by Roy W. Spencer, Ph. D.
What can we learn from the IPCC climate models based upon their ability to reconstruct the global average surface temperature variations during the 20th Century?
While the title of this article suggests I’ve found evidence of natural climate cycles in the IPCC models, it’s actually the temperature variability the models CANNOT explain that ends up being related to known climate cycles. After an empirical adjustment for that unexplained temperature variability, it is shown that the models are producing too much global warming since 1970, the period of most rapid growth in atmospheric carbon dioxide. This suggests that the models are too sensitive, in which case they are forecasting too much future warming, too.
Climate Models’ 20th Century Runs
We begin with the IPCC’s best estimate of observed global average surface temperature variations over the 20th Century, from the “HadCRUT3″ dataset. (Monthly running 3-year averages are shown throughout.) Of course, there are some serious concerns over the validity of this observed temperature record, especially over the strength of the long-term warming trend, but for the time being let’s assume it is correct (click on image to see a large version).
Also shown in the above graph is the climate model temperature reconstruction for the 20th Century averaged across 17 of the 21 climate models which the IPCC tracks. To provide a reconstruction of 20th Century temperatures included in the PCMDI archive of climate model experiments, each modeling group was asked to use whatever forcings they believed were involved in producing the observed temperature record. Those forcings generally include increasing carbon dioxide, various estimates of aerosol (particulate) pollution, and for some of the models, volcanoes. (Also shown are polynomial fits to the curves, to allow a better visualization of the decadal time scale variations.)
There are a couple of notable features in the above chart. First, the average warming trend across all 17 climate models (+0.64 deg C per century) exactly matches the observed trend…I didn’t plot the trend lines, which lie on top of each other. This agreement might be expected since the models have been adjusted by the various modeling groups to best explain the 20th Century climate.
The more interesting feature, though, is the inability of the models to mimic the rapid warming before 1940, and the lack of warming from the 1940s to the 1970s. These two periods of inconvenient temperature variability are well known: (1) the pre-1940 warming was before atmospheric CO2 had increased very much; and (2) the lack of warming from the 1940s to the 1970s was during a time of rapid growth in CO2. In other words, the stronger warming period should have been after 1940, not before, based upon the CO2 warming effect alone.
Natural Climate Variability as an Explanation for What The Models Can Not Mimic
The next chart shows the difference between the two curves in the previous chart, that is, the 20th Century temperature variability the models have not, in an average sense, been able to explain. Also shown are three known modes of natural variability: the Pacific Decadal Oscillation (PDO, in blue); the Atlantic Multidecadal Oscillation (AMO, in green); and the negative of the Southern Oscillation Index (SOI, in red). The SOI is a measure of El Nino and La Nina activity. All three climate indicies have been scaled so that their net amount of variability (standard deviation) matches that of the “unexplained temperature” curve.
As can be seen, the three climate indices all bear some level of resemblance to the unexplained temperature variability in the 20th Century.
An optimum linear combination of the PDO, AMO, and SOI that best matches the models’ “unexplained temperature variability” is shown as the dashed magenta line in the next graph. There are some time lags included in this combination, with the PDO preceding temperature by 8 months, the SOI preceding temperature by 4 months, and the AMO having no time lag.
This demonstrates that, at least from an empirical standpoint, there are known natural modes of climate variability that might explain at least some portion of the temperature variability seen during the 20th Century. If we exclude the post-1970 data from the above analysis, the best combination of the PDO, AMO, and SOI results in the solid magenta curve. Note that it does a somewhat better job of capturing the warmth around 1940.
Now, let’s add this natural component in with the original model curve we saw in the first graph, first based upon the full 100 years of overlap:
We now find a much better match with the observed temperature record. But we see that the post-1970 warming produced by the combined physical-statistical model tends to be over-stated, by about 40%. If we use the 1900 to 1970 overlap to come up with a natural variability component, the following graph shows that the post-1970 warming is overstated by even more: 74%.
Interpretation
What I believe this demonstrates is that after known, natural modes of climate variability are taken into account, the primary period of supposed CO2-induced warming during the 20th Century – that from about 1970 onward – does not need as strong a CO2-warming effect as is programmed into the average IPCC climate model. This is because the natural variability seen BEFORE 1970 suggests that part of the warming AFTER 1970 is natural! Note that I have deduced this from the IPCC’s inherent admission that they can not explain all of the temperature variability seen during the 20th Century.
The Logical Absurdity of Some Climate Sensitivity Arguments
This demonstrates one of the absurdities (Dick Lindzen’s term, as I recall) in the way current climate change theory works: For a given observed temperature change, the smaller the forcing that caused it, the greater the inferred sensitivity of the climate system. This is why Jim Hansen believes in catastrophic global warming: since he thinks he knows for sure that a relatively tiny forcing caused the Ice Ages, then the greater forcing produced by our CO2 emissions will result in even more dramatic climate change!
But taken to its logical conclusion, this relationship between the strength of the forcing, and the inferred sensitivity of the climate system, leads to the absurd notion that an infinitesimally small forcing causes nearly infinite climate sensitivity(!) As I have mentioned before, this is analogous to an ancient tribe of people thinking their moral shortcomings were responsible for lightning, storms, and other whims of nature.
This absurdity is avoided if we simply admit that we do not know all of the natural forcings involved in climate change. And the greater the number of natural forcings involved, then the less we have to worry about human-caused global warming.
The IPCC, though, never points out this inherent source of bias in its reports. But the IPCC can not admit to scientific uncertainty…that would reduce the chance of getting the energy policy changes they so desire.
There is a previous guest post on WUWT positing that there are various natural cycles that work together to create the climate. When the cycles are in phase, we get a warm period or a cold period. When the cycles are out of phase, the effects tend to cancel themselves out.
Does anybody recall the post and is there a model using this hypothesis?
“jack mosevich (14:15:22) :
[…]
I know that there is confusion about this as some people accuse modelers of curve fitting, which is certainly not true.”
If they would be curve fitting, they would be done with their job in a week. They try to model the physical systems in such a way that they can run it, say across the 20th century and compare the output with the observations or what GISTEMP gives them for an observation. A model that is closer to this observation wins against models that did a worse job.
Problem is, they parameterize (assume a preset value for) the humidity, the amount of cloud cover, they can’t compute the humidity or the cloud cover in the simulation because these are small-scale local physical processes that are much too small for their grid cells, whether they’re 100 km across or 10. Even worse, we don’t know all cloud formation mechanisms by now.
They’re lucky if their model manages to find out that the Sahara is a desert.
A recent breakthrough was the model from Mojib Latif’s institute in Kiel; AFAIK he predicted a while ago the change of the PDO. He incorporated the thermohaline circulation. So that’s where you are: We slowly get models that incorporate stuff that the ocean does.
They’re nowhere near predictive power whatsoever yet. Curve fitting – what Dr. Spencer in fact did here – would do a better job as a forecasting tool, given the state of the art.
DirkH, It is a good point that the models are unstable and why we never see a model that levels out at (say) +14C or any other number. The instability probably enhances the variability but should still allow natural oscillations to emerge. Couldn’t the variability could result in something like the natural oscillations even embedded within an exaggerated secular warming trend?
Leif Svalgaard (13:48:17) : Usually, when you fail a prediction, the failure is cumulative and it gets worse and worse as time goes on..
Brilliant! Yes! This is the true Markov process of reality; it’s like orienteering with a malfunctioning compass: each step in the wrong direction takes you further away from the next control point flag. Then after a while you are lost. I mean really lost. Standing in the middle of nowhere, and you have no idea where to go…. Just like IPCC… HELLO?
Leif Svalgaard (14:04:27) quoues Oliver K. Manuel (13:59:06) :
‘. . . it now appears that astrology may have had a better scientific foundation than the Standard Solar Model of a Hydrogen-filled Sun!’
“It is statements like that that make some people not take WUWT seriously. Let us at least try to preserve a modicum of science.”
– – – – – – –
Dream on, Leif.
In fact, astrology still has a much better scientific foundation than the Standard Solar Model of a Hydrogen-filled Sun!
Here’s “Why the Model of a Hydrogen-Filled Sun Is Obsolete” http://arxiv.org/pdf/astro-ph/0410569v1
Grow up, Leif. Climategate has exposed the hand of consensus scientists.
Shame on you for reverting to the same old deceptive ploy: “Let us at least try to preserve a modicum of science.”
With kind regards,
Oliver K. Manuel
Emeritus Professor of
Nuclear & Space Science
Former NASA PI for Apollo
That 14 model run average is rubbish! My Solar-Ocean model returns much better results.
http://tallbloke.wordpress.com/2010/01/05/my-simple-solar-planetary-energy-model
Of course they won’t explain real cause of the natural variation. Too many reputations at stake.
“Eric (skeptic) (14:42:10) :
DirkH, It is a good point that the models are unstable and why we never see a model that levels out at (say) +14C or any other number. The instability probably enhances the variability but should still allow natural oscillations to emerge. Couldn’t the variability could result in something like the natural oscillations even embedded within an exaggerated secular warming trend?”
Yes, that’s possible. Maybe Mojib Latif’s model can. He still emphasizes that he’s a firm believer in global warming even tough his model forecasts a cold spell of a decade or three; afterwards he says it gets worse than we thought (warm).
We could think of it as the addition of two models, one with, say an exponential runaway and one with a stable oscillation. Over time though, the exponential wins and the instability dominates the system. Like Hansen predicted for 2000 in a prediction from 1981 i think, his first warming-catatrophe paper. He said that in 2000 the runaway would totally dominate any natural variability. As we know now, he was 12 years off 😉
They key problem of the models is IMHO that their assumptions about positive feedback (CO2->CO2 and CO2->water vapour) are wrong. Well, and, as Dr. Spencer points out, too high climate sensitivity for a given forcing.
Gentlemen…Oliver and Leif,
I sense the mountain and Mohammad here – you both add much to this site – and we’re far richer for it.
I understand both positions – but, after all, this is a place of opinions, sometimes very different. Thanks for being here.
Mike
Oliver K. Manuel (14:50:23) :
In fact, astrology still has a much better scientific foundation than the Standard Solar Model of a Hydrogen-filled Sun!
As I said, he wasn’t satirical.
Dear Oliver K. Manuel,
Our planet is spinning and wobbling with regular changes in orbit, tilt and axis. The resulting natural non-equilibrium oscillations of the climate system – intrinsic and non-linear-chaotic in nature – may cover a wide range of timescales. In particular heat redistribution due to the slow ocean cycles may take hundreds of years, just like watching a huge century long “heat splash” in slow motion.
The sun is invariant. The intrinsic natural oscillations in the climate systems have no need for a variable sun to sustain the (unpredictable) oscillation.
Best Regards,
Invariant
Dear Oliver K. Manuel,
Our planet is spinning and wobbling with regular changes in orbit, tilt and axis. The resulting natural non-equilibrium oscillations of the climate system – intrinsic and non-linear-chaotic in nature – may cover a wide range of timescales. In particular heat redistribution due to the slow ocean cycles may take hundreds of years, just like watching a huge century long “heat splash” in slow motion.
The sun is invariant. The intrinsic natural oscillations in the climate systems have no need for a variable sun to sustain the (unpredictable) oscillations.
Best Regards,
Invariant
I have always had some difficulty with unstable systems that have a slowly drifting mean. If they are relatively stable, it it quite possible that the mean will drift, but the climate models that have positive feedback are expected to oscillate. I wonder whether, if one ran the models for long enough, would there be long term oscillations or would the Earth blow up? If the former is the case, we get into the awful difficulties of representing long term periodicities as a linear trend. If the latter occurs, does this suggest that the models are representing anything real in the short term?
I’m still very suspicious of a class of models that have, if think, at least 27 non-linear equations at each node and considerable homogenisation, with some parameters that are guesses and, being a semi-chaotic system must be sensitive to initial conditions. I suspect (from experience in modelling in another field) that have to a wide range of constraints within the models to stop them either blowing up or doing nothing. The physical meaning of these constraints would be interesting.
Richard Saumarez (15:19:37) : I have always had some difficulty with unstable systems that have a slowly drifting mean. If they are relatively stable, it it quite possible that the mean will drift
Indeed. Yes! Our climate may oscillate around an oscillating equilibrium. In terms of Kelvin, however, the oscillations are rather small, a couple of Kelvin is little compared to ~300 Kelvin! While the positive feedback mechanisms may dominate oscillations around equilibrium, the oscillations of the equilibrium itself may be controlled by strong negative feedback mechanisms.
This is the kind of an article to make a lukewarmist purr.
The next ten years are going to be very interesting, and really likely the next five will tell the tale.
If there is a large natural variability component that is basically a 60 year sin wave, with peaks at 1934 and 1998, then that’s one area of comparison (and not too alarming). . . now we need to see how the predicted troughs in the mid-1970s vs 2028 look. . . .if we don’t see continued drifting down over the next several years from the satellites, it might be time to take AGW a bit more seriously.
Wow! When the UK’s Guardian publicly acknowledges something is wrong in the murky and cosy world of NGOs, quangoes and dodgy science funded by the British taxpayer, then you know the train is about to hit the buffers – big time!
Richard Tyndall (13:35:26) :
Sorry to go off topic straight away but the Guardian newspaper in the UK is claiming an exclusive showing that Jones at the CRU covered up problems with data from Chinese weather stations
http://www.guardian.co.uk/environment/2010/feb/01/leaked-emails-climate-jones-chinese
*sine wave, not “sine way”. . .d’oh.
Dr Roy’s assessment would be valid if the actual data on which he is making a comparison is correct. However, the plain fact is the actual data is false. It has been shown that both GISS and HadCru have been altered to make temperatures before 1960 appear lower than actual (from site adjustments and lack of recording stations) and temperatures since 1960 appear higher from UHI and removal of stations from rural and elevated sites. Further, there is no doubt that the CO2 data curve is incorrect. All actual CO2 measurements prior to 1960 have been ignored and been replaced by guessed proxy data. Since 1960 the measurements at Mauna Loa (active volcano in Hawaii) maybe accurate but one has to be suspicious of the smoothed trend with no cycles as shown by earlier measurements. Satellite data of CO2 indicates that the CO2 is not evenly spread around the world with higher levels in the mid northern latitudes and very low levels in the southern polar regions. The other thing is that temperature actually leads CO2 which none of the models show. It maybe more interesting to look that models which leave out CO2. That is correct -no model temperature increase (other than variations from natural ENSO and NAO oscillation) and no actual temperature increase (when all the manipulations have been removed)
“I assume that the models are NOT constantly updated [assimilated] with the newest observations, but are allowed to ‘run free’ based only one the initial conditions and the processes being modeled.”
Leif brings up a good question, and based on my knowledge of the AOGCMs, they are not allow to “run free,” but instead have “forcings” (read source terms) added to the governing differential equations to reflect best guesses of the effects of CO2 emissions, aerosols, volcanoes, etc. You can tune these forcings to give you the desired solution (in this case, the Earth’s “average” temperature), which is why hindcasting is so successful, and true blind forecasting is not so great.
I have always wondered why climate modelers would claim great accuracy for a hundred year forecast and yet have poor skill for a forecast one year out. It seems to me that weather “noise” could be sufficiently “filtered out” after one year of modeled time, and since your solution is not so far from your initial condition, your result should be reasonably good, right? Of course, if you look at the algorithms, climate models aren’t very much different from the numerical weather prediction codes (in terms of their time marching character), so likely they still suffer from the tendency towards chaotic solutions that NWP codes do, which would imply that the solutions, even on decadal scales, are effectively unpredictable…
In any case, these questions make it doubly important that modelers properly document and validate their codes before using them to generate solutions upon which policy decisions are based. GISS, in particular, have failed miserably in this regard…
Richard Tyndall (13:35:26) :
The Grauniad?, It look like the warmistas are throwing Jones to the wolves.
That’s under the bus to our American friends, the whole this is faling appart when they have started to turn on eachother.
Oh, sorry Grauniad is an old joke, they can’t even be bothered to spell check their articles.
Happy days.
Alan
Their story contains nothing new, it’s just that the penny dropped for them finally. (But I do hope this news flurry causes some more digging into the unreleased findings in the Wang case.)
I’ve made a Word copy of the Guardian article so many of us are gobsmacked by, as I’m sure it will be pulled … this wouid be (and is) like old-style Soviet Pravda denouncing Lenin or similar .. it’s so out of character for the Graun. Bewildered but delighted nevertheless.
@RichieP:
Perhaps the Guardian is attempting to present a “balanced” view (ie examples of support from both sides)?
Dr. Spencer wrote:
“This absurdity is avoided if we simply admit that we do not know all of the natural forcings involved in climate change.”
Bravo.
See here:
http://www.sfu.ca/~plv/r..AM..EMnAM.._.png
The green curve occurs AT EARTH. Many so-called “pseudo-scientists” have been obsessed with a relative of the black curve, which occurs AT THE SUN.
Perhaps it is time for the mainstream to clue in to the confounding (and for some of the “pseudoscientists” to stop looking to the sun for what can be explained closer to home – i.e. Earth!)
All 3 curves relate to EOP (Earth Orientation Parameter) records, which convey information about past terrestrial climate.
…so my question is:
Why aren’t climatologists studying EOP?
(I’m not expecting a good answer.)
Thanks to Dr. Spencer for pointing the way to refreshing reality.
Invariant (15:17:27) “Our planet is spinning and wobbling with regular changes in orbit, tilt and axis. The resulting natural non-equilibrium oscillations of the climate system […] The intrinsic natural oscillations in the climate systems have no need for a variable sun to sustain the (unpredictable) oscillations.”
Bravo! …except that not all of the oscillations look “(unpredictable)”. It will be interesting to see what happens once the brighter mainstream minds decide to get more serious about investigating links between EOP & climate.