the Air Vent

Because the world needs another opinion

Experts or little white lies?

Posted by Jeff Id on June 11, 2011

UPDATE, It appears that my post uses data published yet not recommended by Phil Jones.   Perhaps a retraction by Dr. Jones  is in order or is it as Lucia points out in her post, a case of white noise.

Douglas J. Keenan 

in comments below notes:

Here is a quote from that: “global and regional time-series should be calculated using unadjusted data”. Indeed, the authors have criticized others for attempting to use HadCRUT3v for time series. Note that Jones is one of the authors.

Here is the full quote:

Whether variance adjusted or unadjusted data should be used in an analysis depends on what is to be calculated. If it is necessary that  grid-box anomalies have a spatially and temporally consistent variance, then variance adjusted data should be used. Otherwise, better results may be obtained using unadjusted data.  In particular, global and regional time-series should be calculated using unadjusted data.

The barely significant adjusted data should NOT be used for trend analysis per Dr. Jones himself.  Will climate wonders never cease.

————————-

Phil Jones made a few famous quotes around the time of climategate.  One of them was brought up again in a happy correction to the record as reported by the BBC on June 10th.  Lucia covered it here already.  Back a year and a half ago, Phil let slip in an unusually difficult interview for a climate scientist that there was no statistically significant warming since 1995.

B – Do you agree that from 1995 to the present there has been no statistically-significant global warming

Yes, but only just. I also calculated the trend for the period 1995 to 2009. This trend (0.12C per decade) is positive, but not significant at the 95% significance level. The positive trend is quite close to the significance level. Achieving statistical significance in scientific terms is much more likely for longer periods, and much less likely for shorter periods.

This refers to the arbitrary yet regularly used 95% threshold or 1/20 chance that the result happened by accident alone.  Now in a new article Phil reports this:

Climate warming since 1995 is now statistically significant, according to Phil Jones, the UK scientist targeted in the “ClimateGate” affair.

Yay!!  We all knew it was coming, because as the data record grows longer even in a temperature stable world, statistical thresholds are naturally crossed.  The Earth would have to cool quickly in order to prevent this threshold from being crossed.  We discussed the issue in 2009 here, just days prior to climategate.

Lucia took the annual averages and corrected she for AR1 (autocorrelation), she found that the claim by Jones was still invalid.  Well, that caught my interest so I looked more closely at the data and wrote a downloader for the monthly HADCRUT3 and HADCRUT3V data in R.  I then dug up some old algorithms and did some of my own plots.  HADCRUT3 is a simple gridded version of the temperature data where anomalies are combined by grid and averaged.  HADCRUT3V has some sort of variance adjustment as described by Jones 2001, which ‘corrects’ the variance.  I have not read or looked for the paper and so cannnot comment on its veracity.

I made the following plot using the code below.  This uses all the available data, calculates a trend and a confidence interval for that trend based on the Quenouille AR1 degrees of freedom correction.  Nothing too magical about that. The red lines are the +/- confidence interval, the black line is the slope of the data in C/Decade for each month to the most recent month.  In other words, I fit a slope for the data from every month in history starting with 1980 January to present,, 1980 February to present, March etc, all the way until 2008 because a slope for three years of global temperatures is silly.

It looks from this plot that Phil Jones called it right at  the crossing point.  The first moment that the data showed significance for 1995, he held a press conference (or at least a phone call/email) to correct the record and proclaimed, the temperature trend from 1995 to present is significant!!

Look how closely he called it.

The black ‘slope’ line just peaks over the top of the red line for under half of 1995.  Since we are in June of 2011 we can still say 16 years with no significant trend, but the silliness of the thing is what this post is about.  I don’t have the data for  last months ‘variance’ adjusted version and can’t recreate it because of this quote on the HADCRUT temperature page:

All the files on this page (except Absolute) will be updated on a monthly basis to include the latest month within about four weeks of its completion. Updating includes not just data for the last month but the addition of any late reports for up to approximately the last two years. In addition to this the method of variance adjustment (used for CRUTEM3v and HadCRUT3v) works on the anomalous temperatures relative to the underlying trend on an approximate 30-year timescale. Estimating this trend requires estimation of grid-box temperatures for years before the start of each record and after the end. With the addition of subsequent years, the underlying trend will alter slightly, changing the variance-adjusted values. Effects will be greatest on the last year of the record, but an influence can be evident for the last three to four years. Full details of the variance adjustment procedure are given in Jones et al. (2001). Approximately yearly, the optimally averaged values will also be updated to take account of such additional past information

Now there is nothing nefarious about the statement here, but it does leave one curious if this months adjustments are what pushed 1995 over the line.  I also processed the unadjusted gridded data presented on exactly the same page and found a different result.

Woah!! So close, no cigar.

Good try though.  Maybe next year.  I wonder why Phil didn’t mention this dataset hadn’t quite made the line yet?  It is from his webpage after all.

Now from the climategate emials, can you imagine the pressure Phil Jones experienced from his colleagues when he let slip that trends since 1995 weren’t significant?   We already knew that but the admission must have cost him something because look how quickly he came out with the correction, and look how quickly the press covered it.

A college professor from a long time ago said:

An expert is just a drip under pressure.

You wonder why people question the experts.


loc="http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3gl.txt"
#loc="http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3vgl.txt"

wd=c(5,7,7,7,7,7,7,7,7,7,7,7,7,7)
hadc=read.fwf(loc,skip=0,widths=wd)
mask=rep(FALSE,324)
mask[seq(1,324, 2)]=TRUE
hh= t(hadc[mask,2:13])
dim(hh)=c(162*12,1)
maskb= hh!=0
hh=hh[maskb]

hadcrut=ts(hh,start=1850,deltat=1/12)

plot(hadcrut)

plot(window(hadcrut,start=1995))
mm=lsfit(time(window(hadcrut,start=1995)),window(hadcrut,start=1995))
abline(mm, col="red")
ssq=function(x) {sum(x^2)}

cal.sig=function(dat=dat, st=0,en=2020)
{
	###  Get trend
	fm=lm(window(dat, st, en)~I(time(window(dat, st, en))))

	###  Initialize variables
	N=length(window(dat, st, en))
	I=seq(1:N)/frequency(dat)
	rmI=ssq(I-mean(I))

	###  Calculate sum of squared errors
	SSE=ssq(fm[[2]])/(N-2)

	###  Calculate OLS standard errors
	seOLS=sqrt(SSE/rmI)*10

	###  Calculate two-tailed 95% CI
	ci95=seOLS*1.964

	###  Get lag-1 ACF
	resids=residuals(lm(window(dat, st, en)~seq(1:N)))
	r1=acf(resids, lag.max=1, plot=FALSE)$acf[[2]]

	###  Calculate CIs with Quenouille (Santer) adjustment for autocorrelation
	Q=(1-r1)/(1+r1)
	ciQ=ci95/sqrt(Q)

	return(c(fm$coef[2]*10,ciQ))
}
tim=time(window(hadcrut,start=1980))
slope=rep(0,length(tim))
ci=rep(0,length(tim))

for (i in 1:(length(tim)-12))
{
	mm=cal.sig(window(hadcrut,start=tim[i]))
	slope[i]=mm[1]
	ci[i]=mm[2]
}
sl=window(ts(slope,start=1980,deltat=1/12),end=2008)
nci=window(ts(-ci,start=1980,deltat=1/12),end=2008)
pci=window(ts(ci,start=1980,deltat=1/12),end=2008)
#savePlot(paste("e:/agw/pics/hadcrutV3GL significance.jpg"),type="jpg")

#plot(sl,main="Hadcrut V3GL Slope Significance Since Year X",xlab="Year",ylab="C/Decade", ylim=c(-.5,.5))
plot(sl,main="Hadcrut 3GL Slope Significance Since Year X",xlab="Year",ylab="C/Decade", ylim=c(-.5,.5))
lines(nci,col="red")
lines(pci,col="red")
grid()
#savePlot(paste("e:/agw/pics/hadcrutV3GL significance.jpg"),type="jpg")
#savePlot(paste("e:/agw/pics/hadcrut3GL significance.jpg"),type="jpg")

#plot(sl,main="Hadcrut V3GL Slope Significance Since X",xlab="Year",ylab="C/Decade", ylim=c(.09,.12),xlim=c(1994,1996))
plot(sl,main="Hadcrut 3GL Slope Significance Since X",xlab="Year",ylab="C/Decade", ylim=c(.09,.12),xlim=c(1994,1996))

lines(nci,col="red")
lines(pci,col="red")
grid()

#savePlot(paste("e:/agw/pics/hadcrutV3GL significance zoomed in.jpg"),type="jpg")
#savePlot(paste("e:/agw/pics/hadcrut3GL significance zoomed in.jpg"),type="jpg")


46 Responses to “Experts or little white lies?”

  1. Ted said

    Jeff.
    I enjoy your articles but hate your page setup your graphs are always only showing 50%, unless you click on it.
    can you reconfigure your display page to allow a easy flow of graphs and written info without constantly clicking on the graph to see a full view?
    Thanks Ted,

  2. Jeff Id said

    Try CTRL and ‘-‘ key.

  3. lucia said

    Jeff–
    Did Jones mean based on monthly? With HadCrut3V? He would have been wise to be specific– or at least not write something that strongly suggest he used annual data.

    The trend over the period 1995-2009 was significant at the 90% level, but wasn’t significant at the standard 95% level that people use,” Professor Jones told BBC News.

    “Basically what’s changed is one more year [of data]. That period 1995-2009 was just 15 years

    This wording strongly suggests he is using annual data. But at least if things work out with monthly data then his claim might be justified and his sin is merely lack of clarity.

  4. Jeff Id said

    Lucia,

    The whole thing is a shoulder shrug except that if he used monthly data, he’s called it right to the edge. I can’t imagine another field even bothering to report significance on something like this.

  5. Jeff Id said

    If someone has a copy of the variance adjusted data from any time between January and April, I would be interested in comparing it.

  6. lucia said

    JeffId–
    I think the only reason to report this is because of the previous news story. But he would have been wise to say “monthly data” and name the observational series. Let’s also home for his sake may doesn’t come in cooler than April. Even if monthly data show significance, it might have been wise for him to wait a few months so that no one excited reports “reversals”.

  7. This issue was raised at Bishop Hill on Friday:
    http://www.bishop-hill.net/blog/2011/6/10/jones-post-1995-warming-significant.html

    I e-mailed both Phil Jones and the BBC journalists on Friday afternoon, as per my comments there. R code was included.

    The reference for the data sets is Brohan et al. [JGR, 2006]. A preprint is at
    http://www.cru.uea.ac.uk/cru/data/temperature/HadCRUT3_accepted.pdf

    Here is a quote from that: “global and regional time-series should be calculated using unadjusted data”. Indeed, the authors have criticized others for attempting to use HadCRUT3v for time series. Note that Jones is one of the authors.

    So I do not believe that Jones would have used HadCRUT3v. I used HadCRUT3 for the calculations. I believe that is correct and what Jones would have used.

  8. […] the Air Vent on […]

  9. Jeff's Dad said

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  10. lucia said

    If significance is only achieved the the data set Jones advises people not to use, then he certainly should have waited until it is shown with his recommended data set. I’m sort of amazed he didn’t just wait a few months or at worst wait until Jan 2012.

  11. Jeff Id said

    Lucia, The guy looks pretty busted to me. This post looked fairly favorably into the data, for him to claim significance so quickly when we can’t find it is probably a significant indicator of a drip under pressure. 😀

  12. lucia said

    JeffId–
    Sure. I think both you and I bent over backwards to find a way to interpret his claim having some foundation. Right now it looks like the best justification he could give might be: “Using a data set I think people should not use, considering monthly data, I announced significance at the first possible time when anyone could begin to claim significance”.

    We all know that eventually there will be significance. So…. why didn’t he just hold his horses and wait until he could make a correct claim?

  13. RomanM said

    To quote Brohan et al. (including Prof. Jones) from 2005, referenced above :

    Variance adjustment is successful at the individual grid-box scale: comparison with synthetic data shows that the inflation of the grid box variance caused by the limited number of observations can be removed without introducing biases into the grid-box series. At larger space scales, however, variance adjustment does introduce a small bias into the data. Whether variance adjusted or unadjusted data should be used in an analysis depends on what is to be calculated. If it is necessary that grid-box anomalies have a spatially and temporally consistent variance, then variance adjusted data should be used. Otherwise, better results may be obtained using unadjusted data. In particular, global and regional time-series should be calculated using unadjusted data.

    In particular, not only can there be bias, but “variance adjusting” is a smoothing procedure. Fitting a slope to smoothed data is known to distort the significance level by making the fit look better than it actually is by making it look more “significant” than it is is . Calculating the size of that effect in this case would probably not be easy.

    This said, anyone who thinks that something magical occurs at the .05 or .01 level should probably take a statistics course.😉

  14. Jeff Id said

    Reading the paragraph from Roman’s comment, what could possibly be the purpose of ‘variance’ adjustment, other than stating significance?

    or perhaps I should say — incorrectly stating significance.

    I’m serious about this, what could be the purpose?

  15. […] The Air Vent comments: Experts or little white lies? […]

  16. BarryW said

    When you present it the way you did you can also state that the trend of the trends had been decreasing since about 1992, is less than 1 deg/century at the 1995 crossing point, and the trend has actually gone negative! Of course I’m chopping off any data after 2005 but hey if he can ignore the data before 1995…..

  17. David Gould said

    Jeff,

    Here is a post I put on the Blackboard addressed to Lucia:

    Lucia

    I think that we discussed what test Phil Jones used in a thread a while back. Based on what he said, all he did was:

    1.) take the yearly values from here:

    http://www.metoffice.gov.uk/ha…..+sh/annual

    2.) work out the r value

    3.) use a two-tailed test in a calculator like this:

    http://faculty.vassar.edu/lowry/tabs.html#r

    4.) and find that the 1995-2009 value is not significant at the 95 per cent confidence level (two tailed value of 0.0726) and that the 1995-2010 is significant at that level (two tailed value of 0.0328)

    He did not change his test. The autocorrelation for the 1995-2010 values (assuming that I have done the calculation correctly, which is a big assumption, I must admit) is effectively non-existent. The residuals offset by one have an R^2 value of .003.

    So assuming no autocorrelation is not a horrible crime in this case.

    Looking at the values that they have used, they are not the ones that I believe that Phil Jones used. The values from the met office link above are:

    1995 0.275
    1996 0.124
    1997 0.356
    1998 0.517
    1999 0.263
    2000 0.239
    2001 0.399
    2002 0.456
    2003 0.459
    2004 0.431
    2005 0.474
    2006 0.427
    2007 0.402
    2008 0.312
    2009 0.439
    2010 0.496
    2011 0.277

    So that difference is likely the reason for the difference in the outcome of the significance tests.

  18. David Gould said

    My suggestion is that it is sometimes perhaps best to assume that your opponents are not telling ‘little white lies’. After all, the much maligned expert – while obviously less competent than the amateur – gets it right sometimes …

  19. Jeff Id said

    David, my titles intended cleverness may be missed. The “white lies” is an addition to the title which was simply Experts. Now it is referring to the noise characterization or in this case ‘white’ noise assumptions of Lucia’s post. There are a hundred ways to make this trend significant or not. How do you model noise? But to call the press while it is on the edge of an arbitrary limit is nothing but PR propaganda . How is it that a ‘scientist’ could feel such pressure to release a statement like this on data which is so borderline? What is the meaning when it is .001 degrees different?

    Thus

    LIttle….white noise…lies…

    or perhaps

    Noise

  20. Jeff Id said

    David,

    I found that the arima fit to the data you provided had an AR1 of 0.22. My suggestion is that using the annual data, Lucia is probably correct but I’ll check it in the morning.

  21. David Gould said

    Jeff Id,

    The fact that you use the phrase ‘white lies’ to counterpoint ‘white noise’ does not disguise the fact that you are deliberately associating the word ‘lies’ with Phil Jones and his statement that the 1995-2010 trend is statistically significant. Phil Jones used the exact same method for this statement that he used when confirming that the 1995-2009 trend was *not* statistically significant. Given the hay that sceptics made with that comment (and I doubt that many of them said, ‘well, there are a hundred ways to make this trend not significant), I think that it is completely reasonable for Phil Jones to use that same method to show statistical significance for the 1995-2010 period.

    Be more generous to your opponents – in other words, do not automatically attempt to paint them with the word ‘lies’.

  22. Jeff Id said

    David,

    If the jackalope cannot be honest about autocorrelation, a statistical feature that no premier global temperature scientists would miss, then the tease is fully appropriate.

    My post was very generous in that I looked for ways to make his statement correct. He tricked me.

  23. Jeff Id said

    Lie is one of my least used words. I don’t use it often but thought ‘little white lie’, would colour it appropriately in this case. If your description of his calculation is correct, then the critique hit the bull’s eye.

  24. Carrick said

    “Little white lie” suggests putting spin on a story to me. It looks to me like this is what Phil Jones is doing. He wouldn’t be the first researcher to do so, and I’m not sure what’s so awful about making such a suggestion. Jeff isn’t suggesting (to me anyway) that Phil is somehow a horrible person by spinning the story a bit.

    David I also asked this on Lucia’s blog. Why exactly do you think autocorrelation is unimportant? (I am certain you’re wrong, just interested in your explanation of how you came to that conclusion.)

  25. David Gould said

    Carrick,

    Because the correlation value (r^2) between the residuals offset by one year is so low. A high level of correlation would require a high value. If I have this wrong, that would be good to know.

    Note I am not saying that this generally the case for yearly temperature values – it could be that there is a high level of autocorrelation there. But for the values between 1995-2010 in this particular dataset there appears to be little autocorrelation.

  26. David Gould said

    And I did have it wrong: the value is .01, three times as much (I left in the 2011 value by mistake). This does indeed tip it out of statistical significance.

  27. Geoff Sherrington said

    The press releases that the public believe say “The period since 1997 has included the N hottest years since temperature recording began” The present pattern, though far from free of noise, suggests a plateau, so that with each passing year on the plateau, the value of N is likely to increase and look more persuasive. That is the one-liner that you have to contend with. One has to be a bit more savvy than John Citizen to comprehend the nuances of the Jones boy.
    BTW, I agree absolutely with Roman “This said, anyone who thinks that something magical occurs at the .05 or .01 level should probably take a statistics course.” The meaning of probability calculations depends on the nature of the work under study – in fields outside climatology – as well as on the quality of the input data.

  28. Thanks to Lucia for taking a look and publishing the email I sent to the Blackboard..

    The problem is, the intent of this headline is to be used to prove the ‘sceptics’/’lukewarmers’ wrong somehow. It HAS BEEN sent around the world’s media, and Jeff’Id’s, Keenans, and the Blackboards fact checking will be never be communicated to the masses.

    What also gets lost, is not whether the world is warming, plateauing, cooling, etc, or the rate of which over what timescale, but none of this Proves the actual cause of temperature changes

    The cause AGW or natural or realisticall what % of both (and nobody knows what % of either) which is of course the whole point. The argument has descended to a media propaganda soundbite, it’s warming again, proof of AGW?!?!?
    (what happened to nature, has every warming, cooing process stopped, or all cancelled each other out in a bizarre equilibrium, where only AGW makes a difference?)

    The very simplistic message that the ‘sceptics’ are wrong, because the world is warming, is what this Phiul Jones staement and BBC article was intended to convey, not least repeated by the Carbon Brief, who twittered and spun this article to the world’s media (ie their twitter followeres is a who’s who of the AGW media,NGO extablishment, including the Committee on Climate Change and UEA, Climate progress, Guardian environment, washington POst, Time, Independent, BBC, etc)

    Carbon Brief:
    “The claim that global warming has stopped – one of the most overused and deeply flawed climate sceptic arguments – can finally be laid to rest today, following the publication of new data analysis by one of the country’s leading climatologists”

    http://www.carbonbrief.org/blog/2011/06/global-warming-since-1995-statistically-significant

    Comments are open (slow moderation at the weekend – ie paid staff) but no one that it will have been distributed to will ever read the comments…

    Carbon Brief Background (sceptical scientists, LIndzen, Mckitrick, etc) smeared by the CB.
    http://wattsupwiththat.com/2011/05/14/smear-job-by-the-carbon-brief/

    http://wattsupwiththat.com/2011/02/18/the-carbon-brief-the-european-rapid-response-team/

  29. Did anyone notice Paul Dennis’ comment at Bishop Hill about the BBC article(a UEA colleague of Jones)

    “I’m rather bemused by the article. 1995-2009, no significant warming, 1995-2010 significant warming and perhaps 1995-2011 no significant warming depending on this years temperature. Who knows! Adding a year to the trend and suddenly claiming significance as the headline asserts (‘Global warming since 1995 ‘now significant’) really shows a complete lack of understanding of linear regression, let alone the nature of the data.

    Jun 10, 2011 at 6:32 PM | Paul Dennis ”
    http://bishophill.squarespace.com/blog/2011/6/10/jones-post-1995-warming-significant.html#comments

  30. Søren Rosdahl Jensen said

    I have made a similar plot, but using arma(1,1) correction for auto-correlation, rather than AR1. This gives wider confidence intervals, and my plots do not show a significant trend for HADCRUT3 since 1995
    Data from here: http://hadobs.metoffice.com/hadcrut3/diagnostics/global/nh+sh/monthly

    Plots are here

  31. mrnkalon said

    How the chickens come back to roost.

    “The problem is, the intent of this headline is to be used to prove the ‘sceptics’/’lukewarmers’ wrong somehow.”

    Justifiably so.

    The question posed to Phil Jones about whether warming since 1995 was significant came from sceptics/lukewarmers in the first place. Sceptics/lukewarmers then spread it around the internet left right and center. The whole non-issue was set up by sceptic/lukewarmers in the first place. You reap what you sow.

  32. mrnkalon said

    The blame game.

    Lucia: “This wording strongly suggests he is using annual data. But at least if things work out with monthly data then his claim might be justified and his sin is merely lack of clarity.”

    It’s not clear because it’s a news article. That’s not a sin. The sin if anything is your bold assumption that he was using annual data and not even bothering to check monthly data.

    Jeff Id: “The whole thing is a shoulder shrug except that if he used monthly data, he’s called it right to the edge. I can’t imagine another field even bothering to report significance on something like this.”

    It was a non-issue until sceptic/lukewarmers made it an issue by spreading the “no warming since 1995” claim. Complaining that it’s a non-issue at this point and even suggesting it’s some fault of phil jones to even be mentioning it is ridiculous. Blame lies with the sceptics/lukewarmers.

    “We all know that eventually there will be significance. So…. why didn’t he just hold his horses and wait until he could make a correct claim?”

    Funny because those headlines back last year read “no warming since 1995”, not “no warming since 1995 but we all know that eventually there will be”

    Why didn’t those who pushed the “no warming since 1995” claim wait until 2012 so they could make a correct claim?

    The blame phil jones game is fun. But the blame sceptic/lukewarmers is a far far easier game.

  33. Jeff Id said

    Actually, the whole exercise came about here because of claims by the pro’s that there was no cooling. I can’t say who brought it up elsewhere.

  34. RomanM said

    #32 mrnkalon:

    It’s not clear because it’s a news article.

    If it is not a lame and transparent propaganda effort by Mr. Jones, what exactly makes this newsworthy?

    From the BBC interview, the (much maligned according to David Gould in comment #18) statistical “expert” expounds in a non-descript fashion:

    Basically what’s changed is one more year [of data]. That period 1995-2009 was just 15 years – and because of the uncertainty in estimating trends over short periods, an extra year has made that trend significant at the 95% level which is the traditional threshold that statisticians have used for many years.

    First, we have the single tree which proves that this is the currently warmest that it has been in a million years. Now, we have 2010, the single year whose average temperature proves that AGW has stealthily been marching on unabated.

    Climate science statistics boggles my “amateur” mind…

  35. boballab said

    #34 RomanM:

    Climate science statistics boggles my “amateur” mind…

    Now if you had only taken one of Dr. Steig’s Matlab classes climate science statistics would be a snap. 🙂

  36. […] […]

  37. Anonymous said

    #13 Roman M

    In particular, not only can there be bias, but “variance adjusting” is a smoothing procedure. Fitting a slope to smoothed data is known to distort the significance level by making the fit look better than it actually is by making it look more “significant” than it is is .

    How HadCrut’s variance adjustment methods affect trend significance would make a great demonstration for a post at “Statistics and Other Things” don’t you think? 😉

  38. Layman Lurker said

    Sorry Roman, #36 was me

  39. Tom Bakewell said

    The def of expert I learned is “X is of course the unknown. And a spirt is merely a drip under pressure…” I think I found it in an early 60’s issue of Radio Constructor.

  40. Genghis said

    Excuse my ignorance, but what exactly has been the amount of warming since 1995?

    CO2 levels have dramatically increased since then. Has the Temperature?

    And while I am at it. Does anyone know the actual Global average temperature baseline that this is all predicated on?

  41. Lynn said

    I think your definition of ‘expert’ is missing a short phrase. The way I learned it is, “An expert is a has-been drip under pressure.”

  42. boballab said

    #40

    Genghis:

    Excuse my ignorance, but what exactly has been the amount of warming since 1995?

    CO2 levels have dramatically increased since then. Has the Temperature?

    And while I am at it. Does anyone know the actual Global average temperature baseline that this is all predicated on?

    Of the question of what amount of warming has there been since 1995 depends on which dataset you use: GISS, HadCrut or NCDC for surface or UAH or RSS for TLT. All of them have different rates due to the way they handle the underlying data.

    As to you question of the Global average temperature baseline that also depends on which dataset you are using and in some cases what year it was made/updated in.

    Nasa GISS baseline is the 30 year average between 1951 to 1980 . You can also convert their global Land and Land/Ocean Combined anomaly datasets back into absolute temperatures by adding the number 14 to them as per the GISS website:

    Best estimate for absolute global mean for 1951-1980 is 14.0 deg-C or 57.2 deg-F,
    so add that to the temperature change if you want to use an absolute scale
    (this note applies to global annual means only, J-D and D-N !)

    http://data.giss.nasa.gov/gistemp/tabledata/GLB.Ts+dSST.txt

    From there you can change 30 year baselines to match the other datasets to make a more apples to apples comparison.

    The Baseline for NCDC is 13.9°C over the 1901 to 2000 time period for their combined land/ocean datasetwith 16.1° C for Ocean only and 8.5° C for land only. This can be seen on their website here:
    http://www.ncdc.noaa.gov/cmb-faq/anomalies.php#grid

    For HadCrut they use the mean of the 30 year period 1961-90 as shown on their websites:
    http://www.cru.uea.ac.uk/cru/data/temperature/#filfor

    However to find out what value to use to change baselines you have to go back to the Jones et al 1999 paper (didn’t anything like this in brohan 2006 for the update to HadCrut 3)

    [Jones et al. (1999) report the 1961-1990 reference period means for the globe, northern hemisphere, and southern hemisphere as 14.0°C, 14.6°C, and 13.4°C, respectively.]

    http://cdiac.ornl.gov/trends/temp/jonescru/jones.html

    For the RSS and UAH datasets the baseline length depends on when you got your copy of the dataset. If the copy you have is from before Jan 2011 then the baseline period is of 20 year lenghth of 1981-2000, if it is after the baseline is now the 30 year length of 1981-2010. So far I haven’t seen a number to add to their anomalies to turn them back into absolute temps to change baseline periods with.

  43. Jeff Id said

    Lynn, sounds more correct.

  44. Genghis said

    Thank you so much Boballab. Especially for the sources.

    I thought the NCDC temps for the ocean at 16.1˚ C and the land only at 8.5˚ C to be especially thought provoking. I had no idea the average ocean temperature was that much warmer than the land. It certainly does make sense though when looking at a globe.

  45. andykn said

    @Boballab

    ?

    Since when have absolute temps only been 14 deg C below the GISS baseline? All you’re doing is changing arbitrary baselines from one misrepresented by sceptics as having some conspiratorial significance to a different one thay can’t.

  46. boballab said

    @Andykn

    Maybe you need to lay off the Koolaide for awhile because your brains are addled

    1. Nowhere did I state that the absolute temps were 14°C below the GISS baseline.

    2. That 14°C number and procedure was provided by Dr. Jim Hansen of NASA GISS (The Father of the Modern AGW theory) not me. That is why it is in a blockquotes and with a link to the NASA GISS dataset. Hit the link and read it yourself.

    3. Explain how I’m picking arbitrary baselines for the Global Temperature Anomalies? Dr. Hansen picked the 1951-80 Baseline for GISS, Dr. Phil Jones picked the 1961-90 Baseline for HadCrut, Dr. Peterson and his team at NCDC picked the 1901-2000 baseline for theirs, Dr. Christy and Spencer went to a 30 year baseline for the UAH dataset as soon as they had a 30 year baseline period that matched the World Meteorological Organizations guidelines.

    4.8.1 Period of calculation
    Under the Tec hnic al Reg ulatio ns (WMO‐No . 49), climatological standard normals are averages of climatological data compute for the following consecutive periods of 30 years: 1 January 1901 to 31 December 1930, 1 January 1931 to 31 December 1960, and so forth. Countries should calculate climatological standard normals as soon as possible after the end of a standard normal period. It is also recommended that, where possible, the calculation of anomalies be based on climatological standard normal periods, in order to allow a uniform basis for comparison. Averages (also known as provisional normals) may be calculated at any time for stations not having 30 years of available data (see 4.8.4). Period averages are averages computed for any period of at least ten years starting on 1 January of a year ending with the digit 1 (for example, 1 January 1991 to 31 December 2004). Although not required by WMO, some countries calculate period averages every decade.

    http://www.wmo.int/pages/prog/wcp/documents/Guide2.pdf

    Same with the team at RSS. So again explain how I’m picking the arbitrary baselines again?

    So Andykn before coming back in here and making yourself look more stupid then you already do, go read the faq pages for each dataset, the papers they are based on and the WMO guidelines, then try to make an intelligent remark. Here is a hint for you: The specific 30 year baseline period does not effect the linear regression trend of the dataset, only how many anomalies are above or below the baseline. When comparing two different datasets that use different 30 year baselines the zero point on the graph is not the same for both datasets, you must put them on the same baseline to get the same zero point.

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