UPDATE 1, 2 JAN 2011, 23:10 NZT
An answer for RW, of Hot Topic — see end.
There, I did it again — ventured over to Hot Topic. When will I learn?
Briefly optimistic someone wanted answers and really was listening, I was called liar and worse, then quickly censored. “Open and frank discussion forum”, indeed!
I’m posting the deleted response to Gareth’s demand for an apology and a reply to an HT reader. diessoli — see the end of this post for my response to your comments.
WARNING
What follows is just “I said, he said” argy-bargy. It’s not important and is posted simply to document my last encounter with the proprietor at Hot Topic, Gareth Renowden. I think the exchange typifies his lack of charity and his stubborn refusal to admit that NIWA has made or even could make a mistake, but others will have a different opinion.
It started with a visit to read about an ‘award’ HT published (actually recycled from the Pacific Institute) — the 2010 Climate B.S. of the Year Award. NOTE: BS means Bad Science, apparently. Anyway, you can verify my conversation there if you’ve a mind to hurt yourself.
I left a short note pointing out the hilarity of awarding a prize to four unrelated statements and making a couple of comments. Gareth asked me, as he often does, to apologise for my “smear campaign against NZ climate scientists.”
I sent this response:
Gareth,
You really don’t understand, do you? This is nothing to do with me or any particular scientists. And please don’t pretend that you’re actually offended by my comments about NIWA and its scientists, even they weren’t offended; Renwick and I had several good conversations. They were, I’m sure, annoyed, but I goaded them to get some damned response; they’d been literally ignoring our scientists for years — now tell me you’re comfortable with that discourtesy among scientists!
I’ve been trying to discover the truth about the NZ temperature record. You know the story — or you should, by now.
Of course, you’re standing solidly on the ground prepared for you by NIWA, who themselves continue, at least publicly, to ignore what we’ve actually said. They (and you) rigorously refute the argument that the temperatures have risen, when our argument is about how the temperatures were determined.
We said: “What changes did you make?”
They said (oddly): “You should not claim that adjustments are not required, when everybody knows they are required. For instance, altitude adjustments are required in Wellington.” I challenge anyone to search the latest review and discover altitude adjustments made in Wellington; they were not made in the old series and they are not there in the new. So why did they describe altitude adjustments? Only to criticise the Coalition for apparently not understanding.
We said: “Why did you make the adjustments?”
They said: “The methodology is published, look here and here and here. Replicate the adjustments yourselves.”
We said (after weeks of searching): “The methodology is not contained in those documents. What is described depends so much on operator decisions it’s impossible to replicate Salinger’s adjustments.”
They said: “We told your scientists all this years ago in an email. You know this by now, you’re troublemakers.”
We said: “We’ve found the email. It doesn’t contain what you claim it does. Publish it so everyone can see what it says.” They never did.
They said: “Everything is based on Salinger’s thesis.” But the thesis was locked up in the VUW library so tightly we couldn’t get to it. Eventually, after several months, the library provided a CD we could use for a few weeks. Anyway, the thesis didn’t contain a replicable method. It’s not surprising the ‘method’ was never used anywhere and never published.In short, NIWA’s defence of the old series was relentless, so their decision to replace it with anything at all was a defeat. They finally realised that it was so full of holes that they could not, in science or logic, continue to support it.
That, for a part-time, unpaid group of sceptics, is a victory.
If you disagree, then tell me what happened to the old series? Remember, we were asking them for the so-called “Schedule Of Adjustments” and they had produced one for Hokitika when they announced: “We’re going to produce an entire new series. It will cost $70,000.” Why did they decide that? Why didn’t they just explain the old adjustments? Because they didn’t know what they were! That was a victory for us, because they had maintained through thick and thin not only that they did know, but also that we should know. They haven’t apologised for that.
Whether the graph shows warming or cooling is not relevant; we don’t care what it shows, we just want it to be trustworthy. We’ll examine the science behind it in good time — although it’s not yet complete, as they still must furnish the confidence intervals. And the “peer review” it’s had so far is not worth much when you actually read it. Basically the BoM agree that adjustments are required and NIWA’s evidence “in general” supports them. The BoM say nothing at all about the methods, logic, consistency, etc, mentioned by NIWA’s CEO.
As to the vexed question of ‘smearing’ NZ scientists: that’s the very question being debated, isn’t it? You cannot claim the debate is settled, since NIWA themselves have just capitulated and thrown away the original series, which leaves our original claims, questions and ‘smears’ (as you call them) unanswered — unrefuted. Not only that, they’ve ignored Salinger’s ‘methods’ in producing the new series, abandoning their support of him. They’ve also ignored the ridiculous 11-station series they rustled up, cherry-picking stations that show warming as if to prove that warming occurred (falsely claiming those stations had not moved and required no adjustments). Although the graph was on their web site for many years, they disclaimed it recently as not being an ‘official’ series; nobody believes that, least of all the students who have copied the graph for their projects, or the courts who have had the graph presented to them in evidence.
Of course, we know of a series of seven (famous) unadjusted stations that show no warming, so which set wins? Can you say? No doubt there are a dozen or so stations that need no adjustments that show no warming; I haven’t gone there, since I don’t care about warming or cooling. So, our questions about the original series will remain forever unanswered and our allegations unrefuted; our questions, if any, about the current series are not yet formulated. Nobody knows who is right and who is wrong. Are you competent to pronounce the validity of the new series or the old one? Even the BoM have not gone so far; they claim a complete ‘reanalysis’ would be required.
No apology is possible until these matters are settled. With the production of a new series, our examination begins all over again, but until the error margins are published as NIWA promised, we have to wait, because, as you know, without their estimates of error the series is incomplete — for what can we judge? The science has not been done yet.
Happy New Year.
This is the other comment which was censored at the same time:
diessoli,
Kelburn: all the adjustments are like that, where the target site is adjusted to a reference site. But no adjustments are made by a calculation based on the change in altitude.
Yes, R & H is cited, but not Salinger’s thesis. Not that I’ve seen!
Look, everyone thinks we ought to do our own series, but that’s not what we’re on about. Sure, one of the scientists might have a go one day, but the whole point has been to examine — to peer review — what NIWA has done! But nobody can do a peer review unless the science is all in place. That’s what we’ve been waiting for; now, we start to wait again, because they still haven’t done it all.
[At this point I noticed my longer comment, posted first, had been cut.]
Sorry, that’s all. Gareth’s eviscerated my explanation of why I’m not apologising. You’ll have to read it at www.climateconversation.wordshine.co.nz and you’ll be welcome there.
Tony,
Despite your assurances, Gareth does not run any “open and frank” discussion; he’s just censored my whole comment, calling it “disinformation and lies”, the slithy tove.
I’ll put it up on the CCG site where the air truly is free.
Farewell and
Happy New Year,
Richard Treadgold.
UPDATE 1 5:10 p.m. NZT
RW: Please explain which part of my statements to you is rubbish. Please notice my questions, especially the last three. They’re pertinent to our criticism of NIWA and I am curious as to how you answer them.
Views: 520
We’d better get some nibbles in for the trolls.
Happy New Year everyone!
Ho, ho! Chortle!
Good on you for trying Richard and happy New Year to everyone!
Wahoo!
Hap-py New Year!
By the way, here is a little something from UEA to brighten up the New Year.
http://www.bishop-hill.net/blog/2010/12/31/the-naked-climatologist.html
Note my “which one is the Emperor?” comment
Thanks Andy.
Still working my way around the lake…
A challenge to the Climate Conversation Group, Climate Science Coalition, Hot Topic, Open Parachute and NIWA.
1) Plot a 15 year moving average of the 7SS NZTR composite actual temperatures 1909-2009
http://www.niwa.co.nz/__data/assets/excel_doc/0011/99965/NZT7_Data_FINAL.xls
Excel: Copy the 7SS composite actuals to A1
Tools – Add Ins – Data Analysis – Moving average – A1:A100 to B1
Insert Chart B15:B100
What do you see?
2) De-trend the 7SS actuals for the normal warming since 1850 that the latest science shows to be 0.5 C/100 yr that is accounted for by solar variation and climatological causes or use the IPCC figure of 0.45 C if living in the past is your preference.
Excel:
Create a column 1850 to 2009 (A1) [Start the series 1850 1851 1852 then extend using the bold + bottom right corner of the last entry]
Create a column 0 to 159 (B1) [Use the bold + as before]
Create a column (C1) =0.005*(B1)+13.6 [Use the bold + again to extend to row 160]
Now copy in the 7SS composite actuals from row 59 to 159 (D60)
Calculate the anomaly (E60) =(C60-D60)*-1 and extend to row 160
Plot a 15 yr moving average using the technique in 1).
What do you see?
3) Perform a linear regression on the 15 year moving average de-trended anomaly data.
Excel: Tools – Data Analysis – Regression
For 1923 (E74) to 1953 (E104)
What do you see?
For 1953 (E104) to 1963 (E114)
What do you see?
For 1963 (E114) to 2009 (E160)
What do you see?
—————————————————————————————————————————-
Note: the column:row addresses have not been checked on an actual spreadsheet so you’ll have to check for yourself.
The jump is more likely 1952 to 1962 than 1953 to 1963 but something to check
Should add to 3)
For 2000 (E151) to 2009 (E160)
What do you see?
You’ve got to wonder.
Ken at Open Parachute just cannot comprehend my challenge – he can’t plot the first moving average even after I’ve highlighted the instructions. Maybe third tome lucky.
His guard dog Cedric has a ferocious bark too but hasn’t managed a bite yet.
Guard dog Cedric?
http://thewhitedsepulchre.blogspot.com/2010/03/cedric-katesby-lives.html
Cedric seems prone to hissy fits.
Lot’s of talk ABOUT science but no-comprendo when presented with a column of data.
There’s probably people around (China mostly) that could compute a moving average in their heads and plot it on graph paper with a pencil faster than Ken with Excel.
Richard Treadgold – care to comment on Richard C’s analysis? I am interested in whether you wish to be associated with such naive rubbish.
Can I attribute your organisation’s support to this when I write about it?
Personally I would be extremely embarrassed – but then again you pout out the “Are we getting warmer yet?” press release and that was absolute rubbish. So it might be right up your street.
Hi, Ken,
First, I want to thank you for sticking up for me at HT — although it was a bit ironic, don’t you think, that you should find yourself supporting me? It was the principle you were defending, not me personally, but still, I appreciate your gesture.
As for Richard C’s analysis, I don’t know what to say about it. He hasn’t offered any conclusion that I’ve seen, and neither has anyone else, including your good self, so I haven’t a clue what it means. I haven’t had time to ponder it or discuss it with anyone.
Please explain what you mean by ‘naive rubbish.’
My “association” with anything said on this blog (including your comments!) does not extend either to approval or even mere understanding unless I explicitly say so.
Cheers.
I’d be interested to see a critique of Richard C’s analysis if you have one, Ken. Perhaps we could discuss it here. I haven’t had a chance to look at the data in any detail, other than plotting the pre- and post 1960 trends in Excel.
Andy, there is a bit of a critique from me here: http://openparachute.wordpress.com/2010/12/24/another-local-climate-change-denial-meme/#comment-19744.
Richard Cummings analysis is naive rubbish. meaningless rubbish. He doesn’t understand things like anomalies or the nature of regression and statistical significance. He is just playing around and showing himself to be foolish in the process.
Even Treadgold comments: “As for Richard C’s analysis, I don’t know what to say about it. He hasn’t offered any conclusion that I’ve seen,. . . . I haven’t a clue what it means. “ And we know how low his standards are, don’t we?
Basically Cumming gives no justification for his 15 year averaging, none at all. (It obviously makes the statistical significance look excellent – but that is false (and I don’t think he understands regression or statistical significance).
Cumming offers no justification for subtracting his 0.5 degrees per century. Only a fool would subtract such a global model from regional data. And no excel spreadsheet is required anyway – try calculating 0.9-0.5 and you get an answer, a meaningless one, but an answer.
There are certainly some strange people commenting on this blog and Cumming is one of nthe strangest.
Ken,
An explanation would be more informative. Can you ignore what you want to insult about the man and instead explain why you say the analysis is ‘rubbish’?
My knowledge of statistics is inadequate, that’s all. But my meagre understanding of what Richard C says doesn’t reflect on him, but on me.
Your comments about Richard C’s understanding is speculation. I think what’s relevant and interesting is your analysis of his statements, not the insults you want to fling after you read them. How does the 15-year averaging improve the statistical significance?
This is clear — you disagree with his subtraction of the global warming. But why do you call him a fool and why call it a ‘global model’?
Oh, we’re all strange, Ken. And you’re commenting here, too, aren’t you?
Naive, rubbish, strange..
I have to agree that these are not words i would use in a technical discussion. If it is flawed, then I would appreciate a more direct approach.
“Cumming offers no justification for subtracting his 0.5 degrees per century.”
Point 2) of the challenge is “no justification”?
2) De-trend the 7SS actuals for the normal warming since 1850 that the latest science shows to be 0.5 C/100 yr that is accounted for by solar variation and climatological causes
“Basically Cumming gives no justification for his 15 year averaging, none at all”
None is required. A moving average is rudimentary data smoothing i.e. a tool to aid data analysis. That’s why MS provide “Moving Average” under “Tools” “Data Analysis”. If you want to use an alternative data smoothing technique – fine, tell us about it.
“He doesn’t understand things like anomalies or the nature of regression and statistical significance.”
NZQA disagree, besides, what is significant about 0.9 C warming 1909-2009 if an abrupt 0.4 rise occurred within the space of one decade (1952-1962) and 0.5 of the 0.9 is normal climate?
Then there’s the possibilities of the early years being pulled down (still not resolved) and UHI. Not much room for post 1977 anthropogenic warming due to fossil fuel emissions is there?
Notice that Cumming refuses to face up to the criticism that he is trying to subtract a global model (0.5 degree/century) from regional data. No justification for this. Only a fool would seriously do this.
Come on Richard Cumming – respond to this criticism properly. Why “correct” regional data using a global model?
As for data smoothing – what possible use is it apart from presentation? It interferes with statistical analysis. Again attempts at regression after such smoothing are naive in the extreme. The honest way to show a trend is to regress the original data and show the line – together with its statistical significance. This is what I did in Another local climate change denial meme
There is no honest need to smooth data – apply the regression to the original data. Why do you refuse to do that?
The temp increase in 1940 – 1960 is discussed by NIWA in terms of regional effects (eg winds). There is a regional reason for the regional effect.
As for your appreciation of statistics – come on. You provided a regression trend for 1999-2009 – no indication of statistical significance at all (it wasn’t significant). That is either ignorance or dishonesty.
“no indication of statistical significance”
English comprehension is not your strong suit, is it Ken?
1) What is your understanding of the phrase “just for fun”? Used both here at CCG and at OP.
2) What is your understanding of the word “unadjusted”? Used both here and OP.
“As for data smoothing – what possible use is it apart from presentation?”
You will never know will you unless you use it, will you? (BTW, how’s that moving average coming along? Cracked it yet?)
“Why do you refuse to do that?”
I don’t refuse and have done so in appropriate cases.
“Why “correct” regional data using a global model?”
“mean atmospheric warming in New Zealand over the last 100 years matches worldwide trends” – NIWA
http://www.niwa.co.nz/news-and-publications/publications/all/wa/9-4/world
So Clearly Richard you are not convinced by Cumming’s little fiasco, either.
Anyone else want to put their 2 cents worth in?
Now Richard – tel me what you think Cumming’s “motives” are for this little exercise.?
You asked me to concentrate on the topic and so far i am the only one to actually comment on Cumming’s little challenge – no one else seems to understand what he has done.
Richard – look at the IPCC figures (unfortunately it doesn’t seem possible to get them to show in your comments). You will see the huge disparity over the last 50 years indicating the impossibility of explaining temperature increases in that period simply by natural factors. (Human influence need to be included to get a reasonable fit). That is the elephant in the room you refuse to face up to and talking about the acknowledged lack of precision in aerosol effects is simply an attempt at diversion.
Richard Cumming, your use of the quote from NIWA is disingenuous. It refers to the fact that the warming trend over 100 years is similar to the global trend. Don’t forget there is a huge range involved. Regional data is never expected to be smooth.
But regional data includes regional trends and regional variability. This makes any point by point subtraction of global data foolish. The fact that you continue to deny the problem indicates a fundamental lack of understanding on your part.
“You will see the huge disparity over the last 50 years indicating the impossibility of explaining temperature increases in that period simply by natural factors.”
Yes, especially when the those natural factors are so inadequately modeled (TSI only).
Richard Cumming – you are away with the birds to say:
“Yes, especially when the those natural factors are so inadequately modeled (TSI only).”
How come the modeling worked extremely well until 50 years ago??
And this is just an outright lie:
“I should point out too, that the 7SS has already had smoothing applied by NIWA.” If you don’t provide evidence for you mistaken claim I will assume you acknowledge that.
No smoothing is required – and certainly it is incorrect to statistically analyse smoothed data.
Your deduction of a global model from regional data was completely unwarranted. A simple reading of NIWA’s report will show you missed huge natural but regional effects.
All you have done is the simple sum 0.9-0.5=0.4 – but have fooled yourself with an unnecessary and incorrect spreadsheet. And the result is meaningless anyway.
“How come the modeling worked extremely well until 50 years ago??”
But it didn’t did it, especially the 1940s warm trend and it it hasn’t done so well the last decade either. Plus if you look at the AR4 table of forcings you will discover that Natural Category contains TSI only
“If you don’t provide evidence for you mistaken claim”
The 7SS is averages of the means of each years data (smoothing) and it also NOT the “original data” – that’s raw data.
“No smoothing is required – and certainly it is incorrect to statistically analyse smoothed data.”
See “On the trend, detrending, and variability of nonlinear and nonstationary time series”
Wu, Norden, Huang, Steven, Long, and Peng, 2007
Proceedings of National Academy of Sciences
https://www.climateconversation.org.nz/2011/01/rotted-minds-at-hot-topic/#comment-35071
Ken,
You have no evidence for that. I have said only that I don’t understand it and have not had time to ponder or discuss it.
I have no evidence for that.
Well done, Ken.
What do you mean?
I presume you refer to the “disparity” between a set of computer-modelled temperatures and a set of observed temperatures. I guess it’s only impossible to explain the (imagined) “disparity” by including the natural factors we know of and can measure. But variations in cloud cover, for example, could easily account for the temperatures, but we don’t know what they were.
No, but when the modellers include some factors estimated to approximate a possible human influence, they get a reasonable fit. They are limited to guessing what the likely human factors were and their magnitude and they get no fit at all from first principles, because they don’t know them all.
There, I’ve faced it. You say it was a diversion attempt; you have no evidence for that. What do you mean, “the lack of precision”? That’s too gentle. What I actually said was that the IPCC (or the paper/s they relied upon) blatantly overstated the effects and their magnitude! They are grasping at straws there, my man.
Richard – you obviously have not looked ast the IPCC figures – otherwise you wouldn’t say:
“I presume you refer to the “disparity” between a set of computer-modeled temperatures and a set of observed temperatures. I guess it’s only impossible to explain the (imagined) “disparity” by including the natural factors we know of and can measure. But variations in cloud cover, for example, could easily account for the temperatures, but we don’t know what they were.”
It is possible to obtain a good fit of actual temperatures to a whole range of models. However, only if human influences are included. When they aren’t there is a huge discrepancy over the last 50 years. Natural influences can’t explain this by themselves.
Go and look at the figures. I provided a link in my comment – of go to Climate change is complex
I should point out too, that the 7SS has already had smoothing applied by NIWA.
“The honest way to show a trend is to regress the original data”
Couldn’t agree more.
“original data” trend +0.3 C/century.
Subtracting 0.5 C/century normal climate yields -0.2 C of unequivocal cooling.
It’s worse than we thought.
The “original data” trend +0.3 C/century.was for the 7SS unadjusted by NiWA but it is still smoothed to annual means. Is there a link to the unsmoothed 7SS raw data anyone?
The raw data from the original New Zealand temperature readings has a trend +0.06°C per century since 1850.
Subtracting 0.5 C/century normal climate yields -0.44 C of unequivocal cooling.
A step change in Earth’s Climate outlook
Meanwhile, Dr. Syun-Ichi Akasofu of the University of Alaska has published a paper in Natural Science saying that since 1850 the earth has been recovering from the Little Ice Age—and that this natural recovery is still continuing at about 0.5 degree per century. Ice cores and seabed sediments show this moderate, natural 1,500-year cycle has been occurring for the last million years. The Modern Warming is likely to be about as warm eventually as the Medieval Warming that blessed the earth with sunny growing seasons from 950–1300 AD.
At the same time, however, Dr. Akasofu has identified a 50–60 year sub-cycle driven by Pacific Ocean temperatures, which shifted to cool in 1940, to warm in 1976, and back to cool again as of 2000. He is predicting another 20 years of modest cooling for earth before the longer warming trend reasserts itself.
http://climatechangedispatch.com/home/8396-a-step-change-in-earths-climate-outlook
Akasofu’s 2010 paper seems to be gaining traction.
Leon Clifford: Global warming may be less than IPCC predicts
[See graphic (becoming iconic hopefully)]
Physicist and Arctic research expert Syun-Ichi Akasofu of the International Arctic Research Center at the University of Alaska Fairbanks in the US predicts that the temperature in 2100 will be 0.5C ± 0.2C higher than today, rather than the 4.0C± 2.0C predicted by the IPCC.
http://climaterealists.com/index.php
Full paper here
“On the recovery from the Little Ice Age”, Akasofu 2010
http://www.scirp.org/Journal/PaperInformation.aspx?paperID=3217&JournalID=69#abstract
Studiously ignored in some quarters obviously
The Climate Realists link to the Akasofu articke should be
http://climaterealists.com/index.php?id=6944
CLIMATIC FLUCTUATIONS SINCE THE LITTLE ICE AGE—SHORT-TERM CLIMATE CYCLES
Prof Don Easterbrook
The global climate has warmed progressively since the LIA, but not at a constant rate. Oscillations between warm and cool periods have occurred in a fairly regular fashion about every 25-35 years (Figure 7). Global temperatures have risen about 1° F per century since the cooling of the Little Ice Age, but the warming has not been continuous. Numerous ~30 year warming periods have been interspersed with ~30 year cooling periods (Figure 7). However, each warming period has been slightly warmer than the preceding one and cool period has not been quite as cool as the previous one. For example, the present warm period (1977–2007) is slightly warmer than the 1920–1950 warm period, and the 1947–1977 cool cycle (Figure 1) is not quite as cool as the ~1880–1910 cool period.
http://myweb.wwu.edu/dbunny/research/global/glacialfluc.pdf
[1 F = 0.56 C]
“On the recovery from the Little Ice Age”, Akasofu 2010 is a one stop for de-bunking the following CAGW scary stories:-
Temperature rise
Sea level rise
Sea ice extent
Glacier retreat
CO2 influence on temperature
The paper establishes a normal rate of global temperature rise since 1650 of 0.5 C/century.
Speculates on the possibility that solar and cosmic ray influences are the major climate change causes.
Suggests that the warming has halted since 2000 due to multi-decadal change and predicts that temperatures will be flat or declining for the next 30 years or so.
Figure 9 is the most compelling visual summary, highlighting the IPCC’s bizarre assumption and prediction.
http://www.scirp.org/Journal/PaperInformation.aspx?paperID=3217&JournalID=69#abstract
Judging by this attribution Renowden is part of the “team” now.
“The 2010 Climate Bad Science (B.S.) Detection and Correction Team
Peter Gleick, Kevin Trenberth, Tenney Naumer, Michael Ashley, Lou Grinzo, Gareth Renowden, Paul Douglas, Jan W. Dash, Ove Hoegh-Guldberg, Brian Angliss, Joe Romm, Peter Sinclair, Michael Tobis, Gavin Schmidt, John Cook, plus several anonymous nominators, reviewers, and voters.
[* “B.S.” means “Bad Science” doesn’t it?]”
His censorship on HT is hardly surprising as I doubt he would want to be embarrassed by sceptics making a fool of him in front of his new friends.
His position will get even more obdurate now. I very much doubt he looks at new information any more. In his world, despite evidence to the contrary, the ice is ALL going to melt and their dire predictions will come true.
Strange really, I find it odd anyone would consider a model showing a hypothesis as evidence.
Still, nature will keep proving them wrong and we are seeing more research on feedbacks.
I think that 2010 was a tipping point in public opinion against AGW. I’d wager that this year we see a major government or two be vocal in detailing the hypothesis on AGW and exposing the lack of evidence over positive feedbacks and hence the lack of “predicted” extra warming (which hasnt arrived…).
People are starting to see through how they use language and especially omission to deceive and suppress an accurate representation of the facts.
Pointman has a good way of putting how the worm will turn in the internet age.
http://thepointman.wordpress.com/2010/12/21/the-msm-and-climate-alarmism/
Nice article by Pointman
The latest from EURef has some good links
http://eureferendum.blogspot.com/2011/01/happy-new-year.html
especially this one on CDM
The Lucrative Business of Polluting
Will Trading System Encourage Emissions?
http://www.spiegel.de/international/business/0,1518,736801,00.html
Brilliant article Richard – thanks.
“At the end of the day, there will be one big winner and two big losers. The big winner is of course the Internet. Without the aid of a single organ of the MSM, it slowly but surely tyre-levered this story out to Joe Public, despite the MSM’s efforts to ignore or poo hoo it. That is a unique event. A precedent and the shape of things to come. MSM take note.
The big losers are science and the MSM….”
Tell those head in the sands at Hottopic that there is going to be a mini iceage and its starting now. Several geologists are along this line.. Coldest winter in UK for 1000YEARS! (iceagenow)
Emissions are totally irrelevant.
A well-composed and level-headed response, RT. For HT to censor that is unbelievable. You said nothing ad-hom or insulting. Clearly he has no reply to the logical and sound arguments you propound.
Here is a new paper highlighted by Anthony Watts absence of correlation between temperature changes … and CO2 which will no doubt annoy the Team. Muahaha!
Happy New Year!!
HT are a lost cause, and they’ll get no further help from me.
Nice little paper, Mike, thanks. You have a great year.
Warwick Hughes has been reading Report on the Review of NIWA’s “Seven-Station” Temperature Series and has a short post http://www.warwickhughes.com/blog/?p=753#comments
with links to earlier posts and GISS graphics illustrating UHI history and influence on temperature data
You might like to leave a comment on his site or alternatively RichardT ask him to do a guest post for you
Val, that’s timely.
I’ve asked Warwick to comment on my challenge and whether it could be applied to the Australian record.
Also that the residual warming after de-trending the 7SS might be UHI.
My provocative language is an attempt to get a reaction from Cumming. I have made technical criticisms which he ignores. – in a manner suggesting he neither understands what he has done or what my criticisms mean.
No one else here seems prepared to hazard a guess at what he has done. He doesn’t porovide any justifications or conclusions. What does one do?
Does anyone else agree with Cumming’s 15 year averaging of data followed by regression analysis? (Richard Treadgo’d – averaging reduces variability which helps presentation but gives a false idea of statistical significance – it also includes data from outside the range used for the regression. It is more honest, and correct to use the original data. Any statistics he gets from the averaged data is meaningless – especially its statistical significance.
Does anyone else agree here with Cummings subtraction of 0.5 degree/century (determined from global data – therefore a global model. He is using it to “adjust” regional data. It is naive in the extreme to think that can correct for local, regional, natural effects. Naive in the extreme. What do you say?
Incidentally a valid “correction” using models of natural temperature effec ts is described in my post Climate change is complex. This is from the IPCC, it uses global – not regional – data and shows that natural facxtors are unable to explain temperature changes over the last 50 years.
For example the figure below shows the results of simulations of global temperature from 1900 to 2005. Figure a included all the natural and anthropogenic influences. The black line is the actual measured global temperature anomaly (obtained by subtracting the average temperature for 1901 to 1950). The individual simulations are shown as thin yellow curves. The red line is the multi-model ensemble mean (see Figure 9.5 – AR4 WGI Chapter 9: Understanding and Attributing Climate Change).
Figure b is a similar plot using simulations which consider only the natural influences on climate. The individual simulations are shown as thin blue curves. The thick blue line is the multi-model ensemble mean.
So, climate scientist have considered both natural and anthropogenic influences. And they are unable to reproduce the global temperature changes since 1970 unless anthropogenic influences are included.
That is why the IPCC has concluded that there is a high probability (>90%) that human influences are contributing to the current observed global temperature increase.
Also – have a look at Gareth’s spoof NZ cooling since 1909!. Effectively this is what Cumming seems to be trying to do – although as he won’t explain its hard to tell. But Cummin’gs analysis is even funnier.
“shows that natural facxtors are unable to explain temperature changes over the last 50 years.”
This has been de-bunked all over the world – including Open Parachute.
See here a reply to the rest of your points.
https://www.climateconversation.org.nz/2011/01/rotted-minds-at-hot-topic/#comment-34928
What you are really disputing is not my application of a trend but the scientific findings that 0.5 C/100 yr is normal climate since 1850. Those papers are not going to go away.
Thanks, that’s clear. If it’s true that he doesn’t understand, then that will emerge. What more could you want?
What’s the huge problem? If he doesn’t answer you adequately you point that out.
Thanks, I can follow that.
Yes, I see.
Considering the controversy over the cause/s of the 1945-1965 cooling period, especially the likelihood that both the magnitude and the cooling effects of man-made aerosols have been overstated by the IPCC, this is a highly contentious conclusion. It is more likely that natural factors were at work here and we simply don’t know what they were.
You should know that to say it must be ‘x’ because we don’t know what else it could be is argumentum ad ignorantiam.
Yes, I already read that; it’s funny.
So you say.
I see you’ve sent another comment in, thanks. Look, just a tip, Ken, for what it’s worth: tone down the language, concentrate on the topic. You just get people’s backs up. The conversation is just as interesting, since we’re all here because we’re interested in the topic, but there’s less emotional distraction and everyone can concentrate on examining the real issues.
I guess I’m saying: let’s pretend everyone here is a friend, trust their motives and talk freely about the topic. You can still debate vigorously, (“that notion is nonsense!”) but remove the personal aggravations.
Cheers.
The moving average has validity in the context of filtering high frequency signal from the dataset.
From Wikipedia:
Mathematically, a moving average is a type of convolution and so it is also similar to the low-pass filter used in signal processing.
http://en.wikipedia.org/wiki/Moving_average
From my time working as a geophysicist in the oil business, I know that there is a lot of this filtering required to tease out various signals. A lot of the time, an eyeball approach is used in data interpretation.
“The threshold between short-term and long-term”
15 is probably not the interval threshold for the 7SS. I just went 5,no,10,no,15,yes.
I’ll have look to see if I can identify a better smoothing interval between 10 and 15 although 15 seems fine.
I’d now like to run the 7SS raw data through similar smoothing to see what that throws up.
Links anyone?
14 is the threshold, much better than 13 through my eyes but 15 will do meantime.
here’s a timely article
http://www.quadrant.org.au/blogs/doomed-planet/2011/01/who-are-the-climate-denialists-now
(a couple of paras)
Although the climate change bandwagon may appear to roll on unstoppably regardless of all doubts or discredit, it has in fact suffered a serious loss of momentum in public acceptance. It has lost power and is now only coasting while trying to maintain a face saving facade for those so deeply committed that any graceful retreat is unthinkable.
Worse still from the alarmist perspective, has been the painfully obvious failure of climate itself to cooperate. For the past three years all over the world savagely cold winter weather has repeatedly set new records for snow and low temperatures. Time after time global warming conferences have been greeted by record and near record cold weather. Trying to dismiss this as merely coincidence or just weather, not climate, has lost all credibility; especially after it has happened repeatedly amidst a background of extreme winter conditions over large areas. Continuing to offer this increasingly lame excuse has only made it look more like a lie or delusion than an explanation.
Regardless of the ongoing hype and spin of the diehard proponents of AGW, the attitude of a large majority of the electorate has turned decisively against the idea of any imminent threat. This shift in sentiment is unlikely to reverse anytime soon. It developed over time and involves not just the Climategate emails but a much wider shift in the balance of public awareness as well as a sense of betrayal and dishonesty by researchers claiming certainty and righteousness. Fool me once, shame on you. Fool me twice, shame on me. Once a belief is abandoned, few people readily return to something they have decided was false. All the spin and hype is now achieving is to exacerbate the discredit. For supposedly intelligent people, this kind of behaviour does not indicate it.
Meanwhile, as the warmists continue their doomscrying and seeking further hundreds of billions of dollars to carry on their vast charade, the whole economic structure upon which everything depends is teetering on the brink of disaster with little effort to address or to even recognise the very real and present dangers which confront us.
It’s such a cold December: 2010 ends on a chilly note where people live
Dr. Ryan N. Maue
http://wattsupwiththat.com/2011/01/03/its-such-a-cold-december-2010-ends-on-a-chilly-note-where-people-live/#more-30811
conclusion
We are talking hundredths here? Really?
It’s a foregone conclusion that the official government data from whatever nation or agency will show that 2010 was the hottest year ever. It just has to be that way — please don’t look at that snow burying NYC or the bone-chilling historical cold throughout the UK and Europe, that’s just the weather. Instead, look at the articulate press releases with the bubble-plots from NOAA/NASA to see the real story of 2010, the hottest year ever by a few hundredths of a degree C. Yes, we are talking about hundredths and tenths of a degree during the past 10 to 30 years– that’s all. The Earth’s temperature varies a lot, from hour to hour, day to day, season to season, year to year for a bunch of reasons of which the sun is order 1, but even through all of that, you must know that the global temperature has changed only on the order of a 1-3 percent during the past 30-years. And, it isn’t a spatially homogeneous change, either. Not even close. AGW is built upon the premise of a slow, very slow upward trend that will eventually accelerate. But, that’s a long ways off — today, we are talking about hundredths of a degree C. How many trillions of dollars is that worth to you?
On the trend, detrending, and variability of nonlinear and nonstationary time series.
Wu, Norden, Huang, Steven, Long, and Peng, 2007
Proceedings of National Academy of Sciences
A Definition of Trend
Extrinsic and Predetermined Trends. The most commonly seen trend is the simple trend, which is a straight line fitted to the data, and the most common detrending process usually consists of removing a straight line best fit, yielding a zero-mean residue. Such a trend may suit well in a purely linear and stationary world. However, the approach may be illogical and physically meaningless for real-world applications such as in climatic data analyses. In these studies, the trend often is the most important quantity sought (3), and the linearly fitted trend makes little sense, for the underlying mechanism is likely to be nonlinear and nonstationary.
Another commonly used trend is the one taken as the result of a moving mean of the data. A moving mean requires a predetermined time scale so as to carry out the mean operation. The predetermined time scale has little rational basis, for in nonstationary processes the local time scale is unknown a priori.
More complicated trend extraction methods, such as regression analysis or Fourier-based filtering, also are often based on stationarity and linearity assumptions; therefore, one will face a similar difficulty in justifying their usage. Even in the case in which the trend calculated from a nonlinear regression happens to fit the data well fortuitously, there still is no justification in selecting a time-independent regression formula and applying it globally for nonstationary processes. In general, various curve fits with a priori determined functional forms are subjective, and there is no foundation to support any contention that the underlying mechanisms should follow the selected simplistic, or even sophistic, functional forms, except for the cases in which physical processes are completely known.
Conclusions
In this article, we proposed a definition for trend of nonstationary
nonlinear data, which in turn made it possible to perform a detrending operation on the data and to determine the variability about the trend line. The key to making this definition of trend feasible is the realization that the trend is one of the many local properties of the data; therefore, it has to be associated with a time scale. Without reference to a time scale, the trend will be confusingly mingled with local cycles. Other general methods such as least-squares or maximum likelihood fits might fit the data well, but they are extrinsic. Although some of the extrinsic functions used in fitting data, such as exponential, power law, and hyperbolic baselines, are nonlinear models, there is no guarantee that the externally determined nonlinearity characteristics correspond to those embedded in the mechanisms generating the data.
As most of the underlying mechanisms of either natural or human-induced variability are only incompletely known, it is almost impossible to decide which of the myriad functions to choose so as to render the best extrinsically determined trend. Therefore, to have a meaningful trend, the method has to be adaptive (so as to let nature speak for itself). The EMD method fits these requirements well. This work has demonstrated an application of the present approach to annual GSTA. It has been shown that this approach not only defines the trend but also reveals some intriguing intrinsic properties of the data. Experience with various real-world data indicates that the variance of the detrended data with respect to any known extrinsically determined trend is larger than that corresponding to the intrinsically fitted variance. However, a rigorous proof of this statement still is under investigation.
http://rcada.ncu.edu.tw/reference008.pdf
Richard C,
You were right, those other comments were caught by the spam filter. I’ve removed them and reinstated this first attempt. Does this cover what you wanted?
Why it should suddenly catch short comments with a single link I don’t know.
Yes, perfect. I’ve logged out, come back in again, hit F5 but the other comments are still there (I’ll refresh a few times to check)
This paper advocates Empirical Mode Decomposition (EMD) for climate data.
i.e. Out
Straight line best fit
Moving mean
Linear regression
Nonlinear regression
Fourier filtering
In
Empirical mode decomposition
—————————————————————————————————————————-
See “Climate Science’s Dirtiest Secret”
“With the climate science party-line case for global warming rapidly unwinding there is growing interest by researchers from outside the climate change community in applying advanced statistical techniques to climate data. It has long been recognized that statistical acumen is lacking among mainstream climate scientists. This dirty little secret was first publicly disclosed during Congressional hearings regarding the 2006 Wegman Report. Even newer analyses have revealed that many of the predictions made by the IPCC reports and other global warming boosters are wrong, often because inappropriate statistical techniques were applied”
[Snip]
Empirical Mode Decomposition
[Snip]
In 2007, Zhaohua Wu et al. published a paper on the use of EMD to illustrate the determination of the intrinsic trend and natural variability in climate data (see PNAS “On the Trend, Detrending, and Variability of Nonlinear and Nonstationary Time Series”). In their paper they explain the complexities of analyzing climate related data:
[Snip]
The assertion that simplistic analysis (that is a very relative term here) will not work unless the underlying physical processes are completely understood is a warning to all those who attempt to relate trends in climate with trends in other physical phenomena. Wu et al. extracted linear and multidecadal trend data for a set of temperature data using EMD. The data used were the annual global surface temperature anomalies analyzed by Jones et al. and posted at the web site of the Climate Research Unit, University of East Anglia, UK
[Snip]
Breaking down the underlying signals in the temperature data yields an interesting statistical explanation for the anomalous temperature increases in the 1990s: “The extreme temperature records in the 1990s stand out mainly because the general global warming trend over the whole data length coincides with the warming phase of the 65-year cycle.” Here are the major conclusions from the paper:
* The linear trend gives a warming value of 0.5°C per century.
* The overall adaptive trend was close to no warming in the mid-19th century and is ≈0.8°C per century currently.
* The multidecadal trend rate of change is much larger than the overall adaptive trend but oscillates between warming and cooling.
* The higher frequency part of the record in recent years is not more variable than that in the 1800s.
From these analyses the predicted temperature rise by 2100, assuming the current trends continue, would only be 0.8°C, significantly less than even the low-end IPCC predictions. This is in fairly close agreement with the statistical break analysis previously reported. From the figure above is would appear that the long-term trend rate of increase has flattened out while the multidecadal trend, which peaked in 1998, is headed downward and is expected to drive the overall temperature trend into cooling. If the current trend is maintained, the peak of the cooling period will be around 2030, followed by a warming trend that will peak around 2060. As with all non-stationary data, the underlying system may change and the future trends vary in unpredictable ways.
One of the most interesting things they found was that the time scale of the multidecadal trend was not constant, but varied from 50 to 80 years with a mean value slightly higher than 65 years. “Significantly, other than the familiar overall global warming trend, the 65-year cycle really stands out,” state the authors. “The origin of this 65-year time scale is not completely clear because there is no known external force that varies with such a time scale.” Remember, all of this is strictly from analyzing historical data. It is in no way calculated from the underlying mechanisms that cause Earth’s climate to change, as GCM attempt to do.
http://www.theresilientearth.com/?q=content/climate-sciences-dirtiest-secret
—————————————————————————————————————————–
Really looking forward to applying EMD to the 7SS in view of all that.
Empirical Mode Decomposition for Determining Intrinsic Climate Trend – Google search
http://www.google.co.nz/#sclient=psy&hl=en&safe=off&q=Empirical+Mode+Decomposition+for+Determining+Intrinsic+Climate+Trend&aq=&aqi=&aql=&oq=&gs_rfai=&pbx=1&fp=28f6b3b14a1a140e
Turns up plenty of links to climate applications
EMD code here. Under Windows, the binary runs directly without installation (haven’t tried it yet).
http://sidstation.loudet.org/emd-en.xhtml
EMD flow chart here
Analysis of Temperature Change under Global Warming Impact using Empirical Mode Decomposition
Md. Khademul Islam Molla, Akimasa Sumi and M. Sayedur Rahman, 2007
http://www.waset.org/journals/ijice/v3/v3-6-59.pdf
ALL VISITORS:
12:39 NZT.
Please refresh your display (press F5) because I’ve just deleted and reinstated a number of comments on this thread.
Richard Treadgold.
For Hottopic
A report in the December 3, 2010, issue of Science has reinforced what many scientists have suspected all along: variation in the Sun’s output causes significant change in Earth’s climate…..This new work indicates that even small variations in the Sun’s output can have significant affect here on Earth. This is unsurprising, since the energy that drives Earth’s climate comes from the Sun. Monsoon floods and decades long droughts are both part of the natural variation driven by our neighborhood star, but every climate fluctuation that causes human discomfort is blamed on anthropogenic global warming…..Their [Marchitto et al.] work is in agreement with the theoretical “ocean dynamical thermostat” response of ENSO to radiative forcing. Here is their description of the work: The influence of solar variability on Earth’s climate over centennial to millennial time scales is the subject of considerable debate. The change in total solar irradiance over recent 11-year sunspot cycles amounts to <0.1%, but greater changes at ultraviolet wavelengths may have substantial impacts on stratospheric ozone concentrations, thereby altering both stratospheric and tropospheric circulation patterns…..This model prediction is supported by paleoclimatic proxy reconstructions over the past millennium. In contrast, fully coupled general circulation models (GCMs) [IPCC climate models] lack a robust thermostat response because of an opposing tendency for the atmospheric circulation itself to strengthen under reduced radiative forcing." [Thomas M. Marchitto, Raimund Muscheler, Joseph D. Ortiz, Jose D. Carriquiry, Alexander van Geen 2010; Science 3 December 2010: Vol. 330 no. 6009 pp. 1378-1381]
cest la vie
Solar scientists (including Lockwood and Frolich) have been taken to task at WUWT
http://wattsupwiththat.com/2011/01/02/do-solar-scientists-still-think-that-recent-warming-is-too-large-to-explain-by-solar-activity/
“That’s the big update that all of our solar scientists need to make. They need to stop tolerating this crazy charade that allows the CO2 alarmists to ignore the impact of decades of grand maximum solar activity and misattribute the resulting warming to fossil fuel burning. It is a scientific fraud of the most disastrous proportions, giving the eco-lunatics the excuse they need to unplug the modern world.”
Ouch.
“Kelburn: all the adjustments are like that, where the target site is adjusted to a reference site.”
Yes. That’s how you homogenise a timeseries.
“But no adjustments are made by a calculation based on the change in altitude.”
Because that’s not how you do it – and Niwa have not done it like that. The temperature difference caused by the lapse rate is an explanation for why the Kelburn site is cooler, but also serves to make the difference plausible. If the difference would have been, say, much smaller than what you expect from the lapse rate it would have raised a red flag and required more detailed research why that might be the case.
The latest report does actually mention this:
“The monthly mean temperature at Thorndon (Site 5) in December 1927 was 14.7 °C, while at Kelburn (Site 6) it was 13.7 °C, a difference which is close to that which would be expected for sites with an elevation difference of 122 m.”
“Yes, R & H is cited, but not Salinger’s thesis. Not that I’ve seen!”
Than look at page 4 and the references on page 12.
And even if they would not have cited his 1981 thesis, that does not mean that “[…][NIWA] ignored Salinger’s ‘methods’ in producing the new series, abandoning their support of him.”
First R&S (not R&H) is based on his what was developed in Salinger’s thesis, secondly: Science has moved on in the last 30 years and if there are better homogenisation methods available now, they will of course be used.
BTW. why did you put methods in quotes in your comment?
I totally disagree that “the science has not been done”. If you don’t want to create your own series, fair enough, but there are 169 pages with references that document how the temperature record has been created and what adjustments where made. There is more than enough that you can peer review. The descriptions of how uncertainties are measured can be reviewed separately.
D.