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Remember how all the news stories keep telling us the evidence is growing and getting stronger than ever “against the skeptics”?
David Stockwell has done a beautiful graph of the value of climate sensitivity estimates that of recent climate research that Steven McIntyre discussed in detail.
The trend looks pretty clear. Reality is gradually going to force itself on the erroneous models.
…
Indications are that around 20202030 climate sensitivity will hit zero. ;- )
The red line is ECS — Equilibrium climate sensitivity — which means after the party is all over in years to come, in the long run, this is how much the planet responds to a doubling of CO2.
The blue line is TCR — Transient Climate Response — is an estimate of what happens in the next 20 years. It’s a short term estimate.
Obviously the big question is: What happens when climate sensitivity goes negative?
Check out NicheModelling, Stockwell’s great blog, it deserves more attention.
h/t David, Lance, Ken
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In the topsy turvy world of modern science, big-government has strangled science to the point where bright outsiders know more than the fully trained “experts”.
Maurice Newman, the chairman of the P.M’s business advisory council, daringly wrote in The Australian:
“It’s a well-kept secret, but 95 per cent of the climate models we are told prove the link between human CO2 emissions and catastrophic global warming have been found, after nearly two decades of temperature stasis, to be in error.”
In Senate estimates, a Greens spokesperson asked Dr Rob Vertessy, Director of the Australian Bureau of Meteorology (BoM) on his view of this. “That is incorrect,” he said, showing how little he knows about climate models, where everyone (even the IPCC) is trying to figure out excuses for their failures. Some even invent time-travelling climate models that can finally “predict” today’s climate correctly a decade after it happened.
If Maurice Newman was wrong, he was far too generous to the climate modelers. Instead of a 95% failure rate, it’s well up over 98%. Hans von Storch et al published a paper nearly two years ago comparing models and observations of a 15 year long pause. Statistically von Storch […]
A new telescope has peered into the Sun to see solar magnetic flux ropes for the first time. Severe flux rope twists have been described as being like “earthquakes” on the sun, and are linked to eruptions of large solar flares that change magnetic fields, and cause radiation and energetic particles to rain on Earth.
We don’t know much about solar magnetic flux ropes. We know they affect space weather, but thanks to climate experts we already “know” they can’t possibly, ever in a million years, affect Earth’s weather. Even though we’ve only just been able to see them and have no long term data on them, we have Global Circulation Climate models (which don’t include these solar factors), so we have 95% certainty that none of the particles, fields or radiation changes have much impact on Earth. They might fritz satellites, electronics and communications, but Earth’s atmosphere has no electrical component (wink), and the models “work” (kinda, sorta, apart from “the pause”, the arctic, the ocean, the antarctic, and the holocene) without any of this fuzzy solar stuff. Got that? Repeat after me. The Sun does not affect Earth’s climate. (Good boys and girls. You are fit for a […]
The Climate Council calculate the “odds” that one warm year could be as hot as it was. But those “odds” depend on a logical fallacy, major, inexplicable adjustments and models we know are broken. There are invisible assumptions underlying that claim which are documentably untrue. The “odds” might as well be lotto results.
The fallacy is argument from ignorance, a failure of logic and reasoning like saying “X is true, because we can’t think of anything else“.
To estimate meaningful odds, scientists would have to understand the major driving factors of our climate, well enough to be able to assign probabilities to outcomes. But their models are hopelessly broken, they can’t predict a decadal average on a global or continental scale. They can’t hindcast the past “bumps” without using major adjustments to make the raw observations fit the models. They don’t know why the medieval warm period was warm, they don’t know why the Little Ice Age was cool. They don’t know why the world started warming 200 years before we poured out industrial levels of CO2. They don’t know if the mystery factors driving our climate for the last 4.5 billion years are still operating. If we can’t predict […]
Two papers on ocean heat released together today. The first says the missing heat is not in the deep ocean abyss below 2000m. The second finds the missing heat in missing data in the Southern Hemisphere instead. Toss out one excuse, move to another.
The first paper by Llovel and Willis et al, looked at the total sea-level rise as measured by adjusted satellites*, then removed the part of that rise due to expanding warming oceans above 2,000 m and the part due to ice melting off glaciers and ice-sheets.** The upshot is that the bottom half of the ocean is apparently not warming — there was nothing much left for the deep oceans to do. This result comes from Argo buoy data which went into full operation in 2005. (Before Argo the uncertainties in ocean temperature measurements massively outweigh the expected temperature changes, so the “data” is pretty useless.)
Figure 2 | Global mean steric sea-level change contributions from different layers of the ocean. 0–2,000m (red), 0–700m (green), 700–2,000m (blue). The dashed black curve shows an estimate for the remainder of the ocean below 2,000m computed by removing the 0–2,000m estimate from the GRACE-corrected observed mean sea-level time […]
Finally, for only the 87th time, climate modellers have uncovered the definitive proof they’ve been finding in different forms every year since 1988.
ARC extreme unscience – corrected at no cost to the Australian taxpayer. Click for a big printable copy.
They seek, and find, the most excellent propaganda they can pretend is science. Look, this is the specific handprint of non-specific climate-change! Everything bar climate-sameness is proof the climate changes. How inane? The unscientific vagueness gives this poster away as being more about propaganda than about communication of science.
… in a special edition of the Bulletin of the American Meteorological Society, examining extreme events around the world during 2013, a series of papers home in on the Australian heat waves, and identify a human influence.
Using short, noisy records, with flawed and adjusted data, it is possible to run broken climate models and show “definitively” that current heat-waves and hottest years are due to man-made emissions. And if you believe that, you could be gullible enough to be a Guardian journalist.
That is, climate models that do not include solar factors like magnetic fields, solar winds, cosmic rays, solar spectral changes, or lunar effects are able to […]
You won’t believe… Research shows surprise global warming ‘hiatus’ could have been forecast
[The Guardian] Australian and US climate experts say with new ocean-based modelling tools, the early 2000s warming slowdown was foreseeable. Australian and US researchers have shown that the slowdown in the rate of global warming in the early 2000s, known as a so-called “global warming hiatus”, could have been predicted if today’s tools for decade-by-decade climate forecasting had been available in the 1990s.
And I’ve got a model that would have predicted the 1987 stock market crash, the GFC, and the winner of the Melbourne Cup. What I would not have predicted is that lame excuses this transparent, would be made by people calling themselves scientists, Gerald Meehl, and repeated by people calling themselves journalists. (That’s you, Melissa Davey). Though I’m not surprised that research this weak had to be published by Nature. (Where else?)
Although global temperatures remain close to record highs, they have shown little warming trend over the past 15 years, a slowdown that earlier climate models had been largely unable to predict.
This has been used by climate change sceptics as evidence that climate change prediction models are flawed.
Imagine that, the stupid […]
Remember how CO2 is supposed to cause warmer winters, and warmer nights? Well now CO2 also produces cold snaps. No matter what weather you get, there is a citation to blame CO2. Nature (the formerly great science journal) and Northeastern University have produced another permutation of outputs from models we know are broken.
The first line in the press release is false and smugly so: “most scientists — 97 percent of them, to be exact — agree that the temperature of the planet is rising and that the increase is due to human activities….” 10 seconds on Google would have shown — 60% of geoscientists and engineers don’t agree.
If Kodra and co were trying to be accurate, they could have said “97% of annointed climate scientists agree… “. If they were trying to be scientific, of course, they wouldn’t mention a consensus at all. If they had good evidence, they’d talk about that instead.
They dug deep in The-Book-of-Cliches for the press release. Strip away the advertising spin and I think this is the nub of the work:
“While global temperature is indeed increasing, so too is the variability in temperature extremes. For instance, while each […]
We could spend hours analyzing the new IPCC report about the impacts of climate change. Or we could just point out:
Everything in the Working Group II report depends entirely on Working Group I.
( see footnote 1 SPM, page 3).
Working Group I depends entirely on climate models and 98% of them didn’t predict the pause.
The models are broken. They are based on flawed assumptions about water vapor.
Working Group I, remember, was supposed to tell us the scientific case for man-made global warming. If our emissions aren’t driving the climate towards a catastrophe, then we don’t need to analyze what happens during the catastrophe we probably won’t get. This applies equally to War, Pestilence, Famine, Drought, Floods, Storms, and Shrinking Fish (which, keep in mind, could have led to the ultimate disaster: shrinking fish and chips).
To cut a long story short, the 95% certainty of Working Group I boils down to climate models and 98% of them didn’t predict the pause in surface temperature trends (von Storch 2013) . Even under the most generous interpretation, models are proven failures, 100% right except for rain, […]
The backdown continues. Faced with the ongoing failure of their models, the search rolls on for any factor that helps “explain” why the official climate scientists are still right even though they got it so wrong. The new England et al paper endorses skeptics in so many ways.
The world might warm by only 2.1 degrees this century, not 4c. (Skeptics were right — the models exaggerate). There has been and is a pause in warming which the 95%-certain-models didn’t predict. (The science wasn’t settled.) What the trade-winds giveth, they can also taketh away. If they “cause cooling” after 2000, then they probably “caused warming” before that. How much less important is CO2? Ultimately, newer models are less wrong if they include changes in wind speed, but they don’t know what drives the wind. It’s curve fitting with one more variable.
As usual, the models still can’t predict the climate, but they can be adjusted post hoc with new factors to trim their overestimates back to within the errors bars of some observations.
As I said nearly 2 years ago, Matthew England owes Nick Minchin an apology:
Nick Minchin: ” there is a major problem with the warmist argument […]
Joint Post: Geoff Sherrington and JoNova
The IPCC Synthesis Report first order draft has been leaked (h/t Tallbloke) . It is part of the big Fifth Assessment report see the parts already released here. The Synthesis Report supposedly summarizes the science. In the real world the topic du jour is the plateau, pause, or hiatus in warming which the IPCC can no longer ignore. Instead the masters of keyword phrases test new bounds in saying things that are technically correct, while not stating the bleeding obvious. Luckily we are here to help them. : -)
Translating IPCC-spin:
“The rate of warming of the observed global-mean surface temperature has been smaller over the past 15 years (1998-2012) than over the past 30 to 60 years (Figure SYR.1a; Box SYR.1) and is estimated to be around one-third to one-half of the trend over the period 1951–2012. Nevertheless, the decade of the 2000s has been the warmest in the instrumental record (Figure SYR.1a).”
Translated: Yes temperatures are not rising faster as we predicted, even though more CO2 was pumped out faster than ever. Let’s ignore that this shows the models were wrong, the important thing is to […]
Nicola Scafetta has a new paper (in long line of papers) on a semi-empirical model which has a better fit than Global Circulation Models (CGM) favored by the IPCC. We ought be careful not to read too much into it, but nor to ignore the message in it about the grand failure of the GCM’s. Scafetta used Fourier analysis to find six cycles, then uses those six cycles to produce a climate model he runs for as long as 2000 years which seems to match the best multiproxies. In terms of discovering the absolute truth about the climate, this is not an end-point way to use Fourier analysis, as it is just “curve fitting” With six flexible cycle frequencies (plus amplitude and phase) there are 18* 6 tuneable parameters, more than enough to model any wiggly line on a graph, and there are scores of astronomical cycles to pick from. *.[Nicola Scafetta replies to this below, pointing out he uses the “6 major detected astronomical oscillations”, and their phases are fixed. I am happy to be corrected. His model is more useful than I thought. Apologies for the misunderstanding. – Jo]
But Scafetta’s work suggests it’s madness not to pay […]
And the public conversation finally starts to move on to discussing not whether the IPCC is wrong, but why it was wrong, and what we need to do about it. Credit to Judith Curry and the Financial Post. I’ve posted a few paragraphs here. The whole story is in the link at the top. – Jo
Judith A. Curry, Special to Financial Post
Kill the IPCC: After decades and billions spent, the climate body still fails to prove humans behind warming
The IPCC is in a state of permanent paradigm paralysis. It is the problem, not the solution
The IPCC has given us a diagnosis of a planetary fever and a prescription for planet Earth. In this article, I provide a diagnosis and prescription for the IPCC: paradigm paralysis, caused by motivated reasoning, oversimplification, and consensus seeking; worsened and made permanent by a vicious positive feedback effect at the climate science-policy interface.
In its latest report released Friday, after several decades and expenditures in the bazillions, the IPCC still has not provided a convincing argument for how much warming in the 20th century has been caused by humans.
We tried a simple solution […]
Finally climate scientists are starting to ask how the models need to change in order to fit the data. Hans von Storch, Eduardo Zorita and authors in Germany pointedly acknowledge that even at the 2% confidence level the model predictions don’t match reality. The fact is, the model simulations predicted it would get warmer than it has from 1998-2012. Now some climate scientists admit that there is less than a 2% chance that the models are compatible with the 15-year warming pause, according to the assumptions in the models.
In a brief paper they go on to suggest three ways the models could be failing, but draw no conclusions. For the first time I can recall, the possibility that the data might be wrong is not even mentioned. It has been the excuse du jour for years.
Note in the chart that while the 10 year “pause” passed the basic 5% test of statistical significance, by 13 years, the pause was so long that only 2% of CMIP5 or CMIP3 models simulations could be said to agree with reality. By 16 years that will be 1% of simulations. If the pause continues for 20 years, there would be “zero” […]
How bad are these global forecast models?
When the same model code with the same data is run in a different computing environment (hardware, operating system, compiler, libraries, optimizer), the results can differ significantly. So even if reviewers or critics obtained a climate model, they could not replicate the results without knowing exactly what computing environment the model was originally run in.
This raises that telling question: What kind of planet do we live on? Do we have a Intel Earth or an IBM one? It matters. They get different weather, apparently.
There is a chaotic element (or two) involved, and the famous random butterfly effect on the planet’s surface is also mirrored in the way the code is handled. There is a binary butterfly effect. But don’t for a moment think that this “mirroring” is useful: these are different butterflies, and two random events don’t produce order, they produce chaos squared.
How important are these numerical discrepancies? Obviously it undermines our confidence in climate models even further. We can never be sure how much of the rising temperature in a model forecasts might change if we moved to a different computer. (Though, since we already know the models […]
This beautiful graph was posted at Roy Spencer’s and WattsUp, and no skeptic should miss it. I’m not sure if everyone appreciates just how piquant, complete and utter the failure is here. There are no excuses left. This is as good as it gets for climate modelers in 2013.
John Christy used the best and latest models, he used all the models available, he has graphed the period of the fastest warming and during the times humans have emitted the most CO2. This is also the best data we have. If ever any model was to show the smallest skill, this would be it. None do.
Scores of models, millions of data-points, more CO2 emitted than ever before, and the models crash and burn. | Graph: John Christy. Data: KMNI.
Don’t underestimate the importance of the blue-green circles and squares that mark the “observations”. These are millions of radiosondes, and two independent satellite records. They agree. There is no wiggle room, no overlap.
Any sane modeler can only ask: “But how can the climate modelers pretend their models are working?” Afterall, predicting the known past with a model is not-too-hard; the modeler tweaks the assumptions, fiddles with the fudge […]
Clouds over Amazon forest (Rio Negro). Image NASA Earth Observatory.
What if winds were mainly driven by changes in water vapor, and those changes occurred commonly in air over forests? Forests would be the pumps that draw in moist air from over the oceans. Rather than assuming that forests grow where the rain falls, it would be more a case of rain falling where forests grow. When water vapor condenses it reduces the air pressure, which pulls in more dense air from over the ocean.
A new paper is causing a major stir. The paper is so controversial that many reviewers and editors said it should not be published. After two years of deliberations, Atmospheric Chemistry and Physics decided it was too important not to discuss.
The physics is apparently quite convincing, the question is not whether it happens, but how strong the effect is. Climate models assume it is a small or non-existent factor. Graham Lloyd has done a good job describing both the paper and the reaction to it in The Australian.
Sheil says the key finding is that atmospheric pressure changes from moisture condensation are orders of magnitude greater than previously recognised. The paper concludes “condensation […]
Professor David Frame and Dr Daithi Stone have produced a paper claiming the IPCC predictions in 1990 were successful and seem accurate.
Those who read the actual FAR report and check the predictions against the data know that this is not so.
They ignore the main IPCC predictions (the prominent ones, with graphs, in the Summary for Policymakers) They don’t measure the IPCC success against an IPCC graph or within IPCC defined “uncertainties”. They measure success against a “zero trend” — something they defined as any rise at all beyond what they say are the limits of natural variability (which they got from the very models that aren’t working too well). Circular reasoning anyone? Frame and Stone themselves say the IPCC models didn’t include important forcings, and may have been “right” by accident.
Why did Nature publish this strawman letter? It’s an award-winning effort in selective focus, logical fallacies, and circular reasoning to be sure, but does it advance our understanding of the natural world? Not so.
Frame and Stone have produced a Letter to Nature saying that 3 is a lot like 6 (they are both larger than zero). If you ignore the Summary for Policymakers, pick a line […]
by Joanne Nova and Anthony Cox
UPDATED: See also Has the EPA done due diligence on the IPCC Report.
The theory that failed
It takes only one experiment to disprove a theory. The climate models are predicting a global disaster, but the empirical evidence disagrees. The theory of catastrophic man-made global warming has been tested from many independent angles.
The heat is missing from oceans; it’s missing from the upper troposphere. The clouds are not behaving as predicted. The models can’t predict the short term, the regional, or the long term. They don’t predict the past. How could they predict the future?
The models didn’t correctly predict changes in outgoing radiation, or the humidity and temperature trends of the upper troposphere. The single most important fact, dominating everything else, is that the ocean heat content has barely increased since 2003 (and quite possibly decreased) counter to the simulations. In a best case scenario, any increase reported is not enough. Models can’t predict local and regional patterns or seasonal effects, yet modelers add up all the erroneous micro-estimates and claim to produce an accurate macro global forecast. Most of the warming happened in a step change in 1977, […]
Yet more observations from the planet show that modelers misunderstand the water based part of the climate – on our water based planet.
Modelers thought that dry ground would decrease afternoon storms and rainfall over those frazzled parched lands (though I don’t remember many headlines predicting “More Drought means Fewer Storms” ). But observations show that storms are more likely to rain over dry soil. Why? Probably the dry soil heats up faster than moist areas thanks to the cooling effect of evaporation, and that in turn creates stronger thermals over dry land. Modelers assumed that wetter soils means more evaporation and thus more rain, but the moisture laden air is evidently coming from further away.
It’s another example of a point where climate modelers assume a positive feedback, yet the evidence suggests the feedback is negative. Once again water appears to be the dominant force with feedbacks (it does cover 70% of the surface). In a natural stable system the net feedbacks are likely to be negative. Positive feedbacks make the system less stable (and more scary and harder to predict.)
Climate change models misjudge drought: “A four-nation team led by Chris Taylor from Britain’s Centre for Ecology and […]
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JoNova A science presenter, writer, speaker & former TV host; author of The Skeptic's Handbook (over 200,000 copies distributed & available in 15 languages).
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