From the University of York:
A new study led by a University of York scientist addresses an important question in climate science: how accurate are climate model projections?
Climate models are used to estimate future global warming, and their accuracy can be checked against the actual global warming observed so far. Most comparisons suggest that the world is warming a little more slowly than the model projections indicate. Scientists have wondered whether this difference is meaningful, or just a chance fluctuation.
Dr Kevin Cowtan, of the Department of Chemistry at York, led an international study into this question and its findings are published in Geophysical Research Letters. The research team found that the way global temperatures were calculated in the models failed to reflect real-world measurements. The climate models use air temperature for the whole globe, whereas the real-world data used by scientists are a combination of air and sea surface temperature readings.
Dr Cowtan said: “When comparing models with observations, you need to compare apples with apples.”
The team determined the effect of this mismatch in 36 different climate models. They calculated the temperature of each model earth in the same way as in the real world. A third of the difference between the models and reality disappeared, along with all of the difference before the last decade. Any remaining differences may be explained by the recent temporary fluctuation in the rate of global warming.
Dr Cowtan added: “Recent studies suggest that the so-called ‘hiatus’ in warming is in part due to challenges in assembling the data. I think that the divergence between models and observations may turn out to be equally fragile.”
Dr Cowtan’s primary field of research is X-ray crystallography and he is based in the York Structural Biology Laboratory in the University’s Department of Chemistry. His interest in climate science has developed from an interest in science communication. This is his second major climate science paper. For this project, he led a diverse team of international researchers, including some of the world’s top climate scientists.
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So help me out here if the different in data types (air temp vs some other temp) are responsible for the divergence, How can they be ok when the models and data generally agree between 75 and 95?
* “difference in data types…”
Jaye…it’s like Taylor said
First they cooled the past…by making up (adjusting) temperatures cooler….to make it look like warming was going faster…accelerating
Then they fed that fake warming trend into the climate models….
…when the climate models extended that trend…..it went off the chart
They will never be able to model climate (temperatures) as long as they are using their own fake temp data
Furthermore, they do err in trying to model chaotic phenomena with traditional, non-chaotic math.
Because the models are ‘cooked to hind cast this period. The thing is, if the correction he’s talking about gets made to the 1975-1995 peri on, it will then likely be to low to match actual a – like the preverbial thread, this thing just keeps unraveling…
Roger that, I used to do a fair amount of bayesian pattern recognition. We were very diligent about separating the training data from the test data. So the hindcast is all about using training data as test data?
“Most comparisons suggest that the world is warming a little more slowly than the model projections indicate. ”
A blatant lie. Biased much? It’s far from “a little..”
Which is why every time one of these charts is published, a bright red vertical line needs to be drawn showing the year in which the model was made. Otherwise, people look at these charts and think the models work fairly well for some period of time – when in fact it’s simply “cooked to hind cast”. Even Anthony fails to do insert such a line when publishing the charts.
aneipris…
“Most comparisons suggest that the world is warming a little more slowly than the model projections indicate. ”
A blatant lie. Biased much? It’s far from “a little..”
Yes, it sticks out like a sore thumb. They have no conscience. Once you start lying, it gets easier as time passes.
Patrick B, for CMIP5 your bright red line is January 2006. Now you can draw as many as you want, yourself. Essay Models all the way Down in ebook Blowing Smoke, which even posts a more complex version of the above image (actual CMIP5 model tracks, since as RGBatDuke is fond of pointing out, averaging them is statistical nonsense)— WITH the bright red line you request.
I wonder if a simple neural net program, trained on (proper) historical temperatures would do better than these models? (Of course the interval of time over which it is trained would make a significant difference.)
The climate models use air temperature for the whole globe, whereas the real-world data used by scientists are a combination of air and sea surface temperature readings.
=============
The training was done with a combination of air and sea surface temperature readings. This means that the training was faulty, because it should have been done with air temperature for the whole globe.
So what Dr Cowtan et al have truly discovered is that the models were incorrectly trained, which would explain why their predictions have turned out to be so bad.
Yes, and even making the (implicit) observation “that the models were incorrectly trained” doesn’t say enough. They didn’t train or rely upon themselves.
I understood that the climate models do disparate projections for the troposphere, stratosphere, and the surface, and, as bad as they are for the surface, they are worse in the troposphere. I saw a vertical presentations of the models vs. the observations for this once, perhaps in a Christopher Monckton post.
As far as the surface air vs. the surface water T, well were not the SSTs just modified to match.
…modified to match closer to the models. Also, where is the evidence that the relationship between the SST and the air T 2 m above has changed? I thought we were now having record SST anyway?
There are really just two possibilities.
1) The science is “settled” and they should stand by their 25 year old predictions (which have been falsified by subsequent observations).
2) They can update their models to reduce the discrepancy that exists between the old models and observations. However, in this case the science is clearly not “settled”, and they need to begin to seriously think about why they’ve been so blatantly wrong, and perhaps even listen to the skeptics occasionally.
Instead, all to often, we get these weasel treatments: changing their predictions while simultaneously arguing that they’ve been right all along.
This is a two edged sword for warmistas. If the model temperature growth is too high based on the way it’s calculated, that affects the long term estimates, and reduces that scary 1100 scenario. So to get the models fixed, CAGW is eliminated, right? Will be interesting to see how this is received.
As a side note, I hope this puts to rest their refusal to pay attention to anyone but a ‘climate scientist’ – this guy is clearly not one, but seems to be accepted anyway
Taylor
Oops meant 2100 scenario
I wager that his acceptance is a result of finding a way to raise recent temperatures.
I think Dr. Cowtan may be juggling his apples a bit. GISS and HADCRUT use “a combination of air and sea surface temperature readings.” However, satellite and balloon data do not. They measure as much of the troposphere as they can, which makes them very much like the model output.
If the serious divergence between data and models didn’t actually exist (as claimed by Dr. Cowtan), then there wouldn’t be any need for the on-going data manipulation by NCEI, GISS, and UKMO. For example, the Karl, er al., 2015 Science paper released with much cheering from the CAGW crowd.
the problem is that the climate models use land and sea temeratures for their training, so they should match the land and see temps in their predictions – if their predictions have any skill.
so in this Dr Cowtan is incorrect. The training was done with apples and the comparison is to apples, but the models themselves describe oranges.
in point of fact the training and comparison should have been done using air temps all along, because the models describe air temps. but that wasn’t done because the data isn’t available prior to 1970 or so.
It is my understanding that SST is slightly warmer then the air above it as a global mean.
So, according to Dr. Cowtan the climate modelers do not know how to compare “apples to apples”…. What way you look at it there’s the same result – incompetence!
Where’s the link?
http://onlinelibrary.wiley.com/doi/10.1002/2015GL064888/abstract
Dr Cowtan added: “Recent studies suggest that the so-called ‘hiatus’ in warming is in part due to challenges in assembling the data. I think that the divergence between models and observations may turn out to be equally fragile.”
Yes, and that also means that any prior agreement was even more fragile, does it not?
Every global surface temperature dataset should be using air temperatures, not ocean temperatures. However, there is no doubt while using the satellite data, which shows a much larger divergence between observational data and model output. Satellite data and model output data can be compared almost perfectly directly.
Loo crazy makes the main point. Cowpat has ignored satellite data.
iPad autocorrect has made two interferences with what I typed. Apologies to both parties wrongly named. Does anyone know how to turn the darned thing off?
And… the lower stratosphere wv .Which collapsed after 97 . Concurrently with the “hiatus” , that of course ,did not really occur.
–
Eos, Vol. 95, No. 27, 8 July 2014
Another Drop in Water Vapor
PAGES 245–246
–
See page 2 .Fig 1
Well, auto correct leads to some interesting sentences, and the world need a bit of humor, so I say, carry on.
Yes, the obvious answer is that we have a pristine satellite record of the atmosphere, and the models are worse then ever compared to the observations, however, bypassing that for a moment, let us examine what they did, and claim.
I take it that the IPCC has a modeled SST but did not use it, but instead used a modeled 2m air surface in their projections. Now the say they are using it, the previously unused modeled SST, to compare to the claimed SST observations, instead of a modeled 2m air surface in their projections. They claim that the models assume the 2m air T above the oceans would rise faster then the SST.
1. What are the physics of this claim based on?
2, How do we know that the 2m air surface above the oceans did not change at exactly the same rate as the SST, and therefore the models of the air T are now as wacked as ever?
3.. I do not think we have any accurate 2m air surface T record above the oceans.
4. Why did they make this obvious bonehead comparison, if they had a modeled SST to use all the while?
5. Could it be that the wanted the scariest projections possible?
6. Could it be that traditional physics assumes that the oceans drive the atmosphere, are on average warmer then the surface air temperature, and there is still no evidence that this is not true, and there is still no evidence that the 2m air temperature is not as far below the models as ever?
7. How much have the SSTs been adjusted?
we already have enough apples to oranges problems in the temperature record … land measurements are of the AIR above the ground … sea surface measurements are of the water NOT the air above the water … its a mess and this “study” is just an a** covering exercise …
So the lead scientist in the “study” is what ? a X-ray crystallography professor … riiiiiight … he’s qualified (according to the warmists no)
Either there’s something odd about this new bit of research, or there’s been something odd about modeling for quite a while.
Why have models been producing results which can not be compared to observations?
Why have people been comparing observations to model results?
How did modelers know that their results were reasonable, if they could not be compared to other data?
Here’s the abstract. Co-Authors are familiar–Zeke H, Michael Mann, ..
Also familiar was the fast track to publication–The draft was first received June 10, revision July 20, published July 29, in plenty of time for the run-up to December in Paris. One month. I normally wait 3 months to get peer reviews finished, a month or so revising, and then wait 6-18 months before it appears in the journal.
Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures†
Authors
Kevin Cowtan,
Zeke Hausfather,
Ed Hawkins,
Peter Jacobs,
Michael E. Mann,
Sonya K. Miller,
Byron A. Steinman,
Martin B. Stolpe,
Robert G. Way
Accepted manuscript online: 29 July 2015Full publication history
DOI: 10.1002/2015GL064888View/save citation
Cited by: 0 articles Check for new citations
Article has an altmetric score of 43
†This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/2015GL064888
Abstract
The level of agreement between climate model simulations and observed surface temperature change is a topic of scientific and policy concern. While the Earth system continues to accumulate energy due to anthropogenic and other radiative forcings, estimates of recent surface temperature evolution fall at the lower end of climate model projections. Global mean temperatures from climate model simulations are typically calculated using surface air temperatures, while the corresponding observations are based on a blend of air and sea surface temperatures. This work quantifies a systematic bias in model-observation comparisons arising from differential warming rates between sea surface temperatures and surface air temperatures over oceans. A further bias arises from the treatment of temperatures in regions where the sea ice boundary has changed. Applying the methodology of the HadCRUT4 record to climate model temperature fields accounts for 38% of the discrepancy in trend between models and observations over the period 1975-2014.
“Mann” – do they want anyone to take it seriously?
Article has an altmetric score of 43
How is the Altmetric score calculated?
While the most important part of an Altmetric report is the qualitative data, it’s also useful to put attention in context and see how some research outputs are doing relative to others. The Altmetric score for a research output provides an indicator of the amount of attention that it has received. The score is a weighted count
The score is derived from an automated algorithm, and represents a weighted count of the amount of attention we’ve picked up for a research output. Why is it weighted? To reflect the relative reach of each type of source. It’s easy to imagine that the average newspaper story is more likely to bring attention to the research output than the average tweet. This is reflected in the default weightings:
http://support.altmetric.com/knowledgebase/articles/83337-how-is-the-altmetric-score-calculated
From the table of scores if they wrote a wiki page and each of the 9 authors put it on facebook, each tweet once, got 20 friends to tweet it and 2 blogs wrote about it, that would be – 45 points.
So much for impact score.
It’s easy to make a prediction fit the data if you then change the data to fit the prediction.
So the only test that matters in real science is whether the model predicted the data as it was defined when the prediction was made.
Otherwise … it would be like betting on a horse race and then changing your bet after it was run. Does anyone seriously think anyone would change their bet so that they were more likely to lose?
+1
If changing the data doesn’t work, they can always try changing the prediction and hope nobody notices.
Or have so many predictions that there’s bound to be at least one that is remotely suitable.
Curious why you didn’t use any of the actual graphics from Cowtan et al. They show something dramatically different from Christy’s graphic that you used. Seems a little misleading, don’t you think?
You can plot for yourself all the data. Go to KNMI explorer for the CMIP5 archive. Go get UAH and RSS for satellite, and so on. Cowtan et. al did NOT use the full CMIP5 archive. They cherry picked stuff that was less divergent from observation, yet another ‘cheating tell’ like yhe push formrapid publication. Their figure is by definition a misleading representation of the publicly available CMIP5 archive. Christy’s figure gives the whole truth, and nothing but the truth, cause it uses themwhole archive– except an average of model runs (an IPCC favorite, so fair to to do in this circumstance) is still statistical nonsense. A point made in a previous comment.
Why does the UAH and RSS plot in the graph above not look anything like these:
http://woodfortrees.org/plot/uah
http://woodfortrees.org/plot/rss
I somehow entered only part of my name before the comment posted.
Why does the UAH and RSS plot in the graph above not look anything like these:
http://woodfortrees.org/graph/rss
http://woodfortrees.org/graph/uah
Me cholas is inadvertently comparing oranges with segments. The famous Christmas and Soencer graph uses annual data, while the woodforcarbonsinks graph uses monthly data.
ristvan, that doesn’t answer my question.
Why post the Christy graph, which tells you nothing about the Cowtan paper? Why not post the actual graphs from the Cowtan paper?
Zeke, Mann… I don’t know why you bother….
This is quite humorous. It seems that whenever they are eager to make a point in favor of AGW (in spite of it’s obvious problems) they invite Mann and the other ‘usual suspects’ – in disregard of their real reputations. Is ‘climate science’ even interested in integrity and veracity?
Are they saying that observations are wrong because they don’t use the same data as the models?
Hi katherine009. Nope.
They are saying model-data comparisons are normally biased because they usually include the modeled air temperature over the oceans, while the data include sea surface temperatures for the oceans. The bias results because the models show a higher warming rate for the marine air than the sea surface. Their results show, if you replace the marine air temperature outputs of the models with the modeled sea surface temperatures, then the model-data difference decreases. Nothing new. They just quantified it using the UKMO HADCRUT data.
So, in other words, he has less knowledge and understanding of climatology than a sophomore, just a lot more ego. He sounds like what he’s really doing is selling ad space in a glossy, rhetorically speaking. “let’s cobble together a thesis, stick some 50 cent names on it, get a buddy to peer it, and walla, more grant funds….”
The big difference between climate models and models running algorithms for the stock exchange ,is that the models working on the stock exchange sometimes come up with the right answers. Climate models predict wrongly forever with zero accountability. Hedge funds fail if their model is not fit for purpose, climastrologists just ask the suckers for more money.
How did “voila” become walla?
Is the models predict anomalies associated with a decrease in solar activity?
http://www.cpc.ncep.noaa.gov/products/stratosphere/strat-trop/gif_files/time_pres_HGT_ANOM_ALL_NH_2015.gif
What two satellite datasets are these? What region of the earth and what level of the atmosphere are they for? Is there an averaging among multiple years? I don’t see these curves peaking strongly at 1998 the way the UAH and RSS global TLT datasets do.
yes, what data – adjusted data is working better now? for model belief? for Paris?
well, the hiatus is back in print
Can’t even get this bit right and yet can anybody trust them?
http://www.woodfortrees.org/plot/uah-land/from:1979/plot/rss-land/from:1979
Interesting that the UAH trend is lower than RSS, although a bit steeper. I presume this is still 5.6 and not version 6?
http://www.woodfortrees.org/plot/uah-land/from:1979/plot/rss-land/from:1979/plot/uah/from:1979/trend/plot/rss/from:1979/trend
Lets presume you are not a troll, just a newby deserving a response. The two sat data sets are UAH and RSS. Google is your friend. Same satellite raw MSU signals in the various channels, different processing algorithms. Temp results since 1979 for lower and upper troposphere and stratosphere. (Not surface air temps, per se. But for anomalies, no biggie.) UAH new beta v6.0 corrects a simpler algorithm ‘field of view’ issue (the Earth is curved…), and is now much closer to RSS. The problem and the solution for v6.0 can be read on Roy Spencer’s blog. The peer reviewed technical paper version on the v5.6 to v6.0 UAH is in the works, but obviously not receiving the stunningly expedited Cowtan treatment–else I would also provide that reference.
Yes, I just posted a similar question Mr. Klipstein.
These do not look at all like RSS and UAH that I know.
They are 5 year running averages. Original post at Dr. Spencer’s blog.
I don’t see an option to reply to Bart in his comment below, so I am putting my reply here. The graph at the top of this article is not showing any normal 5 year running mean of satellite datasets since the satellite curve is plotted from 1979 to 2015. The satellite datasets start with 1979.
Dr Cowtan said: “When comparing models with observations, you need to compare apples with apples.”
You do need to compare apples to apples which is why Dr. Cowtan knew to compare the apples to orangutans. (and please send more grant money)
you need to compare apples with apples
==========
during training of the models you have to train apples to apples as well. The models represent air temps, but were trained using surface and ocean temps.
In effect you have trained a horse to act like a monkey, and wonder why it it is so bad at climbing trees.
🙂
The satellites do not show any warming. The problem is it difficult to fiddle with the satellite data.
http://realclimatescience.com/wp-content/uploads/2015/07/ScreenHunter_10030-Jul.-30-09.22.gif
The cult of CAGW is going to keep to their agenda until there is in your face global cooling.
There an interesting race that few are aware of. What will occur first?
1) The first public announcement that the solar cycle has been interrupted or
2) The first observations of unequivocal global cooling.
http://wattsupwiththat.files.wordpress.com/2012/09/davis-and-taylor-wuwt-submission.pdf
Greenland ice temperature, last 11,000 years determined from ice core analysis, Richard Alley’s paper. William: As this graph indicates the Greenland Ice data shows that have been 9 warming and cooling periods in the last 11,000 years.
The past warming and cooling cycles correlate with solar cycle changes. i.e. The past cyclic warming and cooling periods have a physical cause which is physically capable of causing cyclic warming and cooling in both hemispheres. Big surprise cyclic changes to the sun causes cyclic changes to the earth’s climate.
Who would have thought up that wild idea?
P.S. There are periods of millions of years in the paleo record when atmospheric CO2 was high and planetary temperature was low and vice versa. There is not even correlation.
The so called without ‘feedback’ calculation of forcing for a doubling of atmospheric CO2, did not take into account the fact that CO2 increases the lap rate (another big surprise hot air rises and is replaced with falling colder air which offset greenhouse warming. Again who would come up with that wild idea?) which reduces the warming for a doubling of atmospheric CO2 without amplification from 1.5C to 0.1C to 0.3C.
The same calculation did not include the fact there is an overlap of water’s absorption spectrum and CO2’s absorption spectrum. As there is a great deal of water vapour in the lower atmosphere, particularly in the tropics (70% of the planet is covered in water) that also reduces the warming due to a doubling of atmospheric CO2 to roughly 0.1C to 0.3C.
http://www.climate4you.com/images/GISP2%20TemperatureSince10700%20BP%20with%20CO2%20from%20EPICA%20DomeC.gif
The first public announcement that the solar cycle has been interrupted
The solar cycle has not been ‘interrupted’ [whatever that means], so no such announcement will be forthcoming.
Exactly. Instead of whining about the mismatch, why not just use the state-of-the-art temperature record that measures precisely what the models are built predict — satellite…
Of course, the measurements that align with the models show cooling.
Do these scientists “work” to be this naive and ignorant?
You leave out a third option, the most frustrating and terrible one, and the one most likely to occur:
Since Earth’s climate operates on a different time-scale than our own brief little moments in the sun, there will be no definitive, inarguable global cooling in our lifetime, and perhaps much longer, just as there is no definitive, inarguable global warming. It is a ridiculous show of hubris to think that our puny temperature sampling networks, and rudimentary conception of how climate functions, allow us to define and speak authoritatively about “global temperature” at all.
This is terrible because it means there will probably BE NO MOMENT when CAGW believers have to admit they’ve been wrong, and the skeptics get to finally feel that warm glow of vindication.
It will take some unforeseen speech from a famous person that sets off the light bulb in enough people’s heads (like Gore with his sanctimony at just the right moment), or the rise of a different imminent and unstoppable manmade disaster, to get the idea of CAGW to go away. Even then it will persist in the dark corners of the world, like Ebola, biding its time, waiting to leap back into the light…
It leaves this layman shaking his head in astonished wonderment.
You’d think that, before engaging in all the decades of study, the expenditure of billions of dollars and the claims of impending doom, the climate boffins would have agreed to a definition of terms.
These clowns have permanently damaged the credibility of “climate science.” I don’t believe a word out of them— and I’m amazed when anybody else does.
Worst than that… They have permanently damaged the credibility of science in general. They keep harping about how certain scientists (and skeptics) are nothing but shills for the oil companies when in actuality, the vast majority of scientists today are funded by the government. And many (take for example the current crop of “Climate Scientists”) have become shills for the current executive branch, regardless of which party. President Eisenhower warned about this is his farewell address:
“
the climate boffins would have agreed to a definition of terms
====================
Climate Science hasn’t even defined “climate change”.
1. climate change – refers only to human caused.
2. climate change – refers to both human caused and naturally caused.
3. Climate change should only refer to naturally occurring change – which includes naturally occurring global warming (or cooling) . If one wishes to refer to some perceived (goodness knows there is no empirical evidence of any of this) additional climate change being potentially caused by additional warming, or AGW, then that would be referred to as ACC.
Climate is a range of parameters, not just temperature, each of which is highly variable.
Materially, climate change is not climate change until the change is outside the bounds of natural variation when viewed and measured over at least a multi-centennial scale, if not a millennial scale.
Given what we know of the past, the idea that climate should be viewed as something to be assessed over a 30 year period is farcical in the extreme.
Presently, we have yet to observe any real climate change
The models are way off and it will become worse going forward.
my suggestion….stop making up, adjusting, fudging, and lying about surface temps
You’ll never get it as long as you are using fake data.
BTW…here’s the paper
http://onlinelibrary.wiley.com/doi/10.1002/2015GL064888/abstract
I find it interesting that, as shown in Figure 2, the adjustments required to “correct” for the difference between air and air+water temperature measurements followed a accelerating downward trend. How would a “correction” to a temperature measurement result in a smooth trend over time with the largest deviations occurring today? Did the air and water measurements agree more closely in 1900, or was there simply more land? /sarc on Perhaps this plot is an indication of the rapidly rising sea levels with the fraction of land decreasing rapidly with time.
exactly….they give it away
“Applying the methodology of the HadCRUT4 record to climate model temperature fields accounts for 38% of the discrepancy in trend between models and observations over the period 1975-2014.”
HadCRUT faked the past….cooled it…to show a faster trend
…when they feed those fake numbers in it….they got a fake trend
“You’ll never get it as long as you are using fake data.”
That’s wrong.
The only way they can get it is using fake data.
Otherwise, with real data, they’re done.
” The research team found that the way global temperatures were calculated in the models failed to reflect real-world measurements. The climate models use air temperature for the whole globe, whereas the real-world data used by scientists are a combination of air and sea surface temperature readings.”
Dr Cowtan must be kidding, right? Is he saying that these scientists do not know how to correctly verify their own projections? If I would have pulled this in my Freshman Physics lab, the instructor would have failed me on the spot.
Dr Cowtan’s
interest in climate science has developed from , the fact there is ton of grant cash and some fame in climate ‘science’ while it crystallography there is no cash and no one wants to know what our doing , but let us call it ‘an interest in science communication.’ instead
It seems to me that water acts as a buffer for air temperature, and since water is approximately 2/3 of the earth’s surface, it would naturally close the gap between the hypothetical models and the real world observations. A no-brainer paper.
Brian – they’ve found an easy way out.
Thanks for clearing sights – Hans
There is a logical contradiction there: the models don’t even agree between themselves, so how can they possibly all agree with reality?
bingo
+1