The Australian‘s War on Science 31

Ian Musgrave has written the post I was going to write on Jon Jenkins’ article in the Australian, so I just want to emphasize that fitting a degree six (yes, degree six) to temperature data does not produce a meaningful trend line in any way shape or form. Go read.

Note that if the editors at the Australian had bothered to read their own paper just three days earlier they would have known that the Jenkins’ claims about the Oregon petition and global cooling were rubbish.

News Limited blogger Grame Redfearn also pointed out the enormous holes in Jenkins’ arguments and talked to Australia’s acting chief climatologist Michael Coughlan:

Of climate change contrarians such as Jon Jenkins, Coughlan has this to say.

“We have produced rebuttals of all of these arguments – they have all been addressed. But they just keep trotting them out. No matter how many times you tell them they’re wrong, they just keep going. The general approach seems to be – if we keep banging away at an untruth, people will start to believe it”.

Let’s not forget that these contrarian views are not being expressed on a bit of street press or some fringe web site somewhere – they’re being repeated over and over in Australia’s only national newspaper. So now comes the revelation – and that is Coughlan’s view of The Australian newspaper itself.

“The Australian clearly has an editorial policy. No matter how many times the scientific community refutes these arguments, they persist in putting them out – to the point where we believe there’s little to be gained in the use of our time in responding.”

Since I already uploaded them, I might as well include my versions of the graphs that Musgrave posted.

Here’s the graph that the Australian printed.

It’s been copied from Lorne’s Gunters’ article in the National Post (Canada’s version of the Australian), but with this caveat removed:

Moreover, while the chart below was not produced by Douglass and Christy, it was produced using their data

and the ridiculous sixth-degree fit attributed to the University of Alabama at Huntsville.

That graph ends in July was already out of date when Gunter’s article was published in late October. Here it is with the latest data (up to November) included.

i-141306e9ab0ac163a1acc608e54485ea-uahtlt5.2.png

Note that the latest observation lies right on the linear trend line, completely refuting Jenkins claim that satellite data showed that warming “had completely reversed by 2008″.

(Hat tip to Tobias Ziegler for pointing me to the Readfern post.)

Update: Ian Musgrave has more on what is wrong with high order polynomial fits.

Comments

#1 jade
January 7, 2009

So when do temperatures in the lower troposphere hit absolute zero?

You would assume that an “expert on computer modelling” could not possibly have missed the absurdity of using that polynomial fit as a trendline. But have you seen his website?
#2 Dano
January 7, 2009

“We have produced rebuttals of all of these arguments – they have all been addressed. But they just keep trotting them out. No matter how many times you tell them they’re wrong, they just keep going. The general approach seems to be – if we keep banging away at an untruth, people will start to believe it”.

Yes.

That’s the strategy, right there.

Best,

D
#3 kent
January 7, 2009

As I lay on the beach in Roatan it is hard to believe in global cooling. I am pink all over and loving it. The strange thing is that, while living at 49 degrees north, for many years I noticed that the sun was much stronger than now. In the 90s the sun felt like it was irradiating my skin. sort of felt like I was being deep fried. That is not the case now. Something that was there then, is not there now.
Everwhere I look they say the cold is setting records, but of course that is not a trend ackording to the warmists. The truth is a trend can last a pico-second or a million years. The current trend is not up but down.
This trend and the current climate is what the media is picking up on. It is hard to say it is warm when the pee freezes before it hits the ground. You guys are going to have to wait a few more decades before the data starts to support your beliefs. A broken clock is right at least once a day and in most cases twice a day but only very briefly.
Six more weeks of our Central American trip to go, I just hope the snow is gone by the time we fly home, but I doubt it, It will still be winter.
#4 Chris O'Neill
January 7, 2009

As I lay on the beach…

No disagreement with Tim’s article here. kent must think it’s correct.
#5 Boris
January 7, 2009

In the 90s the sun felt like it was irradiating my skin. sort of felt like I was being deep fried.

May we float you into space to measure solar irradiance?
#6 Bud
January 7, 2009

As a complete statistical layman, and at the risk of sounding like an idiot, I have a question about the polynomial fit.

Between around 1983 and just before 1985, the difference between the highest temp and the lowest temp is about 0.6 degrees C. Over the same time scale, between 2006 and 2008, the difference is 0.8 of a degree. So why is the huge steepness of the gradient of the latter compared to the former so noticeably out of proportion with the relative difference in temperature?

Cheers.
#7 Bud
January 7, 2009

Erm… that should probably have read “statistics layman”. I may be a statistical layman as well, but that’s another story…
#8 Gareth
January 7, 2009

The primary source for the temperature graph is Roy Spencer’s blog, but the good doctor restricts himself to a fourth order polynomial fit because it “smooths out the large amount of monthly variability in the data and helps reveal the underlying ‘trends’. How helpful…
#9 Jason Leggett
January 7, 2009

Ah, yes… Roy Spencer. For Roy, graphs are more of an art form than a way of presenting scientific results. It’s the medium through which he chooses to express his deep, dark hatred toward the climate science community:

http://www.realclimate.org/index.php/archives/2008/05/how-to-cook-a-graph-in-three-easy-lessons/
#10 Dano
January 7, 2009

I went over there to leave a comment at Roy’s blog, but alas I forgot that most Denialist Misinformation Purveying Distribution Channels as a rule don’t allow comments.

Best,

D
#11 Robert
January 7, 2009

Bud wondered:

So why is the huge steepness of the gradient of the latter compared to the former so noticeably out of proportion with the relative difference in temperature?

The simplest way to explain it is that for the middle period, there are years both to the left and right that also have to fit so the change over the middle parts get constrained. However, when you get to the end of the time series you don’t have any more points to the right so the ending fit whipsaws where ever it wants. That’s why adding just a few more months to the data changed the ending fit so much. This problem is exacerbated with higher order polynomial fits, which is why you don’t see serious analysts using sixth-degree polynomial fits for data like these.
#12 Lank
January 7, 2009

I agree with Jennifer Marohasy…. “This data does not suggest dramatic global warming. Neither the warming of the late 20th century, nor the cooling since 1998, is of an unusual rate or magnitude.”

How can any sensible person suggest that this graph, however it is assessed, shows runaway global warming as James Hansen and other alarmists insist is occuring?
#13 fragment
January 7, 2009

There seem to be a few versions of the polynomial rollercoaster doing the rounds. I think the one at Icecap is earlier than those already posted.
#14 WotWot
January 7, 2009

11

Thanks for that clear explanation, Robert.
#15 Michael
January 7, 2009

Lank, quoting Jen,
“…nor the cooling since 1998, is of an unusual rate or magnitude.”

Thankfully, Jen clarifies what she means by “unusual” in comments,
“As regards definitions of dramatic and unusual – I suggest we go with common usage and based on our general understanding of the geological record (say the last 6 million years).”

Well, when I talk about something being unusual or dramatic, I routinely consider the last 6 million years for comparison, don’t you?

So we should all just relax. The not-dramatic warming isn’t much to get worried about as long as we consider it within a time span that pre-dates the emergence of the genus from which modern humans sprang.

An avalanche of stupid and it’s………January 8.
#16 Bud
January 7, 2009

Thanks Robert. I know enough to know it really doesn’t look right, but it’s good to know why.
#17 David Irving (no relation)
January 7, 2009

Many, many years ago, while studying the computational aspects of photogrammetry, I was advised of two things: use an odd-degree polynomial for preference when doing a least-squares fit to noisy data; and don’t go over about 5th degree without a bloody good reason. Having subsequently done some numerical analysis, I have a better understanding of why these rules of thumb were suggested, and also why you should never extrapolate beyond your data points with a polynomial.

The graph looks like an Epic Fail, but I’ve never expected better from The Australian.
#18 sod
January 7, 2009

i am not sure, whether everyone does really understand what the sixth-degree fit will do to ANY data.

http://www.purplemath.com/modules/polyends.htm

the end behaviour of a positive degree polynomial will always be the same on both sides. think about it….
#19 Lank
January 7, 2009

Michael (#15) – For most of the past 10,000 years temperatures have been 1 to 3 degrees Celsius warmer than they are today. The 0.6 degree rise in temperatures during the 20th century occurred from the baseline of the little ice age, which saw the coldest global temperatures during the past 10,000 years. Earth has a “rising fever” only if we pretend the little ice age was “normal” and ignore the Earth’s subsequent known temperature trends.
#20 P. Lewis
January 7, 2009

Seems to me that a first-degree polynomial is more than adequate in this case.
#21 Lank
January 7, 2009

Considering the long history of huge temperature variation in the earth’s climate (ice ages etc.), the 0.6 of one degree centigrade average rise reported by the U.N. “experts” for the entire 20th century (a rise so small that you would be unlikely to detect such a difference without instruments) shows, if anything, that the 20th century was a time of exceptional temperature stability.
#22 Lank
January 7, 2009

Many earth scientists would argue that the current warming trend began 300 years ago, at the end of the Maunder Minimum, a 70 year period when there were very few sunspots on the face of the Sun. Between 1700 and 1735, according to the world’s oldest instrumental temperature dataset, the temperature in central England rose by 2.2 degrees C, equivalent to 6.3 C/century, or about ten times the warming of the 20th century.

All this without the help from those nasty man-made CO2 emissions.
#23 Steve Bloom
January 7, 2009

Re #19 (Lank): “For most of the past 10,000 years temperatures have been 1 to 3 degrees Celsius warmer than they are today.”

Lank, if you can’t provide a legitmate scientific source for that piece of drivel (hint: there isn’t one), and taking into account the low quality of the rest of your contributions to this thread, my suggestion to Tim is that it’s disemvowellin’ time.
#24 Chris O'Neill
January 7, 2009

Lank doesn’t argue against Tim’s article so obviously he doesn’t think there’s anything wrong with it. Instead he just makes assertions that he could easily discover are either wrong or strawmen. e.g.

Many earth scientists would argue that the current warming trend began 300 years ago

No earth scientists argue that the CURRENT warming trend began 300 years ago. (Any warming trend, if any, greatly accelerated ~100 years ago.) Not only that but only a minority of results say 300 years ago was cooler than 180 years ago. I can only conclude that Lank has an enormous capacity for self-delusion.
#25 WotWot
January 7, 2009

the 0.6 of one degree centigrade average rise reported by the U.N. “experts”

Your use of scare quotes there says a lot about the quality of your tactics.

Many earth scientists would argue that the current warming trend began 300 years ago,

Care to name a couple of dozen reputable ones?

Besides which, even if there was some natural warming, that does not mean any subsequent input from anthropogenic CO2 is not a serious problem.

And maybe 300 years ago was about the time we humans started having a significant impact on global vegetation cover. Anybody else here can comment on that aspect?
#26 WotWot
January 7, 2009

And maybe 300 years ago was about the time we humans started having a significant impact on global vegetation cover. Anybody else here can comment on that aspect?

Somewhat indirectly, Mr O’Neill has already shown this to be an irrelevant issue.
#27 Steve Bloom
January 7, 2009

Tim, to all appearances this fake curve originated not with Gunter, but with Watts last July (here). Even then, various commenters pointed out that it was completely bogus.

When the Gunter article came out a few months later, Watts posted it and the graph with nary a mention of the prior discussion. Leif Svalgaard immediately pointed out the problem with the curve fit, and at his behest one of the other commenters reconstructed the plot and then extended it 15 years, with an amusing result.

To the surprise of none, neither post ever got a correction. I notice that Watts seldom if ever makes one, doubtless because he knows the majority of his readers don’t look far enough down in the comments to see his admissions of error.

I’m no expert, but it looks to me as if any difference between the Watts 5th-order curve and the 6th-order one subsequently used in the NP and Oz can be attributed to the NP graphic artist’s loose approximation of the Watts curve. In any case the ultimate source seems clear. Gareth in #8 mentions Roy Spencer himself as a possible source, but that seems less likely considering that the Spencer curve is both more recently dated and is a poor match for the others.
#28 elspi
January 7, 2009

“The Australian’s War on Science XXIX”

“The Australian’s War on Science 31″

Tim, when you switch to ARABIC numerals the TERRORISTS HAVE ALREADY WON
#29 Gaz
January 7, 2009

So, Lank, (January 7, 2009 8:12 PM) the temperature rise in the past century was “so small that you would be unlikely to detect such a difference without instruments”.

Good point. Let’s not worry about anything you can only measure with those new-fangled instrument thingies. It can’t be that important.

I think that in the interests of science you have a responsibility to continue standing outside with your shirt off.

Be sure to give us a yell when you notice something, won’t you?
#30 Lank
January 7, 2009

Steve Bloom (#23). It is easy to dismiss my comments with rude remarks like “that piece of drivel” but if you care to study climate science 101 you would have discovered plenty of studies that show the cooling from approximately 11 to 10 thousand years ago (called the “Younger Dryas” event) which ended as suddenly at it began, with temperatures jumping 7° C. Since then, the Earth continued warming up until about 6,000 years ago – the (mid Holocene thermal maximum) when the earth was around 1-3° C warmer than today. Since then, it’s basically been cooling off – not counting various smaller variations. There are many studies which show this e.g. Richard B. Alley, The Two-Mile Time Machine: Ice Cores, Abrupt Climate Change, and our Future, Princeton U. Press, Princeton, 2002;
or Joe Buchdahl, Mid-Holocene Thermal Maximum, see his figure 5.18 at http://www.ace.mmu.ac.uk/Resources/gcc/5-3-2-2.html

There are some useful, more detailed accounts of these changes in the Arctic Climate Impact Assessment reports here…
http://amap.no/acia/
#31 z
January 7, 2009

“This problem is exacerbated with higher order polynomial fits, which is why you don’t see serious analysts using sixth-degree polynomial fits for data like these.”

you don’t use high order polynomial fits unless you have reason to believe the underlying mechanism runs on a high order polynomial basis. this is what the denialists think “computer modeling of climate” is all about, and why they feel justified to condemn it, when they’re not indulging in it. the concept of creating a complex mathematical model reflecting the actual physics of the underlying processes which requires a lot of computer time to calculate is apparently completely beyond them.
#32 Tim Lambert
January 7, 2009

Gunter’s graph is different from Watt’s. It has one more month in it and the degree 6 fit is noticeably different from the degree 5 one — the downturn at the end is steeper and the “trend” goes all the way down to zero. Gunter may well have been inspired by Watt, but his graph produced by the NP.
#33 Tim Lambert
January 7, 2009

I switched to the new-fangled Arabic numbering system because a reader emailed that the triple x was causing a net filter to block the post.

Our idiot communications minister [plans to make such filters compulsory](http://scienceblogs.com/evolvingthoughts/2008/12/the_lies_of_the_internet_censo.php).
#34 Richard Simons
January 7, 2009

To add to the comments of Robert and sod about polynomials; changing data points at one end of a polynomial will change the position of the line at the other end of the data set. As shown by a graph linked to by Steve Bloom, extending polynomials beyond the data used to determine them quickly gives ludicrous results. My own view is that they should only be used as a last resort.
#35 Jimmy Nightingale
January 8, 2009

Lank (#30). If you are going to quote from sources, you should at least make sure that you are quoting correctly.

“Quantitative estimates of mid-Holocene warmth (COHMAP, 1988) suggest that the Earth was perhaps 1 or 2°C warmer than today. Most of this warmth may primarily represent seasonal (summer) warmth rather than year-round warmth.”

This is a bit different from what you have claimed. The explanation for this can be found here:

http://www.ncdc.noaa.gov/paleo/globalwarming/holocene.html
#36 Steve Bloom
January 8, 2009

Agreed, Tim. I was aware they’re not identical and that the NP produced their own graphic, as I noted in the final paragraph of my comment.
#37 Steve Bloom
January 8, 2009

Re #30: Jimmy beat me to it. FYI, Lank, +3C globally would put us back into the Pliocene temp range and result in some serious ice sheet melting. That 7C figure for the YD is also completely wrong. Among other things, bear in mind that there’s little or no evidence for a YD effect in the SH.

Re #35: Thanks, Jimmy.
#38 Lank
January 8, 2009

Thanks Jimmy – I overstated somewhat and this was my mistake.
Here is a collation of various plotted temperature interpretations – most show that over the last several thousand years the earth is in a general cooling trend and that more recently (last 300 or so years) this trend has flattened and reversed. http://globalwarmingart.com/wiki/Image:Holocene_Temperature_Variations_Rev_png

I repeat my earlier comment that considering the long history of huge temperature variations in the earth’s climate (ice ages etc.), the 0.6 of one degree centigrade average rise for the entire 20th century shows, if anything, that the 20th century was a time of exceptional temperature stability. So why not recognise this?
#39 David Irving (no relation)
January 8, 2009

Tim @ 33 – our idiot Communications Minister proves that the terrorists have, indeed, won.
#40 Steve Bloom
January 8, 2009

Also, Lank, not to beat a dead horse or anything, but remember that you first said:

“For most of the past 10,000 years temperatures have been 1 to 3 degrees Celsius warmer than they are today.”

After I objected, you said:

“Since then, the Earth continued warming up until about 6,000 years ago – the (mid Holocene thermal maximum) when the earth was around 1-3° C warmer than today. Since then, it’s basically been cooling off – not counting various smaller variations.”

Notice how these two statements contradict each other?

Aren’t you just a little embarrassed that nearly everything you’ve said in this thread has something wrong with it?
#41 Lank
January 8, 2009

Steve Bloom(#37) you say “That 7C figure for the YD is also completely wrong”. Please give me your version of the YD.
#42 Steve Bloom
January 8, 2009

Re #38: Lank, you’re treading on air again in that second paragraph.
#43 Lank
January 8, 2009

Steve – maybe that should be hot air! The Inuit didn’t seem to mind when the arctic was ‘probably’ ice free 6,000 – 7,000 years ago! Seems that it was a great help to their hunting and migration! This recent study http://www.sciencedaily.com/releases/2008/10/081020095850.htm doesn’t mention the poor polar bears which seemed to have done okay when arctic ice was much less than today…
“Recent mapping of a number of raised beach ridges on the north coast of Greenland suggests that the ice cover in the Arctic Ocean was greatly reduced some 6000-7000 years ago. The Arctic Ocean may have been periodically ice free.” http://www.ngu.no/en-gb/Aktuelt/2008/Less-ice-in-the-Arctic-Ocean-6000-7000-years-ago/
I wonder how this could have occurred without man made CO2 to increase temperatures.
#44 bi -- IJI
January 8, 2009

> Notice how these two statements contradict each other?

But they both contradict Al-Goracular Global Warmism, so the contradiction’s OK! Whee!
#45 Anton Mates
January 8, 2009

#43:

Actually, that article says that the Inuit didn’t get there until 4000-4500 years ago, when the ice had returned–precisely because an icy Arctic was “essential” to their hunting.

As for the polar bears, we don’t really know how well they did. In fact, given how closely related they are to some brown bear populations, I don’t think we even know that there were fully-modern polar bears around in this period–they may have hybridized out of existence, then reconstituted afterwards.

And, needless to say, there are a lot of additional pressures on polar bears now that didn’t apply then.
#46 Anton Mates
January 8, 2009

Oh, and in answer to your last question:

“However, the scientists are very careful about drawing parallels with the present-day trend in the Arctic Ocean where the cover of sea ice seems to be decreasing.”

“Changes that took place 6000-7000 years ago were controlled by other climatic forces than those which seem to dominate today,” Astrid Lyså believes.”
#47 Bernard J.
January 8, 2009

(Gack!)

So I read Jenkins’ mind-bogglingly embarrassing piece…

And, suspending disbelief for a moment and assuming that he hadn’t committed every first-year scientific and statistical blunder in the book of “How Not To Do Science or Statistics”, I considered the implication of the plunging neckline at the right-hand side of the trend-line he relies upon in That Graph.

At first jump one might ask Jenkins if he is predicting a global ice-age over the next decade, as the trend is dropping faster than the price of Detroit real-estate in a financial crisis. But of course, being the ‘computer modeller’ that he is, Jenkins would tell us that one cannot extrapolate beyond the independent axis of a plot (unless of course one ‘accidentally’ loses some of the terminal data, but one wouldn’t do that, because it would be scientific misconduct). I assume that Jenkins would in fact tell us that impending data to the right of the graph might show a completely different trend to the free-fall trajectory that one’s trendline is currently (conveniently) describing.

And if Jenkins actually had sufficient wherewithal to comment on extra-abscissa extrapolation, he would no doubt mention that describing the trends beyond the bounds of the x-axis is a fraught exercise when using high-order polynomials, precisely because they do not cope at all with data outside of the range with which they were originally derived. High-order polynomials have almost nothing to do with the average real-world limited dataset, and this is of course the very point that many here are commenting upon…

Oo, hang on – am I not now encountering an internal inconsistency?!

So I can only conclude that Jenkins is either extremely incompetent in the modelling of any data beyond two points describing a line, or incompetent in reviewing his accompanying graphs, or that he is in fact massaging his message.

There you go: I have made an accusation. Come and get me.

Sadly for science, I am reminded of several other punters’ recent attempts to use polynomials as trendlines. Unfortunately, as I am still on a dial-up link my search engine is not obliging rapidly enough, so if anyone has been keeping tabs on such for posterity’s sake I’d appreciate the links in order to refresh our collective memories.

Even more sadly for science, there are hundreds of Denialists crowing at Jenkins’ apparent scientific/statistical skill, and proclaiming the infinity of his profound insight.

What hope for Homo sapiens (?!) when so many of its number are so statistically innumerate?
#48 Chris O'Neill
January 8, 2009

Gunter’s graph is different from Watt’s. It has one more month in it and the degree 6 fit is noticeably different from the degree 5 one — the downturn at the end is steeper and the “trend” goes all the way down to zero.

If the data has a sudden downturn very close to the end then the higher the order of the polynomial, the steeper the fit will be at the downturn. Of course, it’s hard enough getting statistical significance out of a first order fit to this data let alone anything of a higher order and the higher the order, the harder it is to get statistical significance.

Steve Bloom:

Aren’t you just a little embarrassed that nearly everything you’ve said in this thread has something wrong with it?

When someone has the capacity for self-delusion that Lank has, he can’t afford to be embarrassed.
#49 Valhar2000
January 8, 2009

So what is wrong with using a six degree polynomial fit here? I’m sure there is some valid mathematical reason, but it is not in the least obvious to someone not in the know.
#50 bi -- IJI
January 8, 2009

> So what is wrong with using a six degree polynomial fit here?

Well, the real question is “why use a degree-6 polynomial fit at all”? Degree-6 polynomials don’t seem to correspond to any physical or stochastic processes which are relevant here, and they don’t even produce results which are easy to explain (like, well, degree-1 linear fits).
#51 Bernard J.
January 8, 2009

Um at #47 I should have said “extrapolate beyond the graphed values on the independent axis of a plot”.

My bad.
#52 Eli Rabett
January 8, 2009

Valhar2000 see #11 and #27 (second link). Although bi hinted at it, you get stupid behavior at the end points. It is the statistical equivalent of crack the whip.
#53 t_p_hamilton
January 8, 2009

A simple numerical exercise will show why an arbitrary high degree polynomial fit to a noisy signal is nonsense. Taking a toy of example, let us assume that the fit equation is 14.0 + 0.02 t – 0.000001 t^6, for data ranging from t=0 to t=30 (like a 30 year range starting at 1979). The 0.02 is the warming in degree centigrade per year. What would the temperature be in the year 2079 according to this fit, and according to a linear fit? A linear fit would say 2.0 degree warming in a century, the other would be 16 -1,000,000 = -999,984 degrees centigrade. This is 999,711 degrees below absolute zero.

The only reason the highest degree polynomial has a negative sign is becasue the end points have a falloff. What would the fit be if you choose the data from 1981 to 2006? A positive term for t^6.
#54 Barton Paul Levenson
January 8, 2009

kent writes:

Everwhere I look they say the cold is setting records, but of course that is not a trend ackording to the warmists.

kent, I don’t know if you’re aware of this, but when it’s winter in the northern hemisphere, it’s summer in the southern hemisphere, and vice versa. Global warming is about the mean global annual surface temperature. Global warming doesn’t mean we’ll never have cold winters again.

The truth is a trend can last a pico-second or a million years. The current trend is not up but down.

You’ve been told why this is false before, but you just keep repeating it. That’s not a mistake, that’s either intellectual dishonesty or a stupidity so deep you shouldn’t have the brains to continue to breathe.

Once more, for the record, the trend is up. See:

http://www.geocities.com/bpl1960/Ball.html

http://www.geocities.com/bpl1960/Reber.html
#55 Barton Paul Levenson
January 8, 2009

Lank posts:

For most of the past 10,000 years temperatures have been 1 to 3 degrees Celsius warmer than they are today.

This if false. Where do you get this crap?
#56 Jon Jenkins
January 8, 2009

Hmm, if Tim is going to start a blog on me I would think he should invite me to contribute. However his email inquiry about my background prompted me to have a look. All his questions about me are answered in my inaugural speech when I entered the NSW Parliament (http://www.parliament.nsw.gov.au/prod/PARLMENT/hansArt.nsf/V3Key/LC20031119037). The Greens have already investigated me with vigour Tim!

Tim and others are correct I have no formal climatology background but I have some considerable experience in computer modelling of integro-differential equations, mainly from protein folding but also from other interests in electronics and high frequency circuit simulation which is why I have so many concerns about predictions made from GCM computer models.

Since resigning from the university I have taken an interest in matters climate including downloading Hansen and Schmidt’s GCM code base! In view of the comments here some of you should have a look at the way some of the differential equations are parameterised and the order of the equations used!

Now to the science at hand!

The main criticism seems to be the use of the satellite data and the method of curve fitting used. And surprise surprise I agree with many of the comments! The whole concept of curve fitting can be considered “preposterous”. In effect you can use any curve fitting method you like to achieve any effect you desire. But this has never stopped the AGW people from using it! The underlying processes of surface temperature are so complex and affected by so many separate equations that no polynomial could replicate them! But more importantly many of the processes are chaotic in nature and CANNOT (and I mean in the mathematical sense CANNOT) be modelled at all.

The point of the curve was that there is a trend upwards from the 70′s and a trend downwards since the late 1990′s and that does not change no matter what degree (or type) of polynomial you use until you use the longer term linear fits. However if you add in the most recent temperatures across the Northern Hemisphere even the linear fit starts to fall and makes the recent trend downward even steeper for higher order fits.

However I did not in the article, nor would I now, make any PREDICTIONS about future temperatures based on this or any other degree of polynomial fit to chaotic data and nor should anyone else. But for exactly and precisely the same reasons the predictions of the GCM computer models are equally flawed which is really my key point!

Jon Jenkins
#57 Barton Paul Levenson
January 8, 2009

Sorry, the above should read “This IS false,” of course.

Valhar2000 writes:

So what is wrong with using a six degree polynomial fit here? I’m sure there is some valid mathematical reason, but it is not in the least obvious to someone not in the know.

You try to fit the simplest curve you can. If the simple curve fits well, or as statisticians say, “explains enough variance,” you have no justification for making the curve more elaborate. If you make a curve elaborate enough, you can send it through every point in a graph, but that’s a physically meaningless result.

The use of a sixth-order polynomial probably means, “Linear doesn’t give the answer I want, and quadratic doesn’t give the answer I want, and cubic doesn’t, and quartic doesn’t, and quintic doesn’t, but when I make it sixth-degree I get the answer I want!”
#58 P. Lewis
January 8, 2009

But more importantly many of the processes are chaotic in nature and CANNOT (and I mean in the mathematical sense CANNOT) be modelled at all.

OK, so consider the following statements (statements that can be seen in quite a few textbooks IIRC).

In mathematics, chaos theory describes the behaviour of certain dynamical systems “that is, systems whose states evolve with time” that may exhibit dynamics that are highly sensitive to initial conditions (popularly referred to as the butterfly effect). As a result of this sensitivity, which manifests itself as an exponential growth of perturbations in the initial conditions, the behavior of chaotic systems appears to be random. This happens even though these systems are deterministic, meaning that their future dynamics are fully defined by their initial conditions, with no random elements involved. This behavior is known as deterministic chaos, or simply chaos.

Chaotic behaviour is also observed in natural systems, such as the weather. This may be explained by a chaos-theoretical analysis of a mathematical model of such a system, embodying the laws of physics that are relevant for the natural system.

There seems to be a divergence between your statement and the above extract. Can you please elucidate?
#59 sod
January 8, 2009

The point of the curve was that there is a trend upwards from the 70′s and a trend downwards since the late 1990′s and that does not change no matter what degree (or type) of polynomial you use

here is my challenge:
please show us a third degree polynomial, that points downward at both ends!

(no need to fit it to any data. juts a graph will do!)

until you use the longer term linear fits. However if you add in the most recent temperatures across the Northern Hemisphere even the linear fit starts to fall and makes the recent trend downward even steeper for higher order fits.

this is FALSE. there is NO linear fit to the entire satellite data, that points downward.

i think you got confused and you were talking about cherry-picked short periods?!?

However I did not in the article, nor would I now, make any PREDICTIONS about future temperatures based on this or any other degree of polynomial fit to chaotic data and nor should anyone else. But for exactly and precisely the same reasons the predictions of the GCM computer models are equally flawed which is really my key point!

so the precisely same reasons, that stop your false use of a incredibly simple mathematical model from giving projections of the future, also stops the complicated models of real climate scientists from working?

sorry, but this claim again is simply false.
#60 P. Lewis
January 8, 2009

Now that you have popped in, Prof Jenkins, perhaps you could help in clarifying a couple of things for us. There are many here that will likely like to know the answer.

If you have read the various comments and followed links, then you will know that there is “concern” over the date at which the data in your analysis were curtailed.

So, when did you submit the piece to The Australian for consideration for publication?

Or perhaps they solicited the piece from you in the first instance. If so, what date was it solicited and when was the piece prepared by you and the date submitted?

TIA.
#61 ChrisC
January 8, 2009

Jon Jenkins @56

The underlying processes of surface temperature are so complex and affected by so many separate equations that no polynomial could replicate them! But more importantly many of the processes are chaotic in nature and CANNOT (and I mean in the mathematical sense CANNOT) be modelled at all.

Sir. you are wrong, wrong wrong on this count.

I have spent my career modeling complex, and in many cases chaotic systems. I have worked on Numerical Weather Prediction models, which do an excellent job at predicting the future state of the weather (a chaotic system) when used correctly. These models are used by weather agencies across the world and have demonstrable skill.

I have worked on models for turbulent flow in atmospheric flows (and more general flows) and turbulent flows around aerofoils. The flow around these objects is complex and has many of the These state of the art models are now so precise that they can be used by engineers for design work. I’ve also worked on dynamical models of machinery, which can have chaotic behaviour. Modelling these systems is an intriguing mix higher mathematics (fun with topology and differential geometry), physics and numerical analysis.

This is just the experience I’ve gained in a relatively short career. The modeling of complex systems is difficult, and the presence of chaotic behaviour means that the dynamics and initialisation of the model must be treated specially. However, it is a flat out flasehood to say these systems cannot be modeled.

As for climate modeling, if you’ve studied the subject you should have learned that certain statistical behaviour of the climate systems is not chaotic at all.

I suppose the oft used example is that I can predict that January in Australia will be (on average) warmer than June. Another example is the average global temperature of the last 30 years can be modeled adequately by:

T = linear trend + ARMA noise process.

A GCM is not suppose to forecast the weather on June the 14th, 2030. It’s suppose to give an estimate of the statistical mean state of the atmosphere for the winter of 2030. Many of these variables (for example those found in the zonally averaged momentum equations) can be shown by analysis to exhibit no chaotic behavior once transients have died out.

Your statement is wrong, and your graph is misleading. I hope you can admit that.
#62 Jon Jenkins
January 8, 2009

“So, when did you submit the piece to The Australian for consideration for publication?”

A week or so ago.

“Or perhaps they solicited the piece from you in the first instance. If so, what date was it solicited and when was the piece prepared by you and the date submitted?”

No they did not solicit, I sent it after the article by Mike Steketee.

What has any of this got to do with the science? Why is it the AGW devotees tend to go after the man rather than debate the issue. If you really want ammunition against me personally the best bit is disclosed in my departing speech from the Parliament: I was diagnosed with a brain tumour in 2007 and need to take anti-seizure medication. Does this mean that the science I present is wrong?

As I said above, NO fit, linear, polynomial or anything is relevant when you are talking about complex process with so many degrees of freedom and so many unknown feedbacks. You can fit curves to any time scale of your choosing to give the end scale gradient you desire. However to imply that you can make useful predictions out of this is wrong no matter what side of the AGW fence you sit! All we can really say is that the climate warmed slightly from the mid 70′s to the lat 90′s and the climate cooled slightly form the last 90′s till today.

As to chaos theory, the Russian Academy of Science has been using chaos theory for their climate predictions for some time. And I’ll leave it to you to do the research as to what they predict but I would get out the warm woollies if you believe them. I have about as much confidence in that prediction as I do in the GCM ones.
#63 Gaz
January 8, 2009

Nice of you to visit this site, Prof. Jenkins.

You have by now been alerted to the fact that your graph, which purported to show warming “had completely reversed by 2008″, is several months out of date.

You will also be aware that the UAH data, on which the graph is based, show the global temperature anomaly rose in September, October and November.

By November it was +0.254, right on the 30-year linear trend and pretty much exactly what one would expect after ENSO conditions returned to neutral following a significant La Nina event.

What is your response to this?

By the way, may I offer a suggestion on your expository style?

If you want people to take you seriously, it might be a good idea to avoid language like this: “The warmaholics, drunk on government handouts and quasi-religious adulation from left-wing environmental organisations..”, ” the fraud of the IPCC” “the infamously fraudulent ‘hockey stick’” etc.

You are obviously a man of science. Such inflammatory language, however, could give the reader the unfortunate impression that you have rejected the science not because of a sober and rational assessment of the facts but because of some overriding psychological motivation like, for example, hypothetically speaking, a deep-seated ideological prejudice against government intervention in markets or a fear that your 4WD might be confiscated by faceless bureaucrats.

Another suggestion would be to offer some data and/or sources to back your assertions.

Like this one, for instance: “Cataclysmic volcanic eruptions have often placed more greenhouse gases into the atmosphere in (a) few minutes than man induces in a decade.”

Atmospheric CO2 is rising by about 19 ppm per decade at present. Can you give me an example of evidence showing a volcano has ever (let alone “often”) managed to do more than that in a “few minutes”?

Oh, and I’d suggest you steer clear of those polynomial curves. They’re way too flexible near the end point. They can turn around and bite you right on the bum.
#64 P. Lewis
January 8, 2009

I was at my polite best, with temperate, courteous language in #60. And what do I get in reply, but:

Why is it the AGW devotees tend to go after the man rather than debate the issue. If you really want ammunition against me personally the best bit is disclosed in my departing speech from the Parliament: I was diagnosed with a brain tumour in 2007 and need to take anti-seizure medication. Does this mean that the science I present is wrong?

Please point out to me where my supposed ad hominem attack is on you and where my request is for ammunition against you personally in my comment #60.

I see nothing of the sort. Precisely nothing! So why did you raise that nonsense and accuse me of attacking you personally?

Also, in that quotation above, the diversionary tactic of conflating the two separate issues of your illness and whether that means the science you present is wrong is, I think, contemptible. I’m not too sure whether it’s an “appeal to pity” type fallacious argument or some other documented type (can’t be bothered to run it down at the moment), but it is certainly a red herring. Shame.

But let’s now go back one sentence from the above-quoted personal slur upon me. You also said:

What has any of this got to do with the science?

Sorry, but I expect more from professors. As someone who has worked in academia and who has almost certainly submitted work to journals for peer review, you must surely be aware of the importance of research logs/lab books and document history (dates when work is carried out, submission/revision dates and the like). The questions about submission timing of your article were pertinent because of the implicit question in para 2 of #60, namely:

If you have read the various comments and followed links, then you will know that there is “concern” over the date at which the data in your analysis were curtailed.

You appear to want to dodge around that issue in your diversions above (at least you didn’t answer it above), so let me make it explicit.

Now that we know the time history on the piece (for which I thank you for supplying), given the gestation of the piece is “a week or so ago”, why did you curtail the data where you did, when updating the data (freely available) to November (or even October) would have been the correct thing to do? What is the scientific basis for stopping in … was it July? I look forward to your reply.
#65 Gaz
January 8, 2009

Prof J, please re-read your article in The Australian.

You may find that it is not just “the AGW devotees tend to go after the man rather than debate the issue.”

May I, again, remind you of this passage you wrote: “The warmaholics, drunk on government handouts and quasi-religious adulation from left-wing environmental organisations…”, not to mention the accusation about the IPCC authors: “…44 scientist mates who have vested interests in supporting IPCC computer modelling..” etc etc.

Having said that, I’m sure the question was genuine: many people are genuinely mystified about the apparent decision at the Australian to launch a campaign against climate science/scientists, using the same old recycled (and discredited) talking points over and over.

Any enlightenment on this point would be gratefully accepted, I’m sure.

Now, back to the science.

You claim “All we can really say is that the climate warmed slightly from the mid 70′s to the late 90′s and the climate cooled slightly form the last 90′s till today.”

First, I’m glad that you now aparently have confidence in the instrumental data pre-dating the satellite data which started in December 1979.

Second, please define “today”. In other words, just precisely which cherry are you trying to pick here?
#66 Steve Huntwork
January 8, 2009

I am rather baffled by this discussion about fitting a polynomial curve to a set of known data points.

A single term polynomial fit is an average.
A two term polynomial fit is a trend line.

People do not have any problems when averages and trend lines are shown on a graph of measured data points.

A four term polynomial fit is starting to show the little wiggles in the actual data.

If you add enough terms to a polynomial fit, the original data points will be reproduced exactly.

Where people go wrong, is when they attempt to extrapolate a polynomial curve into the future.

Some people have gotten upset, because they have extroplated this curve, and know that such a drastic drop in Earth’s temperate is not possible. They are correct, but their arguments are based upon a very flawed concept.

Please pay attention to this rather simple lesson about extrapolation.
#67 Eli Rabett
January 8, 2009

Recycling

Gunsalus distinguishes between traditional, assertive bullies, who throw their weight around with bluster and force, and ‘victim bullies,’ who use claims of having been wronged to gain leverage over others.(pp. 123-4) Unlike simple passive-aggression, victim bullies use accusations as weapons, and ramp up the accusations over time. Unlike a normal person, who would slink away in shame as the initial accusations are discredited, a victim bully lacks either guilt or shame, honestly believing that s/he has been so egregiously wronged in some cosmic way that anything s/he does or says is justified in the larger scheme of things. So when the initial accusations are dismissed, the victim bully’s first move is a sort of double-or-nothing, raising the absurdity and the stakes even more……
#68 Gaz
January 8, 2009

Steve Huntwork, I think the point (made by someone else here I think) is more that a high order polynomial is more heavily influenced by the data points at the end of the data series than a linear function is.
For example, both the La Nina in 1989 and the Pinatubo volcano in 1991 were associated with large drops in temperature but the polynomial curve does not fall – it had to take account of the subsequent rises in temperature. Yet there is a similar fall at the end of the series, and the curve drops like a stone.
If, for the sake of the exercise, you add 5 degrees to the latest value, the polynomial fitted curve changes direction and heads toward the sky. In contrast, the gently upward sloping linear trend line through the same data will not change very much.
The bottom line is that if you have a data set that dips down near the end and you wanted to emphasise the new downward “trend”, you’d choose a high order polynomial to do it.
#69 Jon Jenkins
January 8, 2009

Playing the man is attacking specific individual on a non scientific basis (i.e credibility or status or personal issues) rather than attacking the process which is what I did. Example: the continued use of the hockey stick AFTER it was shown to be invalid including the refusal of the IPCC the retract it in later reports is a perfect example. The involvement of a select few people who have vested interests in perpetuating the outcomes of the IPCCC process i.e. more funding and kudos but mostly because it is not open to independent review!

I do not retreat from my comments about the process whereby only a few scientists have the authority to change the world by declaring “we did it” without any form of independent review or question whatsoever!

Back to the science:

Steve Huntwork said it succinctly in his post above but perhaps an explanation for the more mathematically oriented is in order, this is hard to do in this forum because I can’t post symbols etc. But here goes…

The solution (i.e. T) to the climate equations of the earth is complex, it is a giant set of differential equations perturbated by cyclic, impulse and random drivers, some of which we can parameterise (i.e. solar, day/night, seasons etc) and some of which we can’t (clouds, El Nino, thermohaline etc). The outcome is the solution of the Laplacian equations and can be shown by Heaviside’s Rules (and related expansion theorem) to be the ratio of polynomials of greater order than the input. I will try to do this in text but it may not come out, if it doesn’t make sense get a maths text and look up Heaviside’s Expansion Theorem.

let g(s) be the climate equations,

if g(s) = N(s)/p(s) (where N(s) and P(s) are polynomials in (s), which they have to be because that is how the equations are parameterised, see **Note below)

then

L^-1g(s) = Sigma[r=n..r=1] [n(sr) e^(srt) / p'(s)]

Where n = number of zeros of p(s)

in other words the solution will be a massive polynomial.

(Again, see note below about real GCMs)

It follows that the T curve will also be a massive polynomial in (t) and will be best approximated by the largest polynomial possible.

However we all know that curve fitting to a section of a curve is dangerous because even if higher order polynomials fit it better they tend to oscillate around the data at the extremities. But the opposite is true of smaller polynomials which tend to ignore the accumulation of smaller poles and zeros and linearise at the extremities!

So I say again: NO curve fitting technique can claim to be more or less valid than another!

But if the AGW side are going to use curve fitting to make a point then so can anyone else!

** Note on real GCMs: Actual GCMs work differently in practice, the integrals are usually solved by quadratures, unconstrained meshes and/or finite elements. Integrals are typically approximated by cubic spline interpolation (sometimes higher order interpolations are used depending upon the order of differential). Initial values are averaged from historical data and interpolated (there’s that word again) from real data sets. The issue of boundary conditions is pretty much ignored except that they must match at the cell boundaries! (see http://climatesci.org/ for technical description)
#70 Dano
January 9, 2009

Example: the continued use of the hockey stick AFTER it was shown to be invalid including the refusal of the IPCC the retract it in later reports is a perfect example.

*snork*

The involvement of a select few people who have vested interests in perpetuating the outcomes of the IPCCC process i.e. more funding

Chortle.

only a few scientists have the authority to change the world by declaring “we did it” without any form of independent review

heehee.

NO curve fitting technique can claim to be more or less valid than another!

(silence)

if the AGW side are going to use curve fitting to make a point then so can anyone else!

sigh.

Have the comedy writers making on-line parody characters all found work, and all that’s left is washed up, unfunny hacks making these parody characters?

I’m getting a comedy Jones and I need a fix! The parody character Mr Jenkins is not meeting my comedy needs!

Huh? Whassat?

Um…excuse me a minute, please.

Ahem.

Erm, apologies. Someone tells me Mr Jenkins may be real.

Terribly sorry. Apologies.

Gotta go now…um, well, buh-bye!

Best,

D
#71 bi -- IJI
January 9, 2009

Jenkins, that was an impressive load of scienobabble, but there’s one problem: you throw out lots of equations and conclude that

> It follows that the T curve will also be a massive polynomial in (t) and will be best approximated by the largest polynomial possible.

but your equations don’t have T(.) in them. So what I’d like to know is, according to your understanding, T(.) is the solution to… what equation? I’m assuming that t (small letter) denotes the time period. But what’s s?
#72 Richard Simons
January 9, 2009

Do climate modellers really use the fitting of higher order polynomials? As I understood it, they used equations based on sound physical principles. Some may have been derived by fitting curves to experimental results but these would have been more in the way of linear or logistic equations, not sixth order polynomials. Or have I got completely the wrong idea?
#73 Tim Lambert
January 9, 2009

Jon, the hockey stick was not shown to be invalid. Read the [fine NRC report](http://scienceblogs.com/deltoid/2006/06/nas_report_on_hockey_stick_rel.php).

Certainly it is true that a higher-order polynomial can better approximate the data, but that doesn’t mean that a higher-order polynomial gives a better idea of the trend, else we would just set the degree to the size of the data and get a curve that goes through all the data points. For temperature data a linear trend seems to be the best idea. If you think the slope has changed over time, rather than a higher-order polynomial, you could use local regression (loess).
#74 Gaz
January 9, 2009

Prof. J, I guess we can agree on one thing – I’ve said on this site a long time ago that I think the debate about trends is misplaced, because it really devolves, at least implicitly, into a debate about whether the temperature can be described as a function (linear or otherwise) of the date (as opposed to energy inputs, atmospheric composition, etc).

However that does not get around the more important question: has the temperature become warmer and if so has the recent warming been largely the result of greenhouse gas emissions by human activity and can therefore be expected to continue?

Unfortunately you’re yet to say anything of substance on that point.
#75 sod
January 9, 2009

in other words the solution will be a massive polynomial.

i am neither to deep into climate models, nor does your 2 line introduction into the subject contain enough information for me to fully understand them.

but: each of your lines seems to include a ratio of polynomials, making them not polynomials!

It follows that the T curve will also be a massive polynomial in (t) and will be best approximated by the largest polynomial possible.

i asked you above, to provide a third degree polynomial that heads downward at both ends. (when you claimed that the degree doesn t matter)
you ignored that question.

now you claim, that the largest degree is best.

Tim provided this graph with both the linear and your “trend”.

http://scienceblogs.com/deltoid/2009/01/06/uahtlt5.2.png

i fail to see the advantage of the higher degree polynomial. instead both “curves” tend to be better approximations at different times.

However we all know that curve fitting to a section of a curve is dangerous because even if higher order polynomials fit it better they tend to oscillate around the data at the extremities. But the opposite is true of smaller polynomials which tend to ignore the accumulation of smaller poles and zeros and linearise at the extremities!

sorry, but 1998 surely is an extreme point. both curves fitted give exactly the SAME approximation for it!

So I say again: NO curve fitting technique can claim to be more or less valid than another!

did you ask anyone with some knowledge of statistics on this?
i have some massive doubts, that he will agree!
#76 Jon Jenkins
January 9, 2009

“Do climate modellers really use the fitting of higher order polynomials? As I understood it, they used equations based on sound physical principles. Some may have been derived by fitting curves to experimental results but these would have been more in the way of linear or logistic equations, not sixth order polynomials. Or have I got completely the wrong idea?”

Yes you have the right idea just the wrong method! We would all love to be able to solve massive differential matrices (the physical/chemical equations) directly but, unless I have missed some revolution in mathematics/physics, we can’t

So we have to use “tricks” to put the equations into forms which can be solved numerically. There are all sorts of “tricks” used depending upon the equation at hand. The we have to use all sorts of other trickery to solve the remaining equation sets, I have even seen one group try to use harmonic balancing which is novel seeing as the climate never reaches a stable state i.e. it is always being “driven” by some new input.

Climate models are based on a cell size of 2×4 (lat by long) (that was last time I looked at the Hansen/Schmidt code. How can we simulate the climate 100 years form now based on cell sizes of 10,000′s of cubic kilometres? What about mixing and turbulence i.e. a cyclone!!

Oh and Fortran should be banned!!).

However that does not get around the more important question: has the temperature become warmer and if so has the recent warming been largely the result of greenhouse gas emissions by human activity and can therefore be expected to continue?

I wish I could answer those two questiona! The satellite data says the Northern Hemisphere may have warmed slightly but the SH has not! It also shows, depending on which curve fitting method you use, that recent cooling may have occurred. And both of these “beliefs” are borne out anecdotally (i.e. a few years ago NH was hot now they are currently freezing with record lows!)

As to the second question the AGW camp rely on the GCM outputs to say yes but for myself I simply have had too much experience with computer models of much simpler and more constrained systems (i.e. protein folding in my case) to believe this. I KNOW that we cannot even predict the structure of simple 20 AA proteins in controlled environments when we know a great deal about the intermolecular forces involved. I then have to question how we can predict the climate in 100 years when the environment is many orders of magnitude more complex.

In the end, what I am saying regardless of whether the GCMs are right or wrong we MUST become energy self sufficient within ~200 years and good basic science is the only way to do this. “Feel good” stuff won’t cut it when the oil/gas/coal run out and the problem is that schemes like ETS are useless

UNLESS

the money goes back to the science.

Jon
#77 bi -- IJI
January 9, 2009

Jenkins:

> So we have to use “tricks” to put the equations into forms which can be solved numerically.

As far as I know, none of these “tricks” involve starting with mathematical expressions like g(s), N(s), and t(s), and then suddenly concluding something about the temperature record T(t) out of nowhere.

So I ask again: According to your understanding T(.) is the solution to… what equation precisely? And what’s s?

Or are you just throwing out mathematical gobbledygook in order to confuse?

sod:

> i asked you above, to provide a third degree polynomial that heads downward at both ends. (when you claimed that the degree doesn t matter) you ignored that question.

Heheheh.
#78 Jon Jenkins
January 9, 2009

Someone up there said:

“I have spent my career modeling complex, and in many cases chaotic systems. I have worked on Numerical Weather Prediction models, which do an excellent job at predicting the future state of the weather (a chaotic system) when used correctly. These models are used by weather agencies across the world and have demonstrable skill.”

Hmm did any of the computer models predict the current cooling ….ahh NO (http://www.trac.org.au/images/temps_simple2.gif)

Tell you what make you a deal; El Nino transfers about 5PW of energy around the planet (about 50% of the total energy budget). Tell me (and the rest of the world) when the next El Nino event is going to occur and if you are correct you win the debate.
#79 bi -- IJI
January 9, 2009

Shorter Jon Jekins:

GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING! GLOBAL COOLING!
#80 Gaz
January 9, 2009

Professor Jenkins,

I asked earlier what you meant by “today” when you claimed the temperaure had cooled slightly between the late 1990s and “today”.

You’ve given no answer yet, and now you say “The satellite data says the Northern Hemisphere may have warmed slightly but the SH has not!”

Again, to what periods are you referring, precisely?

Do you take the November average as your latest reading, the past year, the past decade, the latest point on your 6th order polymonial, or what?

On a more general and probaly more important note, what do you think of the physics involved in all this, you know, greenhouse gases (GHGs) absorbing energy and all that.

I seems that you’d be too intelligent to insult us with the old “how could such a teeny weeny bit of life-giving cuddly carbon-dioxide do such a mean and nasty thing” line we get so often. (PLEASE don’t disappoint me!!)

So do the GHGs absorb the energy? If not, why don’t you think that? If they do, where does it go if the atmosphere and oceans aren’t heating up? Is there some negative feedback that completely offsets both the GHG forcing and any positive feedbacks? If so, what makes you think they exist and what do you think they might be?

I’m intigued, because, despite repeated claims to the contary, it’s not just the models that lead to the conclusion that antheropogenic global warming is a reality, but the physics as well.
#81 Gareth
January 9, 2009

I seems that you’d be too intelligent to insult us with the old “how could such a teeny weeny bit of life-giving cuddly carbon-dioxide do such a mean and nasty thing” line we get so often.

We’ll leave that to Roy Spencer, shall we?
#82 Jennifer Marohasy
January 9, 2009

Deltoid et al.

The bottomline is that the global temperature, however it is measured but in particular by satellite, shows cooling and this is not how you have predicted it should be.

Indeed you (Tim Lambert) and your mates including John Quiggin, hitched your reputations some years ago to the idea that the world would continue to warm.

You did this, not because you understood the physics, but because that is what leaders at the institutions you believe in were saying would be the case.

But it is not proceeding to plan. Indeed despite a continual increase in atmospheric levels of carbon dioxide, global temperatures are falling.

For more information, click here: http://jennifermarohasy.com/blog/2009/01/29-years-of-global-temperatures-based-on-satellite-data/
#83 Paul
January 9, 2009

re Jenkins…

>I asked earlier what you meant by “today” when you claimed the temperaure had cooled slightly between the late 1990s and “today”.

The earth cools slightly but still temperatures rise.
If i was a person living in 1882 i could be witnessing the temperature cooling. Would I then expect that in 1912 that temperatures would be rising and that by 1950 temperatures would be higher than 1882.

If Jenkins believes that climate scientists can not predict the future with computer models. I hardly think it is appropriate that Jenkins should be proposing that a reduction in temperature is also a good indicator of future temperatures!
I find it a bit hypocritical. But then sceptics aren’t out to prove what is actually happening, they are out to dismantle the science for political reasons.
#84 Gareth
January 9, 2009

Oh dear Jennifer, you really don’t know what you’re talking about, do you?

From the Hadley Centre:

Professor Phil Jones, Director of the Climatic Research Unit, University of East Anglia, explains: “The fact that 2009, like 2008, will not break records does not mean that global warming has gone away. What matters is the underlying rate of warming – the period 2001-2007, with an average of 14.44 °C, was 0.21 °C warmer than corresponding values for the period 1991-2000.”

Try the same exercise with the satellite data. It will still show warming.
#85 paul
January 9, 2009

Marohasy:

>But it is not proceeding to plan.

Ah, that old paranoid conspiracy plan!
That would be Plan 9 or 10?
#86 Gaz
January 9, 2009

paul: “Ah, that old paranoid conspiracy plan! That would be Plan 9 or 10?”

I think it’s Plan 9, Paul. Here’s the link:

http://au.youtube.com/watch?v=6-kCC8WUKYk

You can see Prof Jenkins at 1:56 and Jennifer Marohasy at about 2:20.
#87 Jennifer Marohasy
January 9, 2009

No conspiracy. Just a couple of facts:

1. Tim Lambert has for years been claiming global warming.

2. The globe is not warming.

Jon Jenkins is not only pointing this out. But the national newspaper is daring to publish him. So Tim is angry.
#88 P. Lewis
January 9, 2009

Socratic BS!
#89 Richard Mackey
January 9, 2009

Readers of this discussion should find Professor de Jager’s homepage very helpful. It is rich with careful science and thorough analysis. I strongly recommend it to those interested in understanding the world.

Here it is: http://www.cdejager.com/

Here is an extract from his CV:

He was director of the Utrecht Observatory, founder and first director of the Utrecht Space Research Laboratory, and founder of the Astrophysical Institute of Brussels Free University.

He was general secretary of IAU (International Astronomical Union), president of COSPAR (Intl. organization for co-operation in Space Research) and president of ICSU (Intl. Council for Science). He founded and was first editor of the journals `Space Science Reviews’ and ‘Solar Physics’. He is member of various learned societies, among which the Royal Netherlands Academy of Arts and Sciences, the Royal Belgian Academy of Arts and Sciences, the Academia Leopoldina (Halle, Germany), the Indian Science Academy, Academia Europaea, etc. He received honorary doctorates in Paris and Wroclaw. He was recipient of awards and distinctions among which the Gold Medal of the Royal Astron. Soc. (UK), the Hale Medal of the Amer. Astron. Soc. (for solar research, US), the Jules Janssen Medal (for solar research, France), the Karl Schwarzschild Medal (for astrophysics, Germany), the Gagarin Medal and Ziolkowski Medal (space research, S.U.), the COSPAR medal for international cooperation, etc. He is honorary member of SCOSTEP, the international organization for solar-terrestrial physics.
#90 Richard Mackey
January 9, 2009

Readers of this discussion should find Professor de Jager’s homepage very helpful. It is rich with careful science and thorough analysis. I strongly recommend it to those interested in understanding the world.

Here it is: http://www.cdejager.com/

Here is an extract from his CV:

He was director of the Utrecht Observatory, founder and first director of the Utrecht Space Research Laboratory, and founder of the Astrophysical Institute of Brussels Free University.

He was general secretary of IAU (International Astronomical Union), president of COSPAR (Intl. organization for co-operation in Space Research) and president of ICSU (Intl. Council for Science). He founded and was first editor of the journals `Space Science Reviews’ and ‘Solar Physics’. He is member of various learned societies, among which the Royal Netherlands Academy of Arts and Sciences, the Royal Belgian Academy of Arts and Sciences, the Academia Leopoldina (Halle, Germany), the Indian Science Academy, Academia Europaea, etc. He received honorary doctorates in Paris and Wroclaw. He was recipient of awards and distinctions among which the Gold Medal of the Royal Astron. Soc. (UK), the Hale Medal of the Amer. Astron. Soc. (for solar research, US), the Jules Janssen Medal (for solar research, France), the Karl Schwarzschild Medal (for astrophysics, Germany), the Gagarin Medal and Ziolkowski Medal (space research, S.U.), the COSPAR medal for international cooperation, etc. He is honorary member of SCOSTEP, the international organization for solar-terrestrial physics.
#91 Richard Mackey
January 9, 2009

Readers of this discussion should find Professor de Jager’s homepage very helpful. It is rich with careful science and thorough analysis. I strongly recommend it to those interested in understanding the world.

Here it is: http://www.cdejager.com/

Here is an extract from his CV:

He was director of the Utrecht Observatory, founder and first director of the Utrecht Space Research Laboratory, and founder of the Astrophysical Institute of Brussels Free University.

He was general secretary of IAU (International Astronomical Union), president of COSPAR (Intl. organization for co-operation in Space Research) and president of ICSU (Intl. Council for Science). He founded and was first editor of the journals `Space Science Reviews’ and ‘Solar Physics’. He is member of various learned societies, among which the Royal Netherlands Academy of Arts and Sciences, the Royal Belgian Academy of Arts and Sciences, the Academia Leopoldina (Halle, Germany), the Indian Science Academy, Academia Europaea, etc. He received honorary doctorates in Paris and Wroclaw. He was recipient of awards and distinctions among which the Gold Medal of the Royal Astron. Soc. (UK), the Hale Medal of the Amer. Astron. Soc. (for solar research, US), the Jules Janssen Medal (for solar research, France), the Karl Schwarzschild Medal (for astrophysics, Germany), the Gagarin Medal and Ziolkowski Medal (space research, S.U.), the COSPAR medal for international cooperation, etc. He is honorary member of SCOSTEP, the international organization for solar-terrestrial physics.
#92 Richard Mackey
January 9, 2009

Readers of this discussion should find Professor de Jager’s homepage very helpful. It is rich with careful science and thorough analysis. I strongly recommend it to those interested in understanding the world.

Here it is: http://www.cdejager.com/

Here is an extract from his CV:

He was director of the Utrecht Observatory, founder and first director of the Utrecht Space Research Laboratory, and founder of the Astrophysical Institute of Brussels Free University.

He was general secretary of IAU (International Astronomical Union), president of COSPAR (Intl. organization for co-operation in Space Research) and president of ICSU (Intl. Council for Science). He founded and was first editor of the journals `Space Science Reviews’ and ‘Solar Physics’. He is member of various learned societies, among which the Royal Netherlands Academy of Arts and Sciences, the Royal Belgian Academy of Arts and Sciences, the Academia Leopoldina (Halle, Germany), the Indian Science Academy, Academia Europaea, etc. He received honorary doctorates in Paris and Wroclaw. He was recipient of awards and distinctions among which the Gold Medal of the Royal Astron. Soc. (UK), the Hale Medal of the Amer. Astron. Soc. (for solar research, US), the Jules Janssen Medal (for solar research, France), the Karl Schwarzschild Medal (for astrophysics, Germany), the Gagarin Medal and Ziolkowski Medal (space research, S.U.), the COSPAR medal for international cooperation, etc. He is honorary member of SCOSTEP, the international organization for solar-terrestrial physics.
#93 Jarrah
January 9, 2009

“2. The globe is not warming.”

Anything less than a trend is meaningless. The trend, as shown by the graphs in Tim’s post, is positive. I can’t believe you (or anyone else) doesn’t understand that.

So, to correct your comment:
1. Tim Lambert has for years been claiming global warming.
2. On any meaningful timescale, there is currently global warming.

I look forward to a post on your blog acknowleding these basic facts.
#94 Bernard J.
January 9, 2009

Jon Jenkins.

My bemusement remains.

Given a dataset with a discrete and limited (in a climate context) range of time values accompanied by temperature values, what justification can anyone use for the fitting of a 6th order polynomial with which to represent the interval’s trend (especially as there is no consideration of any of the myriad of other parameters relevant to global climate/temperature in this graph)?

It is a simple question.

If the ordinate had been any other mundane parameter would you allow your undergraduates to use such a fit? And what of the fact that there are decades of preceeding data not included? Especially, what of the fact that including even some of these data in a refit will give a completely different 6th order polynomial? How does this simple fact justify the use of such a trendline format?

Where in common usage do other researchers employ 6th order polynomials to describe the trend in a time series?

If you seriously think that you have the advantage on both time-scale selection and on trend-fitting I hope that you might consider posting over at Tamino’s. You would surely have something to teach the analysts there…
#95 Tim Lambert
January 9, 2009

**Update:** Ian Musgrave [has more on what is wrong with high order polynomial fits](http://astroblogger.blogspot.com/2009/01/whats-up-with-polynomial-fits-yes-it.html).
#96 P. Lewis
January 9, 2009

Professor Jenkins said

Hmm did any of the computer models predict the current cooling ….ahh NO

Well let’s see. Using the Met Office’s Unified Model, Smith et al. (Science 317: 796-799), in a “forecast” to 2014, said:

Our system predicts that internal variability will partially offset the anthropogenic global warming signal for the next few years. However, climate will continue to warm, with at least half of the years after 2009 predicted to exceed the warmest year currently on record.

Well, long way to go, agreed; but they’re doing OK so far.

BTW, you still haven’t answered my polite question at the end of #64 (and implicit in my even more polite #60). I’m still looking forward to your answer. TIA.
#97 sod
January 9, 2009

Jon Jenkins is not only pointing this out. But the national newspaper is daring to publish him. So Tim is angry.

Tim is not angry. he is correcting errors.
#98 elspi
January 9, 2009

Jenkins spews
“in other words the solution will be a massive polynomial.
(Again, see note below about real GCMs)
It follows that the T curve will also be a massive polynomial in (t) and will be best approximated by the largest polynomial possible.”

HORSE SHIT.
It might be represented by a power series but it sure as hell isn’t going to be a polynomial. The fact that you are pretending that they are the same is all the proof we need to know that you are a liar.

Furthermore, we are not getting the the actual numbers here, we are getting data which will always contain some noise. Fitting a sixth degree polynomial to noisy data is much worse than anything Mann ever did. You sir are a fraud. If you want to wander over to Open Mind, Tamio(the pro on time series) will hand you your head.
#99 Eli Rabett
January 9, 2009

The fact is that all climate models, if you run them long enough have 5-10 years that go against any linear trend. You can see this as far back as Hansen et al 1988 if you take out your magnifying glass and look from ~1973-1983.

Jenkins accidentally blunders into a fallacy, that the climate system has infinite degrees of freedom. Because most variables have huge amounts of correlation, the actual number of degrees of freedom is relatively small especially over a global average (more averaging over space and time reduces the number of dof). Here is an example

Jenkins systematically blunders into a worse fallacy aka the stamp collector’s approach that the best description of a thing, is the thing itself. Statistics is the escape from that dead end, and statistics coupled with physics allows us to ask what is producing the observations and produces a reasonable extrapolation. As we have seen Jenkins approach is incapable of extrapolation and thus useless.
#100 stewart
January 9, 2009

Dr. Jenkins:
I can understand that yo umay not be up on the climatology processes, why the various national academies, royal societies, etc. may identify this as an issue, so I’ll just ask you about the statistics.
1. Climate data is strongly autocorrelated at short intervals. What are your adjusted degrees of freedom, to take that into account?
2. What are your fit data, level by level, and your incremental changes? When do they stop being statistically significant (i.e., when do you start fitting more noise than data?)
3. What does inclusion of data beyond your endpoints do to your graph? Does your polynomial trend better fit the data for September 2008 on (or from 1978), or does the simple linear trend (or statistically significant lesser polynomial trend) fit better? (A quick plot of predictions vs. residuals will be fine).

As a low-level statistician/psychologist, I’m interested in knowing these things. I’m sure you wouldn’t want to fit curvy lines to data without any interest in the actual meaningfulness of this. And of course, we know that trendlines mean nothing without associated significance levels (taking autocorrelations into account) and fit to data outside the range. I’d hate to assume that you and those making use of your work are producing meaningless propaganda.