On occasion, comments posted on WUWT are backed up with data or graphs from the commenter, and are so germane that they merit their own post for discussion. This is one of those cases. Bill Illis has done a couple of guest posts on WUWT, the most recent about the “Trade Winds Drive the ENSO“. In the comments about the story on “When you can’t believe the model” he posted a significant comment on his work with NASA GISS model E (Global Climate Model) backed up with his own research graphs. For those brave enough to slog through it, here is the manual for Model E. I thought Bill’s comments were worth sharing. – Anthony
Image above is from my stock imagery and for illustration only, not from Bill Illis.
Guest Comments by Bill Illis
Awhile ago, I pulled apart the components of GISS’s Model-E and then extended the forecast it would have provided from 2003 (the end date of the data provided by GISS) to 2013, ten years.
The model would be off by about 0.15C in the first five years.
The more detailed version of this extension is here:
Click for a larger image
The simpler version is below.
Click for a larger image
Another way to look at is they have huge GHG temperature impacts built in (no way to get to +3.0C without it) but they need to build in almost as big negative temperature impacts from other sources to keep the hindcast close to the actual temperatures we have seen so far.
One could conclude they are just plugging the big negative numbers into the hindcast after the fact to make it work.
Which is close to the point Leland Teschler was trying to make in this article. (seen here)
Click for a larger image
Without a large uptick in temperatures in the next few years, the modelers really have to go back to the drawing board (or they need to discover another “negative forcing” to keep the models on track to reality).
I will once more repeat here that the deviation of “projections” to reality are inevitable for all the GCM models.
These models grid the globe with an arbitrary grid, take solutions of nonlinear coupled differential equations and use the first order terms ( means) as an approximation to the true. They have numerous unknown parameters to hindcast and force their view to the model. What happens though after a number of time steps into the future is that the true solutions that are highly divergent, and cannot be approximated by the first order terms ( and actually not really calculable,) diverge from reality more and more as time goes on.
I think this is an inherent flaw in the logic of GCMs and modelers have to sit down with their thinking caps on ( if they have them). I believe the way Tsonis et al are approaching modeling is much better fitted to the chaotic problem of climate behavior. http://www.nosams.whoi.edu/PDFs/papers/tsonis-grl_newtheoryforclimateshifts.pdf
It is worth giving the abstract here:
A new dynamical mechanism for major climate shifts
Anastasios A. Tsonis,1 Kyle Swanson,1 and Sergey Kravtsov1
Received 5 April 2007; revised 16 May 2007; accepted 15 June 2007; published 12 July 2007.
[1] We construct a network of observed climate indices in
the period 1900–2000 and investigate their collective
behavior. The results indicate that this network
synchronized several times in this period. We find that in
those cases where the synchronous state was followed by a
steady increase in the coupling strength between the indices,
the synchronous state was destroyed, after which a new
climate state emerged. These shifts are associated with
significant changes in global temperature trend and in
ENSO variability. The latest such event is known as the
great climate shift of the 1970s. We also find the evidence
for such type of behavior in two climate simulations using a
state-of-the-art model. This is the first time that this
mechanism, which appears consistent with the theory of
synchronized chaos, is discovered in a physical system of
the size and complexity of the climate system.
Citation: Tsonis, A. A., K. Swanson, and S. Kravtsov (2007),
A new dynamical mechanism for major climate shifts, GeophysRes. Lett., 34, L13705, doi:10.1029/2007GL030288
They use “the Pacific Decadal Oscillation (PDO), the North
Atlantic Oscillation (NAO), the El Nin˜o/Southern Oscillation
(ENSO), and the North Pacific Oscillation (NPO)”
Thank you – It (and the attached manual) begin to address several fundemental questions on GCM data I brougt up a few nights ago.
It’s a fairy-story isn’t it!
The Chinese have increased their coal consumption from 1 to 3 bn tons in the last 10 years (a lot of coal trains..). (Global fossil fuel consumption is close to 10 bn tons of carbon per year). The Chinese coal is said to be rich in sulfur content, which you may realize just by looking at photographs from China. If the Chinese decided to use scrubbers in all their power stations, and steel mills, and in their cement industry, which has moved there from Europe and other places, ….
then with all the sulfur dioxide gone from the atmosphere….
Model E would predict an unprecedented raise of global temperatures.
Bill Illis, tell me that I am wrong!
Why else would Dr. Hansen not speak up to that problem: Stop the Chinese coal trains…
It’s mindboggling that there are intelligent people out there that don’t see how stupid this is.
Makes me a little sad.
Could I suggest the strong negative forcing they have missed is:
“The cold winds of change”
lol.
It’s always going to 5-10 years in the future that the models will be “proved right”, and any current discrepancy is down to “weather”.
This kind of reminds me of the HIV-AIDS fiasco (which the media pretend does not exist) – for several decades the World Health Organisation (another pseudo-scientific political organisation, sort of like the IPCC) has been predicting massive increases in AIDS in the West due to a not-yet-happened HIV epidemic. It’s only recently they’ve (quietly) admitted it’s not going to happen. Not so surprising when you realise the HIV-AIDS models they’ve used are just plain wrong.
So, the non-GHG hindcast is a data set provided by GISS to make the result appear like GHG + non-GHG matches the actual temperature record… And you are saying that the non-GHG data set is generated after the fact by someone to make it appear that the model’s predictive ability is better than it actually is?
It is very important that you explain exactly what you are describing here in very clear terms. This is going to generate controversy and speculation since you seem to be implying something untoward. Please fill in the blanks:
I am saying, in no uncertain terms________________
I am NOT saying_________________
Sorry for other topic, but I’ve been following AMSU temperatures and have discovered an astonishing silmilarity for January and February of 2006 and 2009. Some similarity with 2007 is also noticable but the correlation between 2006 and 2009 is really incredible. The same forcings have to be involved…?
http://discover.itsc.uah.edu/amsutemps/
You have to choose 5 km, 2006 and 2009
What’s up?
Hi,
aren’t you supposed to show the +- 1 sigma (at least) boundaries of the model and the experimental error bars to check if the two trends are consistent or not?
Anyway, as you said, we’ll see in a few years if that specific model was right or not. I just hope someone will remember…
By the way: from AMSU data, it looks like Feb 09 will be very close to Feb 05 or 06
It all comes down to the validity of the individual components in the complete GISS Model-E. Since neither the components not the complete model have been validated, it means the results are worthless. GIGO.
Bill Illis: Thanks again. I always find your posts and comments informative.
I took a look at the GISS Model E hindcasting data in these two posts:
http://bobtisdale.blogspot.com/2008/09/giss-model-e-climate-simulations.html
http://bobtisdale.blogspot.com/2008/09/giss-model-e-climate-simulations-part-2.html
The first curiosity I found was the Model E adds a slope to the volcanic aerosol data that doesn’t appear in the Sato Index Data used as the forcing.
Model E Output for Volcanic Aerosols:
http://i34.tinypic.com/inc32t.jpg
Model E Input of Volcanic Aerosols:
http://i38.tinypic.com/2i6copc.jpg
There’s a logical explanation for that, but I don’t know what it is.
The second was GISS uses the Lean et al (2000) TSI Reconstruction (Data with Background) as their solar forcing, after acknowledging that it’s outdated. Why would they use outdated TSI data other than to add to the slope of the hindcast?
I am very interested in this. Where exactly does GISS Model E fit in the galaxy of climate models?
Is it so different from others that these problems woudl be unique to it?
Re my previous post, I should have added, well done Bill and keep up the good work. I wonder if this will be headline news in the MSM!!!!!
If AGW has actually bought us roughly +0.5C and stopped inevitable cooling, I guess I will be thankful — as I prefer becoming too warm to becoming too cold.
It could be truth that AGW is offsetting declining temperatures. Something to think about. Still, this result seems to fuel my skepticism.
US considers a national climate service
Programme would merge climate-change data from multiple agencies.
Published online 19 February 2009
Nature | doi:10.1038/news.2009.108
http://www.nature.com/news/2009/090219/full/news.2009.108.html
Thank you, Mr. Illis.
“Without a large uptick in temperatures in the next few years, the modelers really have to go back to the drawing board (or they need to discover another “negative forcing” to keep the models on track to reality).”
If the models are periodically tweaked to match actual past past data, that’s just curve fitting. So by 2100, the models should give very accurate results for what has happened up until then. Or in 2100 you could look out the window and see where the shoreline is or if there are any glaciers in sight.
I hope no one is going to work on Model E for the next 91 years, but it’s nice work if you can get it.
Let’s hope there isn’t a large uptick in temperatures in the next few years, then.
Bill,
What have you actually done here? It’s very unclear. Did you compile and run the complete Model E? Your green line seems much smoother than what GISS people report.
Maybe the IPCC should put in a request for a new model. The current one they are using seems to suffer from a really bad Y2K bug.
Good work Bill.
One problem with saying they have a 0.15C difference in five years is that the GISS monthly data is at best ±0.2C and may be worse than that. It would take 7 years jut to drift away from the monthly data scatter.
For any curve fit model, extrapolation is fraught with danger. I think my old science teachers used to say “interpolate data with caution never extrapolate”.
For some additional clarity, I’ll put up the other non-GHG components individually.
Aerosols,
http://img175.imageshack.us/img175/6919/modeleaerosolshb4.png
Volcanoes,
http://img101.imageshack.us/img101/7802/modelevolcanoesmr4.png
Land-Use,
http://img127.imageshack.us/img127/7097/modelelandusexr5.png
Solar,
http://img355.imageshack.us/img355/3111/modelesolarej8.png
Net Other forcings,
http://img127.imageshack.us/img127/5221/modeleothertw0.png
Actual Model E hindcast versus GISS’ temperature anomaly, R^2 0.544
http://img355.imageshack.us/img355/9043/modelehindcastoz1.png
You can compare Model E’s hindcast to the simple model I built (R^2 0.713) using the ENSO, AMO and only about half the GHG impact they have built in. (There are no aerosols or volcanoe impacts built into this model.)
http://img301.imageshack.us/img301/7785/finalgissmodelns3.png
Hi Bill and Anthony,
Thanks for the article – very interesting but, alas, not surprising.
“For those brave enough to slog through it, here is the manual for Model E. ”
Anthony – you’re being very charitable calling the material you linked to a manual. No equations, no detailed description of the algorithms, just what you see at the link plus a few papers. Other organizations do a much better job with their documentation (e.g. NCAR, GFDL, etc.).
Bill – did you modify any of Model E’s subroutines, or did you just do some runs using the model as it exists today with the available input data? Thanks.
AnnaV
You are right and I am surprised that Tsonis is not more frequently analysed on blogs dedicated to the climate because I am convinced that he is on the right track .
D.Koutsoyiannis who also has a similar statistical approach (power laws and scaling) comes independently to similar insights .
This :
This is the first time that this
mechanism, which appears consistent with the theory of
synchronized chaos, is discovered in a physical system of
the size and complexity of the climate system.
says it all .
However I think that you have not the right idea about what the GCM do .
They do NOT solve any coupled non linear PEDs (Navier Stokes) .
With the too coarse gridding they are obviously unable to do that .
What they do instead is merely conserve energy , mass and momentum IN AVERAGE what is much easier .
As the system is cut up in cells , f.ex 100kmx100kmx1km , the bulk of the cell is actually represented by only 1 point with 1 velocity , 1 pressure , 1 density and 1 temperature .
So the only thing you need is to write the boundary conditions with the 6 cells surrounding the one you look at (6 other points with different parameters) and then go one temporal step farther by conserving energy , mass and momentum .
All the complexity is concentrated in the equations describing the boundary conditions and the way how the characteristic parameters (subgrid parametrization) change .
And then , of course , as it is a numerical exercice , you get rounding errors and such that make you violate conservation laws so you must make sure that those deviations are “absorbed”/”redistributed” numerically over the whole system before going a step farther .
So the right picture of a GCM is more a simulation of a discrete system with N points (like N molecules) that obeys conservation laws and some boundary conditions rather than solving fluid dynamic and thermodynamic equations for a continuum .
And you are saying that the non-GHG data set is generated after the fact by someone to make it appear that the model’s predictive ability is better than it actually is?
No. What happens is the forcings resulting from all the Non-GHG climate drivers (such as sulphate aerosols) are tuned to produce a fit to the historical temperature record.
Since the non-GHG forcings are fictional and bear no resemblance to the actual forcings, they have no predictive value. So even if the forcing for CO2 is exactly right, the model will never produce accurate predictions (except by chance or by replicating the same trend).
Of course, those who follow the progress of Anthony’s Surface Stations Project will know the surface temperature record has serious problems and tuning the models to the flawed historical data makes the models even more wrong.
At first I thought Bill had the model running on some system, but I see he’s mainly “modeling the model.” It would be a lot more interesting if we had the model runs stretched out to 2013 or even model runs started with recent conditions to give it a fresh start.
The former condition would run into the problems Anna noted, the latter would reult in projections/forecasts within error bars and be dismissed on RealClimate.
Perhaps another thing to do, which would require being able to compile and run the model, is to include a “reality check” – a new forcing that reflects observed vs modeled results. If that could be approximated into the future, that could be a big help with keeping the model from drifting into fanatasy.
The plot of the reality check could provide a lot of guidance as to where the errors are in the model. An Electrical Engineering analogy is that negative feedback used in an amplifier to make it more linear can show where the open loop error is. (In practice, we know that already – various non linearities in transistors and tube/valves are the main culprits and negative feedback is a trivial way to improve things. Other solutions tend to run hotter or have complicated fitlers.)
Ah well, maybe by the time the Obama’s stimulus package cranks up, the new Great Climate Shift (the PDO is adequate explanation) will provide enough guidance to come up with an accurate GHG forcing approximation. (Or an accurate model!)
Frank K,
The data comes from a page GISS put up for Model E (and I have to give GISS a big thumbs up on this one since it is relatively easy to use compared to some of the other climate model sites I’ve been to.)
I didn’t run any models or use the code, I just downloaded the info from the site.
http://data.giss.nasa.gov/modelE/transient/climsim.html
GCM/AGW models were never about describing reality. They have always been about selling an idea to a very particular group of ‘buyers’- policy makers. The models, and their promoters, have done an excellent job in the regard. That these ‘buyers’ are the same people who destroyed our economy and financial system by believing financial models is not coincidental.
How much warming is being caused by the burning of 10 billion tons of hydro-carbons plus heat generated by other power sources and is this being taken into account in the models? Also how much warming is coming from solar heating due to soot from these coal plants? Thanks
“I was at my home at 14.00 August 11, 2008, and my outside temperature registered 91°F . Then it started to cloud up and by 16.30 there was a thunder shower. The temperature dropped to 71°F . Where did all the heat go? It went 5.5 miles up, where the temperature is usually about –55°F (as trans-Atlantic pilots like to report) and subsequently out into space, carried there by the powerful heat carrying capability of liquid water when it turns into vapor and consumes 972 Btus per pound and then back into liquid, releasing that latent heat of vaporization into space as thermal radiation. This happens almost every day in the summer in the temperate zones and all the time in the tropics, and it’s not taken into account in the AGW computer models, because models can’t model rain, clouds, lightning, storms and hurricanes very well at all, because it’s too complicated and chaotic. AGW computer models also don’t model ocean current oscillations, which are major factors in effecting the Earth’s heat balance. This is why myopic atmospheric science projections are getting so far away from the observed global temperatures, since the Pacific Decadal Oscillation switched to it’s cold phase in late 2006.”
From http://ccd4e.org/drpierre_latour_and_jeff_temple/
Off topic sort of but I just saw where Senate Majority leader Harry Reid said on thursday that they were going to tackle climate change ,global warming was what it use to be, by this summer .What a waste of money and time.How do you tackle something that is natural and runs in cycles.This is nothing more than socialism at its finnest having control on the American public.Next they will telling us we have to turn heat dowm in winter and raise our air conditioner up or we will be charged for excessive use.The days of horse and buggy just may return too.
IMHO, when all is said and done, modelers will have succeeded in accurately predicting the past. Many models now predicting an El NINO, by July. We shall see.
TomVonk (04:45:46) :
You are right and I am surprised that Tsonis is not more frequently analysed on blogs dedicated to the climate because I am convinced that he is on the right track .
For me the surprise is why the modelers/climatologists are not going full speed ahead on this type of models.
I know that they cannot be solving coupled differential equations of any type in GCM. I think they think they are because they are using mean values for everything within their grid volumes. The mean is the first moment of any solution of a system, no? If the real equations were linear and well behaved and a perturbation expansion of the solution made sense their method would have worked, imho. It is the high probability that the true (unknown) solutions are highly divergent that clobbers the models.
anna v,
I’ll have to look more into the paper by Tsonis et al. But until I do, can you translate the abstract a bit for me? What is meant by a “synchronous state?” Could this be something like sinusoidal oscillations, which are periodically disrupted and reform about different base states and perhaps with different amplitudes? Or are the “synchronous states” completely chaotic?
In my research on bidecadal oscillations, I’ve encountered Tsonis before:
J.B. Elsner and A.A. Tsonis, 1991: Do bidecadal oscillations exist in the global temperature record? Nature. 353, 551-553.
Their answer was “no,” and I believe that their conclusions were based on weak support and with longer data (since 1991) are easily refuted.
But your link to Tsonis has me curious, so I will try to see what, if any, connection there might be to this new way of modeling, and that “older” paper with Elsner.
Basil
To Werner Weber: I can tell you exactly why no one in the US agw movement, and certainly not Dr. Hansen, is too concerned with the Chinese coal trains. Chinese trains have absolutely nothing to do with setting up a new command and control regime combined with confiscatory energy tax policies here in the US.
That’s all this game is really about, and anything else is just window dressing. The lack of concern about the Chinese situation is as good a proof of that as anything.
Also: “US considers a National Climate Service.”
Whatchya wanna bet it’s going to be managed and staffed by purely political
appointees, who will of course make sure that the right “message” is conveyed to the public? We wouldn’t want anybody upsetting the “consensus” now, would we?
Frank Mosher, IMHO, when all is said and done, modelers will have succeeded in accurately predicting the past.
With all due respect, the “modelers” have not yet even accurately predicted the past!
Great article Mr. Illis.
Watts up with the word ‘germane’
REPLY: ??
Allen63 (02:59:05) :
It could be truth that AGW is offsetting declining temperatures.
If that werre the case, then Hansen et al should be singing the praises of CO2.
“It’s mindboggling that there are intelligent people out there that don’t see how stupid this is.”
I think the same thing every time I see how much some people pay for modern art. It’s incredibly easy for intelligent people to deceive themselves in a way that wouldn’t occur to a child.
terry46 (05:54:47) The days of horse and buggy just may return too.
[sigh] Lets hope not…..
Every time I see one of the tree huggers pining [horrible pun intended] for the ‘good old days’, when things were ‘natural’, I know they have never been around any real quantity of horses….
Every winter the horse shows visit south Florida…and for those three months, truck load after truck load of stable sweepings are found dumped in odd corners of the countryside as waste haulers look for ways to avoid the tipping fees. Multiply that by several million and you begin to see one of the results of where many of the greens plans could lead us.
I have been a profesional environmentalist for 40 years…clean air, water, soil etc. MATTER to me…but I haven’t gone stark raving crazy in the process!
Just another rant from the swamp….cdl [rant over]
wws wrote:
‘Whatchya wanna bet it’s going to be managed and staffed by purely political
appointees, who will of course make sure that the right “message” is conveyed to the public? We wouldn’t want anybody upsetting the “consensus” now, would we?’
AGW is one tactic in a political war whose goal is a centralized command and control economy. The goal is clear — and the strategy is the utilization of fear.
Remember, the elites will always have a large carbon footprint and enjoy the finer things in life. Prez Obama is flying all over America and Canada for photo ops while “Nancy with the laughing eyes” flys a 757 to Rome to meet with the Pope.
Our Prez tells corporations to limit salaries to $500,000 and get rid of the corporate jets while he jets around on AF1 eating expensive Wago beef. A US national Climate Service will create another constituency group who will vote for elitist politicians.
I am sorry to get off topic.
Kohl Piersen (02:48:31) asked:
“I am very interested in this. Where exactly does GISS Model E fit in the galaxy of climate models?
Is it so different from others that these problems woudl be unique to it?”
Can anyone answer or point to references (whatever). I really would like to know whether a single model can be considered representative, and where this one fits into the scheme of things. Is it better? worse? than others etc etc
Craig D. Lattig (07:22:15) :
terry46 (05:54:47) The days of horse and buggy just may return too.
[sigh] Lets hope not… truck load after truck load of stable sweepings are found dumped in odd corners of the countryside as waste haulers look for ways to avoid the tipping fees. Multiply that by several million and you begin to see one of the results of where many of the greens plans could lead us.
Up to our necks in horsecr*p.
At least we’d know who to blame. They’d be the ones using their horses to push the cart.
I found the code in Hansens program to calculate temperature…
T = 58 + 5 * Log2(CO2/260)
The other 50,000 lines are there to make it look impressive
Bill,
The models using exagerated anthropogenic aerosol cooling to counter the amount of predicted anthropogenic greenhouse gas warming and prevent a runaway greenhouse effect is nothing new. But your suggestion that volcanic aerosols should be eliminated from the equasion is beyond ridiculous in my view. I’m also bothered by the limited ocean circulation calculations you used. There needs to be a separate calculation for each individual ocean circulation, not just 3 of them. And you need to show different data for each, not a cumulative number. But nevertheless, you are definately on the right track considering you are including ocean circulation at all.
Some day soon, we should shift strategy and start thanking/congratulating Gore and his minions for stopping global warming.
Someone like Harry Reid just might fall for it. Would that be fun or what? Imagine Hanson’s shock if Reid called a press conference to claim credit for the end of global warming.
But timing is everything and the moment is not now.
vukcevic (03:02:33) : “‘US considers a national climate service Programme would merge climate-change data from multiple agencies.'”
So there will be no way for anyone to check up on what the climate is really doing, just one data set with as many “homogenizations,” and “corrections” as they want.
Fortunately nature works outside models: Chaiten volcano is erupting now and (as local paper say) throwing out 20 m3/sec instead of 9 m3/sec (expected)
http://uk.reuters.com/article/scienceNewsMolt/idUKTRE51I77H20090220
Werner Weber:”then with all the sulfur dioxide gone from the atmosphere….
Model E would predict an unprecedented raise of global temperatures”
It would be exactly the contrary, SO2 is the seed of cloud formation.
Using modeler’s own linear approximations for forecasting, 0.15 deg positive bias error / 5 years = 0.03 deg/year over 100 years is 3 deg/Century. Using their own circular logic this entirely disproves their own theory. >grin<
Basil (06:13:41) :
An exposition of the connection of neural nets, climate and chaos is given here by Tsonis:
http://www.uwm.edu/~aatsonis/BAMS_proofs.pdf
I think in a sense it is the same logic as with analogue computing: since one cannot solve the coupled differential equations one can model the equations themselves (make analogues) and let the system solve them.
There have been discussions of the Tsonis and Koutsogiannis papers in CA .
Kohl Pierson, go to lucia’s http://rankexploits.com/musings/ for a good amount of information. If you want a detailed discussion, find the argument, I believe it is on the Pat Frank thread, between Gerald Browning and Schmidt at RC. Also, read the cross posts at CA, just in case RC edited or deleted something. For your own, read Tebaldi, C. and R. Knutti, 2007, The use of the multi-model ensemble in probabilistic climate projections, Philosophical Transactions of the Royal Society A, 365, 2053-2075, doi:10.1098/rsta.2007.2076, PDF (0.3 MB) http://www.iac.ethz.ch/people/knuttir/papers/tebaldi07ptrsa.pdf
“One could conclude they are just plugging the big negative numbers into the hindcast after the fact to make it work.”
This is a key statement: a devastating one if true, but an incendiary one if simply conjecture. Does Bill Illis reach this conclusion? – or is he just speculating that others have reached this conclusion? Has he done the necessary research to come to a conclusion?
Hopefully it is well known that climate models do not track GMT well if one includes just GHGs, and they do not get much better by adding our current understanding of solar energy. However, they track well if aerosols are added.
Over a year ago, I spent a couple of months studying GCM use of aerosols, including available data sets on aerosols that can be used as inputs. The data on aerosols are more extensive than most skeptics realize. Nevertheless, on a global scale, aerosol data sets are sketchy relative to the number of grids and years in the models. Also, one must estimate (or assume / conjecture) what the forcing impact of aerosols is on temperatures. (This estimation process makes laughable the statement that GCMs are based on solid, well-understood physical principles.) While I did not conclude that aerosols are simply dummy variables used arbitrarily to make the hindcast fit, I do get the impression that the data sets chosen and the forcing impact estimated are definitely conveniently chosen.
Bill C: Where does Bill Illis say that volcanic aerosols should be eliminated from the equation? My take on what he’s written and provided is that he notes that they’re not included in his model, so that the user can take it into consideration.
Bob, think about it… if they’re not included in the model then they’re obviously eliminated from the equasion.
Bill Illis,
Great analysis. Much better than the IPCC’s projections: click
I can relate to many of the issues folks have raised about modeling. I developed a FORTRAN model for my MS thesis to calculate the direct current response to buried resistive bodies (things, not coprses!). I still remember a few dreams of being stuck in a do loop and unable to get out… 🙂
Adjusting model inputs to yield model outputs that compare well with reality isn’t a bad thing. If a model can’t accurately predict the known data then it is close to useless. So the tuning of the models in of itself is nothing to merit raised eyebrows.
What should raise eyebrows are when the inputs are tweaked beyond the range of ‘normal’ for said input. If the only way to get a model (any model, not just GCM) to match real world output is to feed it non-real-world input then the model is wrong and needs to be changed.
When the inputs are something we can measure, say the amount of sulfate particulate in the atmosphere, we can readily test the fidelity of the model input to reality. When the model input is parameterized, ie not a measurable property of the real world but an aggregated one, then there is no way to compare the fidelity of the model input to the real world. Tweaks of parameterized inputs done to accurately hindcast must be very explicitly explained and justified. Absent that explanation and justification, the model and its outputs should be viewed with a high amount of suspicion.
Bob and Mike C,
I just meant to say they are not included in the model (not that they aren’t required).
When I started doing this reconstruction, I originally thought that I would need to include a volcanic impact as well.
But after accounting for the ENSO and the AMO, there really isn’t any volcanic impact that needs to be included. Other than Pinatubo, the other volcanoes (including Krakatoa, Santa Maria, Nova Rupta, Agung, and El Chichon) did not influence the temperature trend very much at all.
I could plug some (negative) impact here or there but I did not want to start using plugged data, I just wanted it to be a straight-up mathematical calculation.
There is some room for some negative numbers with Pinatubo though.
I did look at this very closely because it did not make sense to me but the data is the data. It is possible that the ENSO and the AMO go down due to the volcanoe influence and my residuals would then show little need for them but the base temperature data does not show much impact either.
Here are some charts showing it. I think the blue lines are the actual temperature lines in all these charts and some of them come from other projects so there is a different focus in some of them.
http://img372.imageshack.us/img372/3685/volcanoehadleyxs2.png
http://img297.imageshack.us/img297/16/krakatoata5.png
http://img232.imageshack.us/img232/760/elchichonks8.png
Santa Maria and Nova Rupta occured in this chart. See if you can pick out the dates?
http://img142.imageshack.us/img142/535/1020modelfa6.png
I see Mount Pinatubo had a larger impact than the others.
http://img55.imageshack.us/img55/2716/mountpinatubanb7.png
Now where the volcanoes have the greatest impact is in the stratosphere. If you go back to 1963 with Agung, this same trend exists in the stratosphere temps. An immediate 1.0C to 1.5C increase in temperatures followed by a decline of 1.5C to 2.0C at which point the stratosphere temps stabilize and then potentially build back up until the next volcanoe.
I wonder if the optical depth calculations used to estimate the volcanoe influences are really just picking the high stratosphere impact but that the surface is not being impacted as much as the optical depth data would indicate should be occuring. The stratosphere layers are often isolated from the surface layers.
http://img258.imageshack.us/img258/235/uahstratvolcanoesyb5.png
Bill,
Great job! I’ve been saying the same thing for over a year at RC (I reposted your pertinent comments below). I have received nothing but poor responses and/or attacks when I do post these issues. Essentially the answer has been, “Temperature is going to go up anyway, so your point is without merit. No need to change our methodology.” Regarding aerosols, I looked into the data as well (led by a lady researcher from UM). No one can answer the question why aerosol cooling is going up every year when in fact North America and Europe have cleaned up emissions from their power plants and factories. Plus, the former Soviet Union pollutes a lot less today than it did in the 70 or 80’s. Granted China is a mess, but the trend numbers that I’ve seen (both past and present) don’t pass the smell test (my doctoral thesis in chemical engineering was SOx/NOx removal from coal-fired power plants). Trust me, climate modeling is a big hoax that Gavin and the others all realize. There only hope is that things get warmer (not cooler). A cooling climate exposes their fallacy much like falling home prices exposed the fallacy of sub-prime mortgage-backed securities being rated AAA. I’m not saying that malice is involved, but ego and greed (just like the current financial mess).
Chris
Great quotes:
“Another way to look at is they have huge GHG temperature impacts built in (no way to get to +3.0C without it) but they need to build in almost as big negative temperature impacts from other sources to keep the hindcast close to the actual temperatures we have seen so far. One could conclude they are just plugging the big negative numbers into the hindcast after the fact to make it work. Without a large uptick in temperatures in the next few years, the modelers really have to go back to the drawing board (or they need to discover another “negative forcing” to keep the models on track to reality).”
Quick question, just so that I can appear knowledgable to my ever decreasing circle of AGW “believers.” Does GCM stand for Global Climate Models or General Circulation Models?
35 years ago, I had the dubious pleasure of providing some input on the mining industry for the construction of Canada’s first computer modelling of the national economy. The first models had some 30 to 40 equations to describe the economy historically and when it was given a trial run for the future, Canada appeared to be heading for a long term growth of about 10% a year. They adjusted the equations several times without much sucess and finally a colleague picked up a piece of chalk and drew an upward sloping line on the blackboard and said this is a model of the Canadian economy – an average annual growth of about 4%. I think this kind of “targetting” figures largely in the climate models.
Bill, I would take into consideration the location, type and strength of the individual erruptions. Santa Maria, being in Guatemala should have a global impact. El Chichon, near Mexico City mainly affected the northern hemisphere according to direct optical thickness measurments. Novarupta was in Alaska so it would have had little impact other than high lattitudes in the northern hemisphere. Agung, Krackatoa and Pinatubo are all in low lattitudes (Pinatubo definately had global effects according to optical thickness measurments).
El Chichon knocked down global temps that otherwise would have increased by the 82-83 El Nino. Pinatubo knocked down global temps that would have been higher due to the string of El Nino’s in the following 2-3 years.
So the challenge for you is to calculate the change in solar forcing created by each volcano. Then you need to calculate the temperature change created by individual ENSO events. Then you need to do the same with each of the other ocean circulations (AMO, PDO and etc). That way you will have done what the AGW modelers have failed to do thus far… include all of the inputs into your model without having to increase the magnitude of any one to compensate for the lack of magnitude of another.
Bill Illis: Volcanic eruptions not only lower global temperatures by reducing downward shortwave radiation, but those that occur in the tropics also suppress the “poleward” heat transfer of El Nino events. Mount Pinatubo (16N, 120E) squashed the 1991/92 El Nino and the minor mid-year El Nino in 1993. El Chichon (19N, 93W) totally counteracted the 1982/83 El Nino.
http://s5.tinypic.com/16c0vat.jpg
The 1902 eruption of Santa Maria (14N, 91W) would have been been counteracted by the 1902/1903 El Nino. The 1912 eruption of Novarupta (58N, 156W) is a high-latitude NH eruption. It might have had some effect on the 1911/1912 El Nino, hard to tell with the time lags of El Nino impacts on high latitudes. And then again, back in the early 1900s the data was kind of sparse, which is another reason the 1911/12 El Nino and the Novarupta eruption may not be showing that well in your early graph.
http://s5.tinypic.com/wbf82f.jpg
If you’ve chosen not to include volcanic eruptions because you don’t have a place for them in your model is one thing; not including them because you can’t see the effects in the data is another.
Off topic: I’m finishing up a post you’ll enjoy on OI.v2 SST data. I removed the North Atlantic SST anomaly data from the global SST anomaly data. It sets the trend way high, obviously, but it also suppresses lots of worthwhile data in the rest of the oceans. There is at least one thing you’ll find very interesting. It may help with your efforts. I’m trying to get it done by tomorrow A.M. With luck (getting some time to finish it), it’ll be done tonight.
Regards
Don’t be so shocked or disappointed about what the warmists are after … It has nothing to do with saving the planet or the environment or proving their point that their predictions of a scorched earth with high water is at hand.
This about getting money from the rich to give to the poor and also about controlling populations. The free spirited middle class is too unpredictable and hard to control. Plus they generate far too much envy from the loser classes.
End of story. This is politics not science. If the warmists fail, their masters will find a new fear to leverage their evil.
timbrom (12:24:35) :
“Quick question, just so that I can appear knowledgable to my ever decreasing circle of AGW “believers.” Does GCM stand for Global Climate Models or General Circulation Models?”
While I have seen both usages, I believe the latter is correct.
Bill Illis (05:26:15) :
I still can’t see where you get your projections. You haven’t run the model. The GISS page you link to just has data to 2003. How did you calculate the extension? Are you fitting curves to past data and then extending them? If so, what curves are you using?
Robert Wykoff (07:39:24) :
“I found the code in Hansens program to calculate temperature…
T = 58 + 5 * Log2(CO2/260)
The other 50,000 lines are there to make it look impressive”
That’s been my take on the whole idea of “sensitivity”. If you know that (ie what change in degC for a given change in CO2 ppm) why do you need anything else? I’ve raised this point before in different places but have never got a reply.
Nick Stokes,
There are two components to the extension; the GHG component and the non-GHG component.
(This is going to get technical now but I guess I should fully explain it so…)
For the GHG side, Model E – GHG forcing temperature impact fits very well over time to Temp C (anomaly versus Kelvin) = 4.053 Ln (CO2) -23.
I use CO2 as a proxy for all the GHGs but this is a reasonable proxy since CO2 is the biggest GHG and N2O is increasing at exactly the same rate. The other GHGs, Methane and CFCs have stabilized recently so using just CO2 could slightly over-estimate the 2003 to 2013 trend but not by very much at all. (Actually there has been a recent uptick in Methane concentrations while it looked up to 2006 that it had stabilized. The preliminary numbers into the fall of 2008 show the uptick continuing.)
So, from 2003 to 2008, I used the actual global CO2 numbers and from 2008 and onward, I used the forecast CO2 growth rate trends (which are just slightly exponential).
I’ve been able to simulate the IPCC temp forecasts using this method and the math works backwards and forwards so I have no problem having faith in it.
For the Non-GHG component, I just fitted a polynomial function starting in 1995 to Model E’s non-GHG forcing (starting in 1995 allowed the big impact from Pinatubo to settle out of the numbers). For 2003 on, the negative forcing from Pinatubo still has a few years to completely return to the no-volcano-normal (which increases the trend slightly in the first few years) and then afterward, the negative trend from Aerosols and Solar forcing kicks in to make the trend downward again.
So there is a very slight increase in the non-GHG component for a few years after 2003 and then it will start down again.
It is possible that a little more negative impact should be built in for Solar given the recent decline in the Sun but there is a little built in already for the non-GHG component to decline so I just left it at that. It is also possible that slightly more negative trend could be included for the Asian brown cloud but European, North American and Russia’s aerosols impact is supposed to be declining now so I just left it at that again. We are only talking about a maximum 0.05C change in this either way.
Add it all up and there you go. The first chart linked to in the post shows it as best I can.
OK Bill,
but now I can’t see the connection to Model E at all. You’ve used the forcing data that they used, but that isn’t model E output – it’s just general atmospheric data that they’ve collected and make conveniently available. You’ve used general IPCC data, and IPCC projections about CO2 emission, none of which is connected with Model E. And you seem to have used the log relation of CO2 to temp, which again is ancient, and nothing to do with model E. You haven’t run model E, nor, as far as I can see, used the results of other runs. So why is this post titled “Short term trends from Giss Model E”?
Robert Wykoff (07:39:24) :
“I found the code in Hansens program to calculate temperature…
T = 58 + 5 * Log2(CO2/260)
The other 50,000 lines are there to make it look impressive”
What Hansen is doing here is now easy to understand. He’s taking whatever the present CO2 level is at, and dividing it by 260, which he has decided is the “proper” CO2 level. This factor then tweaks his temperature. The problem with this is that CO2’s insolation ability follows a diminishing returns curve, not a Log curve that would curve upward logarithmically. Hansen is operating on the idea that our thin atmosphere is capable of a runaway greenhouse effect like Venus is. This is the big fraud in his code.
It’s good to see the simpler formulas that Hansen has recently “nailed”. They can be falsified without major excursions into the computer codes.
Bill Illis:
From your posting above:
“Actual Model E hindcast versus GISS’ temperature anomaly, R^2 0.544
http://img355.imageshack.us/img355/9043/modelehindcastoz1.png
You can compare Model E’s hindcast to the simple model I built (R^2 0.713) using the ENSO, AMO and only about half the GHG impact they have built in. (There are no aerosols or volcanoe impacts built into this model.)
http://img301.imageshack.us/img301/7785/finalgissmodelns3.png ”
—
I note that there is no arbitrarily and increasingly negative “land use” fudge factor (er, correction) built into the simple model either. [I assume the Model E textbook adds, “It is left as an exercise for the student to explain exactly why land use would be a negative factor w/r future global temperatures.”]
Your note on the graphic for aerosol “correction” shows that Hanson’s (Model E ) aerosol correction values differ greatly from the historical record of how much pollution (smoke primarily) has been produced at what levels from which sources. [Again, this is left as an exercise for the student to explain why the values are what they have entered ….]
For your own equation, please let me play devil’s advocate (er, AGW zealot) for a moment with your “simple model.” It appears to be a “curve fit” of past data “using the ENSO, AMO and only about half the GHG impact.”
Since the ENSO and AMO are chaotic, random events that don’t (or do they???) follow a predictable pattern, can we use them to predict the near future, or can we at best predict only a 70 year 1/2 degree temperature cycle? Are they a valid index for the future – even if they can’t be predicted nor fully explained at this time?
It appears logically reasonable to include a (small) CO2 factor in predicting future temperatures – the cleverly presented theorectically valid “logic” of the CO2 religion is, after all, the ONLY thing that keeps their faith alive. Why would your CO2 fudge factor be so much lower than Hanson’s – other than that your factor actually fits the observed data over time, that is.
For your “curve fit solution” what is the source of the input values (ie, what exactly is “input” when you calculate a term for ENSO; who determines this value, and how often is it updated? [Hanson’s Model E “urban use factor” and “aerosol factors” for example, are not explained, do not have a validated “source”, are not publically reported, are not checked, and does not appear to be based on any historically valid (verifiable) public data, nor any logical extrapolation form today’s (assumed) data. Are your extrapolations any better?
Why are you using the (R^2 0.713) term, and what is its source? If TSI changes, does this value change?
Is your “simple model” valid over a short period (6 – 12 months)? Can you “predict” the next 6- 18 months based on today’s ENSO and PDO states – even if longer term predictions are not practical nor reasonable?
Converting forests to croplands, for example, raises the surface albedo since forests generally reflect less sunlight than the croplands do. Of course, clearing forests also releases CO2 which can cause more warming…But, if one is using the actual amount of CO2 in the atmosphere to determine the net forcings, any such change would be reflected in that term.
Bill
CO2 is the biggest GHG?
Regarding the formula in Model E’s code “T = 58 + 5*Log2(CO2/260)”, I imagine this was a little tongue in cheek comment. A variation of the formula would fall out of the model runs, not be in the code.
I think the natural cycle model can predict fairly accurately what is “due” in the future. We have other models that use that phrase. For example, earthquake and volcanic models use this terminology to warn us that we are “due” for an earthquake here or there, etc. Then we can go about making preparations for that event. Global models based on naturally occurring cycles (even ones that don’t follow a set 10 year on, 10 year off pattern) can predict that we are “due” for a trend down or up, and what to look for when the trend hits.
Great study!
Just eyeballing, it seems modelE is deviating from reality today more than it ever did in the hindcast. This puts paid to the realclimate crowd’s claims that the current cooling is just “weather”. The deviation between model and reality attributable to “weather” vs “climate” should be more-or-less stationary, so we’d expect no greater deviation today than in the past.
In other words, either the current deviation between model and reality is due to more than just weather – ie genuine cooling of the climate – or their model was drastically overfit. Either way, the realclimate crowd and the IPCC are wrong.
Re: Aerosols in the atmosphere leading to cooling.
As some of you may know, I follow the energy industry, and particularly the oil industry, pretty closely. The petroleum product that produces atmospheric aerosols much more than any other is jet fuel exhaust.
It is quite interesting that jet fuel production peaked in 2000 at around 1.6 million barrels per day, and has declined approximately 12 percent since then (U.S. data only, see below for link). As the U.S. produces approximately one-fourth of all refined products in the world, it may follow that world-wide jet fuel also has declined.
Perhaps one of the Gandalfs on WUWT can comment on this information wrt the aerosol component of the GCM. My wizardry is not sufficient for this task. But, if I understand what I have read thus far, aerosols counter the effect of CO2. If CO2 is steadily increasing, but aerosols are decreasing, then the global temperatures should rise significantly.
U.S. Jet fuel production from EIA is hereclick.
God does not play dice, humans have only the liberty to fool themselves playing a supposedly god´s game. These models are just X-Box or Playstation games played by grownups.
I don’t know anything about climate models and not much about climate (or solar) science, so probably got my facts/conclusions wrong. A few years ago I saw a science program (Horizon) on global dimming. If my memory is correct they said that during the last century the sunlight reaching the Earths surface had reduced (global dimming) as a result of manmade soot in the air, and in recent years the soot was reducing and the sunlight reaching the surface increasing. That seemed to make sense because I thought I had read that the Earths albedo had been reducing, then increasing about the same time. i.e. I thought the soot was absorbing sunlight, reducing albedo, causing global dimming and warming the atmosphere by absorbing the sunlight. And presumably the temperatures may fall if we are reducing soot (I believe they have levelled off or dropped in recent yeRS)?
The Horizon program (Hadley centre) came to the opposite conclusion; that the dominant effect of soot was helping the formation of more reflective clouds; reflecting more sunlight causing dimming and cooling which was offsetting the CO2 warming. Thus they concluded they had previously underestimated the CO2 warming effect, and as we reduce soot the warming will be even worse. I thought the dimming theory should mean the albedo should have been increasing when I thought the measurements (Earthshine/satellite data) showed it was reducing while we were dimming? And I thought I had seen research that showed that soot reduced clouds (by warming the air, making it harder for droplets to form).
I’ve probably got my facts wrong as I’ve not seen it discussed like this before (although I saw a month or 2 ago NASA were saying that reducing soot should help reduce temperatures, I couldn’t find more details – I was hoping it might have been discussed at WUWT). My understanding is that current climate models include the global dimming effect, i.e. assume atmospheric soot mostly cools.
Just wondering if anyone thought this could be a reason for the discrepancy; i.e. soot rather than CO2 caused a lot of the warming.
I’m also interested in solar affects. Did Leifs comments a month or 2 ago about the paper “Linkages between solar activity, climate…” (sunspots and rain in South Africa) mean he doesn’t believe it shows a link between sunspots and rain at that location? – sorry, I missed the discussions when the paper first came out. I don’t think Leif was impressed by graph 2? – MAR (mean average rainfall, I think?) vs years into the 21 year solar cycle, unfortunately it’s over a year since I read the paper, but at the very least does it not show that for the 5 consecutive cycles the rainfall was always below average at the end of the cycle and above average at the start? Isn’t the probability of that being more than coincidence too high to ignore? Or is their data/maths wrong? I thought they were saying the level of rainfall depended on how sunspots increased.
Probably not relevant, but about the same time there was some discussion about tides on the Sun; shouldn’t Leifs equation to calculate the tide include something for the properties (e.g. compressibility) of the object (Sun, planet etc), e.g. wouldn’t plasma have a different tidal bulge to solid rock or liquid water? I probably misunderstood?
yes, you didn’t post the final graph of Bill Illis (118439) . This graph seems to purport to show that we are on a ‘lower trajectory’ and the results are consistent with a climate sensitivity of about 1.62C. Of course it shows nothing of the sort; just the transient response.
See this post for a detailed analysis. Bill’s graphs in fact seems exactly consistent with the IPCC core preductions: 550ppmCO2 by 2060, 1.5C in reality plus another 1.5C in the pipeline; climate sensitivity of 3C for a doubling.