As we did roughly a year ago (and as we will probably do every year around this time), we can add another data point to a set of reasonably standard model-data comparisons that have proven interesting over the years.
First, here is the update of the graph showing the annual mean anomalies from the IPCC AR4 models plotted against the surface temperature records from the HadCRUT3v, NCDC and GISTEMP products (it really doesn’t matter which). Everything has been baselined to 1980-1999 (as in the 2007 IPCC report) and the envelope in grey encloses 95% of the model runs.
The El Niño event that started off 2010 definitely gave last year a boost, despite the emerging La Niña towards the end of the year. An almost-record summer melt in the Arctic was also important (and probably key in explaining the difference between GISTEMP and the others). Checking up on our predictions from last year, we forecast that 2010 would be warmer than 2009 (because of the ENSO phase last January). Consistent with that, I predict that 2011 will not be quite as warm as 2010, but it will still rank easily amongst the top ten warmest years of the historical record.
The comments on last year’s post (and responses) are worth reading before commenting on this post, and there are a number of points that shouldn’t need to be repeated again:
- Short term (15 years or less) trends in global temperature are not usefully predictable as a function of current forcings. This means you can’t use such short periods to ‘prove’ that global warming has or hasn’t stopped, or that we are really cooling despite this being the warmest decade in centuries.
- The AR4 model simulations are an ‘ensemble of opportunity’ and vary substantially among themselves with the forcings imposed, the magnitude of the internal variability and of course, the sensitivity. Thus while they do span a large range of possible situations, the average of these simulations is not ‘truth’.
- The model simulations use observed forcings up until 2000 (or 2003 in a couple of cases) and use a business-as-usual scenario subsequently (A1B). The models are not tuned to temperature trends pre-2000.
- Differences between the temperature anomaly products is related to: different selections of input data, different methods for assessing urban heating effects, and (most important) different methodologies for estimating temperatures in data-poor regions like the Arctic. GISTEMP assumes that the Arctic is warming as fast as the stations around the Arctic, while HadCRUT and NCDC assume the Arctic is warming as fast as the global mean. The former assumption is more in line with the sea ice results and independent measures from buoys and the reanalysis products.
There is one upcoming development that is worth flagging. Long in development, the new Hadley Centre analysis of sea surface temperatures (HadISST3) will soon become available. This will contain additional newly-digitised data, better corrections for artifacts in the record (such as highlighted by Thompson et al. 2007), and corrections to more recent parts of the record because of better calibrations of some SST measuring devices. Once it is published, the historical HadCRUT global temperature anomalies will also be updated. GISTEMP uses HadISST for the pre-satellite era, and so long-term trends may be affected there too (though not the more recent changes shown above).
The next figure is the comparison of the ocean heat content (OHC) changes in the models compared to the latest data from NODC. As before, I don’t have the post-2003 model output, but the comparison between the 3-monthly data (to the end of Sep) and annual data versus the model output is still useful.
To include the data from the Lyman et al (2010) paper, I am baselining all curves to the period 1975-1989, and using the 1993-2003 period to match the observational data sources a little more consistently. I have linearly extended the ensemble mean model values for the post 2003 period (using a regression from 1993-2002) to get a rough sense of where those runs might have gone.
Update (May 2010): The figure has been corrected for an error in the model data scaling. The original image can still be seen here.
As can be seen the long term trends in the models match those in the data, but the short-term fluctuations are both noisy and imprecise.
Looking now to the Arctic, here’s a 2010 update (courtesy of Marika Holland) showing the ongoing decrease in September sea ice extent compared to a selection of the AR4 models, again using the A1B scenario (following Stroeve et al, 2007):
In this case, the match is not very good, and possibly getting worse, but unfortunately it appears that the models are not sensitive enough.
Finally, we update the Hansen et al (1988) comparisons. As stated last year, the Scenario B in that paper is running a little high compared with the actual forcings growth (by about 10%) (and high compared to A1B), and the old GISS model had a climate sensitivity that was a little higher (4.2ºC for a doubling of CO2) than the best estimate (~3ºC).
The trends for the period 1984 to 2010 (the 1984 date chosen because that is when these projections started), scenario B has a trend of 0.27+/-0.05ºC/dec (95% uncertainties, no correction for auto-correlation). For the GISTEMP and HadCRUT3, the trends are 0.19+/-0.05 and 0.18+/-0.04ºC/dec (note that the GISTEMP met-station index has 0.23+/-0.06ºC/dec and has 2010 as a clear record high).
As before, it seems that the Hansen et al ‘B’ projection is likely running a little warm compared to the real world. Repeating the calculation from last year, assuming (again, a little recklessly) that the 27 yr trend scales linearly with the sensitivity and the forcing, we could use this mismatch to estimate a sensitivity for the real world. That would give us 4.2/(0.27*0.9) * 0.19=~ 3.3 ºC. And again, it’s interesting to note that the best estimate sensitivity deduced from this projection, is very close to what we think in any case. For reference, the trends in the AR4 models for the same period have a range 0.21+/-0.16 ºC/dec (95%).
So to conclude, global warming continues. Did you really think it wouldn’t?
In your graph of temperature measurements vs model projections, you discuss Scenario B, while it appears that Scenario C is almost identical to HadCrut3 and GisTemp. All three are about 0.185K/decade. Is this not the general trend from 1900, and considered a reflection of natural warming coming out of the LIA?
The CAGW worry I have is based on 3K/century. I expected that we would be in the acccelerating >2.0K/century by now, 22 years after the 1988 initiation of the concerns. At any rate, while global warming is certainly still occurring, doesn’t your graph here suggest that there is only a “background” type of warming going on, the non-feedback type that we thought would be such a problem?
I’m also confused by the comparison between the temperature graphs and the ocean warming graphs, certainly by the Lyman portion of the ocean heating graph. If the oceans take up and hold the heat so much more than the atmosphere, and then warm the atmosphere because the oceans are warmer, why do the two trends of ocean heat and atmospheric temperature not follow each other? Up to 2002 the Lyman measurements match, as if the ocean and atmosphere were in equilibrium. Then they diverge, and do so from the other data compliers’. Did Lyman’s methodology change in 2002?
Rather than support the CAGW, this post seems to support global warming of a moderate level, but not of a disasterous level. The Lyman divergence is very odd. It is possible that Lyman is measuring a transfer of oceanic heat from warm waters to cool waters through circulation changes than increased retention of solar energies?
[Response: ‘C’AGW is not any actual scientific hypothesis, theory or result. To my knowledge it has never appeared in the text of any IPCC, NAS or Royal Society report. It only exists in contrarian blogs when people want to argue against some strawman. Since I don’t know what it is, nor have I ever written about it or seen it honestly described, I have no idea whether what I wrote supports it or not. If you would like to know what the scientific projections are and why people are concerned about ‘business-as-usual’, please see any of the reports I mentioned above (or read this). The updates here all support that concern. – gavin]
Adelady #37, thank you. I think I know where I’ve been going wrong: it’ll still be colder at the poles (or at high altitude) whatever the average global temperature: the ice is a symptom of that, not a cause.
J Bowers #41, Thank you too: very much of interest. My sense of wonder is being spoiled rotten :)
“So to conclude, global warming continues. Did you really think it wouldn’t?”
No, I figured it would. I study history, which tells me we have another 400 years or so of Global Warming to go with the occasional two or three decades of slight cooling here and there.
What I find disturbing is that if Congress had instituted the draconian emission restrictions being recommended in ’88 then these observations through 2010 could be used now to pat ourselves (as in the USA/UN/whoever imposed draconian CO2 restrictions) on the back for avoiding “certain” warming.
The other thing that bothers me is that if one of the lines of evidence for the current warming having man’s fingerprint is that the models without man’s influence do not coincide with reality that is warmer. This being the inverse should imply man’s influence is negligible since the closest match to reality is with draconian emission restrictions that didn’t happen.
[Response: You have misinterpreted the logic completely. There are very clear fingerprints of change that are only associated with changes via increasing CO2 etc. – gavin]
>”[Response: Wanna bet? – gavin]”
>”But once again we have someone going on about cooling in the blog comments who backs off when pushed.”
‘Easily’ hasn’t been defined. I would be surprised if you were willing to bet on GISStemp GLOBAL Land-Ocean being in the top 8. I am already betting quite heavily that it won’t be warmest and mildly that it won’t be in the top 5 so I don’t want to bet a fortune on it not being in top 8 and do not want to bet on Giss not being in the top 10. It should be noted that there is a big difference between those. Seems like I am also at least partly agreeing with Isotopious. If it wasn’t for my existing positions, I might try to push Gavin on what he means by ‘easily’.
(Last intrade trade price for gisstemp being in top5 was 67% so if Gavin is looking for something like even odds on Giss being warmer than +0.52C he could easily lay it off for a guaranteed profit.)
49 Septic Matthew
Well my point is that a model that is tuned to match a climate signal only, should not track, accurately, a record that is both a climate and weather signal especially when we know that these medium term effects can be quite strong, even if they cycle out in the longer term.
Look at the 2001 to 2011 climate and weather signal and the GISS model which is showing an opposite, climate only, trend over the full decade.
Now we say that that doesn’t falsify the model because a noisy weather signal is masking the climate only signal. Now that was for a forecast period.
So let us look at the decadal trends for each of the decades since 1950 the decades when CO2 is supposed to have become a dominant forcing factor. These decades are also decades which the GISS model has back cast against.
http://www.woodfortrees.org/plot/hadcrut3gl/from:1951/to:1960/trend/plot/hadcrut3gl/from:1951/to:2011/plot/hadcrut3gl/from:1961/to:1970/trend/plot/hadcrut3gl/from:1971/to:1980/trend/plot/hadcrut3gl/from:1981/to:1990/trend/plot/hadcrut3gl/from:2001/to:2011/trend/plot/hadcrut3gl/from:1991/to:2000/trend
So what does the GISS model show for these decades/
Well when I look at it the GISS decadal, climate only, signal trend, matches the weather and climate decadal signal trend. Up, down, up, up, and up. In none of them do we see an opposite trend over the whole decade.
However in the first decade which GISS forecasts, rather than backcasts, this opposite trend in signals emerges.
Now, I am not saying this couldn’t be coincidental but it adds weight to my point that the model should not be so accurate on the backcast. Does this suggest excessive tuning in the backcast well its some evidence for it.
Alan
One wonders, with OHC are we not missing some at the poles? Two thirds of ice loss appear to be from underneath, according to recent research. That is supported by other recent findings that warm currents are infiltrating northward under ice shelves and into fjords around Greenland and into the Arctic basin more than previously thought.
Is some of that heat playing peek-a-boo, or being sent into the atmosphere due to the physics of ice melt and growth?
Regarding 2011 temps: the late ice growth, almost total lack of any ice over 2.5 meters thick and the new report on Greenland melt all indicate (to me, at least) the La Nina (I realize LN was later in the year and most GIS melt ends about Sept., but the transition from EN to LN was underway during the melt.) may not hold temps down as much as we might hope.
But, then, we just hit a high, so I suppose the yo-yo is gonna assert and take us back down a bit. But don’t bet much on it.
#53 What I find disturbing is that if Congress had instituted the draconian emission restrictions being recommended in ’88 then these observations through 2010 could be used now to pat ourselves (as in the USA/UN/whoever imposed draconian CO2 restrictions) on the back for avoiding “certain” warming.
Huh????? It is absolutely certain that warming has occured since 1988. So what is your point???????
Re: #55 (Alan Millar)
There are 5 best-known global temperature estimates, surface data from GISS, HadCRU, and NCDC, and lower-troposphere estimates from RSS and UAH. Four of the five show a positive (warming) trend in the last decade (but not statistically significant), but you chose to display the only one that shows a negative (not significant either) trend and declare it to be “the” trend. Why?
There are other factors affecting global temperature besides greenhouse gases, some of which have a profound impact on short-term variations. When estimates of their impact are removed (see this), the global warming trend becomes evident. In fact, when compensated for exogenous factors, all 5 data records show a positive trend over the last decade (including HadCRU), all show 2010 as hottest year, and 4 of 5 have 2009 as 2nd-hottest.
Note to moderators: the recaptcha thing has gotten much more difficult, and is now a genuine pain in the ass. I submit that your real mission is not to provide more data for a (admittedly fascinating) scientific study of pattern recognition, it’s to disseminate accurate information on one of the world’s most important scientific issues. Please stop impeding your primary mission; get rid of recaptcha and serve your readers, not investigators of spam-detection technology.
Two related points
First, Hansens A, B and C are not models, but emission scenarios that are fed into the same model. Thus A and C are much further from what actually happened than B, which is actuallypretty close to reality. This points to the 1988 team having an excellent understanding of what was likely to happen
Second, for an exercise such as this, comparisons of the actual emissions to those that were assumed in the model would help peg how good the models were.
#55 Well when I look at it the GISS decadal, climate only, signal trend, matches the weather and climate decadal signal trend. Up, down, up, up, and up. In none of them do we see an opposite trend over the whole decade.
The past decade is too short a period to actually define a trend, but there is no indication whatsoever that either the climate or weather signal (whatever you mean by that????) is in the midst of any of cooling trend.
Nothing that you and John W write (or think) makes any sense because it is grounded in the misconception that the weather or climate has cooled over the past decade. It has not.
Oh, and Iso-whateveryournameis….
ENSO is not seasonal.
61
Not this year it isn’t. Apart from Nino 1+2 regions near the coast, there has been no change what so whatever.
But I guess it will eventually weaken, probably this year, or in early 2012. The historically record is awfully short though….
That’s the problem with all this magical natural variability. The little bit#h might hang around for a decade for all I know, given that climate change will lead to more extremes and tipping points…
lol
RE #53 Response: “There are very clear fingerprints of change that are only associated with changes via increasing CO2 etc”
I agree with your science assertion, basic physics. However, the logic from the IPCC:
“Numerous experiments have been conducted using climate models to determine the likely causes of the 20th-century climate change. These experiments indicate that models cannot reproduce the rapid warming observed in recent decades when they only take into account variations in solar output and volcanic activity. However, as shown in Figure 1, models are able to simulate the observed 20th-century changes in temperature when they include all of the most important external factors, including human influences from sources such as greenhouse gases and natural external factors.”
So, the same logic applied to models of 1988 vintage suggests human influence is negligible. I’m sure models of the 21st century are “new and improved” and surely do a much better job. The question would be is anyone prepared to apply the logic that the IPCC uses to indict human activities to acquit if model predictions don’t hold up to the test of time? (i.e.: If the temperatures don’t fit you must acquit! LOL)
[Response: Nothing in that quote contradicts my point at all. Read the whole of the chapter on attribution, and pay special attention to the discussion of fingerprints. That the observations match patterns (for instance, stratospheric cooling/trop warming, increasing OHC, radiative signatures) that were predicted decades ago for the impacts of increasing GHGs AND that you can’t explain what is seen without including the extremely well-known effect of GHGs is, to most logical people, a strengthened argument for attribution. The simulations from 1988 – or even earlier – have proved skillful, though if you think that means they were perfect (or that they would need to be), you are somewhat confused. – gavin]
“I study history, which tells me we have another 400 years or so of Global Warming”
John W, you seem to think that this would happen in the absence of CO2 emissions. How, exactly, do you jump to this conclusion?
“History” is a vague, all-encompassing thing. Palaeoclimate, now, actually studies past temperature and climate. Objectively, not based on anecdote. And nothing in the science suggests that you are correct. What is it about “history” that offers a different explanation?
RE: #63
I think you dismiss anecdotal evidence too quickly. Remember, anecdotal evidence has started many scientific inquiries, such as plate tectonics and global warming and it is one of the main reasons why global warming is so indisputable. I don’t think I’m jumping to conclusions, although it may be fair to characterize it as unscientific. Looking at just recent history we have the Roman Warm Period around the 1st century, 500 years later the dark ages (massive crop failures and starvation), another 500 years the Medieval Warm Period and 500 years later the Little Ice Age. Of course it’s not exactly 500 years but just as an approximation it works out. So, given that man’s activities probably does have some influence (i.e.: magnitude and duration) of the current warming period I’m guessing we’ll probably continue to warm for another 400 years or so. So, yes, you’re right not really scientific, more like an intuitive conclusion; it may be only another 100-200 years if man’s influence is smaller than I personally believe or I could be just plain wrong.
> Alan Millar
> Woodfortrees
You’re doing exactly what he warns against, you realize, fooling yourself with the tool he provided (using periods too short to be useful to detect trends in these data sets).
Anyone new to this will do well to read the notes to see what Alan is trying.
“After many requests, I finally added trend-lines (linear least-squares regression) to the graph generator. I hope this is useful, but I would also like to point out that it can be fairly dangerous…
Depending on your preconceptions, by picking your start and end times carefully, you can now ‘prove’ that:
Temperature is falling!…”
http://www.woodfortrees.org/notes.php
How long a time series of temperature data do you need to determine a trend? You need to know how much variation there is, for any collection of data, to know how many data points you need to have to test.
For annual data, one data point per year, for global temperature, you need upwards of 20 years.
Looking at pictures? Good way to fool yourself — or others.
There’s a good high-school-level explanation with an exercise you can do for yourself at Robert Grumbine’s site. See
http://www.google.com/search?q=grumbine+results+trends
He says, among much else worth reading:
“How to decide climate trends
…. you need at least 15 years for your average to stabilize, 20-30 being a reasonable range…. But most tempests in blog teapots are about trends….”
Alan Millar seems to have come up with a new meme for his yearly visit to object to the model-data updates – he claims there is something called climate, and another thing called weather [I’m with him so far], then a 3rd thing, which he claims is somehow a combination of the first 2, called the temperature record. I hate to see him confuse himself further, but maybe he could clarify so as not to confuse us? Or maybe he could wait for next years update and use the time to rethink his groundbreaking theory.
[tamino – CAPTCHA ia a bit of a pain at times, but I bet it saves the mods time weeding out some of the more ignorant contrarians – I just clicked the recycle 50 times, only 5 of them were the iffy new style]
#
Can’t somebody just re-run Hansen’s old model with the observed forcings to the current date? Why are we forever wed to his old Scenarios A, B and C? I want to separate the physical skill of the model from his skill in creating instructive emissions scenarios.
Comment by carrot eater — 22 Jan 2011 @ 7:57 AM
#######
seconded. If I had a couple wishes granted for free CPU time it would be carrot’s suggestion and my suggestion.
Show how well H88 would do with the observed forcings
and show how well ModelE does.
Including atmosphere and oceans, how much fluctuation in heat content is there in the Earth system for a model at equilibrium? Flux in equals flux out as an average, but I’m curious to what extent and on what time scales imbalances occur. I guess I’m ultimately trying to get a sense for how much annual or decadal variations in surface temperatures are a function of atmosphere-ocean heat exchange vs. earth-space imbalances (I realize the two don’t function entirely independently).
reCAPTCHA: A mechanism for translating illegible gibberish into legible gibberish by leveraging the internet hive mind.
Isotope, these things don’t have to be your guess, you can consult the record and model analysis. My “guess”, living on the west coast of Canada, where the phases of ENSO have noticeable influence, is that the current LaNina will decay to a neutral condition before mid-year, as most of the models suggest. :)
By the way, Alan, if you find someone who can do the work, it is possible to test significance over shorter time periods:
“….. by removing the influence of exogenous factors like el Nino, volcanic eruptions, and solar variation (or at least, approximations of their influence) we can reduce the noise level in temperature time series (and reduce the level of autocorrelation in the process). This enables us to estimate trend rates with greater precision. And when you do so, you find …”
See for yourself:
http://tamino.wordpress.com/2011/01/21/phil-jones-was-wrong/#more-3350
John W … Europe is not the world, the US is! Oh, wait, the US isn’t the world, either.
Seriously … what is the basis for your claim that regional events recorded in history accurately record *global* temperatures? Particularly in the face of paleoclimate reconstructions to the contrary?
The NODC OHC data starts in 1955. Your comparison starts in 1970. Do you have a link to the Model E OHC output data in annual or monthly form starting in 1955?
55, Alan Millar: So let us look at the decadal trends for each of the decades since 1950 the decades when CO2 is supposed to have become a dominant forcing factor.
So it’s back to 1950 instead of back to 1900?
> since the 1950s
Citation needed. You appear to be off by about 200 years.
Try here:
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/tssts-2-5.html
\… very high confidence that the effect of human activities since 1750 has been a net positive forcing …\
Ps, this might be worth rereading:
http://www.digitalspy.com/forums/showpost.php?s=56d70aadd1c95e30814139d9aab77758&p=47494153&postcount=2401
RE #63 response
I’m not disputing that if it quacks like a duck and waddles like a duck it’s a duck. What I’m saying is that the duck may be a small duck. The magnitude of warming is expressed in temperature (the size of the duck). 1988 predictions may have correctly identified it as a duck (manner of warming consistent with GHG forcing) but woefully missed the size of the duck.
#72
Yes, I realize the history of Western Civilization doesn’t necessarily match the world, however, I don’t believe “my take” is contradictory to paleoclimate reconstructions per se; I just don’t have to take all the uncertainties into consideration, a benefit of not being a climatologist.
http://www.cgd.ucar.edu/asr/asr03/ccr/ammannasr1.jpg
#47 – A question, when a model is initialized far in the past (1850 has been mentioned as a starting year), how can the initialization be accurate enough given the relative scarcity of data from those times?
Since the climate models are physical models they will converge on their version of physical reality regardless of the initial conditions. Starting conditions don’t affect the final outcome if the models are run for long enough.
I did not read through all the posts in this thread, but it seems to me that Hansen’s scenario C is the best match for measurements. What is scenario C?
John W:
You are right about one thing. You are plain wrong.
Anecdotal evidence didn’t start global warming theories, or plate tectonics. The only reason Wegener’s continental drift theory struggled is because he couldn’t correctly propose a mechanism. In global warming, the mechanism came first, and the observations a very late second.
A regional warm period and the LIA gives you less than two data points. To extrapolate that to a cycle requires more than intuition, it requires a really active imagination.
Anecdotes might be a nice starting point for ideas, but when we have scientific evidence that all fits together, then that trumps anecdote every time. And the evidence says that your cycle does not exist.
71 Hank et al
I don’t know why people on here appear to think I am trying to say that the Earth is cooling. I don’t think that.
My point is that I don’t think the models are accurate, as there is evidence they were tuned to make an apple look like an orange.
I do not think a period of a decade is significant, in judging what a true climate signal is.
So I would expect a model to have an opposite signal, some times, in those sort of similar time periods.
When the hindcast is five for five and the forecast is none for one, it may be coincidence but it raises a flag. When you combine that with how there is so much leeway on how we estimate certain forcings in the models surely you cannot just ignore this?
Is the decade 2001-2010 the hottest on record? Yes!
Is that evidence that the warming trend continued during the decade? No!
Sorry, no credible scientist would assert such a thing. I don’t know if any accredited scientists on here has said that but I would be utterly amazed if they had.
The only way, the last decade could not have been the ‘warmist ever’, is if a cooling trend had set in over the whole decade, that was equal or greater than the previous warming decades trends.
I don’t know any scientist who has alleged that. The last decade is no evidence for a continung warning trend, no evidence for a cooling trend, just evidence for a pause.
Now you might not want to agree with the latter but it is a fact. Not that that fact will subsequently turn out to be true, that will emerge later.
Also the record cannot be paused too long as we know the Earths climate is always on the move. So we shall see.
Alan
John W says:
You seem to be under the misapprehension that Scenario C somehow corresponds to negligible human influence. That could not be further from the truth. Yes, Scenario C imagines that we start to constrain our emissions but CO2 levels in the atmosphere continue to increase by 1.5 ppm per year until year 2000 and it is only after year 2000 that CO2 levels in the atmosphere cease to increase (remaining at 368ppm). Even after that, temperatures would continue to rise as we adjust to the CO2 already in the atmosphere. (See here for details of each scenario: http://pubs.giss.nasa.gov/docs/1988/1988_Hansen_etal.pdf )
[It is also interesting to note that the stabilized level of CH4 assumed in Scenario C is 1916 ppb whereas the actual level has stabilized just under 1800 ppb.]
Alan Millar:
I don’t think that.
What you are saying is that there’s evidence of scientific misconduct as the models are tuned to mislead.
That’s a very serious charge that won’t be taken seriously by knowledgeable people.
Alan Millar: you are no longer making any sense, so I can’t address the substance of recent your comments. However, you really should be aware that your claims equate to an accusation of serious fraud.
Do you actually understand what you are saying? You are claiming that climate scientists have routinely lied in scientific papers, kept all of this secret in some kind of giant conspiracy, and misled not just the public but all the scientific institutions in the world, as well as governments around the globe.
Is that what you intended to say?
I’m very confused about all those PDO discussion, is it really contributing to the sst slowdown or not? It would be useful if some expert write an article about it.
John W.
Let’s throw out everything we know, and pretend that you are right. Let’s pretend there is a 500 year cycle over the last 2 millennia. Year 1, high, 501, low, 1001, high, 1501, low, 2001, high.
Instantly we run into a problem. According to your theory, we should be at a high now, and about to cool. But you predict 400 years more warming! That’s a massive contradiction.
But we soldier on. Let’s pretend you never said that, and that you are claiming we peaked about now.
Firstly, if we are at a peak, then there should be no trend either way. We should be stable, at the high point. But that’s not what we are seeing, we are observing a highly significant, very rapid warming trend.
Uh oh! Wrong again. Let’s forget this pesky cycle thing and pretend you are arguing that because the temperature has cycled in the recent past, it might in the future.
Let’s look at the peak to valley temperature change – let’s say 1 whole degree between the mediaeval climate anomaly and the LIA (and that’s being charitable, it is actually considerably less). 1 degree over 500 years is…. 0.02 degrees per decade.
We are seeing almost ten times that rate of warming at the present. That makes any contribution from any imagined cycle absolutely negligible. So, wrong again!
Okay, enough wrongness. How about we return to the real world and evaluate our initial supposition?
I’m currently looking at various global temperature reconstructions over the last 2 millennia. I see no peak in the first century. I see no trough in the dark ages. I see marginally higher temperatures from 800-1200. I see the LIA clearly, although reconstructions differ as to the magnitude of the event.
I see a massive spike representing the present day.
History teaches us one thing clearly: current global temperatures are unprecedented in recorded history.
Alan Millar, #82, Have you been listening to my brother, Bloke from the Pub? He has all manner of theories if you’ll buy him a beer, and you can use them to fill your mind with oxymorons like “decadal trends”, and that will help you ignore the science some more. Or you can drop the hubris and try to learn something. Your call.
> I would expect a model to have an opposite signal,
> some times, in those sort of similar time periods.
Wrong. You can’t _get_ a signal out of annual global temperatures in a decade. Any decade.
You can imagine one by eyeballing lines. People do this all the time with even shorter time spans. It’s a hole many people fall into often.
You are not alone–you’ve fallen in with a bad crowd easily misled.
You misuse the line-drawing tool at woodfortrees in exactly the way he warns against. You claim you found “a fact” — you found what you expected and misinterpret it, repeatedly.
Clue: use 20-year periods; see what you can say about it.
Clue: http://scienceblogs.com/stoat/2007/05/the_significance_of_5_year_tre.php
85 Didactylos
“However, you really should be aware that your claims equate to an accusation of serious fraud.
Do you actually understand what you are saying? You are claiming that climate scientists have routinely lied in scientific papers, kept all of this secret in some kind of giant conspiracy, and misled not just the public but all the scientific institutions in the world, as well as governments around the globe.”
Don’t make the most ludicrous assertions which have no relation whatsoever to my words. It kind of throws doubt on your judgement and objectivity.
It’s not my fault that you don’t like the data I have presented. Take it up with the data.
Just to repeat, so that you may reflect.
I have said that if a model is set up to match a certain signal ( not just climate) yet matches a signal that contains an additional cyclical factor which can change that signal significantly over the short and medium term then you would not expect it to show great accuracy over the short to medium term.
That is such an obvious fact that there can’t be a serious arguement.
Concerning the GCMs, it is a fact that they contain forcing factors whose calculated values and effects over time are in no way agreed or settled. Black Carbon and Land Use are just a couple of examples.
Now the modeller has to decide the value himself, he is not going to find an agreed value.
I am sure you have heard of confirmation bias. When you look at data and variables there is a bias towards those values that help your hypothesis. That is a well observed phenomenum in science whether you like it or not. That is not fraud, that is human nature!
[Response: Do you think that scientists are not well aware of the possibility of confirmation bias or have no sense of “human nature” as you call it? Possibilities don’t prove, or even imply, actualities.–Jim]
I just give you data that shows, on the backcast, the models, surprisingly, hit all the decadal trends since 1950 in a signal it was supposedly not tuned to match.
On the forecast it misses the decadal trend. Not an issue in itself, it can be expected to miss occasionally for the reasons stated. The surprising thing is is that it didn’t miss any on backcast.
Might be coincidence. Is confirmation bias involved? Well you couldn’t entirely rule it out just looking at the data.
No fraud or conspiracy needed.
Alan
Alan Millar (#55),
Now we know what temperature record you’re looking at (Hadcrut, variance-unadjusted). For reference, where is the GISS model hindcast from 1950 onwards you’re comparing this with?
Re: #90 (Alan Miller)
I already asked why you base your claim about the “decadal trend” on the *only* data set (out of 5) that shows a negative trend, and when *none* of the trends is significant.
Now you say the forecast “misses the decadal trend.” Have you computed the uncertainty level in your estimate of the “decadal trend”? Do you even know how?
Since you don’t seem to know how meaningless “decadal trends” are, you use the only data set that gives you what you want and ignore the others, and you act as though there’s no uncertainty in your “trend” estimate, your level of certainty amounts to nothing more than hubris. I suggest you are an example of the “Dunning-Kruger” effect.
Alan Millar:
Why do you not understand the implications of what you say?
All climate models explain in the literature exactly how they were constructed and used. It seems you have never read any of these papers, but despite that, you claim (sorry – “insinuate”) the scientists have tweaked things to suit themselves.
That is an accusation of serious fraud.
Now, can you grasp that?
Or are you going to continue repeating yourself instead of engaging your brain?
It’s bad enough you keep saying all this nonsense, but it really isn’t acceptable that you don’t actually understand what you yourself are saying.
And the “data” you have presented? For laughing! You have just made vague and nonsensical claims of fraud, without understanding anything you have said. No data. You also seem to be ignoring the fact that the modelled 10 year trends suffer from the same thing any 10 year trend does – huge error bars. So no, your ramblings about “decadal trends” are not data. You aren’t even discussing decadal trends, which makes me wonder whether you even understand the term. You haven’t shown any understanding of anything else, so my money says you don’t. And just as a final insult, you cherry-picked not only the temperature product, but the interval and the starting points. We’re not morons, so we noticed. Bad luck. This means that you no longer have the benefit of an assumption of good faith.
Oh, I’ve no patience with your ignorance. Go away and annoy someone else.
Alan Millar says of aerosols and land use: “Now the modeller has to decide the value himself, he is not going to find an agreed value.”
No, Alan, the modeler will not decide on a “value” at all, but will instead model the processes using the best possible physics available. There will be a degree of subjectivity in selecting which physics is “best”, but once selected, that’s it for the model. The fact that some models perform better then others may argue that they have chosen better representations. However, the fact that pretty much all the models agree, regardless of which representations they have of the phenomena you posit, pretty well on the trend suggests that the processes you identify are only of secondary importnace.
Alan, if you put in physics that represents reality poorly, you cannot compensate for that by putting other poor representations. The model would produce garbage. Maybe you ought to investigate actually how these models work before pontificating with such certainty. Or not. Those of us who have looked do appreciate comic relief.
92 Didactylos
[edit. ok, that’s it. take it elsewhere]
Alan Millar — Here is a ultrasimple decadal model. Study it.
https://www.realclimate.org/index.php/archives/2010/10/unforced-variations-3-2/comment-page-5/#comment-189329
John W @ #77
Even a duck at half the size is a pretty frightening prospect as we in Western Australian Agriculture are dealing with much lower and less predictable rainfall.
The only way the models can be wrong (in direction) is if they have grossly underestimated natural variability, and a global cooling trend is established in the long term observations.
Many would think such a cooling outcome to be extremely unlikely (in the deep psyche impossible), but until the models have the ability to predict the short term variations occurring over the time interval of one year, we don’t know how well the models have estimated natural variability.
What will the Global Temperature be in 12 measly months? Somewhere in a cloud? lol
Not really sure why anyone even brings up Hansen’s 1988 “predictions”. I’d be embarrassed. Scenario A assumes continued growth in CO2, pretty much in line with what has actually happened. Scenario B assumed reductions in CO2 emissions, and C assumed a major decrease in emissions starting in 2000. So the prediction has drifted far away from actual temperatures. The prediction for 2010 would be approximately twice what the actual anomaly has been. Pretty darn far off, so please stop bringing it up. It is a good example of a model proven wrong.
[Response: Actually this comment is a good example of definitive statement that is completely wrong. How can you state something so confidently without doing the least bit of checking? (All the correct answers can be found in the linked post and data). – gavin]
Alan,
Enough people have already pointed out issues with your thinking about ‘decadal trends’ and the data interpretation, so I won’t pile on, but I think it’s still worth saying a few words about the actual implications of model-obs agreement.
You interpret very good model-observation agreement in hindcasts as evidence for model tuning, and that the exceptional agreement means they must be wrong (post #31). It’s important to understand why models can produce such good agreement in light of the large uncertainties in radiative forcing and climate sensitivity, and how all the models which produce similar 20th century trends can disagree by a factor of two or three in 21st century temperature projections. Indeed, models do simulate similar warming for different reasons as discussed in e.g., Knutti, 2008. There are reasons why the AR4 runs did not span the whole possible space of aerosol forcings & sensitivity (e.g., Kiehl, 2007, GRL) and thus do not sample the full range of uncertainty. Inclusion of calculated indirect effects from aerosols for instance or if unknown/un-included forcings are significant this may lead to more model-obs disagreements. It’s also certainly plausible that model development choices are made with knowledge in mind of the current climate state and the observed trends, even if done unconsciously.
However, the agreement provides a useful constraint on the models parameter-space, so this at least gives us a consistent explanation of the response to the applied perturbation. Note that the consistency between modeled and observed temperature trends is not an attribution, and is not taken to be by experts in the attribution field. But models are not tuned to the trends in surface temperature, and as Gavin noted before (at least for the GISS model), the aerosol amounts are derived from simulations using emissions data and direct effects determined by changes in concentrations.
In weather forecasting, models assimilate information to constrain the present state in order to allow for better predictive capacity. Similarly, it can be useful to benchmark climate models against the observed record to establish some sort of reasonable initial state for future predictions. The confidence in model performance comes primarily from the fact that they are based on the fundamental laws of physics (conservation of mass, momentum, etc) and have also now reached an exceptional level of maturity which allows them to simulate the mean state and variability in various climate variables rather well. For global temperature anomalies, we are doing pretty well. For other variables (precipitation, sea ice loss), statistics (e.g., the mean state, extremes) or depending on the spatial scale you are interested in model performance varies and the degree to which model tuning can be accomplished while still maintaining a reasonable climatology and consistency with observations is limited.
Finally, the same uncertainties which plague the observational record modeling may be less important in the future. For example, I think it’s fair to say that the relative importance of GHG’s and aerosols are on the same footing in the 20th century (although clearly positive forcings have won out, which itself is a constraint on aerosol effects) although GHG’s should be much more significant compared to aerosols in the coming century.