Commentary from Nature Climate Change, by John C. Fyfe, Nathan P. Gillett, & Francis W. Zwiers
Recent observed global warming is significantly less than that simulated by climate models. This difference might be explained by some combination of errors in external forcing, model response and internal climate variability.
Global mean surface temperature over the past 20 years (1993–2012) rose at a rate of 0.14 ± 0.06 °C per decade (95% confidence interval)1. This rate of warming is significantly slower than that simulated by the climate models participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). To illustrate this, we considered trends in global mean surface temperature computed from 117 simulations of the climate by 37 CMIP5
models (see Supplementary Information).
These models generally simulate natural variability — including that associated
with the El Niño–Southern Oscillation and explosive volcanic eruptions — as
well as estimate the combined response of climate to changes in greenhouse gas
concentrations, aerosol abundance (of sulphate, black carbon and organic carbon,
for example), ozone concentrations (tropospheric and stratospheric), land
use (for example, deforestation) and solar variability. By averaging simulated
temperatures only at locations where corresponding observations exist, we find
an average simulated rise in global mean surface temperature of 0.30 ± 0.02 °C
per decade (using 95% confidence intervals on the model average). The
observed rate of warming given above is less than half of this simulated rate, and
only a few simulations provide warming trends within the range of observational
uncertainty (Fig. 1a).
Figure 1 | Trends in global mean surface temperature. a, 1993–2012. b, 1998–2012. Histograms of observed trends (red hatching) are from 100 reconstructions of the HadCRUT4 dataset1. Histograms of model trends (grey bars) are based on 117 simulations of the models, and black curves are smoothed versions of the model trends. The ranges of observed trends reflect observational uncertainty, whereas the ranges of model trends reflect forcing uncertainty, as well as differences in individual model responses to external forcings and uncertainty arising from internal climate variability.
The inconsistency between observed and simulated global warming is even more
striking for temperature trends computed over the past fifteen years (1998–2012).
For this period, the observed trend of 0.05 ± 0.08 °C per decade is more than four
times smaller than the average simulated trend of 0.21 ± 0.03 °C per decade (Fig. 1b).
It is worth noting that the observed trend over this period — not significantly
different from zero — suggests a temporary ‘hiatus’ in global warming. The
divergence between observed and CMIP5-simulated global warming begins in the
early 1990s, as can be seen when comparing observed and simulated running trends
from 1970–2012 (Fig. 2a and 2b for 20-year and 15-year running trends, respectively).
The evidence, therefore, indicates that the current generation of climate models
(when run as a group, with the CMIP5 prescribed forcings) do not reproduce
the observed global warming over the past 20 years, or the slowdown in global
warming over the past fifteen years.
This interpretation is supported by statistical tests of the null hypothesis that the
observed and model mean trends are equal, assuming that either: (1) the models are
exchangeable with each other (that is, the ‘truth plus error’ view); or (2) the models
are exchangeable with each other and with the observations (see Supplementary
Information).
Brief: http://www.pacificclimate.org/sites/default/files/publications/pcic_science_brief_FGZ.pdf
Paper at NCC: http://www.nature.com/nclimate/journal/v3/n9/full/nclimate1972.html?WT.ec_id=NCLIMATE-201309
- Supplementary Information (241 KB) CMIP5 Models

Gene Selkov says:
September 5, 2013 at 8:14 am
I know. I want to ask them if they have not heard of computers. On the other hand, it is no surprise that data management is the weakest link in their computing chain. Setting aside the question of their basic assumptions for the moment.
Jean Parisot says:
September 5, 2013 at 8:27 am
Yes, work on the matrix is very important. However, to do that you must have reasonably good historical data and you must believe that nature exists outside your computer. Alarmists have trouble with both ideas.
ferd berple says:
that really is the crux of the problem. the assumption that natural variability is simply noise around a mean.
That, and the assumption that natural variability started in 1998…
– – – – – – – –
Why use the term ‘global warming’ in that passage when the dispassionate and / or indifferent term would be something like ‘temperature changes’. If one constructs that passage with ‘temperature changes’ as a context instead of ‘global warming’ as a context then the passage would be clearer science communication with minimum implied presumption of things like ‘global warming’.
For me, the repeated use of ‘global warming’ (4 times in just that passage alone) is the essence of hidden flawed premises. Where there are hidden flawed premises one expects circumstantial conclusions at best and at worst convenient conclusions.
A good strategy is to now stop playing the already gamed GW game. To do so one needs to disallow the biased terminology that predetermines a general context and spin of the outcomes.
Better to use a different set of terms which are scientifically dispassionate and non-spun.
John
richard verney says:
September 5, 2013 at 2:36 am
Bingo! A “pause” in warming is compatible with theory, but a pause coincident with a substantial increase in the main forcing factor is much less so.
Gail Combs says:
September 5, 2013 at 7:14 am
>>>>>>>>>>>>>>>>
“It varies. The Horse Latitudes (between 30 and 35 degrees, north and south) were called that because of all the dead horses tossed overboard when the sailing ships got stuck in a no wind situation.”
This is one of at least 3 explanations for the term “Horse Latitudes” and not my favorite.
First – Spanish ships perhaps carried many horses over the years but these sailors were not inclined to sail into the subtropical high pressure zones as they knew they were there, and a Spaniard would be disinclined to throw horses overboard. Some of the crew might go over first. Also, why is the zone named in English and not Spanish? [Paintings exist of unloading horses where there were no docks by forcing the off the deck and into the ocean and then leading them on to land. The difference was important to the horse.]
Next – the English ships carried “napped” crew members.
http://www.worldwidewords.org/topicalwords/tw-nap1.htm
Some of these taken from pubs to which was owed a bar bill – paid by the ship’s crew gathering agents. The new “sailor” did not earn wages until this “dead horse” payment was recovered by the ship’s purse. About 2 -3 weeks out from England the “dead horse” was paid off and the sailor would begin to be paid. Paying off the dead horse was cause for celebration so an effigy of a horse (straw horse) would be hoisted over the water and cut loose to drift in the sea. Songs were sung – shanties. This one is well known – The Dead Horse Shanty:
http://shanty.rendance.org/lyrics/showlyric.php/horse
—–
Another explanation for the term “horse latitudes” comes from the phrase “to horse” in the sense of “to push” or “to pull” something that doesn’t want to go. Sails without wind would present such an occasion and might induce a crew to try to pull (by rowing) a ship out of a calm area. This explanation requires that one believe the English sailors were unaware of the STHP zones and frequently found themselves therein. Thus, would begin an argument about whether Spanish or English were the better sailors. Don’t do there. But it would explain the use of English words for the phrase.
There is also the confusion between the “doldrums” and the horse latitudes.
“Day after day, day after day,
We stuck, nor breath nor motion;
As idle as a painted ship
Upon a painted ocean.”
See the Rime of the Ancient Mariner by the English poet Samuel Taylor Coleridge – in the lines above speaking of the equatorial area doldrums and not the STHP “horse latitudes.”
Steven Mosher says:
September 5, 2013 at 7:53 am
…..if you just interested in opposing the IPPC storyline then you
just ignore the fact that some do better and you argue that the whole lot are bad.
so…which models do you feel do the better job?
david eisenstadt says:
September 5, 2013 at 9:10 am
Steven Mosher says:
September 5, 2013 at 7:53 am
…..if you just interested in opposing the IPPC storyline then you
just ignore the fact that some do better and you argue that the whole lot are bad.
“so…which models do you feel do the better job?”
Interesting question because it might elicit an interesting answer. But, as you know, all the models are based on the same circular reasoning. What is the probability that a worthless model will produce a curve that seems to match reality?
ferd berple says:
September 5, 2013 at 7:05 am
Very well said. The “radiation-only theory,” used by all Alarmists is purely deterministic. No chaos there, no attractors. Worse, it is pure unwilling to posit the existence of natural regularities that affect temperatures. It is not bounded by reality.
davidmhoffer:
I am disappointed that there have been no congratulations for your excellent post at September 5, 2013 at 8:34 am which says in total
Perhaps this will help be people to understand your profound point.
Average wrong is wrong.
Richard
“The point is that there is a very specific reason involving the type of mathematical problem it is as to why weather forecasts diverge from reality. And, the same does not apply to predicting the future climate in response to changes in forcings. It does not mean such predictions are easy or not without significant uncertainties, but the uncertainties are of a different and less severe type than you face in the weather case.”
No they are NOT, but we’ve been through this before [sigh]…
* Climate models are highly non-linear, coupled sets of differential equations, with associated boundary and initial conditions which are, for many variables, poorly known.
* Climate models are NOT boundary value problems but initial value problems, and are prone to numerical instabilities and error after running for many time steps. To squash these errors, modelers introduce unphysical smoothing and other numerical tricks.
* There are NO guaranteed solutions to these equations, numerically or otherwise. The models as formulated may even be ill-posed, though that is often difficult to assess to to the very poor documentation provided by the developers in some cases (the most prominent of which is NASA GISS and their awful “Model E”).
David S says: @ur momisugly September 5, 2013 at 8:38 am
…. Ok they haven’t started the electric shocks yet but the skeptics are labeled “deniers” and some folks suggest they be sent to re-education camps.
>>>>>>>>>>>>>>>>>>
NAH, they will just send in a Swat Team to scare you.
This is a much better experiment;
Knit-picking ??? Unlike climate science, in language, consensus is all-important. Nitpicking, with no hyphen, is the accepted word.
kadaka (KD Knoebel) says:
September 5, 2013 at 5:49 am
gnomish said on September 5, 2013 at 2:59 am:
kadaka, your experiment will not make your desired point unless a) your container has no bottom and b) your “water” has no contaminants–just like the ocean.
@Steven Mosher 8:09 am
A counter hypothesis is that the Berkley Earth scalpel runs amok with high density data, because the homogeniality of the network is an invalid assumption.
what to me appears to be minimally discussed wholesale decimation and counterfeiting of low frequency information happening within the BEST process. Dec. 13, 2012 (Circular Logic….)
—-
The [AGU Dec 2012] poster does NOT assuage my concerns. It reinforces I have not misunderstood the BEST process. “Results” amounts to comparing two untrustworthy methods with similar assumptions against each other. ….
The Rohde 2013 paper uses synthetic error free data. The scalpel is not mentioned. My concern is the use of the scalpel on real, error riddled data. Jan 21, 2013 5:58pm (Berkley Earth finally….)
A class of events called Recalibration…. A property of this “recalibration class” is that there is slow buildup of instrument drift, then quick, discontinuous offset to restore calibration [Scalpels cuts at what appear to be discontinuities] Not only will Instrument drift and climate signal be inseparable, we have multiplied the drift in the overall record by discarding the correcting recalibration at the discontinuities.. The Scalpel is discarding the recalibrations, keeping the drift. Jan 23, 2013 11:30 am (ibid)
The denser the network, the more likely the scalpel will make the cut at recalibration events because most of the neighbors are not recalibrated at the same time.
Steven Mosher
Simple steps of research: The null hypothesis is that there is no significance between models and observations. Define the measure. In this case, the degree in which models are discrepant from observations. Run the experimental models and take measures of discrepancy between models and observations of temperature and CO2. Look at results. Dang. We must reject the null hypothesis and accept that there is a significant discrepancy. The models are falsified in that they do not reflect observed temperature measures in the face of observed increasing CO2. The next phase should be to examine the why’s and do more work on the models, possibly even rejecting or severely trimming the case for CO2.
There is no reason to go all adolescent angsty over the term “falsified”. If really good experimenters did that we would not have a lightbulb that works. And let me add, one that works a %$#*& of a lot better than the “is the light on I can’t tell” twisty ones.
Richard Barraclough:
Thanks for your post at September 5, 2013 at 9:40 am.
I enjoyed that.
Richard
Or, the modeled average is what you expect but never get. ROTFLMAO!
If they had plotted the SST data,(which is the best metric for climate change) from 2003 when the warming peaked they would see the current cooling trend – but that would be a step too far for Nature. For an estimate of the coming cooling see
http://climatesense-norpag.blogspot.com/2013/07/skillful-so-far-thirty-year-climate.html
I always thought the CAGW modelers were claiming that their failed predictions were simply a matter of variability.
I would “correctly” model winnings from a coin toss game by predicting that I make nothing on each toss. Obviously, this isn’t going to happen. I’m obviously going to win some and lose some. In the long term, I should win/lose nothing, but in the near term I might win or lose quite a bit. For example, after 15 tosses, it’s possible that I’ve won 10 and only lost 5 for net winnings of 5. This would erroneously suggest a trend of 0.33 wins per toss.
Likewise, I thought the modelers were claiming that their models are correct and that time will eventually prove this.
==================================================================
Depends who you ask.
http://www.foxnews.com/us/2013/08/30/new-age-education-fuzzy-math-and-less-fiction/
@richardscourtney at 9:56 am
Re: Richard Barraclough: at 9:40 am. Knit-picking vs. Nitpicking
I think Knit-picking is the better term.
Pull loose threads of logic and data and see what comes unraveled.
At least dr. Norman Page got it right
http://wattsupwiththat.com/2013/09/05/statistical-proof-of-the-pause-overestimated-global-warming-over-the-past-20-years/#comment-1408688
henry says
but there are are only a few of us
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/
who really know what is coming:
HOW CAN WE STOP THIS GLOBAL COOLING?
It looks like all the media and the whole world still believe that somehow global warming will soon be back on track again. Clearly, as shown, this is just wishful thinking. All current results show that global cooling will continue. As pointed out earlier, those that think that we can put more carbon dioxide in the air to stop the cooling are just not being realistic. There really is no hard evidence supporting the notion that (more) CO2 is causing any (more) warming of the planet, whatsoever. On same issue, there are those that argue that it is better to be safe than sorry; but, really, as things are looking now, they are now also beginning to stand in the way of progress. Those still pointing to melting ice and glaciers, as “proof” that it is (still) warming, and not cooling, should remember that there is a lag from energy-in and energy-out. Counting back 88 years i.e. 2013-88= we are in 1925.
Now look at some eye witness reports of the ice back then?
http://wattsupwiththat.com/2008/03/16/you-ask-i-provide-november-2nd-1922-arctic-ocean-getting-warm-seals-vanish-and-icebergs-melt/
Sounds familiar? Back then, in 1922, they had seen that the arctic ice melt was due to the warmer Gulf Stream waters. However, by 1950 all that same ‘lost” ice had frozen back. I therefore predict that all lost arctic ice will also come back, from 2020-2035 as also happened from 1935-1950. Antarctic ice is already increasing.
To those actively involved in trying to suppress the temperature results as they are available on-line from official sources, I say: Let fools stay fools if they want to be. Fiddling with the data they can, to save their jobs, but people still having to shove snow in late spring, will soon begin to doubt the data…Check the worry in my eyes when they censor me. Under normal circumstances I would have let things rest there and just be happy to know the truth for myself. Indeed, I let things lie a bit. However, chances are that humanity will fall in the pit of global cooling and later me blaming myself for not having done enough to try to safeguard food production for 7 billion people and counting.
It really was very cold in 1940′s….The Dust Bowl drought 1932-1939 was one of the worst environmental disasters of the Twentieth Century anywhere in the world. Three million people left their farms on the Great Plains during the drought and half a million migrated to other states, almost all to the West. http://www.ldeo.columbia.edu/res/div/ocp/drought/dust_storms.shtml
I find that as we are moving back, up, from the deep end of the 88 year sine wave, there will be standstill in the speed of cooling, on the bottom of the wave, and therefore naturally, there will also be a lull in pressure difference at that > [40 latitude], where the Dust Bowl drought took place, meaning: no wind and no weather (read: rain). However, one would apparently note this from an earlier change in direction of wind, as was the case in Joseph’s time. According to my calculations, this will start around 2020 or 2021…..i.e. 1927=2016 (projected, by myself and the planets…)> add 5 years and we are in 2021.
Danger from global cooling is documented and provable. It looks we have only ca. 7 “fat” years left……
WHAT MUST WE DO?
1) We urgently need to develop and encourage more agriculture at lower latitudes, like in Africa and/or South America. This is where we can expect to find warmth and more rain during a global cooling period.
2) We need to tell the farmers living at the higher latitudes (>40) who already suffered poor crops due to the cold and/ or due to the droughts that things are not going to get better there for the next few decades. It will only get worse as time goes by.
3) We also have to provide more protection against more precipitation at certain places of lower latitudes (FLOODS!),
Richard Barraclough says:
September 5, 2013 at 9:40 am
Knit-picking ??? Unlike climate science, in language, consensus is all-important. Nitpicking, with no hyphen, is the accepted word.
————————
Accepted because it’s the actual word, referring to the eggs of lice. “Knit-picking” is bogus folk etymology with no historical basis whatsoever. There is however a form of knitting called picking.