I was aware of this story yesterday, but I didn’t like the original plot, (see at the end of this post) since use of straight line linear trends doesn’t accurately reflect the reality of the observation data. While it is often hard to find any reality in climate models, linear trend lines mask the underlying variance. Today, Dr. Spencer has produced a graph that I feel is representative and very well worth sharing, because it does in fact convey an EPIC FAIL speaking directly to the accuracy of an ensemble of climate models. – Anthony
Dr. Roy Spencer writes:
In response to those who complained in my recent post that linear trends are not a good way to compare the models to observations (even though the modelers have claimed that it’s the long-term behavior of the models we should focus on, not individual years), here are running 5-year averages for the tropical tropospheric temperature, models versus observations (click for full size):
In this case, the models and observations have been plotted so that their respective 1979-2012 trend lines all intersect in 1979, which we believe is the most meaningful way to simultaneously plot the models’ results for comparison to the observations.
In my opinion, the day of reckoning has arrived. The modellers and the IPCC have willingly ignored the evidence for low climate sensitivity for many years, despite the fact that some of us have shown that simply confusing cause and effect when examining cloud and temperature variations can totally mislead you on cloud feedbacks (e.g. Spencer & Braswell, 2010). The discrepancy between models and observations is not a new issue…just one that is becoming more glaring over time.
Read his essay here: http://www.drroyspencer.com/2013/06/still-epic-fail-73-climate-models-vs-measurements-running-5-year-means/
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Here is the linear plot from Dr. Spencer’s post yesterday. He writes:
Courtesy of John Christy, a comparison between 73 CMIP5 models (archived at the KNMI Climate Explorer website) and observations for the tropical bulk tropospheric temperature (aka “MT”) since 1979 (click for large version):
Rather than a spaghetti plot of the models’ individual years, we just plotted the linear temperature trend from each model and the observations for the period 1979-2012.
Note that the observations (which coincidentally give virtually identical trends) come from two very different observational systems: 4 radiosonde datasets, and 2 satellite datasets (UAH and RSS).
If we restrict the comparison to the 19 models produced by only U.S. research centers, the models are more tightly clustered:
Now, in what universe do the above results not represent an epic failure for the models?
Mario Lento, irrespective of what the IPCC uses for the Summary for Policy Makers, the RCP is for predictions of future changes, not comparison to historical ones. It is not just wrong to use the RCP8.5 out of context, it completely invalidates the argument. We know RPC wasn’t 8.5 in the recent past, that’s why the database allows you to pick the historical RPC numbers for analysis of models compared to historical observations. What Dr. Spencer did is like setting the absolute population growth predicted for the next 20 years, apply it to 1950, and compare it to actual population growth from 1950. It’s completely flawed; this is a climate change skeptic epic fail.
Adam,
If there is a model that actually matches the observed values let’s see it. Like maybe a model that treats water vapor as a forcing and not a feedback? Like maybe a model that recognizes the natural negative feedbacks to water vapor forcing? Like maybe a model that doesn’t plunge us into a full on glacial stage in about 45 minutes and freeze the oceans solid in a few years when 400ppmv of a trace greenhouse gas is removed?
Joel,
C’mon. Really? Questioning the satellite data? It’s not just UAH. All the satellite groups agree.
There is nothing wrong with the concept of models. You just have to get them right.
Evan Thomas says:
The quote “…this is not the end, beginning etc’… was made after the battle of El Alamein which the Brits with their Commonwealth allies (no US, you guys weren’t that interested) won.”
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True. After WWI ended just two decades prior, Americans did not want to become involved in another European war, and after Pearl Harbor we had our hands full with the Japanese threat to the entire Pacific. [One Australian newspaper wag made a clever quip about both Yellow races: the Japanese and the Americans.]
But then Hitler made the one major blunder that cost him everything: four days after the attack on Pearl Harbor, Hitler unilaterally decalred war on America. Wars are usually won by the side that makes the fewest blunders, not the side with the most brilliant strategy.
The U.S. entry into the war had the same result as it did in WWI, decisively tipping the balance against Germany. Instead of a negotiated peace to end the war, it brought about unconditional surrender — which let out and confirmed the evil gremlins unleashed by the Russian revolution. And that is the world we have inhabited ever since.
Mario Lento says:
June 9, 2013 at 2:59 pm
David vun Kannon says:
June 9, 2013 at 7:43 am
RCP8.5 is the most extreme set of assumptions used in these models. There are others. All Dr Spencer has shown is that the model runs with the most extreme assumptions aren’t the closest to reality. That isn’t “EPIC FAIL”, that is just chartspam. I’d also recommend the breakout of each of the observational datasets, as joeldshore mentioned above.
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No David: It’s an Epic Fail. Do you know which charts are used for the IPPC’s “Summary for Policy Makers?” THE MOST EXTREME models. Stop being in denial of reality. I’m tired of the games your ilk play, hoping the naive will fall in line.
I suggest that you stick with the truth, contrary to your assertion the IPPC’s last “Summary for Policy Makers” included scenaria from B1 to A1F1(most extreme) as well as constant 2000 concentrations. It doesn’t improve your case when you can so clearly be shown to be exaggerating!
E.g. http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-spm.pdf
Table SPM.3. Projected global average surface warming and sea level rise at the end of the 21st century.
Figure SPM.5.
Figure SPM.6. Projected surface temperature changes for the early and late 21st century relative to the period 1980–1999.
Phil: You missed the point: “For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios.”
This is extreme, and what I refer to. They think anything less is unlikely… if not impossible.
They show models, as I said, but they don’t believe them… only the extreme ones.
The link posted by Paul Vaughan above to an alternative source for Dickey, J.O.; & Keppenne, C.L. (1997): “Interannual length-of-day variations and the ENSO phenomenon: insights via singular spectral analysis” is now also inoperative; I got an error message of a creepy type I’ve never seen before
Mario Lento says:
June 10, 2013 at 7:36 pm
Phil: You missed the point: “For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios.”
This is extreme, and what I refer to. They think anything less is unlikely… if not impossible.
They show models, as I said, but they don’t believe them… only the extreme ones.
That’s not what you said, you said: ” Do you know which charts are used for the IPPC’s “Summary for Policy Makers?” THE MOST EXTREME models.” As I was able to easily show what you said is untrue!
Phil: You’re being a bit argumentative for no reason. THE MOST EXTREME models are the ones they say are most likely to happen. So yes – they “USE” the most extreme ones to make their case. The other 1 model which is not alarming is the model that predicts what happens if we dial back to 2000 levels, which would be a drastic impossible scenario. ALL THE REST ARE MOST EXTREME.
There, I fixed it for you.
Mario Lento says:
June 10, 2013 at 10:25 pm
Phil: You’re being a bit argumentative for no reason. THE MOST EXTREME models are the ones they say are most likely to happen.
I’m not being argumentative for no reason, I objected to your telling untruths, capitalizing them doesn’t help!
Frank K. says:
June 6, 2013 at 2:13 pm
….And then I look at some of the source code of these models and am aghast at how bad it is (e.g. NASA/GISS).
Its written in Fortran… Ekkk.. Why do they insist upon using Fortran for scientific coding? What is wrong with C++ for mathematical computation? IS there really that big an advantage?
And when it comes down to serious number crunching, assembly is going to be needed anyway to best utilize functions, unless the compilers in Fortran are magical.
Phil. says:
June 11, 2013 at 4:41 am
Mario Lento says:
June 10, 2013 at 10:25 pm
Phil: “You’re being a bit argumentative for no reason. THE MOST EXTREME models are the ones they say are most likely to happen.”
I’m not being argumentative for no reason, I objected to your telling untruths, capitalizing them doesn’t help!
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Like they say, you can lead a horse to water… I stand by what I wrote and tried to bring attention to the truth. You choose to drink Koolaid instead of water. Stay confused for the rest of your life. I’m done tutoring.
“In what universe …”?
In the free-money AGW universe, of course.