASA are telling us the truth about the temperatures. They are Climate Alarmist Propagandists and nothing more.
They ought to be prosecuted for lying to the American people and the world.
The problem with the graph isn’t the presentation of it, its that the graph uses adjusted data where the adjustments add significant warming. This is well known. Anyone that has looked at the temperature records around the world should know that 1921 was a warm year in China, Europe, the US, etc. There is no way that temperatures in the early 70s were warmer than 1921.
The graph is a outright fraud.
Nelson,
Agreed, the important argument is whether only factually observed temperatures are used or if temperatures created or altered in the minds of people are used.
If the latter, there is no scientific justification for admitting the concept of statistical uncertainty. There is no text book on the treatments of guesses. There are texts on the interpolation and extrapolation of spatial data, especially when looming at the distribution of grades in a mine, but these have an important difference -nobody claims that a point grade here is one sigma higher than a point grade there and so sets a record. We just say that the interpolation gets to send that block of ore to the ore stockpile, or the low grade stockpile or the waste rock dump, or however the particular mine process stream is designed.
There was lengthy discussion of temperature uncertainties on WUWT a couple of years ago in 3 articles I wrote, search “Sherrington uncertainty”. I have not seen any major gains in understanding this problem of adjustment since then, only ongoing interminable argument as “sides” refuse to accept positions of each other or abide by the proper NIST guidelines. Geoff S
There is no climate crisis.
There is a lot of [climate] hysteria about.
The only crisis is there are not enough caves on earth for people to hide in during inclement weather.
E. Calvin Beisner – – – Nicely done, Sir.
Full honesty would require that the proponents of the global warming scam also admit that the gentle mild warming we’ve had has been nothing but good news for life on Earth both human and otherwise. The crisis is entirely “man-made” as in invented in the human imagination with the assistance of bad math and compliant computers.
I’m hoping I get another 1c out of whatever drives it.
With the assistance of bad actors, liars, and greedy power elites.
“With the assistance of bad actors, liars, “
What I don’t get is why they want to help destroy the society that they are part of, by promulgating the lies and deceit of the climate agenda…
.. aiding in the moronic Net-Zero and idiotic anti-CO2 agendas.
Are they really that DUMB that they can’t see the scam they are supporting !??
They’re grifters positioning themselves to profit from “investing” in worthless things made “requirements” by stupid policies.
You know, like wind and solar “farms” and battery powered cars.
The total data difference, top to bottom (of the data) is about 1.7°C which converts to the difference between 68°F and 71°F (approx.) That is a discernible difference if one is walking from one room to another in an office building — for most people. But the Daily Average temperatures, from average high to average low, each month, in my state (New York), are remarkably consistently about 15°F apart.
So, for people in New York State, the appropriate scale would be 15-20°F or 8-10°C.
From our average experienced lows to our average experienced highs.
At that scale, the GAST (Land and Sea) graph would show a slow and gentle slight warming of the last 140 years — which is a realistic viewpoint.
Land and sea is a big place. Global average temp is not a very useful measurement. People around here say they will have to modify farming practices because of Global Warming. But in fact, average winter and summer temps have gone down since records started in the 1930’s. I saw a map one time showing temp anomalies with most warming in the western Arctic at night. Global Average Temperature itself is deceptive. The average human has one testicle and one ovary.
Try hopping back and forth between NYC and Canberra or Dubai once a month or weekly and you have a better idea of what the Earth “experiences” all the time. GAT is a farce! The “anomaly” of GAT is a farcical hoax!!
The main effect of greenhouse warming, which is the main symptom of warming after 1975, is warmer winters. Thet climate change is VERY easy to notice here in SE Michigan. No Ph.D. scientists, GATs or thermometers required.
And no evidence human released CO2 had anything to do with it..
And no evidence that “climate change” is anything other than cyclical, natural changes. The climate warms for a few decades and then it cools for a few decades, and then this pattern repeats.
Cherrypicking one part of the cycle, the warm part, is misinterpreting the situation.
Which is of course 100% good news.
“climate change is VERY easy to notice here in SE Michigan” [Richard Green]
You don’t say where you are, but consider Wayne County, (the Detroit region). Reported population in 1850 was 42,756. This grew to 2,666,751 in 1970. Then things ‘turned-south’; dropping to 1,751,169 in 2023 (est.). That’s a lot of people firing up the SUV and leaving. Now, consider that the average human generates around 100 watts in a day – a bright light bulb.
All the human produced heat should be VERY easy to notice. I, however, in a very rural area with more cattle than people for the last hundred years – experience no change. Tomatoes still won’t set fruit. 😒
I don’t know about Michigan, but here in NC I haven’t seen any noticeable “climate” change over the last 16 years since moving here.
One thing I learned as a research scientist is that, often, solving a problem or rendering it a non-problem is not in the senior scientists’ economic interest.
This is undoubtedly the case with climate scientists. What are they supposed to do if humanity says: ‘this really isn’t a big deal: we’ll keep monitoring things, but we don’t need to spend billions any more on climate modelling.’
In the private sector, this happens to employees often. They are laid off due to a business division no longer being very profitable. They just have to get on with life, find a new job and start afresh.
But apparently, this can’t happen in academia. Their strong global trades union (unofficial but remarkably pervasive) has had this gravy train going strong for 40 odd years now.
When argument is based on deception, misrepresentation, collusion, rather than honest, dispassionate analysis, the need to scare becomes necessary.
What we need are some politicians who say: ‘Enough with the fearmongering! Deep budget cuts for warmists, new funding streams for basic research on natural climate variations!’
Where else could a tenured “climate scientist” get a job?
So, gotta keep the current gig going until retirement.
I don’t think there are many climatologists like Judith Curry or Roger Pielke Jnr who can stand on their own 2 feet and apply their expertise in self-employed enterprises.
There are 2 undeniable problems with global average temperature constructs that render them not fit for purpose –
1) the probity of the inputs .
2) the provenance of the inputs
Both graphs in the above article are said to depict “Global Land and Ocean Temperature Anomalies, 1880–2016”. That’s real cute, but here are just a few of the MAJOR problems inherent in such a “data” set:
1) How, if at all, has the data been “adjusted” to account for the fact that there was very sparse distribution of “global” temperature measurements pre-1950 compared to post-1950? What is the rationale that says it is scientifically credible to present them as being comparable in any way?
2) How, if at all, has the data been “adjusted” to account for the fact that the accuracy of thermometers (of all types) has increased markedly from 1880 to 2016?
3) How, if at all, has the data been “adjusted” to account for the fact that many more land stations and ocean buoys designed specifically to obtain scientifically accurate/representative temperatures have been emplaced post-1950 compared to pre-1950? Examples of the progress post-1950 would be the implementation of the USCRN and the implementation of the Argo program that has deployed about 4000 sea-temperature measuring floats across all of the world’s oceans.
4) How is the sea-surface (liquid water) temperature adjusted to make it truly comparable to the air (near-surface atmosphere) temperature measured by land stations. Is the air over water (to an elevation of say 2 m) just assumed to be the same as the surface water temperature? Alternatively, are only a comparatively few weather station buoys or platforms above the sea surface having ambient air temperature monitoring used for the ocean component that is combined with the land component to obtain the “global average”?
5) Is any of the “ocean” temperature data based on ship measurements of water temperature derived from bucket-retrieved sea water, of from engine-intake water temperature measurements?
6) Has the algorithm, if any, for “normalizing” land temperature measurements (air above surface) for absolute elevation above sea-level (reflecting the dry/wet adiabatic lapse rates) remained unchanged from 1880 to 2016?
7) Have the algorithms for “smoothing and proportioning” both land and ocean temperatures, as measured at many non-uniformly-distributed individual geographic locations, to obtain an areal-adjusted “average” remained unchanged from 1880 to 2016? The necessary areal adjustment is sometimes associated with the data analysis term “infilling”.
8) Has the algorithm for combining “land” temperature measurements with “ocean” temperature measurements to obtain a “global average” remained unchanged from 1880 to 2016?
9) How, if at all, have the land temperature measurements been corrected for the now-well-known-and-scientifically-documented errors due to the Urban Heat Island (UHI) effect. This is a pernicious problem in most third-world countries that have not be able to implement WMO standards for construction and siting of scientifically-accurate temperature monitoring stations.
So many detailed questions for something just presented on face value. Consequently, for anyone who accepts the claim that “global average” temperature can be established to a resolution of ± 0.01 °C year-after-year, as implied by the first graph in the above article . . . well, I have a bridge to sell to you.
ToldYouSo,
There is enough evidence that land and water temperatures change at different rates to make a comparison between them pointless and invalid, like the story of the race between the tortoise and the hard. Geoff S
ToldYouSo
Nicely done. These points can’t be made too many times.
Only in the US is there a set of weather sites suitable for measuring temperature change over time.
Even in so-called modern countries like Australia, UK, EU… a very large proportion of sites are completely UNFIT-FOR-PURPOSE.
One can only imagine how bad sites in 3rd world countries might be!
There are some very unpleasant politicians in critical places who have never had any interest in Public Health but do have a lot of interest in the power and control of an even less healthy kind to their targets – the power of a frequently repeated lie. Each person who repeats these lies is as guilty as the perpetrator and needs to be told so very publicly. A very pernicious lie currently doing the rounds is that carbon dioxide causes warming when there is absolutely zero evidence to support such a claim. Despite several repeated requests for such evidence to be produced zero has appeared in fifty plus years. We are told the evidence is global warming but the figures just don’t suggest or support an argument that carbon dioxide has anything to do with it at all.
Very nice. This is really important, the government needs to stop lying and misleading.
Also the choice of reference period matters
(Reproduced from https://www.climate-lab-book.ac.uk)
Very good article
But the honest chart here is not the best I’ve seen. I prefer the one I used on the home page of my old Honest Global Warming Chart blog:
Honest global warming chart Blog (elonionbloggle.blogspot.com)
On my new blog, I used to present the UAH monthly anomaly chart in 2023 but decided to ban it in 2024 — it is just as misleading as every other temperature anomaly chart. Makes a small GAT increase look huge.
But even an absolute average temperature chart is misleading. The average temperature in the 1800s is a wild guess. Pre-WW2 is not much better. The 1940 to 1975 global cooling has been almost completely “disappeared” … and no one lives in the average temperature.
One average temperature also obscures the fact that the majority of warming is TMIN, not TMAX, and is mainly in the six colder months of the year.
Climate science does not need:
Long term climate predictions
Anomaly GAT charts
A single GAT that does not show TMIN and TMAX
Claims that warming is bad news when the first 48 years of actual global warming, since 1975, was good news.
“majority of warming is TMIN”
This can only be measured at land sites.. mostly in URBAN areas.
It is exactly what the urban warming effect does.
It is NOT FROM CO2
And it is NOT GLOBAL.
The USCRN all rural US average shows faster warming than the mainly non-rural nClimDiv average.
You can’t explain that because you have no inside information about NOAA but will claim you know.
Temperature fluctuations between daytime and nighttime are much greater over land than over water. This is known because ocean diurnal temperatres are measured with ARGO floats.
The diurnal temperatures on land are much more important than oceans because they are much larger variations and almost all people live and work on the land.
You remain ignorant on a wide variety of subjects.
Poor little mindless RG.
Still hasn’t figure what the “R” in USCRN stands for and has been used for, despite being shown dozens of time.
HILARIOUSLY DUMB. !!
You remain deliberately ignorant on basically EVERYTHING to do with maths and science.
Now.. where is that empirical scientific evidence of warming by atmospheric CO2 ?
We have been waiting , like , for evah !!
Increasingly rural area weather stations are closing and urban UHI affected stations are remaining to enhance the warming measure. The lying starts before the graph is even drawn.
Superfluous bureaucrats qualifying their existence. What they produce has a negative value, yet they continue to receive a paycheck. Their short-term weather predictions are fantastic. Their long-term predictions are fantastical.
““Missing Context”: How Climate Catastrophists at NOAA Mislead without Lying”
Ah but the fact is they are lying about the data in addition to this set dressing of scale and color.
Plotting actual measured temperature in the US Historical record (the only long term record with substantial data) against the adjusted data shows how much the data has been altered as in the first graph attached. They have artificially cooled the past and warmed the present.
But the real smoking gun is when you plot these adjustment values against CO2 concentration, it is a straight line as in the second graph attached! Hmm, so they have adjusted the data in a manner which supports their hypothesis that CO2 concentration is the sole cause of warming. Is that not the antithesis of the scientific method? The raw data in fact refutes the CO2 as control knob hypothesis. That the data is changed to fit the hypothesis shows their fraudulent actions in stark detail.
I posit that graphs of their own data manipulation shows they are in fact guilty of lying to the public and all those perpetrating this fraud should be fired, banned from any government or academic employment, and possibly criminally charged and jailed.
It shouldn’t need saying that the truth must be the whole truth and nothing but the truth. Partial truth is not the truth, but the worst lie.