I recently covered a press release from Dr. Ben Santer where it was claimed that:
In order to separate human-caused global warming from the “noise” of purely natural climate fluctuations, temperature records must be at least 17 years long, according to climate scientists.
Bob Tisdale decided to run the numbers on Ar4 models:
17-Year And 30-Year Trends In Sea Surface Temperature Anomalies: The Differences Between Observed And IPCC AR4 Climate Models
By Bob Tisdale
We’ve illustrated and discussed in a number of recent posts how poorly the hindcasts and projections of the coupled climate models used in the Intergovernmental Panel on Climate Change’s 4th Assessment Report (IPCC AR4) compared to instrument-based observations. And this post is yet another way to illustrate that fact. We’ll plot the 17-year and 30-year trends in global and hemispheric Sea Surface Temperature anomalies from January 1900 to August 2011 (the updates of HADISST data used in this post by the Hadley Centre can lag by a few months) and compare them to the model mean of the Hindcasts and Projections of the coupled climate models used in the IPCC AR4. As one would expect, the model mean show little to no multidecadal variability, which is commonly known. Refer to the June 4, 2007 post at Nature’s Climate Feedback: Predictions of climate, written by Kevin Trenberth. But there is evidence that the recent flattening of Global Sea Surface Temperature anomalies and the resulting divergence of them from model projections is a result of multidecadal variations in Sea Surface Temperatures.
WHY 17-YEAR AND 30-YEAR TRENDS?
A recent paper by Santer et al (2011) Separating Signal and Noise in Atmospheric Temperature Change: The Importance of Timescale, state at the conclusion of their abstract that, “Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.” Sea surface temperature data is not as noisy as Lower Troposphere temperature anomalies, so we’ll assume that 17 years would be appropriate timescale to present sea surface temperature trends on global and hemispheric bases as well. And 30 years: Wikipedia defines Climate “as the weather averaged over a long period. The standard averaging period is 30 years, but other periods may be used depending on the purpose.”
But we’re using monthly data so the trends are actually for 204- and 360-month periods.
ABOUT THE GRAPHS IN THIS POST
This post does NOT present graphs of sea surface temperature anomalies, with the exception of Figures 2 and 3, which are provided as references. The graphs in this post present 17-year and 30-year linear trends of Sea Surface Temperature anomalies in Deg C per Decade on a monthly basis, and they cover the period of January 1900 to August 2011 for the observation-based Sea Surface data and the period of January 1900 to December 2099 for the model mean hindcasts and projections. Figure 1 is a sample graph of the 360-month (30-year) trends for the observations, and it includes descriptions of a few of the data points. Basically, the first data point represents the linear trend of the Sea Surface Temperature anomalies for the period of January 1900 to December 1929, and the second data point shows the linear trend of the data for the period of February 1900 to January 1930, and so on, until the last data point that covers the most recent 360-month (30-year) period of September 1981 to August 2011.
Figure 1
Note also how the trends vary on a multidecadal basis. The model-mean data do not produce these variations, as you shall see. And you’ll also see why they should, because they are important. Observed trends are dropping, but the model mean trends are not.
I’ve provided the following two comparisons of the “raw” Sea Surface Temperature anomalies and the 360-month (Figure 2) and 204-month (Figure 3) trends as references.
Figure 2
HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 3
COMPARISONS OF SEA SURFACE TEMPERATURE ANOMALY TRENDS OF CLIMATE MODEL OUTPUTS AND INSTRUMENT-BASED OBSERVATIONS
In each of the following graphs, I’ve included the following notes. The first one reads,
The Models Do Not Produce Multidecadal Variations In Sea Surface Temperature Anomalies Comparable To Those Observed, Because They Are Not Initialized To Do So. This, As It Should Be, Is Also Evident In Trends.
And since those notes in red are the same for Figure 4 through 9, you’ll probably elect to overlook them. The other note on each of the graphs describes the difference between the observed trends for the most recent period and the trends hindcast and projected by the models. And they are significant, so don’t overlook those notes.
There’s no reason for me to repeat what’s discussed in the notes on the graphs, so I’ll present the comparisons of the 360-month and 204-month trends first for Global Sea Surface Temperature anomalies, then for the Northern Hemisphere data, and finally for the Southern Hemisphere Sea Surface Temperature anomaly data. Some of you may find the results surprising.
GLOBAL SEA SURFACE TEMPERATURE COMPARISONS
Figure 4
HHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 5
NORTHERN HEMISPHERE SEA SURFACE TEMPERATURE COMPARISONS
Figure 6
HHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 7
SOUTHERN HEMISPHERE SEA SURFACE TEMPERATURE COMPARISONS
Figure 8
HHHHHHHHHHHHHHHHHHHHHHHHHHH
Figure 9
CLOSING
Table 1 shows the observed Global and Hemispheric Sea Surface Temperature anomaly trends, 204-Month (17-Year) and 360-Month (30-Year), for period ending August 2011. Also illustrated are the trends for the Sea Surface Temperature anomalies as hindcast and projected by the model mean of the coupled climate models employed in the IPCC AR4.
Table 1
Comparing the 204-month and 360-month hindcast and projected Sea Surface Temperature anomaly trends of the coupled climate models used in the IPCC AR4 to the trends of the observed Sea Surface Temperature anomalies is yet another way to show the models have no shown no skill at replicating and projecting past and present variations in Sea Surface Temperature on multidecadal bases. Why should we believe they have any value as a means of projecting future climate?
SOURCE
Both the HADISST Sea Surface Temperature data and the IPCC AR4 Hindcast/Projection (TOS) data used in this post are available through the KNMI Climate Explorer. The HADISST data is found at the Monthly observations webpage, and the model data is found at the Monthly CMIP3+ scenario runswebpage.
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Some typos in Fig. 1?
At least the 1938-68 slope is much larger (in absolute value) than 0.01 degC/decade.
Bob, Bob, you’ve got to stop all this promiscuous data-flinging
and just accept that the consensus is in and the debate is over.
The 20th century warming was ‘Global’, you see,
because we know CO2 caused it all.
Never mind that a third of the world got colder,
we’ll just stop putting thermometers there.
Look, Bob, we know that eeville Satanic Gasses are marching us to Doomsday,
and that only Government can Save Us, with more taxes and control.
Can’t you just get along?
See you at our Durban-fest! (It’s how we reward the believers.)
tokyoboy says: “Some typos in Fig. 1?”
Nope. I just rounded it off. The global HADISST SST anomaly trend calculated by Excel for the 360-month period of June 1938 to May 1968 was -0.0099 deg C/Decade.
If 17 years is necessary to see a trend, HOW did the Global Warming Scare start in the late 1970’s?
Thank you Mr. Tisdale for provideing more confirmation that AR4, Sec8, all subsections that indicated that climate models had large areas of uncertainty has been confirmed.
Now the question arises, there are at least two large discrepencies that pass the 17 year Santor time window. The strat has not been cooling for 17 years and the SST is not complying in a statistically verifiable way.
Ok…..the large question: Why are we spending large sums of money on climate models that continue to produce poor levels of certainty?
This would have been an interesting presentation at Rep Markely’s hearing last week. Then he could have said that four people attended.
OMG, its worse than we thought!
Differentiating the temperature time series and smoothing the differential should obtain a curve with a similar shape to your trends; and that’s basically an operation with a bandpass characteristic. So the information obtained is already part of the spectrum of the original signal as the filter operations are linear.
Hmmm… can we test it with woodfortrees? Yes, seems to work:
http://www.woodfortrees.org/plot/hadcrut3gl/derivative/mean:360
So from a signal theoretical approach it looks like the models get the higher frequencies in the signal completely wrong. Should be interesting to look at with a wavelet analysis.
“Why should we believe they have any value as a means of projecting future climate?”
Good question Bob and the answer is both simple and correct, we shouldn’t.
pete50 says:
November 19, 2011 at 5:08 pm
OMG, its worse than we thought!
Quoting a certain Penn State professor ?
Australia has had a “carbon” tax foisted upon us as a direct result of these models and our own scientists, those in government employ, have been too lazy or too beholden to do what Bob Tisdale has done; challenge the findings with real data. I accept it won’t happen but those who led us here should be jailed for fraud, accepting payment under false pretenses.
toykoboy, at first was thinking the same, but look at the ‘y’ axis label, it is trend rate, not temperature.
wayne says: November 19, 2011 at 5:49 pm…..
Yassuh. Got it. Thanks……. And sorry, Bob.
Completly off topic but just as newsworthy, the B.B.C.(British Bullsh*t Corporation) caught with their pants down http://www.dailymail.co.uk/news/article-2063737/BBCs-Mr-Climate-Change-accepted-15-000-grants-university-rocked-global-warning-scandal.html
The significance of Santer, et al is that they are saying that 17 years without statistically significant warming proves the models wrong.
I’d say your table 1 is proof of no significant warming in SSTs over the last 17 years.
BTW, Santer is referring to surface temps and not as widely claimed by Warmers, troposphere temps.
Good work, Bob. The stuff that really matters is always simple.
Thanks for this Bob it is well done. One would think it would put an end to Santer’s bafflegab. Probably not. In 1975 J. Tuzo Wilson (Geophysicist) was asking why rational men, who have a history of rational thought, are so irrational? I don’t think he had a good answer, none of us do either. I see Roger Pielke Sr. is suggesting you submit this for peer review. Great idea but not sure it would help. This model foolishness is not about science it is about ideology and Wilson’s irrationality.
Figure 1 is showing clearly the superposition of a natural trend of about 60-70 years length and perhaps a linear trend..
The best linear trend estimate can then be deducted at equivalent cycle states, such as the difference between the 2000s and the 1940s, which is approximately 0.2-0.3 degrees according to HadSST3 or approximately 0.3-0.4 degrees per century.
A 30 years timescale such as between 1979 and 2009, starts around a natural cycle minium and end in a maximum cycle maximum, grossly inflating the linear trend. Same error for the period from 1900 until today.
AndyG55 says:
November 19, 2011 at 5:05 pm
If 17 years is necessary to see a trend, HOW did the Global Warming Scare start in the late 1970′s?
__________________________________
Because at the First Earth Summit in 1972 Maurice Strong started the ball rolling.
Fine article, Bob. I always enjoy your well thought out posts. And I really like your charts!
Throw out the models, they are not worth the kWH they consumed on electricity!
Models, models, models. Nothing more needs to be sad. (OOpss… typo….lol).
Nice work Bob.
We used to have 10. Now we have 17 and 30.
It feels like the goal posts are moving.
Iskandar… COME ON, don’t throw out all of the models! Had some great, very soft, models as friends in the past and they do tend to consume many kWh of electricity for sure… they’re just not of the type you are speaking. 😉
FORGET IPCC’s SCARING PROJECTIONS: Mushrooming of Desalination Systems in the M.E. started after 1980.
First, sorry for my English, but I must comment on the matter.
Really, really right, to establish a minimum to know how the weather changes, we would need eternity!