Based on some of the recent comments at the WUWT cross post of my post The Contiguous U.S. Surface Air Temperature Data Through 2012 – Is the Recent Warming Trend Unusual? it became obvious that Tamino was up to his old tricks again. Yup. Tamino is obviously using his normal tactic of misdirection in his post here.
I illustrated in my post the warming periods as they obviously present themselves in the data, and Tamino has presented a 30-year time span of his own choosing for his trend analysis. If we look at the Contiguous U.S. Surface Air Temperatures, Figure 1, the data starts with a cooling period, and that cooling period ended when the surface temperatures reached their minimum at 1917. Looks pretty obvious to me. Surface temperatures then warmed, and they peaked in 1934. Again, it’s obvious. If I had selected other start and end years for that warming period, I would have received numerous complaints. There was then a multidecadal cooling period that started in 1934 and ended when the data reached their second minimum at 1979. After 1979, temperatures warmed.
Figure 1
In an attempt to provide a shorter time period for comparison to the early warming period in my post, I also presented the late warming period with the start year of 1993.
Then there’s Tamino’s post. He used a 30-year time span for his analysis to show that the 30-year trend during the recent warming period had a higher trend than earlier 30-year periods, but he does not illustrate those 30-year periods with the raw data. Here’s why. The period of 1912 to 1941 has the highest 30-year linear trend during the first half of the 20th Century. See Figure 2. It has a lower trend than 30-year periods during the late warming period, because it includes the early warming period AND portions of 2 obvious cooling periods. Would anyone select the years of 1912 to 1941 to define the early warming period? No. They would not. In other words, Tamino selected a time span that does not represent the term of the early warming period.
Figure 2
Tamino comically titled his post “He knows not what he’s doing”. I believe it’s pretty obvious what I’ve done. I’ve selected the warming and cooling time periods as they’ve presented themselves in the data, and I’ve based the trend analyses on those time periods. Tamino calls that cherry-picking. I call it common sense. And it’s also blatantly obvious what Tamino has done. He attempted to draw his readers’ attentions away from the slower rate of warming during the late warming period. It’s called sleight of hand—misdirection.
Has the recent warming period lasted longer than the early period? No doubt about it. Is that any reason to be concerned? No. The mid-to-late 20th Century cooling period lasted for 46 years. Who cares?
What’s obvious is that the warming rate during the recent warming period, though it lasts longer, is much lower than the warming rate of the early period. In other words, there’s nothing alarming about the rate of warming during the recent warming period in the NCDC’s data—even with the cool start year of 1979 and the pleasantly warm 2012 tacked onto the end.
It looks to me like Tamino simply wasted a couple of hours preparing a post for the benefit of his like-minded audience.
SOURCE
Contiguous U.S. land surface air data is available in Table form through the NOAA/NCDC webpage here.
Bob Tisdale - Climate Observations 
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If you want to estimate a second derivative (the time-rate of change of the warming rate), why do you not fit a higher order curve through ALL the data. There is nothing magical about a linear trend (2 fitting parameters) as opposed to a quadratic one (3 fitting parameters) instead of a linear trend over 4 periods (8 fitting parameters). From a statistical and scientific perspective it is always questionable to pick “obvious” (I read this as subjective) start and end points, if the data contain random noise. You may get the same answer, I do not know, but nobody will be able to call you out for cherry-picking as Tamino has done.
Well done Bob. It must get very frustrating having to continually explain yourself but you do it with good grace and rigorous precision. I just hope that he takes in the lesson.
Bob, Thank you for all the time you put into educating us. In spite of your presentation, I would find it hard to believe the magic flute would change its tune.
30 years is commonly selected for climate data so as to represent signal, not cherry picked noise. 18 v. 20 v. 34 years? Your posts are just perfect for WUWT …
“Common sense is the most widely shared commodity in the world, for every man is convinced that he is well supplied with it.”
― René Descartes
John@EF says: “30 years is commonly selected for climate data so as to represent signal, not cherry picked noise. 18 v. 20 v. 34 years? Your posts are just perfect for WUWT …”
30 years, huh? Are you sure? Hansen used 6-year running trends in Hansen et al 2011:
Click to access 20110415_EnergyImbalancePaper.pdf
Would you like me to add to that, John@EF?
Tamino used 30 years to subdue a blatantly obvious, very strong warming that lasted less than 2 decades.
Sou says: “‘Common sense is the most widely shared commodity in the world, for every man is convinced that he is well supplied with it.’
― René Descartes”
I’ll raise you one:
“It is a thousand times better to have common sense without education than to have education without common sense.”
– Robert Green Ingersoll
“Common sense is genius dressed in its working clothes.”
– Ralph Waldo Emerson
This really is silly. Apply your methodology to artificial data with no warming trend, and you also ‘find’ faster earlier warming as Tamino shows. But wait a second – there’s no trend…
Soos says: “This really is silly. Apply your methodology to artificial data with no warming trend, and you also ‘find’ faster earlier warming as Tamino shows. But wait a second – there’s no trend…”
I assume you’re referring to all of the adjustments to the USHCN data. Do you have a link to the unadjusted data for the contiguous U.S., as a single time series? I want to compare it to the sea surface temperatures of the U.S. Coastal Waters, which were far from setting a record in 2012.
I just did the analysis of all the 118 years of data fitting a single wiggly (nonlinear) curve with 4 free parameters (temperature = a + b*time + c*time^2 + d*time^3) that allows estimation of the warming rate that changes continuously over time. For this fit, I use only 4 constants (a,b,c,d) determined from the data by fitting the data as best as one possibly can. It works really well, much better than picking arbitrary start and end times that statistics people do not like as they do introduce artifacts (I am a physicist, not a statistician, hence I am not married to trends). I would not want to take the fun of discovery and solving puzzles from anyone, and the results are a powerful weapon in the fight for truth. Numbers do not lie, people do. [Make sure to take care of rounding errors using common-sense.]
Andreas: Thanks. I’ll take a look. Regards
Bob Tisdale says:
January 16, 2013 at 11:51 am
…
30 years, huh? Are you sure? Hansen used 6-year running trends in Hansen et al 2011:
Click to access 20110415_EnergyImbalancePaper.pdf
…
============
I was referring to surface temperature measurements and the associated variability seen at that level of analysis. Hansen was using 6 year trend data smoothing on individual component measurements w/ an eye on consistency with other studies addressing similar scope and context. The validity of the specific data trend smoothing techniques is dependent on the characteristics of the specific data being analyzed. What’s valid for one type of analysis is invalid for another … your point?
You plainly haven’t understood the last figure in Tamino’s post since it comprehensively contradicts your statement that “…the warming rate during the recent warming period, though it lasts longer, is much lower than the warming rate of the early period.”
FourEcks says: “You plainly haven’t understood the last figure in Tamino’s post since it comprehensively contradicts your statement that ‘…the warming rate during the recent warming period, though it lasts longer, is much lower than the warming rate of the early period.’”
Actually, I plainly have “understood the last figure in Tamino’s post” because I wrote in the introduction to my Figure 2 above: “He [Tamino] used a 30-year time span for his analysis to show that the 30-year trend during the recent warming period had a higher trend than earlier 30-year periods…”
Sure sounds like I understood the last Figure in Tamino’s post. So it appears that you, FourEcks, didn’t bother to read my post in its entirety, or had trouble comprehending it, or have a very short memory, or you have selective-quote syndrome, or all of the above.
John@EF says: “I was referring to surface temperature measurements and the associated variability seen at that level of analysis. Hansen was using 6 year trend data smoothing on individual component measurements w/ an eye on consistency with other studies addressing similar scope and context…”
Actually Hansen was using the 6-year running trends of ocean heat content to define ocean heat uptake, but that’s neither here nor there since you were referring to surface temperature measurements with your comment “30 years is commonly selected for climate data so as to represent signal, not cherry picked noise. 18 v. 20 v. 34 years? Your posts are just perfect for WUWT …”
With your clarification, the first paper that now comes to mind that contradicts your statement is “Knight et al (2009) Do Global Temperature Trends over the Past Decade Falsify Climate Predictions?” As the title suggests, they were more than happy to provide temperature trends for a 10-year period:
Click to access global_temperatures_09.pdf
Adios.
Bob Tisdale says:
January 16, 2013 at 4:35 pm
…
With your clarification, the first paper that now comes to mind that contradicts your statement is “Knight et al (2009) Do Global Temperature Trends over the Past Decade Falsify Climate Predictions?” As the title suggests, they were more than happy to provide temperature trends for a 10-year period:
Click to access global_temperatures_09.pdf
============
????? They don’t DISPROVE because the confidence interval grows increasingly wide as you bring the observation timeline closer to zero. The CI is determined by the characteristics, the variability of the data. Doesn’t contradict my statement at all.
By picking intervals by eye, it seems to me you are unconsciously choosing periods where one particular climate factor was predominant — the sun in the first part of last century, aerosols in the middle of the century, GHGs in the last quarter, ocean weather (ENSOs) in the last 15 years.
By climate is a mixture of *all* such factors, not whichever one happens to be largest in some decade or two. That’s why climatologists look at long intervals — at least 3 decades — and don’t try to make judgements based on short intervals.
John@EF says: “????? They don’t DISPROVE because the confidence interval grows increasingly wide as you bring the observation timeline closer to zero. The CI is determined by the characteristics, the variability of the data. Doesn’t contradict my statement at all.”
You were very specific in your opening statement, when you wrote, “30 years is commonly selected for climate data so as to represent signal, not cherry picked noise. 18 v. 20 v. 34 years?”
Yet you provided nothing to substantiate that claim. The IPCC commonly used periods of less than 30 years in their discussion of surface temperatures in TAR and AR4.
As noted earlier, 30 years is apparently not “commonly selected” if Knight et al used 10 years.
30 years is apparently not “commonly selected” if Santer et al (2011) discussed 17-year trends in “Separating Signal and Noise in Atmospheric Temperature Change: The Importance of Timescale” discussed 17 year trends:
Click to access Santer2011.pdf
Do we need to continue this, John@EF?
davidappell says: “That’s why climatologists look at long intervals — at least 3 decades — and don’t try to make judgements based on short intervals.”
At least 3 decades? Refer to my reply to John@EF above.
Because other people make occasional scientific errors is no excuse for you to do so too.
The fact is, if ENSOs (in particular) can cause relatively quick global surface temperature swings of 0.2-0.4 C in a year or two, and GHG warming is now about 0.2 C/decade, then there are going to be decades (or two) with little apparent warming. Choosing to focus on 10-20 year time periods will always be misleading in one direction or the other.
The only rationale you’ve made for picking start and end points is that “it’s obvious”. But these points are based on extreme weather events and are effectively arbitrary. By your rationale – or lack of it – you could further break up your early warming segment into 3 smaller segments. You would get a much steeper warming curve if you just made it the period 1917 – 1921.
Bob, if you look at short periods like 18 years, you find that periods ending in the 1930’s exhibit the strongest increase. But if you look at longer periods (anything over 35 years) then periods ending in the last few years show the greatest rate of increase.
So back then we had short but rapid warming, whereas now its more sustained.
John Brookes says: “So back then we had short but rapid warming, whereas now its more sustained.”
Agreed. I acknowledged that in the post. And the cooling period from the early-1930s to the late-1970s has lasted longest.
Alex the Seal says: “The only rationale you’ve made for picking start and end points is that ‘it’s obvious’…”
My rationale seems to make more sense than that used by Hansen & Lebedeff (1987). They selected the closest years to period minimums and maximums that were a multiples of 5.
http://onlinelibrary.wiley.com/doi/10.1029/JD092iD11p13345/pdf
davidappell says: “Because other people make occasional scientific errors is no excuse for you to do so too.”
Let’s see. Jones (1988) presented 20-year trends in “Hemispheric Surface Air Temperature Variations: Recent Trends and an Update to 1987”
http://journals.ametsoc.org/doi/pdf/10.1175/1520-0442%281988%29001%3C0654%3AHSATVR%3E2.0.CO%3B2
In Jones et al (1986) Northern hemisphere surface air temperature variations 1851-1984, they presented trends for the period of 1965-1978 (see their Table 5.)
Click to access jones1986.pdf
Hansen and Lebedeff (1987) “Global trends of measured surface air temperature” actually presented a map of surface temperature trends for the period of 1965 to 1985. See their plate 2c.
http://onlinelibrary.wiley.com/doi/10.1029/JD092iD11p13345/pdf
It appears that using periods less than 30 years are not “occasional scientific errors”. It appears to be standard procedure.
> Looks pretty obvious to me.
Selecting data based on what is “pretty obvious to me” has the specific name: “cherry picking”.
> If I had selected other start and end years for that warming period,
> I would have received numerous complaints
There exist STATISTICAL METHODS to determine in which point some trend started and in which it finished. There wouldn’t be complains if you determined those point based on statistical methods instead of cherry picking them.
Hey Bob,
Can you elaborate on what you believe were the major causes of the two warming periods that you are comparing?
Thanks
If you were a Technical Analyst in the stock market, you would use the lowest low to the highest high to define a trend. Seems that Bob used a very common approach to define a trend. Seems reasonable to me.
> you believe were the major causes of the two warming
First of all it should be determined for each of those warmings if it’s actually warming or just fluke – saying other words: if the trend it contains is statistically significant of not.
Matt says: “Hey Bob, Can you elaborate on what you believe were the major causes of the two warming periods that you are comparing?”
Of the subsets I’ve looked at, the Contiguous U.S. land surface air temperatures appear to mimic and exaggerate (with additional year-to-year variations) the variations in the sea surface temperatures of U.S. Coastal Waters for the Gulf and East Coasts:
BTW, I’m looking for the unadjusted Contiguous U.S. Temperature data as a single time series. Any idea where I can find it?
Bob is right to point out that other people use (seemingly) arbitrary trend lengths in the published literature. But still, while you can cherry-pick somewhat by picking the trend length to compare the data over, it’s a whole new level of cherry-picking to use *three* different time lengths in the same comparison. That’s (cherry picking)^2.
As Tamino noted, if you can get the same kind of result by applying the methodology to random noise, then the methodology is no good.
A good starting place would be to look at the statistical significance of the trends.
Windchaser says: “Bob is right to point out that other people use (seemingly) arbitrary trend lengths in the published literature. But still, while you can cherry-pick somewhat by picking the trend length to compare the data over, it’s a whole new level of cherry-picking to use *three* different time lengths in the same comparison. That’s (cherry picking)^2.”
I provided two trends for the recent warming period because it could have been argued that the recent warming period started at two points in time. Second, Hansen and Lebedeff provided trend analysis for “*three* different time lengths in the same comparison”. Did you by chance contact them back in 1987 to complain?
http://onlinelibrary.wiley.com/doi/10.1029/JD092iD11p13345/pdf
Third, also look at Table 5 in Jones et al (1986) “Northern hemisphere surface air temperature variations 1851-1984”. They presented trends for periods with the same start years but differing end years on the same table, and to complicate matters, they then referred the reader elsewhere to determine the time span for the periods.
Click to access jones1986.pdf
(sarc on) Classic climate science at its best (sarc off)
Regards
If you want to know how the trend is changing over time, use ALL the data in a regression that contains BOTH the trend and how the trend changes over time. All you have to do is fit temperature = a + b*time + c*time^2 + d*time^3 estimating the 4 unknown parameters (a,b,c,d) the exact the same way (minimize the least-square error between fit and data). You currently do this for 2 unknowns (a,b) as you are fitting temperature = a + b*time multiple times. This back and forth on how and if and where to select start and end times is really silly and unnecessary. Fitting 4 instead of 2 parameters is not rocket science where one has to pull out heavy hitting papers from Los Alamos to select the “best” interval. Use ALL the data in ONE fit. Google it, then solve 4 linear equations for the 4 unknowns (a,b,c,d). The time-variable trend is then the first derivative of the above, that is, temperature_trend = b + 2*c*time + 3*d*time^2. Done, you now got an estimate for a different trend for each year without anyone able to accuse anyone for cherry-picking.
“(sarc on) Classic climate science at its best (sarc off)”
And Jones (and other climate scientists) have received a lot of flak for employing weak statistical practices in the past. But even in that paper, Jones’ conclusions were not significantly dependent on the choice of starting and ending year – though, error bars would have been helpful. AFAICT, where the conclusions are statistically weak, they say so.
Yet, I still I see many fewer papers nowadays which use bad statistical practices (such as no error bars and no justification for trend length). So is this really your defense, that “well, they did it too, 25 years ago”?
Are you going to tell me that if Mann made statistical mistakes in his Hockey Stick paper, that it’s okay for you to do so, too?
Again: If your results change strongly with minor variations in your start and endpoints, i.e., if your results do not have much statistical significance, then your results are not worth very much. Don’t try to draw conclusions from such results.
Good scientists test their own hypotheses and methods before publishing them. For finding trends, might I recommend applying your method to a random series (both with white and red noise) before you publish your results? This would help you spot any problems with your method before you publicly use it to draw conclusions.
“My rationale seems to make more sense than that used by…”
Sorry are you saying your rationale (Which remains a mystery) is ok because someone else’s is worse?
The problem I have with all of this is that its really ‘splitting statistical hairs’ – the data is patchy, tweaked, tuned and badly abused. With the methods of measurement modified and, maybe, refined over the years. To me trying to get anything truly significant out of the historic record is like knitting fog whilst blindfold. You _may_ be able to do something worth while with a recent accurate well understood unified measurement regime, but go back more than 20 years and there is so much change in many dimensions it becomes more subjective than absolute. Combine that with an almost endemic willingness to not respect SD and true error in measurement throughout processing and you end up with expensive models and resultant projections not worth the expensive paper they are printed on – and they know it.
The only thing you can say with any clear confidence is that Co2 is not trending with temperature in any significant way and that the IPCC predictions in succession were so wide of the mark they almost achieved escape velocity. That should be a massive tell that something fishy is afoot.
Bob,
Obviously tamino is splitting hairs. This is all that is left for the alarmists. As each and every myth gets busted/exposed they grasp at shorter and shorter straws.
But tamino does have Horatio Algeranon, what climate science site would be complete without a resident minstrel?
ecoGuy says:
>> The only thing you can say with any clear confidence is that Co2 is not trending with temperature in any significant way <<
In fact you can't say that with any confidence at all, and a real analysis shows it to be false:
“Global temperature evolution 1979–2010,” G Foster and S Rahmstorf, Environ Res Lett 6 044022 (2011)
http://iopscience.iop.org/1748-9326/6/4/044022
David Appell: Apparently you’re still under the misunderstanding that ENSO can be removed from the instrument temperature using the methodologies employed in Foster and Rahmstorf (2011), and Rahmstorf et al (2012). Sorry to inform you—it can’t:
Have a nice day, ya’ hear.
Oh please. Your Figure 5 is just more cherry-picking of short-term (and arbitrary) trend lengths that fit your agenda. None of it would pass peer review (have you ever tried?).
David Appell says: “…more cherry-picking of short-term (and arbitrary) trend lengths that fit your agenda.”
Thanks, David. That’s one of the funniest comments I’ve read in weeks. Almost spit some iced tea on my keyboard.
Good-bye.
That’s what’s called a non-response — the avoidance of a response, which trying to save face. It doesn’t wash.
And again: have you ever submitted your work to peer review? If not, why not?
David Appell: You’re calling my reply a “non-response”, David? That’s almost a funny as your earlier reply, which had clearly indicated you hadn’t bothered to read or attempted to understand the post I had linked. That reply suggested you simply skimmed through the illustrations—that you had expended no more effort than a brief glance.
The time periods in Figure 5 from that post…
…are not cherry picked. The reasons for the selection of those time periods have been clearly identified in the post and in the videos linked to it. If you don’t want to watch the videos, here are links to an earlier post and supplement that go into more detail than the post I had linked earlier for you:
And the supplement:
Your reply indicated you failed to grasp that the shifts in the sea surface temperatures (Figure 5) were process-related responses to strong El Niño events, which is why those El Niño events were isolated.
Your fixation on Figure 5, David, indicated you hadn’t grasped the significance of Figure 3…
…from that post. If the sea surface temperatures of 67% of the surface of the global oceans do not cool proportionally during the 1988/89 and 1998-2001 La Niñas because of ENSO residuals (warm water that’s left over from the El Niños that led them), then Foster and Rahmstorf (2011) and Rahmstorf et al (2012) have obviously failed to remove the impacts of ENSO from the surface temperature record.
With respect to your question about a peer-reviewed paper, you already know the answer, David, so why did you waste your time asking it?
My findings have not been submitted and they will not be submitted for journal publication. There’s no reason to submit them. The sea surface temperature and ocean heat content records do not support the hypothesis of manmade carbon dioxide-driven global warming. A paper noting that would have no chance of being objectively reviewed by persons whose livelihoods depend on that faulty hypothesis. Let’s put it in perspective: Your income, as far as I know, does not rely on the hypothesis and you haven’t bothered to do more than take a quick look at a couple of graphs. Do you somehow believe someone whose income and reputation rely on a flawed hypothesis would recommend publication?
There are two papers I’m aware of that note the methods used by Foster and Rahmstorf (2011) and Rahmstorf et al (2012) are erroneous. They are Trenberth et al (2002):
Click to access 2000JD000298.pdf
…and Compo and Sardeshmukh (2010):
Click to access CompoSardeshmukh2008b.pdf
Trenberth et al (2002) noted:
“Although it is possible to use regression to eliminate the linear portion of the global mean temperature signal associated with ENSO, the processes that contribute regionally to the global mean differ considerably, and the linear approach likely leaves an ENSO residual.”
The ENSO residuals and their impacts are illustrated in Figures 3 and 5, which were linked and discussed earlier.
Compo and Sardeshmukh (2010) is a step in the right direction. They’re at least looking. They note:
“An important question in assessing twentieth-century climate is to what extent have ENSO-related variations contributed to the observed trends. Isolating such contributions is challenging for several reasons, including ambiguities arising from how ENSO is defined. In particular, defining ENSO in terms of a single index and ENSO-related variations in terms of regressions on that index, as done in many previous studies, can lead to wrong conclusions. This paper argues that ENSO is best viewed not as a number but as an evolving dynamical process for this purpose.”
Trenberth et al (2002) and Compo and Sardeshmukh (2010) existed prior to (and were overlooked by the reviewers of) Foster and Rahmstorf (2011) and Rahmstorf et al (2012).
So even if I were to publish my findings in a paper, misleading papers like Foster and Rahmstorf (2011) and Rahmstorf et al (2012) that misrepresent the impacts of ENSO would still be published and persons such as you, David, would link them as a “real analysis” without comprehending their fatal flaws.
Have a nice day, David.
Ah, Bob: those norty, norty gatekeepers of science, borne of tin-hatted foolery. I posit you will not submit the paper because you know it would, as it has on Tamino’s website, and numerous others, be *ripped to shreds*. To date, you have NEVER provided a source of heat that keeps driving up SSTs and the overall global temperatures, on any of your responses, be they here, at SkS, or elsewhere.
Publish, or perish.
HarryWiggs says: “I posit you will not submit the paper because you know it would, as it has on Tamino’s website, and numerous others, be *ripped to shreds*.”
Actually, Harry, you and your kin at SkepticalScience and Tamino’s only think you’re ripping my findings to shreds because you cannot comprehend what I’ve presented. It is beyond your grasp. It contradicts your beliefs so you dismiss it without attempting to understand it. No loss. The world moves on without you.
HarryWiggs says: “To date, you have NEVER provided a source of heat that keeps driving up SSTs and the overall global temperatures, on any of your responses, be they here, at SkS, or elsewhere.”
Really, Harry? I have. You must’ve overlooked it somehow. I’ve presented that source of heat for more than three years in numerous posts here. Most have been cross posted at WattsUpWithThat. I also discussed them in my comments at SkS, but you must not have been able to fathom what I’d written. Or you (singular) are simply misrepresenting fact—in other words, lying—which is not beyond persons who are proponents of anthropogenic global warming. I spent most of my time on that SkS thread responding to misrepresentations, quotes taken out of context, and the other questionable debate tactics so readily used by bloggers from SkepticalScience. One thing was certain: no one there was interested in learning.
Typically I write something to the effect of: La Niña events also recharge part of the warm water that was released during the El Niño. They accomplish this through an increase in downward shortwave radiation (visible light), and that results from the reduction in tropical Pacific cloud amount caused by the stronger trade winds of a La Niña.
Was that beyond you, Harry?
Maybe it would be easier for you to think of ENSO as a recharge-discharge oscillator, with La Niña as the recharge phase and El Niño as the discharge phase. I’ve even used cartoon-like illustrations in an attempt to make it easier for non-technical people to grasp. Here are a few illustrations from my book to help explain La Niña and the recharge phase:
If you’d like to read the posts in which I’ve discussed the “source of heat that keeps driving up SSTs and the overall global temperatures”, here are some links to posts starting in 2009. In other words, I’ve been discussing the “source of heat that keeps driving up SSTs and the overall global temperatures” for more than 3 years:
And
And:
And:
Wanna try again, Harry? You’re feeding me ammunition for a post at WUWT that will be read by an audience far greater than any you could hope to see at SkepticalScience. Anthony Watts loves posts that show the blatantly obvious falsehoods presented by SkepticalScience and its followers. It’s a losing proposition for you, Harry, so please continue.
BTW, “Publish, or perish,” applies to academia, not the rest of the world.
There are none so blind as them that will not see.
Seems very clear to me Bob.
“BTW, I’m looking for the unadjusted Contiguous U.S. Temperature data as a single time series. Any idea where I can find it?”
Bob,
Steve Goddard linked to the raw data here:
http://stevengoddard.wordpress.com/2012/07/12/ushcn-code-released/
When you download it and plot it you see that all the warming since 1895 is man-made – i.e. by govt.-sponsored hacks with an alarmist agenda:
As you can see, we have actually cooled slightly since 1875. Poof – there goes the warming!
Rob J: Thanks for the heads-up and link.
I asked Steven:
For those visitors who aren’t C++/STL literate, please consider providing the Contiguous U.S. temperatures as a single time series. I’d like to compare it to the sea surface temperatures of the U.S. Coastal Waters.
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