I am, and you will be, too, absolutely delighted by a new paper by Roy Spencer: “Global Warming: Observations vs. Climate Models“.
This is a paper that will be celebrated with great joy and fervor by the great sea of people who are worried, near unto death, that “climate change” is going to cause the destruction of all things.
Roy showed that, “The observed rate of global warming over the past 50 years has been weaker than that predicted by almost all computerized climate models.”
And that, “Climate models that guide energy policy do not even conserve energy, a necessary condition for any physically based model of the climate system.”
He concluded: “Public policy should be based on climate observations—which are rather unremarkable—rather than climate models that exaggerate climate impacts.”
What wonderful news! News sure to be welcomed by activists, politicians, and exhausted windmill replacement blade salesmen the world over!
All those people who drag themselves out to early morning marches can sleep in! Been considering gluing yourself to works of art or the asphalt? No need! And you needn’t keep your appointment with your therapist to work on your devastating climate anxiety. Hallelujah, there is nothing to be anxious about!
I fully expect the White House will invite Roy to receive some kind of medal or award for the great scientific service he has done our panicked nation, and indeed the world. There is no reason for the anxious, nerve-wracking despair we have seen from all quarters. The order of the day shall be Stand Down and Enjoy the Weather!
Right?
Here’s the best bits, which are so good they’re self-explanatory.
We’ll come back to that caption in a moment. Because what it means is that things are even better than Roy has suggested, sober and cautious man that he is.
This is the kind of plot scientists or yore would look at and say, “Oops.” As we are confident modern scientists will do, too. They got it wrong, and badly wrong. Embarrassingly wrong. So wrong that they will surely go back and fix the mistakes before allowing anybody to even see, let alone rely on their models.
What I like best about this are those three lines, the green, black, and blue ones, which show the average temperatures from three different measurement sources. I make the discrepancy between the three 0.2C at the end, or perhaps a bit larger. Say, that’s a lot, isn’t it? Especially when the hand-wringing in the “climate community” has been over tenths of a degree changes.
What this means is that there is more uncertainty in climate measurements than what is normally considered. So much more uncertainty that it is yet another reason not to worry. The good news multiplies!
Roy goes on to suggest why climate models produce too much warming, and gives hints about other causes besides man that account for observed signals in temperature. Read the whole report. It’s good—and cheering!
He says things like, “The models must be ‘tuned’ to produce no climate change, and then a human influence is added in the form of a very small, roughly 1 percent change in the global energy balance.” This kind of tuning over such a small signal would make any model hyper-sensitive to the tuning. Which indeed we see.
Let’s return to the footnote on the first plot, which brings us to this site. Which you might want to play with. One word you’ll see on the site is “hindcasts”. I don’t want to get into the details today, but what it means is that past data is used to make predictions of the past. The past data is first used to create the models which make the predictions.
Nothing wrong with that, of course, because models have to be built somehow. But it does mean hindcasts—predictions of past data that was used once already in creating the models—will be better than forecasts, which are predictions of data never before seen.
So that when we look at the first picture and it looks like the models did better in the past, the reason for that is at least partly because the models are tuned to that data. Which means that true model performance is better estimated at the ends of the series. Which is worse performance. Which is more good news!
Another thing I think is true here (though I welcome correction) is that these are all one- or a few-time-periods-ahead predictions. That is, a climate model today could make monthly or yearly temperature predictions for next month or next year, or two months ahead or two years. Or three years, four, and so on. The predictions farther out will, all evidence suggests, be worse, and even far worse, than predictions made one time period ahead.
I think these pictures are all one-time-period-ahead predictions (made one at a time). If so, and if the farther-out predictions are worse like we expect them, and given the poor performance of these models near term, then that means we must put even less (or even no) trust in long-term predictions.
Which, again, is more great news! Whoo-hooo!, as The View audience would hoot. Because if the models are that bad, there’s no reason to get worked up over them.
I saved the best news for last. Most of what knots peoples’ panties about “climate change” are not small changes in some weird artificial global average temperature, but all the bad stuff that “climate change” is said will cause. Which is every bad thing.
Don’t you see why that’s terrific? Since the climate is not as bad as the models predicted, all that other bad stuff can’t be so bad either. Fantastic! Let us hear the sighs of relief sure to greet this spectacular news!
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Seen on an ASA t-shirt: Friends don’t let friends extrapolate.
But where’s the fun in that?
Let me be among the first to denounce Roy Spencer for weaponizing his obvious White European Male rectilinear quantitative rationalizing and his over-reliance on published evidence for this transparent attempt at denying me, and thousands of others, of our oceanic, nay cosmic, source of anxiety and rage. If I am denied cause for raging at my neighbors, my society, my civilization, and even myself, how can I continue to shout at the sky? And what the hell am I going to do with all my “Save the Planet” t-shirts and keyfobs, the half-dozen reusable stainless steel drinking straws, and that sonofabitch battery-operated car in the garage? My scientismic life is in ruins.
What are you trying to do here Briggs crash the price of oil?
And just like we nipped ivermectin in the bud don’t even ask
about dams.
Query – Are the temperature data sets being used here the real data, or the “adjusted” data the government uses? Which, quite naturally (since their funding depends upon it), always “adjusts” recorded temperatures upwards.
Nice! I had not seen this earlier.
One comment on Dr. Spencer’s white paper: he cites the 2-CO2 meme several times, but only incidently refers in mid stream to the assumed level of pre-industrial atmospheric CO2. This is a trivial fix and should be done.
Three other comments:
1 – the data streams he cites march along in lock-step -and because that means that those responsible for managing the data are peeking over each other’s shoulders and making adjustments accordingly, it cannot be trusted.
2 – many decades (well ~2.5) ago I had the opportunity (on assignment and bored) to review the source code for what was then a major nationally recognized climate model modified to run on the supercomputer at oak ridge. Most of the code was taken up by making it run in parallel with the rest mostly falling into two categories: reflections of the original fortran card deck circa 1960; and, hundreds of patches (many simply inserting “print this_data_table”) put in by grad students etc trying to make it hindcast well.
3 – Dr. Spencer’s white paper here is for the non technical, so a technical comment may not be appropriate – but, regardless of that, he accepts throughout the idea that temperature ‘anomalies” constitute data. They don’t – in fact, they mislead. The idea is that you want to compare a small change in area 1 where the ave daily temp is -X to change in area 2 where the average is +X1 but those deltas reflect non linear change and so cannot be compared except as f(d1) vs f(d2) but that’s not done – instead people compare d1 to d2 as numbers.
I’ve been stockpiling ice cubes. Do you think I should get a refund?
We should display these charts in public near the electric vehicle charging stations so that all stuck in their cars for several hours those waiting in line in the bitter cold can have some reading material.
If the climate hysterics, renewable energy crooks, Jesus-complex gurus (Kerry, Gore, Thunberg, et al), hoodwinked politicians, and other useful idiots ever even read this paper, all it will inspire them to do is double down on climate crisis idiocy.
I’m glad I didn’t buy any carbon credits.
Nobody cares any more. Get with the programme, it’s all about five years plans for war production. 155mm artillery shell production must increase by 500% in all NATO countries.
Now… it is about the rate of warming is not as fast as predicted, not about whether global warming is happening. . Good news.
The large discrepancy between the red climate-models line and blue observations starts around 1995. So, I guess that those models were initially constructed based on the pre-1995 (or earlier) observations as the red line seems to follow the data closely before 1995.
1995 to 2023… that is a long horizon.
It is no secret that as the time horizon increases, the prediction performance is expected to deteriorate. If model uncertainties are incorporated and plotted (bands), the pre-1995 data fluctuation tells me that it is not unlikely that the observations would lie within prediction bands.
Well JH, you’re assuming that the 1995 models were used to make long term forecasts up to 2023.
Briggs believes these are short-term, example: 1995 model used to forecast up to 2000, then updated in 2000 with more accurate data from pre-2000 years to forecast to 2005, then updated earlier in 2003 to forecast up to 2013, then updated in 2007 to forecast up to 2020, etc. etc.
In other words, there is no fixed Weather ’95 model they’ve relied on all these years, but like your Windows Operating System, there are constant updates leading to Weather ’98, Weather 2000, Weather XP, Weather 11 Professional Edition patch ver.3.88.345, all making NEW updated predictions for the years ahead with supposedly improved data…
And YET…
The predictions keep getting further and further away from reality!
Either the new programmers are getting more incompetent due to diversity hiring.
Or the weather’s factors are far more complex and unknowable that scientists thought.
Or the models are deliberately told to say what the WEF wants them to say, meaning the models are rigged with political data and algorithms to match the ruling class’ predictions and nothing at all to do with actual weather data!
Johnno,
Great, you read the post and got something out of it.
If the red lines in the graphs were constructed according to the way Briggs and you describe them, they would have been closer to the observations. For example, if data from 2002 – 2008 in the first graph, during which there appears to be a flat (if not down) trend, were included, the predictions would not fall in the red line with a shaper trend.
The comments after “And YET” are garbage.
JH
No stupid.
The red line is only the predictions. Not corrections after-the-fact to accord with observations.
If they updated the models after-the-fact, those would then be used to make the new predictions.
Your problem is to explain why and how with more data and corrections and updates, do the models get further and further away from reality? And why only up?
As you yourself said, maybe they ought to have trended flat or down with the data. So… why didn’t they?
Let’s help you out here… All models say what they are told to say. Biased assumptions are tailored into the math, by design. And it is instructed to demonstrate warming, no matter what numbers you plug in. Because the scientists dogmatically believes in, and/or whoever is funding these, wants warming results.
Garbage is built in, therefore garbage out. And that is precisely what my YET is pointing out to you – your garbage models.
Johnno,
Gee, you are so.so.so smart by calling me stupid. LOL!
Your problem is to explain why and how with more data and corrections and updates, do the models get further and further away from reality? And why only up?
Problem? I guess either I was unclear or you just don’t understand time series forecasting.
Why only up? Probably because the lines were not constructed based on the following strategy. (Just repeating what I said. And you shall get no more explanations from me.)
There is no doubt that smart people like you would have no problems doing the following. Go online, find temperature data series, attempt to (1) analyze as you described (2) forecast based on a 1995 model (and you shall see why predictions deviate further from the observations). Nothing better than learning by doing.
I’d be a lot happier if the measured data didn’t go “from bottom left to upper right”, regardless if it’s doing so at a slightly lower rate than the model predicts it would.
JH & Johnno
Because the data used to check models via backcasting keeps getting adjusted.
Pure, brazen disinformation typical of Briggs. Infodemia exceeds all levels of decency and urgent measures are needed to deter it.
If Briggs does not immediately end his irresponsible climate disinfo campaign, I will personally report him to Vladimir Vladimirovich’s e-mail to add him to the list of individuals who discredit the goals of the multipolar world’s Special Climate Operation (SCO). Give up your subversion in favor of American hegemony, Briggs. You better listen to me…
Patient,
My army of dedicated minions are even now searching for you. Beware.
(Personally to V.V., by email. No mercy on climate enemies.)
I’ve been following climate science since 1997.
What are called climate models are merely computer games. I call them confuser games.
They predict whatever they are programmed to predict. They are programmed to predict whatever their owners want predicted. Their owners want scary climate predictions and that is exactly what they get.
The only exception is the Russian INM model that apparently tries to make accurate predictions, resulting in the weakest predicted rise of global warming or all modelas, which gets that model ignored. Probably just a lucky guess, IMHO.
The models are all strongly emphasizing radiative physics, mainly CO2, but also SO2. There is very strong scientific agreement on lab spectroscopy measurements of the effect of various gases, in the HITRAN and MODTRAN databases.
Those measurements suggest that CO2 is a weak greenhouse gas above the current 420 ppm (().042%) that could not cause much global warming if atmospheric CO2 doubled, which would take 168 years at the current rise rate of +2.5ppm a year
That would not scare anyone. … So the Climate Howler Global Whiners add a water vapor positive feedback that they claim, with no evidence, could doubler to quadruple the effect of CO2 alone. Suddenly we have an imaginary climate emergency, for which the only solution is fascism.
The 1970s confuser models, as a group, when programmed with a realistic CO2 growth rate and a modest water vapor positive feedback, made 70 year average temperature forecasts that have been remarkably accurate in the first 50 years of the 70 years forecast.
Change the assumptions and the same batch of 1970’s era models predicts a 100% faster global warming rate — the rate used by conservatives to claim the models predict too much warming.
If you are still awake, here is my conclusion:
The confuser games are not models of the climate on our planet. Not enough is known about climate change to create such a model. If a model appears to be accurate, that appearance is just a lucky guess.
Even with great knowledge of Earth’s climate, there is no evidence predicting the climate in 100 years will ever be possible: Except by me: In 1997 I predicted the future climate would be warmer, unless it is colder.
My latest research, since 1997, is even more exciting: I have a theory that it is impossible to prove anything. But I can’t prove it.
https://honestclimatescience.blogspot.com/
Paul Murphy,
Thanks. I think you are talking about the predictor values (attributes data) used in the models.
I was curious as to why the simulated/predicted temperature anomalies appear to align well with observations from pre-1995 in the graphs shown in this post.
I did a quick study this morning. So, the math models can be tuned to compare well or to give the best representation of the temperature observations up to a certain year. They are then employed to make predictions for the years to come. The choice of this certain year may alter the trend of the red line (model average).
If an analyst chooses to tune the models to produce predictions aligning with temperature observations up to 2000, then the trend of the red line (model average) might be dampened as there seems to exist a downward trend during the few years right before 2000.
Furthermore, without accounting for model variabilities, one may easily manipulate the results for propaganda.
The study of global warming seems interesting. However, it is an epitome of “how politics ruins everything.”
I’m always gratified when people like who I think are very smart agree with my estimation. One of the small comforts of the midwit. Dr Roy Spencer was the first guy to introduce me to the idea that the parameters of the used to model the temperature are those of the used to predict the temperature! He also studied the heat island effect – the idea that increased population density near ground reading stations could be affecting their measurements. That is interesting, given that the local weather monitoring station is upwind of a growing city center.
The truth is, I do believe in sustainability as it was defined in the paperback dictionaries. A little thrift is not a bad thing, but when I failed a course in “sustainability” what I learned is the heart and soul of it is Public Private Partnerships. Everyone has their cynical presumptions about those connections, but it provides a verifiable paper trail of the convergence of predatory finance, petty tyrants and Coudenhove-Kalergi’s perverse breeding programme. [He was one of Rothchild’s goons who helped rally the development of the EU.]
I was sitting with an ex-con the other day and a trite teeny bopper song came on. He turned it off saying some sadistic gangsters had given him the beating of his life to that song. It reminds me of how Kalergi chose “Ode to Joy” as its ‘Anthem’
Ah, but the crisis is not over. See that peak in 2016, and then a decline from there? The climate alarmists will claim this decline is due to their actions and surely we must now do even more.