Guest post by Frank Lansner
IPCC – How not to compare temperatures – if you seek the truth.
There are numerous issues discussed intensely when it comes to IPCC-illustrations of historic temperatures, here for example the illustration from IPCC Third Assessment Report:
Fig 1. Taken from IPCC TAR
In short we have heard of problems with 1) the Mann material, 2) the Briffa material, 3) The cherry picking done by IPCC to predominantly choose data supporting colder Medieval Warm Period, 4) Problems joining proxy data with temperature data mostly obtained from cities or airports etc, 5) Cutting proxy data of when it doesn’t fit temperatures from cities, 6) Creating and Using programs that induces global warming to the data and finally 7) reusing for example Mann and Briffa data endlessly (Moberg, Rutherford, Kaufmann, AR4 etcetcetc).
But, as I believe another banal error needs more attention:
8) Wrong compare.
Imagine for a moment that none of the above mentioned problems 1) – 7) has any impact and then lets just focus on the comparing itself. The data of the proxies suffer from 2 impacts:
A) “Technical averaging” – Impact of many series of date summarized.
Check out what happens when summarizing many datasets of temperatures, an example, the cooling episode 8200 years ago:
Fig 2.
Data taken from: http://wattsupwiththat.com/2009/04/11/making-holocene-spaghetti-sauce-by-proxy/
The white graph with the red squares are the resulting average graph: More temperature sets added together tends to flatten the average. Notice for example how many datasets certainly has a down peak between 8000 and 9000 years ago, but the timing for these datasets are slightly off, and so the down peak is almost gone.
So, to some degree we can expect multi proxies to yield an averaged overall graph.
B) “Direct averaging” – on top of the technical averaging, the data series are often averaged further to some degree using 30, 40 and 50 years Gaussian filters.
The result of averaging by A) and B) is, that the variability of the IPCC graphs on a decadal ´timescale are limited to just tenths of a degree K. But in reality, if there where any real temperature peaks on decadal time scale in the Medieval period, we will would not see these much in the typical data series IPCC shows.
Is this a problem?
Well, it certainly becomes a problem if these “super averaged” data are compared with data that is NOT quite as “super averaged”. And this faulty compare is just what IPCC do.
IPCC “Super averaged” data from proxies, are typically compared to “Observed” temperatures, that is, recent temperatures not at all submitted to the same degree of averaging.
Technical averaging – type A) – is to some degree not happening for observed temperatures, so how about type B), the direct averaging, filtering?
Well, For the IPCC graphis shown in fig 1 above, the IPCC text says: “All series were smoothed with a 40-year Hamming-weights lowpass filter, with boundary constraints imposed by padding the series with its mean values during the first and last 25 years.”
Explanation: If your data ends in year 2000, then the last genuine 40-year averaged/filtered point on the graph would be a point for 1980 with average of 1960-2000 near +0,2K anomaly. But the IPCC graph for observed temperatures ends at +0,43 K around year 2000. This more resembles the normal five years average of GISS year 2000 data:
Fig 3. Giss temperatures illustrated in year 2001.
So for IPCC/Mann etc. to get a year 2000 temperature as high as +0,43K, they must have used just normal 5 yr avg. A longer average period would yield lower temperature for the last year.
So, when IPCC wrote “with boundary constraints imposed by padding the series with its mean values during the first and last 25 years.” – they mean: “We don’t use 40 year average/filter in the last 25 years…!”
So the bottom line is: IPCC compares “super averaged” temperatures of the medieval period with a peak in modern temperatures only submitted to 5 years average.
IPCC basically compares a peak in temperatures in recent years with super averaged medieval data where peaks are more suppressed to conclude how much it is warmer today than in the MWP.
This is a problem !
From this illustration it appears that the peak after 1998 to some degree appears related to the big El Nino 1998 peak, here from appinsys:
Fig 4.
So, where there no El Nino peaks in the medieval period that could have affected the compare with recent temperatures? Yes, there where: http://co2science.org/articles/V12/N5/C2.php
So we have every reason to believe that there where also temperature peaks in the medieval period – peaks that just might resemble the recent El Nino Peak.
So no excuse for the IPCC to compare a modern temperature peak with medieval average temperatures.
This is banal, of course, and even IPCC must have been aware of this, one should think.
Here: An illustration where the single year 2004 for observed temperature data explicitly is used in comparison with the super averaged medieval temperature data.
Fig 5. (from here)
Cheers!
“DirkH (04:14:41) :
The important part is this:
‘So, when IPCC wrote “with boundary constraints imposed by padding the series with its mean values during the first and last 25 years.” – they mean: “We don’t use 40 year average/filter in the last 25 years…!” ‘
This is a deception ON PAR WITH THE ORIGINAL HOCKEY STICK !
I have never seen a Hamming filter used like this. You pad your data with averages, extrapolated values, whatever, the best thing is, stop the filter run BEFORE the shoulder of the Hamming filter runs out of data.
These guys are either clueless or criminals.”
**
Dirk H, thankyou and Yes…. This is the core problem you point out so well. These errors are obviously so faulty that they must have been carried out by morons or peoble that for some reason wants to twist the outcome. This is a good useful example of the IPCC ways, and yet again we can conclude that things “happens” to be twisted one way and one way only: To fit the global warming message.
Sleepalot.
For a smoothed plot to leave error bands, needs either a lot of creativity, or a degree logarithmic of incompetence, because the error bands are a part of the smooth plot. The data strip itself can and will leave the error bands, but the smoothing is to deterine trend.
Smoothing is for trend. Smoothing is trend analysis, nothing more nothing less.
So the IPCC is saying that the temp has risen only 0.6C in 1000 years (graph above) to 2004?
“SandyInDerby (02:24:18) :
……… Admonishing a non-native speaker is no way to teach them the nuances of a language.
[Reply: Agree, Sandy. Native English speakers should try to learn the difference between “effect” (verb) and “affect” (noun). Example: “The effect of precipitation affects the climate.” This is the mistake I fix most often. (Many times I don’t bother because it’s hard to keep up.) ~dbs, mod.]”
Sorry to be a pedant but isn’t ‘effect’ the noun and ‘affect’ the verb ;-)? The example is correct though.
And while we are on the subject can people stop using ‘loose’ [opposite of tight] when they mean ‘lose’. Snarl.
cheers David
[Reply: Right. It was 2:20 a.m. here, and I added the parts of speech as an afterthought – in the wrong place. That’s my excuse, and I’m sticking with it. Also right about loose/lose. I correct that all the time. And don’t even get me started on apostrophe use… ~dbs]
“churn (21:49:51) :
Everyone needs to read the books “How to Lie with Statistics” by Darrell Huff and “Freakonomics” by Dubner and Levitt.”
Couldn’t agree more. Add to that ‘Understanding Organisations’ Charles Handy All three – life changing experiences.
cheers David
ps – must get a life 🙂
Christopher Hanley (03:12:18) :
How come neither of the world wars show on that graph?
This problem highlights yet again that no matter how capable these scientists are in their field of science, they struggle to use statistics correctly.
I find it illuminating to see how aggressively they dismiss the offers from statisticians, such a Steve McIntyre, to perform analysis of their raw data. They make much of the fact that these people (who offer help) are not climate scientist, whereas the analysis methodologies are statistical and not scientific, and as Frank has shown in this admirable piece, they appear to be regularly misused (or should that be abused? .
These are professional scientists who are in the main amateur statisticians and even more amateur programmers (if the testimony of many IT professionals, who have commented on WUWT about the quality of revealed program code, is to be believed).
I liken statistics to a carpenters tool kit. A DIYer and a timeserved craftsman both use the same tools, but it’s easy to see who would produce the highest quality, most consistent results.
Sometimes I wonder if they’re not little kids after all. They took to liking splicing and dicing, so they do it 10000 times before bedtime.
Frank, Wonderful analysis. I live in the southern part of the USA. For years we in our area have been criticized about how we speak and how we use verbiage. Of course that is because thought we speak a form of bastardized English so do the folks in the other localized areas of the USA, Great Brittan, Australia, NZ, South Africa, and most of the rest of the “English” speaking world. It may be that I am used to reading many things written by folks from other areas than just where I live that I am able to get the gist of your post. For instance my wife would get angry and tell me to not “tip” her. In a few minutes I would take her hand and help her up the stairs and again she would tell me don’t “tip” me. She is from an other area of the USA and there the word “tip” meant touch. That little difference in colloquialism in speach while we were dating got me in trouble many times. I tend to be sympathetic when some one is trying to get a point across when using a language other than their native tongue.
All that considered I can’t spell and my grammar isn’t worth a “toot”. For me spell checker is a wonderful thing.
Yours is a job well done.
Bill Derryberry
Hello Frank,
This is a great post. I work with DSP filters often, and know what the effects of run on and run off are from a real world applications. When I use these filters, the data supplied is not used until the filtering becomes valid after run on, and ends before run off. To use that data would cause erroneous results, and possible dangerous conditions if what you are controlling is a critical application.
This basic error by the IPCC is indeed banal, and shows either ignorance, or malfeasance. Either does not bode well for the IPCC, since they are the “Official” climate resource. Unfortunately, this type of error in unsurprising from the IPCC. It is indeed unfortunate that they are either incapable of understanding these errors, or complicit in allowing them.
As far as the the format of the post, given my Dyslexia I am lucky to even type straight, no less criticize someone’s posting. I was impressed with the insight and information, and your work is greatly appreciated.
Here is another furfy LOL
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.arctic.png
Guess why?
Thanks! Very helpful, cause as a civil engineer I don’t use much statistics and so was not aware of these tricks. Do these people stop at nothing?
Clueless or criminals? They are so solid in their belief that man’s activities are harmful to the earth that their minds latched onto an interpretation of the data that supported this worldview. They interpreted the data in a way that made sense to them. It did not even occur to them that this method is the polar opposite of legitimate science.
Thank you Frank for another thought provoking post. My view is that all the changes in long-term weather can easily be explained buy the deterministic chaos we observed in Earth’s turbulent systems.
The mistakes made by the IPCC, which you clearly illustrate, are either caused by lack of knowledge, or more likely, yet another deliberate attempt to mislead the public.
“Oh what a tangled web we weave, when first we practice to deceive”
Frank, your article is full of mistakes, and, your point isn’t clear either. If you’re going to criticize the IPCC for making a mistake, you should put your finger on the mistake and not simply take issue with an averaging technique. Your article hasn’t added to my knowledge of any issues.
I have a feeling you are writing outside of your normal pattern of speech. For that, you need an editor.
We do not use average snowfall or rainfall for the planet. Why do we insist on averaging temperatures for the planet?
JUst my perspective. We were not sure of the existence of the western hemisphere before it was discovered. Why are the warmists so incredibly convinced of the temperatures during the same period before discovery?
jdn (06:53:25),
The article is “full of mistakes”?
What mistakes? List them in order.
Bill in Vigo (06:00:31) :
All that considered I can’t spell and my grammar isn’t worth a “toot”.
For me spell checker is a wonderful thing.
===================
Ode to my spell checker (author unknown):
Eye halve a spelling checker
It came with my pea sea.
It plainly marks four my revue miss steaks eye kin knot sea.
Eye strike a quay and type a word and weight for it to say
Weather eye yam wrong oar write.
It shows me strait a weigh as soon as a mist ache is maid.
It nose bee fore two long and eye can put the error rite.
Its rare lea ever wrong.
Eye have run this poem threw it,
I am shore your pleased to no.
Its letter perfect awl the way.
My checker told me sew.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
In this paper
Loehle, C. 2005. Estimating Climatic Timeseries from Multi-Site Data Afflicted with Dating Error. Mathematical Geology 37:127-140.
I showed that if multiple proxies have dating error and you average them, then past variability (like MWP) is damped out, as this post alludes to. This is particularly true when proxies only have dated samples every hundred years or so and interpolate dates in between, as many do. And yes, it is a REAL geology journal.
Tenuc (06:42:27) : …all the changes in long-term weather can easily be explained buy the deterministic chaos we observed in Earth’s turbulent systems.
This is my point of view too! What is the relationship between this , and this quote of Dr. Brooks in Climate Through the Ages (1950)pp. 286-287?
The weather of one year differs from that of another year, the weather of one decade from that of another decade ; why should not the climate of one century differ from that of another century ?
Answer
The Navier-Stokes equations for fluid flow, the heart of climate models, are scale invariant. This means that rapid variations on short time scale (years, decades) may resemble slow variations on longer timescales (centuries, millenia).
Chaotic systems may exhibit scale invariance accross a wide range of scales. In our climate, variations in cloud coverage and ocean circulation may lead to temperature fluctuations over many timescales.
I’ve never understood the viewpoint that the climate should not have large oscillations on long timescales when we observe small fluctuations on short timescales. To me, this seems unfair, and I suspect that this may violate the fundamental scale invariance power laws that is seen in many nonlinear dynamical systems.
Global Temperature Graphs are a lot like Real Estate aren’t they?
Location! Location! Location!
Imagine what a Global Real Estate Value Graph for the last 500 years would look like?
(Forget inflation, just for a moment:-)
Good solid piece Frank, thank you.
Re: jdn (Apr 5 06:53)
Give the guy a break JDN, Frank isn’t a native English speaker.
His points are all well made, as anyone with even an ounce of common sense would realise!
“Turboblocke (03:43:15) :
Re; John Peter (00:59:23)
Booker has presented a slanted article: the costs are shown in an assesment report which you can download here http://www.decc.gov.uk/en/content/cms/legislation/cc_act_08/cc_act_08.aspx and range from £14.7 to 18.3 billion/year but our infamous correspondent neglects to mention the benefits which range from £20.7 – 46.2 billion/year.”
Turboblocke
Please demonstrate the actual (real and measurable) benefits of £20.7-46.2 billion/year to us in the UK. As far as I can see they are at best unreal and will never materialise. They are based on a Brown/Milliband unshakeable belief in man made global warming and that we can have an influence thereon and also that some warming has more dire consequences for the Globe overall than no warming. I am afraid that the consequences will be a further erosion of UK competitivenes as more and more companies are driven out or forced to move intensive industrial activities out of the UK (and Europe). It is typical that few MPs and bureaucrats now have any contact with or appreciation of industry. We are moving towards pre 1990 East Eurpean conditions where more and more of the population watches the rest while productivity and value outputs go down the drain.
OT: Yesterday´s magnitude 7.2 Richter in BAJA CALIFORNIA, MEXICO
http://earthquake.usgs.gov/earthquakes/recenteqsww/Quakes/ci14607652.php
Seems as as zipper being opened (in this case “upwards”) like the Ethiopia “zipper”:
http://wattsupwiththat.com/2009/11/03/big-crack-in-ethiopia-beachfront-property-soon-to-be-available/