Burt Rutan: ‘This says it all and says it clear’

People send me stuff.

Engineer and aerospace pioneer Burt Rutan writes to me in an email today:

The chart the Alarmists do not want you to see.  Human Carbon emissions vs. The ‘Gold Standard’ global temperature data set (chart from C3).

The alarmists are now fighting hard to protect their reputations and their damaged careers, not fighting to protect a failed theory of Dangerous Human GHG warming.

co2-temp-rss

The grey bars represent CO2 emissions in gigatons (GT).

158 thoughts on “Burt Rutan: ‘This says it all and says it clear’

  1. Carbon dioxide goes up and temperature goes down? That meets the standard of IPCC science where any two things that happen at the same time are causally related…ha. Although, carbon dioxide does after all have a higher emissivity than air, which means it cools better than air…

  2. People will reasonably complain that this graph is misleading because the y axis for CO2 emissions starts at 250, thus making the bars give an exaggerated impression of the difference between emissions between 1983-1997 (331) and 1998-2012 (440).

    But, that said, the flat portion of the temperature line ought to nonetheless be compelling to most people.

  3. A graph this deceptive is about as bad as just plain lying, with its second carbon bar appearing more than twice as big as the first, even though 440 is only one third more than 331. A note should be placed above it to warn people. However the point it makes does have some validity.

  4. Wait a second: Changing lines at an exceptionally hot year? This really does look a little cherry-picked. It would take a lot to overcome this dramatic difference, but if we set the line-change at 2000 instead of 1998, it looks like both lines would still come out positive. Burt Rhutan has made outstanding points on the matter, but as dramatic as the visual is, I don’t think this is one of them.

  5. Wow ! Temperature (anomalies) and CO2 plotted on the same graph.

    I defy anyone; no matter their Statistical maths credentials, to make a credible logarithmic relationship out of that data.

    Yeah I know ; I only bet after the results are posted; well that way I always win.
    I bet Burt Rutan knows what a logarithmic curve is.

  6. “People will reasonably complain that this graph is misleading because the y axis for CO2 emissions starts at 250, thus making the bars give an exaggerated impression of the difference between emissions between 1983-1997 (331) and 1998-2012 (440).”

    I will reasonably complain that it is misleading because the temperature range is a minuscule +/- 1 degree. It should be expanded to at least +/- 15 degrees to compare the temperature change to some reasonable number like the range of daily highs over a year in, say, Tuscon AZ.

  7. “””””…..Stephen says:

    January 23, 2013 at 3:46 pm

    Wait a second: Changing lines at an exceptionally hot year? This really does look a little cherry-picked. It would take a lot to overcome this dramatic difference, but if we set the line-change at 2000 instead of 1998, it looks like both lines would still come out positive. …..”””””

    Continue the red line to 2001 if you like (I would); the rest of the blue line is still flatish, and heading down.

    Is it widely known out there in lalaland, that when a function reaches a maximum, the slope goes to zero before it becomes negative. As a corollary, when you look at the data in the vicinity of a local maximum, you will find a cluster of the highest values in the recent data.
    It’s also why the highest altitudes on earth are often up in the mountains.

  8. Burt: Good stuff. As a member of the ‘john doh’ clan, i think it’s a bit busy for the average warmer and members of congress, all of whom we have to convince! . I did study this as i’m interested but is there any way to simplify the essence. Can i suggest, with all due respect, comparing the same time frames. Changing the time frame on the bottom to the same time frame, i’m not sure what that does to the slope comparison, which is the main point of the graph, and so i’m not sure weather (!….scuse the pun) it’s apples to apples. Thx. Great to see you over here. Respect!

  9. Let’s see; the chart presents 30 years of temperature and CO2 data .
    And how old is the earth?? 2, 3 BILLION YEARS OLD.
    So, we are to believe that 30 years of data is meaningful !
    Sorry, but that is total bullshit.
    Look, the AGW thesis is one big lie, a fraud that is being perpetrated by a bunch of radical leftists who seek to impose their socialist/communist worldview upon the West, and in particular upon the bastion of capitalist evil, the USA.
    But , let’s get real, 30 years of data is meaningless. Sort of like flipping a coin ONCE and only once, and asking someone, “is it a fair coin.”

  10. Co2 is now the main driver of climate. Now, where did I hear that again?

    While natural processes continue to introduce short term variability, the unremitting rise of CO2 from industrial activities has become the dominant factor in determining our planet’s climate now and in the years to come.
    Last updated on 11 September 2010 by Michael Searcy.
    skepticalscience

    Indeed, co2 seems to be pulling temperature down slightly.

    On a more serious note, these CAGW scamming calamatologist are sitting in front of their screens absolutely petrified. We know from the likes of Phil Jones that the temperature standstill concerns them greatly.

    Dr. Phil Jones – 5 July 2005
    The scientific community would come down on me in no uncertain terms if I said the world had cooled from 1998. OK it has but it is only 7 years of data and it isn’t statistically significant.

    Dr. Phil Jones – 2009
    ‘Bottom line: the ‘no upward trend’ has to continue for a total of 15 years before we get worried.’

    Recently the Met Office tried to pull a fast one releasing its updated graph on Christmas eve on an obscure page of its website.

    Be in no doubt, these people are worried stiff about their already tarnished reputations.

  11. This graphic is just a bogus as those often presented by CAGW advocates, and is just as unpursuasive. It deserves to be criticized roundly at WUWT. Many posters here have made the point that there are complex processes governing atmospheric CO2 concentrations, that there are numerous sources and sinks, and that anthropogenic emissions are a minor contributor overall. It follows that temperature vs. measured CO2 concentration is the relevant relationship to examine. Evidence of flat – to slightly declining temperature with steadily rising CO2 concentration for an extended period is sufficient to show that CO2 is not a dominant factor driving temperature. There is no need for deceptive graphics.

  12. At this scale, noise dominates signal. The most potent graph of all is contained in a recent Church & White standard sea level study update. Oddly, this simple average of world tide gauges is nowhere to be found on this or any high traffic web site. In it, signal very much dwarfs noise, that signal being a rod straight linear trend going back to the 1800s. It’s plotted in yellow behind dark plots of adjusted “sea level.”

    http://climatesanity.wordpress.com/2011/05/09/links-to-church-and-white-sea-level-data/

    Extracted graph:

  13. Don’t you just love the internet thingy that very honest man Al Gore invented?

    Dr. Phil Jones – CRU – 13 February 2010
    “I’m a scientist trying to measure temperature. If I registered that the climate has been cooling I’d say so. But it hasn’t until recently – and then barely at all. The trend is a warming trend.”

    http://news.bbc.co.uk/2/hi/science/nature/8511701.stm

    I wonder what his view is now?

  14. “””””…..RobertInAz says:

    January 23, 2013 at 3:58 pm

    “People will reasonably complain that this graph is misleading because the y axis for CO2 emissions starts at 250, thus making the bars give an exaggerated impression of the difference between emissions between 1983-1997 (331) and 1998-2012 (440).”

    I will reasonably complain that it is misleading because the temperature range is a minuscule +/- 1 degree. It should be expanded to at least +/- 15 degrees to compare the temperature change to some reasonable number like the range of daily highs over a year in, say, Tuscon AZ……”””””

    Well and the rest; the northern summer Global Temperature range on earth, is more like 150 deg C, not 15 deg C. From about -90 deg C (-130 deg F) at a place like Vostok Station to about +60 deg C in the north African tropical deserts (on the ground).

    Well yes that is the cherry picked extreme range; but a range of 120 deg C is as common as dirt.

    And due to an argument by Galileo Galilei, there is a near infinity of points on earth that will have each and every value in between those extremes; and that happens every day in summertime.

    So who gives a rip if it might have warmed by 1 deg F in the last 150 years.

  15. The whole of data shows +1.31 per century.

    Jeez, most life on earth easily mitigates temperature changes far in excess of 1.31 diurnally.
    Where the heck is the dangerous climate change and who says that increase of this magnitude is not beneficial to ecosystems worldwide.

  16. Stephen says:
    January 23, 2013 at 3:46 pm

    Wait a second: Changing lines at an exceptionally hot year? This really does look a little cherry-picked. It would take a lot to overcome this dramatic difference, but if we set the line-change at 2000 instead of 1998, it looks like both lines would still come out positive…..

    You may have missed this:

    The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.”

    http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2008-lo-rez.pdf

    It’s all about the models my friend.

  17. Russ R. says:
    January 23, 2013 at 4:09 pm

    My those are some lovely cherries you’ve got there… did you pick them yourself?

    Got them out of the “climate scientist” baskets. They were culling out the cherries and keeping the pits. Burt decided the pits were worthless and the cherries were worth far more.

  18. It would take a lot to overcome this dramatic difference, but if we set the line-change at 2000 instead of 1998, it looks like both lines would still come out positive.

    Nah, that’s just as bad as starting in 1998, the peak of an El Nino. It’s starting in 2000, the pit of a La Nina.

    In order to be “fair” about it, you’d need to start before the El Nino (1998) or else after the La Nina (1999 – 2000).

    “Include” them both IN . . . or OUT.

  19. “So we’ve reached a tipping point: Put enough CO2 in the atmosphere and it begins to cool. ”

    Indeed. This proves we must now cut CO2 emissions to prevent a new ice age.

  20. Philip Peake says:
    January 23, 2013 at 3:32 pm

    That is actually a terrible graphic.
    Let’s see what was promised, a simple plot of temperature vs CO2.

    Whether you select “bar graph” like Burt has or “line graph” like several others with their links provided above, the results are the same–presentation mode doesn’t change the overall conclusion.

  21. MarkG says:
    January 23, 2013 at 4:35 pm

    “So we’ve reached a tipping point: Put enough CO2 in the atmosphere and it begins to cool. ”

    Indeed. This proves we must now cut CO2 emissions to prevent a new ice age.

    You’ll have this current administration and all those “climate scientists” so confused they won’t know what to do.

  22. evanmjones says:
    January 23, 2013 at 4:22 pm
    In order to be “fair” about it, you’d need to start before the El Nino (1998) or elseafter the La Nina (1999 – 2000).
    I did both with a combination of the two satellite data sets and it makes no difference. The slope is flat either way.

    http://www.woodfortrees.org/plot/rss/from:1997/plot/rss/from:1997.9/trend/plot/uah/from:1997/plot/uah/from:1997.9/trend/plot/rss/from:1997.9/trend/detrend:-0.0735/offset:-0.080/plot/esrl-co2/from:1997.9/normalise/offset:0.68/plot/esrl-co2/from:1997.9/normalise/offset:0.68/trend/plot/rss/from:2000.9/trend/plot/uah/from:2000.9/trend

  23. @ Ian Weiss

    Thanks, you saved me the trouble.

    In addition I would say that seeing as the alarmists are more concerned about atmospheric CO2 than bulk output (as it’s more closely related and relevant to the theories) it would therefore be more impressive to show the CO2 ppm. However, although you do see such graphs occasionally, I’d advocate plotting the number of parts per million above the 1880 baseline: as that’s when the modern temperature record started and, crucially, because they say temperature has been going up since then in line with ppm, it really is perfectly fair and mathematically sound to start the ppm axis at 280ppm, and plot the actual ppm line from 343ppm in 1983 to 363ppm in 1997 to 393ppm in 2012. That would depict a curve bending relentlessly upwards- even more so after the beginning of the 1998 flatline.

    And the difference between this approach and others I’ve seen would be that the y axis being at 280ppm would at least give a hint of the fact that 26.5% of all the atmospheric increase of CO2 since 1880 has occurred during that 14year decline. Even if we don’t plot it, we should be shouting that fact from the rooftops!

    An alternative would be to explicitly label the y-axis as being ‘ppm over and above 1880 baseline’ and plot 1983 as 63, 1997 as 83 and 2012 as 113, labelling the ppm just above the line at those dates. Seeing ’63;83;113′ would highlight those proportions above the y-axis and drive home the concept of the sudden recent rise during a flatline.

    And, last of all, a third option would be to label the y-axis ‘accumulation of atmospheric CO2 above 1880 baseline (%)’. The labelled points on the line would then be roughly 56% in 1983; 73.5% in 1997; and 100% in 2012.

    I think the third option would look really impressive. I’m no good with graphics…any takers?

  24. The basic problem is that global temperature rise has stopped. A continuation of this trend or a falling temperature trend clearly falsifies the hypothesis that manmade CO2 emissions cause rising temperatures. In the meantime, obviously climate scientologists have failed to predict reality.

  25. That sideways trend will be down soon with the PDO in decline, AMO topping and starting to roll over, the south Atlantic temp trend sharply lower and the solar cycle about to move into a 100 year quiet down cycle. That is the real alarm for some people that know it and they are starting to position their statements around it.

  26. Here is a HadCRUT4 chart from 1900/01 thru 2012/12. I wanted to compare the change in CO2 with temperature. It also has a regression from 2001/01 thru 2012/12, It has a regression of the same length that I can more around with the spinner. What I found is that the last time there was a period comparable to 2001/01 thru 2012/12 was that from 1967/06 thru 1979/05. The first had a trend of -0.24 C / century. The second was -0.23 C / century.

    I did not start the CO2 chart at zero because I wanted to compare the rate of change. Plotting from zero makes that difficult to see.

    http://www.mediafire.com/view/?996hm193b9x14k1

  27. If you go back a couple of more years (1979 maybe) you will see that 1983-1986 was actually a dip, and this the slope of the first part of the graph is quite exaggerated. (use UAH)

  28. evanmjones says:
    “Include” them both IN . . . or OUT.

    Which looks to be what they have done..both IN. They appear (through my wobbly eyes) to approximately cancel each other out as the start of the blue line.

  29. R. Shearer says:January 23, 2013 at 5:30 pm
    …….A continuation of this trend or a falling temperature trend clearly falsifies the hypothesis that manmade CO2 emissions cause rising temperatures………

    I think inserting PREDOMINANTLY between “emissions” and “cause” is the main point.

  30. I wish the AGW crowd would help reduce the amount of human produced CO2 by not exhaling for the next 24 hrs.

  31. So does this mean that the earth has been in equilibrium over the past decade or so, with incoming radiation balancing outgoing? Or is there an imbalance that is being absorbed by the oceans?

  32. Philip Peake says: Let’s see what was promised, a simple plot of temperature vs CO2.

    I’m not a scientist, but maybe it’s so simple you are just missing the point, or maybe you just don’t want to see what’s right in front of you:

    Temps going up, up, up during low CO2 period; temp goes flat during the current, higher CO2 period. I’d love to see a counter argument.

  33. So what if the graph is misleading?
    We are talking climatology standards here.
    I could push for real confusion to our leaders, for this is proof CO2 emissions from the west cause warming and Asian co2 causes cooling .(using climatology standards per IPCC)
    Geographical source is the key, to get the planet warming again we must emit more CO2 in North America.
    The “Climatologists” pushed a claimed correlation, over 22 years as significant and as causation.

  34. Not a fan of this graph for many of the reasons already stated. Lets avoid playing their game here please.

    I think the graph posted by D. B. Stealey deserves to be in the main article a lot more.

  35. Why do people always assume that a linear regression is appropriate for this data set? My engineering professors would kill me for assuming so. You must know the underlying relationship in order to trend plot scattered data. Sometimes it is linear, sometimes it is logarithmic, sometimes it’s a different relationship. If you just plot a linear regression you are fooling yourself into thinking there is a relationship that doesn’t necessarily exist.

  36. Some of you are forgetting that there were two large volcanic eruptions in the first data set of the graph, which mostly explains its positive slope.

  37. It’s refreshing to see a website where so many regulars are ready to call bullshit when they see something isn’t right. One of the reasons I come here.

  38. “”Chris says:January 23, 2013 at 7:27 pm: Some of you are forgetting that there were two large volcanic eruptions in the first data set of the graph, which mostly explains its positive slope.””

    Strongly agree. If it had not been for El Chichon (1983) and Pinatubo (1992) eruptions, the temp anomaly curve may have been flat throughout the time frame 1983-2012.

  39. D. B. Stealey says: Here is another view of the CO2/T [non-]corellation.

    D.B.–this is what I keeping harping on–it shows 1936 as the warmest year, at least up to 2011–yet we keep showing graphs on these postings that show 1998 and 2005 and now 2012 as being hotter globally. Could you elaborate on who did this graph (I see it is supposedly NOAA data) and what data set they (you) used? This graph looks consistent with what I’ve learned here, that the past has been cooled and the present made hotter–so more “current” graphs are incorrect.

    If 2012 is added in, what happens to this graph? Thanks for putting this up and I hope you elaborate.

  40. I believe that if we had had satellite average global temps from 1880, the graph would be dead flat like CET (Central England Temperature), charts. Most data from GISS and Hadcrut, ect., reflect UHI as well as fraudently manipulated as shown again and again by WUWT and Steven Goddards etc..What is really weird is that most climate scientist cannot consider that not only will temps remain flat for the next 1000 years but may actually FALL (as well as rise)

  41. The first 21 days of this January were the coldest in Idaho Falls, ID since they started recording temperatures way back in 1850! Average temperature was just 5.6 degrees F. Blame it on a stagnant high and temperature inversion and too much “bubbly” consumed on New Year’s (obligatory inclusion of “warming caused by CO2″, otherwise it might have been even colder).

  42. The AGW disciples are only going to say that this is a spurious graph and it’s an example of “going down the up escalator”.

  43. The US rivals Saudi Arabia in Fossil Fuel resources with enough Oil, Coal and Natural Gas estimated to last 600 years into the future. However, because of President Obama’s Catastrophic Anthropogenic Global Warming Theory (CAGW) aka [Climate Change] beliefs he has just declared war on the use of these valuable resources decreeing their costs should “skyrocket”. I wonder if he cares that his Climate Change Policies will hurt the poor the most? It seems the only people being enriched by President Obama’s Green Energy policies are the greedy rich. If these resources were freed up for use they would solve our unemployment problems, grow our economy, eliminate our debt and improve the lives of millions of poor people. So are there any viable alternatives to the proven and cheap power source Fossil Fuel provides? For example Green energy: wind turbines, bio fuel and solar? The dirty little secret is Green Energy is unreliable, more costly, does quite a bit of harm to Mother Earth and can provide only fraction of the energy fossil fuel does. President Obama’s belief in Man Made Climate Change is not based on empirical data. It is based on Models. Models that do not take into account the impact of the Sun, Ocean and Clouds on the Climate The real world data shows that the AGW models were wrong. As CO2 has risen the temperatures have not as the models predicted. Given these facts President Obama should reevaluate his belief in Climate Change and start taking advantage of the vast energy resources available to us. The use of these resources would improve the lives of millions of people. especially the poor. Is President Obama’s dream for American one of desolation and hopelessness not growth and prosperity? Do they mirror the dreams of Greenpeace that do not reflect the dreams of the American people for a better more prosperous life?

  44. If you don’t explain WHY temperatures have not increased in accordance with CAGW theory, most people will assume the the lack of warming is due to some unexpected cycle that will soon change direction resulting in rapid warming to catch up with the projections. The CAGW theory says that increasing CO2 will cause water vapor in the upper atmosphere to increase (especially over the tropics), making the greenhouse effect (GHE) stronger, thereby increasing temperatures. Here is the graph of upper atmosphere water vapour versus CO2 in the tropics.

    Increasing CO2 reduces upper atmosphere water vapor, allowing heat to escape to space. The correlation R2 = 0.729 is higher than most any correlation in climate science.

    But we continue building useless, burning windmills. See animation:

  45. No mention in this whole set of the anthropogenic CO2, the supposed cause. Most of the CO2 show in the natural material, not the stuff put into the atmosphere by burning fossil fuel and other industrial processes. It is all interesting and goes to show that the temperature may not be driven by CO2, but the real problem is the political facts that are screwing the energy processes and destroying our economic systems. That is what keeps me awake at night.

  46. This is crazy talk – I just saw the Al Sharpton thread and he knows for damned sure what he is talking about. This Rutan guy has to be some kind of right winger – probably an engineer, not a for real scientist like Michael Mann.
    /sarc

  47. Yea, I won’t be whining any longer. I unfortunately read this post before I read, “A question for Zeke Hausfather”

    So I withdraw my question about the graph. I now have an understanding of what’s been going on with 1936, 1998, 2005, and 2012. Whew… could not wrap my head around why we kept accepting “their” data for the “hottest ever” years and such—(whoever they are at any given time). I could dance for joy with this post—thank you Anthony for putting the “Zeke” post up, one of the most useful posts ever.

  48. A good number of commenters have complained that the graph from mr Rutan is misleading , because of misscaling or because he [breaks] up the temperature anomaly curve in 1998 etc. , but it seems to me they totally ignore the point i think he is really making even though it glares in their faces, the point being the fact that from 1998 till present the accumulated emission of 440 gigatons CO2 of attributed human activity for those 15 years is around 33% higher than the 331 gigatons for the previous 15 year period from 1983 to 1987 , while the linear anomaly trendlines for the same two periods differ by around 1.25 °C centurywise, with the lower emission period being the clear winner of the anomaly championship wiggle race ( ” by a factor of 16 surely unprecedented since long before beginning of history :-) /sarc”).

  49. I just bet ya will eventually come to realize… That warming was caused by a lack of volcanic activity. Lack of stratospheric dust and SO2.

    1995 seemed to be a turning point. A point where activity began to slowly ramp up noticeably after Pinatubo settled out.

    Well kids, it looks like a need to lay low for a while. My big mouth has attracted attention. Love it here. Ta ta for now.

    Eddie

  50. You say its warming,
    And i say its cooling,
    You say its cooling and i say its warming,
    Cooling, warming,warming, cooling,
    Lets call the whole thing ooooooooffff.

    Can we have our taxes back now?

  51. We should be near solar max for this cycle. Wonder what the CAGW calamatologists are going to say when the multiyear line starts going down, say by 2020? [ not really, they should just stfu ]

  52. Box o’ Rocks says:
    “We are warmer now.
    2012 is still warmer than 1982!”
    ==================================

    Although what you wrote is true, please note the name of IPCC’s theory is Anthropogenic Global WarmING and not Anthropogenic Global WarmER.

    It’s becoming obvious the Earth’s temperature anomalies aren’t cooperating with IPCC’s climate model projections.

    In NASA’s 2008 State of the Climate Report, it says periods of no warmING exceeding 15 years would be highly improbable and if such a phenomenon were to occur, it may mean the climate models contain some erroneous assumptions…

    Well, it’s now been 16 years of no warmING, despite annual CO2 emissions increasing about 60% since January 1997….

    With this year’s La Nina cycle, it now seems highly likely 2013 will make 17 years of no warmING.

    It’s now fairly safe to assume NASA’s assessment is correct, and there is a high probability the GCMs got something terribly wrong.

    This isn’t a cherry-picking data. It’s simply a statement of observed phenomenon.

    One man’s cherry-picking is another man’s cherry-flavored Kool Aid…

  53. How many more years of the temperature standstill is required before the likes of the IPCC et al must openly revisit the theory and pronounce their findings to the world? I have 15 years (achieved) and 17 years (very soon). Yet all I see is that they alter their projections (IPCC leak) and Met Office (pulling a fast one) and speculate about the causes of lack of warming, having told us that co2 is now the dominant driver of global warming.

    Refeences: NOAA / Santer et al

  54. Steveta_uk said:

    “Sorry, but not impressed. Here’s another, equally valid way of looking at exactly the same data”

    Not equally valid.

    It shows a steady monotonic CO2 rise but our emissions have accelerated fast whilst the CO2 rate of increase has barely changed at all.

    That suggests that the CO2 increase is primarily natural and so if it were linked to global temperatures it would still not be our fault.

  55. The chart the Alarmists do not want you to see.  Human Carbon emissions vs. The ‘Gold Standard’ global temperature data set (chart from C3).
    ————-
    How on earth can it possibly be called “the chart the alarmists don’t want you to see” when the alarmists published the chart in the first place.

    I could just as intelligently say Burt designs and builds planes that he doesn’t want people to fly in.

  56. The graph is yet another example of perverted data analysis.

    Here is an exercise in analysing trends. Just continue the early part of the trend , the big fat red arrow, and extend it further. Then measure the area above the trend line and compare it with the measurement of the area below the trend line. I say those two areas are equal in magnitude and cancel each other out. This is what you would expect for random variation about a constant trend.

    Why don’t the auditors make a fuss about these kind of data analysis abuses?

  57. The problem is that CO2 is only one forcing factor in global temperature. For instance, Rutan’s blue line commences with the large temperature spike due to the el nino year of 1998 which is die to pacific ocean currents.. Other factors affecting temperature are la nina years, solar cycles, volcanic eruptions, airborne particulates, cloud cover etc. etc.

  58. Philip Shehan says:
    January 24, 2013 at 4:15 am

    What volcano erupted between 1998 and 2012?
    What other solar cycles have occurred between 1996 and 2012 …. that we don’t know about and that the so-called “climate scientists” are telling us don’t affect climate anyway?
    What is the change in MEASURED aerosol levels worldwide? (Local changes – such as India and China? Certainly. Global changes in aerosol levels are ????)
    What measured changes in cloud cover have occurred between 1994 and 2012?

    You’re waving your hands and claiming “effects” from theoretical things that affect climate…. But you forget that there were no actual such changes in the last 16 years.

  59. RACOOK.

    Simply pointing tothe fact that temperature data is very noisy due to the multiplicity of factors affectingtemperature. You can’t expect a smooth correlation between one factor, CO2 concentration, and the temperature. Rutan’s distinction between 1983 and 1997 and 1998 forward demonstrates how one particularly strong factor can affect short term data sets.

    Going back to the beginning of Muana Loa data in 1958 and comparing temperature from that date shows a fairly good correlation through the noisy temperature data.

    http://www.woodfortrees.org/plot/hadcrut3vgl/from:1958/mean:12/plot/esrl-co2/from:1958/normalise/scale:0.75/offset:0.13

  60. Philip Shehan says:
    January 24, 2013 at 4:15 am

    The problem is that CO2 is only one forcing factor in global temperature. For instance, Rutan’s blue line commences with the large temperature spike due to the el nino year of 1998 which is die to pacific ocean currents.. Other factors affecting temperature are la nina years, solar cycles, volcanic eruptions, airborne particulates, cloud cover etc. etc.

    Have you been watching over the years? We were told that co2 is now the main driver of climate. Natural causes of variations would increasingly take a back seat. One simulation rules out 15 years of of no warming, while another rules out 17 years of no warming. These periods are so we can distinguish out the noise from the human ‘fingerprint’. THAT is the issue.

  61. Philip Shehan,
    Below is what I was referring to:

    “The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.”

    http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2008-lo-rez.pdf

    “A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature. ”

    http://www.agu.org/pubs/crossref/2011/2011JD016263.shtml

    “The LLNL-led research shows that climate models can and do simulate short, 10- to 12-year “hiatus periods” with minimal warming, even when the models are run with historical increases in greenhouse gases and sulfate aerosol particles. They find that tropospheric temperature records must be at least 17 years long to discriminate between internal climate noise and the signal of human-caused changes in the chemical composition of the atmosphere.”

    https://www.llnl.gov/news/newsreleases/2011/Nov/NR-11-11-03.html

    “The multimodel average tropospheric temperature trends are outside the 5–95 percentile range of RSS results at most latitudes. The likely causes of these biases include forcing errors in the historical simulations (40–42), model response errors (43), remaining errors in satellite temperature estimates (26, 44), and an unusual manifestation of internal variability in the observations (35, 45). These explanations are not mutually exclusive. Our results suggest that forcing errors are a serious concern.”

    http://www.pnas.org/content/early/2012/11/28/1210514109.full.pdf

    http://www.pnas.org/content/early/2012/11/28/1210514109

  62. Philip Shehan says:
    January 24, 2013 at 4:15 am

    The problem is that CO2 is only one forcing factor in global temperature.
    No, the real problem for Warmists is that C02, and in particular man’s C02 has so little effect that it can hardly be called a “forcing”. The take-home is that it’s nothing we should be alarmed by, and most certainly nothing we should be spending multi-$billions on, and forcing energy prices up. It’s a non-problem. Cooling is something we should be concerned with though.

  63. Can someone remind me if the step increase around 1998 (I know an El Nino year but then persistent higher temperatures) is actually valid? Or was there a c 0.2 degrees adjustment somewhere in the data? Because that is what it looks like. I’m aware that this has been looked at a lot but being a simple sole trained in data analysis we seem to have flat, jump, flat – but no explanation for this shape? Just wondering…

  64. Anthony,
    Several years ago I read a piece by Joe D’Aleo on the urban island effect and “corrections” that were made in 1997 to fix it. Joe showed that the corrections were additive and not negative, so instead of reducing temperature, they were added. He used, if I recall, a Central Park location to show the error.
    On all these temperature graphs you see a step function in the late 1990s and, my guess is that it is not an actual increase but the backwards and incorrect official fudge factor that Joe noted.
    I think it would bear a note to Joe and get his comments on what may be going on here, since, if there is an incorrect modification to the temperature record, then there might not have been much of an actual increase. Instead we would have a gradual increase, a flattening and, based on the past, an eventual decrease.
    If my memory is right and Joe can confirm it, you will have another nail in the manipulated temperature record coffin.

  65. While I agree with the point Burt makes, there are several things wrong with the graph.

    1. The bars for CO2 start at 250.

    2. The important number is not added CO2 per time. The important number is absolute atmospheric CO2 concentration in ppm.

    3. The atmospheric CO2 concentration should be plotted logarithmically (as any doubling of CO2 concentration leads to the same absolute increase of temperatures) to see relevant changes. (An increase from 250 ppm to 500 ppm has the same effect as going from 500 ppm to 1000 ppm – hence the need for a logarithmic scale).

    I think one can make the point Burt attempts, but with a graph that is correct. Just because the alarmists do shoddy hockey-sticks gives us no reason to do shoddy anti-hocke-sticks.

  66. Tony Mach on January 24, 2013 at 5:52 am
    While I agree with the point Burt makes, there are several things wrong with the graph.

    [ . . . ]

    I think one can make the point Burt attempts, but with a graph that is correct. Just because the alarmists do shoddy hockey-sticks gives us no reason to do shoddy anti-hocke-sticks.

    – – – – – – –

    Tony Mach,

    Or we can juxtapose both charts, your suggested one & Burt’s, next to each other. We get an even better understanding through comparison. Nothing would be lost in having both.

    John

  67. Thanks to all those who did graphs going back to 1900 or more with atmospheric CO2 y-axis starting at 280. It does show up the lack of a clear link.

  68. I find useful both Burt’s chart and many of the other charts that commenters suggested. I thank Burt for prompting this educational discussion on the failures of the arguments of alarming AGW by CO2.

    To me the two charts most devastating to the IPCC’s support of alarming AGW by CO2 are Holocene charts similar to the following two charts at the top of this WUWT post:

    http://wattsupwiththat.com/2013/01/21/its-snowing-and-it-really-feels-like-the-start-of-a-mini-ice-age-london-mayor-boris-johnson/

    What alarming possibility about AGW from CO2 are people talking about ?

    Anthony, thanks for the thousandth time for your truly open venue.

    John

  69. @ Charles Bruce Richardson Jr.
    Thanks for that.

    @ Tokyo Boy
    I find your claim incredible. Can you give me a link to any article that supports it? Am I missing something? Was that supposed to be sarcasm?

    @ Lazy Teenager
    You seem to be trying to say so much more than you actually trouble yourself to put into words. (A technique which deprives you of any grounds to decry those who don’t follow your reasoning.) My gues is that your crypticism about ‘the auditors’ is that you perceive hypocrisy in those (such as Steve McIntyre) who call out the nonsense in statistical abuses by the Hockey Team, but not in this particular graph.
    To which the reply is, it has already repeatedly been debunkend here. There is therefore no need to do it again, nor hypocrisy in not doing so again.

    My two cents worth is as follows:
    I want to go on record as decrying this graph. I call on everyone here who considers themselves to be an honest skeptic to also touch base and decry it. Truthful though it may be, for a given value of truth, it really is intentionally misleading.
    That said, I propose to use the graph to demonstrate to an alarmed friend that being skeptical is not the same as being a Holocaust Denier, and that there are reasonable grounds to re-open a closed mind about the issues. Then, of course, I must confess that this graph is almost as dishonest as Mann’s ‘Nature Trick’.

  70. IMO, the people criticizing the graph are missing the point of it. Mr. Rutan is fighting back using the alarmists’ own style of presentation. How often have we seen graphs that show a short period of time (e.g., 20-30 years) with what seems like a worrisome upward trend? So Burt just took a similar length of time, but included the most recent data. Even without the trend lines, this shows that something isn’t following the usual CAGW predictions.

    And as for the CO2 bars, well I don’t think that’s misleading, either, because it fits in with what the alarmists have done, too. They often show CO2 on a similar scale in order to magnify the extent of the change visually. (And no, I’m not going to include links, we’ve all seen this sort of thing before.)

  71. Day-By-Day,

    Here is where that last chart came from. Lots of good charts and info there, like this, which contradicts Shehan’s nonsensical fabrication. I wonder how many hours he spent re-jiggering the WFT database to get that phony overlay? Here is the true non-correlation between CO2 and T. Note that global warming is not accelerating. In fact, global warming has stalled for the past decade at least.

    And here is the only measured correlation between CO2 and T: it clearly shows that ∆CO2 is the result of ∆T — not vice-versa. Because there is no such vice-versa. Empirical evidence proves that CO2 follows temperature. There is no equivalent chart showing that CO2 leads temperature. At current concentrations, CO2 has essentially zero effect on global temperature. Planet Earth agrees.

  72. Warmists used the 97-98 El Nino driven temperatures to proclaim that the warming was irrefutable and that “the science is settled”! I argued (in online discussions back then) that it was inappropriate to use the El Nino as a proof of man-made global warming, and that it would come back to bite them in the backside. They persisted in using it to claim a dramatic warming trend.

    Now…it has come back to bite them in the backside. Now it is ‘cherry picking’ if we show the trend starting from that strong El Nino year. Sorry warmists…we are just following your rules.

    Tad is absolutely right. This is just the same style presentation as the warmists have always used. Show the graph far and wide. Make it as well known as the bogus hockey stick graph. Make it a modern day icon. Once we stop this stagecoach from going over the regulatory cliff, we will have plenty of time to teach proper graphing in science 101.

  73. Philip Shehan says:
    January 24, 2013 at 4:39 am

    Doesn’t match the wiggles, so the similarity is superficial. This does match. This shows the CO2 rate of change is affinely related to temperatures, which leads inexorably to the conclusion that temperatures lead CO2, and therefore CO2 is causally related to temperature, and not the reverse. Moreover, it accounts for the whole enchilada, and human inputs are superfluous, i.e., rapidly sequestered and of little consequence.

  74. Eh, the graph isn’t terrible. The Y-axis thing is very common in business presentation.

    Would it better with a zero-bounded Y-axes? Sure. Is it as bad as “hide the decline?” Not hardly.

    A much more salient complaint is that it would have made a lot more sense to show atmospheric concentration rather than emissions.

  75. Old wine in new bottles, old arguments in new pictures–nothing really in here but a variant presentation of a well-worn argument, a discussion of whether or not the presentation is disingenuous, and Burt Rutan’s name attached to it. I’d have attributed this to a slow news day, were it not for the other dozen articles that appeared the same day–perhaps a backlog being cleared? Anyway, the scale for the carbon bars is misleading, as is breaking up the curve into two arrows, let alone the choice of the break. I sort of hope Mr. Rutan knows this, and is, perhaps overenthusiastically, trying to emphasize a point, rather than simply being confused into believing this graphic himself. Meanwhile, realeased to the general public, this graphic might score some points, but these would have to be weighed against the backlash that would follow as some, at least, found out that it uses some simple ruses, at least one of which is taken straight from the pages of How to Lie with Statistics.

  76. JazzyT,

    Explain this, which clearly shows the non-correlation between CO2 and T.

    The central issue in the debate is whether ∆CO2 causes ∆T. Obviously, it does not.

    The alarmist crowd has cause and effect backward. Since their premise is wrong, their conclusion will necessarily be wrong. And in fact, that is what the planet is telling us.

    There is no measurable AGW. And there never was.

    • • •

    Doug Jones,

    Excellent chart. Thanks.

  77. People will reasonably complain that this graph is misleading because the y axis for CO2 emissions starts at 250, thus making the bars give an exaggerated impression of the difference between emissions between 1983-1997 (331) and 1998-2012 (440).

    But, that said, the flat portion of the temperature line ought to nonetheless be compelling to most people.

    No, that’s not the misleading part. The misleading part is the missing 287 degrees Kelvin. If we were to draw the CO_2 the same way that the temperature is portrayed, as an “anomaly”, the first bar would be roughly -55 GT, and the second bar would be +55 GT. If we were to portray both CO_2 emissions and temperature on an absolute scale, the CO_2 emitted would go up by roughly 1/3 while the temperature went up — well, you wouldn’t be able to resolve the variation compared to the thickness of the line at this scale!. It is, after all, less than 0.4 C out of almost 300 degrees, roughly one part in 700. A one pixel thick line would be absolutely flat at most reasonable screen resolutions.

    I’m just sayin’…

    On the other side of the coin, fitting the two segments this way is entirely arbitrary and rather meaningless. Fitting the entire interval gives you a linear trend somewhere in between, say 0.1/decade give or take or 1 degree a century. Or maybe a bit less. It doesn’t really matter, because a linear fit has no more meaning than a quadratic fit or a logistic fit or a skewed gaussian curve with kurtosis fit. Some of these might work better than others, but lacking a meaningful basis for the model selected you might as well just draw a fairly smooth curve through the data by hand and say “Look, I’ve found a good fit!”

    If you wanted to do something sorta-meaningful, one could import the curve and the two CO_2 data into R, block average the first half and the second half of the temperature series, do a linear model between the two data points each, and discover that there is a comparatively low p-value, suggesting that the relationship is “significant”. Or import the actual CO_2 concentration as a timeseries with the same number of points, form a linear model, and again find from the p-value that the relationship is “significant”. Or import data from the stock market over the same interval, for a linear model, and find that the relationship is “significant”. Or import data from the annual measured height of my oldest son, for a linear model, and find that the correlation is “significant”.

    Sadly, as it is, the graph up above is utterly devoid of statistical or scientific meaning. It doesn’t disprove AGW. If anything it supports the hypothesis, although that support is pretty weak, barely better than an even bet.

    If anybody wants to debate the actual statistical significance of this or that, well, I’ve got R loaded and ready to go. Bring it.

    rgb

  78. Meanwhile, realeased to the general public, this graphic might score some points, but these would have to be weighed against the backlash that would follow as some, at least, found out that it uses some simple ruses, at least one of which is taken straight from the pages of How to Lie with Statistics.

    Yes, exactly. A wonderful book. And of course presenting the global temperature as an anomaly in the first place is right out of one of its chapters, is it not? So that every curve ever presented of Global Warming commits the same sin. Presenting it with the CO_2 “anomaly” on a similar scale is just as bad. Chopping the bottom part of the human fraction of CO_2 — awful. Ignoring the rest of the CO_2 contributed by non-human sources, or the CO_2 sinks — evil. Fitting two linear models at a more or less arbitrary break point — argumentative, not meaningful.

    Why bother? The data is what it is, and says what it says without any fits at all unless the fits have some specific basis!

    Seriously, the best that can be said for the data is that it weakly supports the AGW hypothesis there is a positive linear trend in the overall data for both CO_2 and temperature. If you think that the AGW hypothesis posits a linear relationship, which it doesn’t.

    rgb

  79. I see little reason to declare my graph a “nonsensical fabrication”. It is very simple really. I have plotted the Muana Loa CO2 data since such reords began and the temperature data from the same period and shown that there is a rather good overlay.

    A number of other graphs have done precisely the same thing, using shorter time periods and adopting different y-scaling.

    Bart: could you explain how the use of the Derivate WFT function clarifies things in the presentation of your graph?

    Derivative – Take the first derivative of the data (each sample has the one before subtracted)

  80. Doesn’t match the wiggles, so the similarity is superficial. This does match. This shows the CO2 rate of change is affinely related to temperatures, which leads inexorably to the conclusion that temperatures lead CO2, and therefore CO2 is causally related to temperature, and not the reverse. Moreover, it accounts for the whole enchilada, and human inputs are superfluous, i.e., rapidly sequestered and of little consequence.

    I have to admit, Bart, that the curve you present is at least the kind of curve that would be enormously compelling with just a little more underpinning. At least it kinda slaps you in the face and says “There is something here that needs to be explained”, whether or not one accepts the explanation you offer.

    rgb

  81. I still see flat, jump flat!

    It’s ENSO!

    DaveE.

    I tend to agree. But the time baseline is absurdly short to make any dramatic assertions in a (probably) highly multivariate function with many factors contributing with many timescales and probably multiple internal nonlinearities. Coincidence is too likely, or it might have been ENSO then, but ENSO might produce this jump only when three other variables (e.g. the phase of the PDO, the phase of the moon, whatever) have just the right values. You can’t read too much into the one-dimensional projection of a curve that really lives in five or ten dimensions.

    I don’t think people appreciate this. There may be no simple predictors.

    rgb

  82. Philip Shehan says:
    January 24, 2013 at 1:27 pm

    “Bart: could you explain how the use of the Derivate WFT function clarifies things in the presentation of your graph?”

    The graph shows that CO2 concentration is related to the temperature anomaly by

    dCO2/dt = k*(T – To)

    where “k” is a coupling constant, and “To” is an equilibrium temperature baseline. This relationship holds to a high degree of fidelity over the modern era since precise measurements of CO2 began.

    We choose “k” and “To” to match the two series. Then, when we integrate that function of temperature, starting from the initial CO2 measurement, we get a very close match to the absolute level of CO2 as a function of time, as we must, since we are integrating essentially the same area under the rate curve.

    It happens that, when we choose “k” such that the variations match, the long term slope also matches. The important part is this: that value of “k” produces an excellent match of the curvature in the integrated result. Since the accumulated human emissions also have a curvature, in order to add them in consistently, we would have to back off “k”. But, if we back off “k” significantly, we will no longer match the variations in the original plot.

    The upshot is, there is no room for significant human contributions. The CO2 system on the Earth is very tightly regulated, and human emissions are readily dealt with. But, the equilibrium level changes with temperature, and that is what drives the level of CO2 concentration in our atmosphere.

  83. I should have added, the relationship

    dCO2/dt = k*(T – To)

    squarely directs the arrow of causality in the direction of temperature to CO2. Why? Well obviously, on the one hand, it makes no sense that temperature would depend on the rate of change of CO2 – if CO2 ever stopped rising, T would go back to To, no matter how much CO2 had accumulated.

    Another point: the derivative has a leading phase. For example, if we set T = To + a*cos(w*t), then

    dCO2/dt = k*a*cos(w*t)

    hence

    CO2 = (k*a/w)*sin(w*t) + CO2(0)

    Since the sine function lags the cosine function by 1/4 cycle, we see that changes in CO2 occur after the changes in temperature.

  84. As to how the integral relationship comes about, I can only offer my own speculations. It can help to consider the ocean currents. I hasten to say that I am NOT claiming that this IS what is happening, but it is food for thought as to how it MIGHT be happening.

    Ocean waters are continually downwelling near the poles and upwelling in the tropics. The waters going down have a CO2 concentration which is dependent on the surface temperature. The upwelling waters, too, give up the CO2 they are carrying dependent on surface temperature. Since this is a continuous transport to and from the deep oceans, the rate of change of CO2 is a function of surface temperature

    dCO2/dt = F(T)

    A first order Newton expansion of F(T) is then

    dCO2/dt = F(T0) + F'(T0)*(T – T0)

    setting

    k = F'(T0)
    To = T0 – F(T0)/k

    then leads to the affine relationship

    dCO2/dt = k*(T – To)

    Other continuous transport processes than the oceans act in the same way.

    Great so, now what happens to the human emissions? Assuming there are robust permanent (or, at least, semi-permanent) sinks, we can posit a dual set of differential equations of the form

    dCO2/dt = (CO2eq – CO2)/tau + H

    dCO2eq/dt = k*(T – To)

    where H is the human input rate, and tau is a time constant.

    CO2 now tracks the CO2eq level while, if tau is small, the influence of H is rapidly diminished. How could such a two-tiered response to input CO2 come about? Well, I have several ideas.

    The simplest has to do with where the input to the atmosphere originates. If we neglect phytoplankton for a moment (assuming perhaps that they are not terribly active in the upwelling and downwelling regions, which certainly seems likely enough for the extremely cold downwelling ones) then the CO2 coming out of the ocean, or inhibited from going into it, has to travel a long way to reach land sinks, becomes well mixed in the atmosphere, and takes a long time to be sequestered due to the slow diffusion process. But, the CO2 generated on land near the surface can be rapidly sequestered by land sinks.

    That’s my conjecture and, as such, I am not going to get into any nasty quarrels with people with a chip on their shoulder about it, as so often seems to happen whenever you offer up anything. Others are free to consider other possibilities. But, the result has to conform to the observation. And, the observation says that CO2 is temperature dependent, and humans have, at most, a small effect.

  85. In response to the question: “I wonder how many hours he spent re-jiggering the WFT database to get that phony overlay?”

    Not very long at all actually. I used a plot from an earlier post as a template.

    Steveta_uk says:
    January 24, 2013 at 2:59 am

    As you can see there are precisely two series in my plot. The only additional functions added are the mean for a 12 month smoothing of the data and an offset and scaling to bring them into line.

    In fact spending just a little more time gives a better fit:

    http://www.woodfortrees.org/plot/hadcrut4gl/from:1958/mean:12/plot/esrl-co2/from:1958/normalise/scale:0.75/offset:0.2

    It is probably the simplest of all the WFT graphs presented in this thread.

  86. Bart: Thank you for your detailed explanation. It is a bit complex for me to try to understand all in one go but I will give it some consideration.

  87. Thanks, Bart. But I doubt you’ll get an answer, or even an acknowledgement.

    Regarding the simple-minded overlay of a temperature graph onto a CO2 graph, that means nothing, because it does not show any cause-and-effect relationship. You and I have both shown the CO2/T cause-and-effect: ∆T causes ∆CO2 — not vice-versa. There is no graph like this showing that CO2 leads temperature. The chart proves that changes in CO2 follow temperature.

    Finally, Shehan is still posting his thoroughly debunked SkS chart. There is no credible scientific evidence showing accelerating global warming. None. All of the empirical evidence available shows that global warming is decelerating. Just because John Cook can post a fabricated chart does not mean it is legitimate; it isn’t. This is the real deal, straight from HadCrut. Shehan appears to be about as honest as Greg Laden.

  88. Philip Shehan says:
    January 24, 2013 at 4:10 pm

    I appreciate the consideration.

    The problem with your plot showing somewhat of a match is that it is entirely superficial. It’s basically a flip of the coin, in that they have the same sign for relatively shallow curvature. With that, you can generally get a pretty good fit between arbitrary data sets with an affine transformation merely by using a least squares fit to find the best coefficients of that transformation.

    When, however, you can match the fine detail as well, as we do comparing the CO2 rate of change with temperatures, then you know you’ve got something beyond mere chance.

  89. In case you have not noticed there is an individual on this thread who is incapable of disagreement without indulging in personal abuse.

    I have not posted an SKS chart here.

    I have not spent hours rejigging the WFT data base to get a phony overlay.

    I yield to this person’s expertise in that matter. On another thread he presented the following graph in order to support his contention that the temperature data was “unequivocally” fitted by a straight line.

    http://tinyurl.com/bkoy8or

    Shorn of the irrelevancies, in particular the entirely superfluous line at 9 on the y scale, the fit is hardly “unequivocal”.

    http://www.woodfortrees.org/plot/hadcrut3vgl/compress:12/offset/plot/hadcrut3vgl/from:1880/to:2010/trend/offset

    In response to my repeated question as to why he had presented such a needlessly complicated graph, especially the inclusion of the pointless yellow line, the answer I finally got was:

    “I do not care to waste my time on “series 7 and the horizontal yellow line”.

  90. Philip Shehan says:

    January 24, 2013 at 4:39 am

    RACOOK.

    Simply pointing tothe fact that temperature data is very noisy due to the multiplicity of factors affectingtemperature.
    =========================
    Noisy data is a contradiction in terms. There is data, and there is noise, but there is not noisy data.
    There may be questions about the fidelity of data, but never about the fidelity of noise.
    Noisy data is an invention of noisy global warmers who try to explain away the last sixteen years .

  91. Well I don’t understand howcome Burt Rutan suddenly found himself at the center of an Italian firing squad.

    I just took it that Burt found this data in one of the usual places, and used it to make his arguments.

    So why is everyone shooting at him, when virtually all souces of this sort of data use the same sort of phony axes; and in the case of GISSTemp, Hanson keeps changing the data anyway.

    No matter how you cut it, there is now a flat period that has persisted since somewhere back around 1995 (sans 1998 el nino).

  92. Bart, I agree that the match between data is superficial in the sense that no explanation for the match is offered and no cause and effect relationship is postulated.

    But that is the problem with this whole thread, as many commentators have pointed out.

    Mr Rutan’s diagram is even more superficial, superimposing two bar graphs on temperature data for a limited time period and overinterpreting the data.

    mpainter, I can assure you that “noisy data” is not a term limited to the dscussion of the last 16 years of temperature data. It is a term I have regularly used and encountered in over 3 decades of research experience in the physical and biomedical sciences.

    It refers to the difficulty of detecting the real “signal” in the presece of background “noise”. Thus the term signal to noise ratio, which has a mathematical formulation. A low ratio can be described as a noisy signal or noisy data.

    “Noise” is a term that can be used in at least two contexts.

    In my field of specialisation”noise” refers to truly random noise associated with electromagnetic interference from various sources. Its like the spots and hiss that appeared on old television sets that were off channel. Some of the hiss and spots come from the big bang.

    It is also used in the context of temperature data here to refer to real physical effects which are too complicated or whose contribution is not sufficiently well understood to allow meaninful detailed analysis.

    Global temperature results from a host of contributing factors, giving rise to the ups and downs.

    These are not truly random “noise” but are generally short lived causal factors. They may be well understood but considered as minor variations which can be ignored in approximations. They may be cyclical like solar cycles, or unpredictable like El Nino and La Nina events whose mechanisms is not sufficiently understood. There may be unkown causal factors contributing to the “noise”.

    Long term underlying trends can be inferred from the data by overlooking the fine detail resulting from this “noise”

  93. Philip Shehan says:
    January 24, 2013 at 7:34 pm

    “Bart, I agree that the match between data is superficial in the sense that no explanation for the match is offered and no cause and effect relationship is postulated. “

    No, it is superficial in that it is not at all unlikely that you could make such a match by random chance. The match isn’t good. The two series merely lie somewhat in the vicinity of each other. The only match is of two underlying second order polynomials, and you’ve chosen the constant and linear terms for the best match, so the only thing you’ve got to hang your hat on is that they both bow out slightly in the same direction. That’s pretty thin gruel.

    Compare such a superficial match with that of the CO2 derivative and temperature. They match in all the above, but they also match in all the little squiggly stuff going on. If you try matching the derivative of the CO2 and the derivative of the temperature, where a lot more detail is revealed, you quickly see that there is not really any match at all. The temperature derivative has no real trend, and it leads the CO2 derivative in all the bumps and squiggles.

  94. D.B. Stealey says:
    January 24, 2013 at 12:23 pm

    JazzyT,

    Explain this, which clearly shows the non-correlation between CO2 and T.

    [D.B. Stealey’s link: http://www.woodfortrees.org/plot/rss/from:1995/plot/rss/from:1996.83/trend/plot/esrl-co2/from:1996.83/normalise ]

    Here, I fixed it for you:

    http://www.woodfortrees.org/plot/rss/from:1979/plot/rss/from:1979/trend/plot/esrl-co2/from:1979/scale:0.008/offset:-2.81

    Note that there are three or four excursions below the trendline in the past that are comparable to the most recent ones.

    The central issue in the debate is whether ∆CO2 causes ∆T. Obviously, it does not.

    That’s not so obvious if you’re willing to look at all the data.

  95. Bart says:
    January 24, 2013 at 10:17 pm

    Philip Shehan says:
    January 24, 2013 at 7:34 pm

    “Bart, I agree that the match between data is superficial in the sense that no explanation for the match is offered and no cause and effect relationship is postulated.“

    No, it is superficial in that it is not at all unlikely that you could make such a match by random chance. The match isn’t good.

    Two such curves could match by chance, or there could be a common cause, or cause and effect could be reversed. For such cases, we have to fall back on other information such as other observations and/or theory.

    Compare such a superficial match with that of the CO2 derivative and temperature. They match in all the above, but they also match in all the little squiggly stuff going on.

    It’s been widely ackowledged, for quite some time, that the squiggles in the Keeling curve (CO2 vs. time) are due to plants taking up CO2 as they grow in spring and summer, and releasing it as plant matter (and fallen leaves) decay in late summer, autumn, and maybe early winter. Since land masses are concentrated in the Northern hemisphere, this happens more in the NH growing seasons, so CO2 goes down then and up in NH fall and winter.

    If there’s a series of warm years, at least in the Northern hemisphere, there will be more plant growth, driving down CO2 (conteracted by more decay, too). You could have warm summers and cold autumns, driving down CO2 even more, or cool summers and warm autumns, driving CO2 way up. But the point is this: on a yearly basis, it is very well known that temperature drives CO2, through a very well-understood mechanism.

    In the longer term, the usual explanation is that CO2 drives temperature, through the greenhouse mechanism. To address that, you have to separate short-term fluctuations from long-term trends. In taking the derivative of CO2, you virtually eliminate the long-term trends. Some graphs have used “isolate” which does something similar in letting only high frequencies through. (In two dimensions, as in image processing, this used to be called “unsharp masking.”) So, you and others have looked at the high frequencies, and seen temperature driving CO2 on the short term.

    In the long term, we have to isolate the lower frequencies and look at the long term trends. This is easy to do by taking a 24-month running mean:

    http://www.woodfortrees.org/plot/esrl-co2/derivative/mean:24/plot/gistemp/from:1959/scale:0.2/offset:0.075

    Now, this can’t have the same explanation as the short-term fluctuations, i.e., plant growth and decay with some variations on the scale of several years. There’s too much CO2 to have been released by natural processes that we know, like volcanoes, massive plant decay, or the like. (There has been CO2 released by slash-and-burn deforestation, which is considered anthropogenic CO2, but if there were huge natural forest die-offs, we would have noticed.) We haven’t been burning enough wood from standing forests to account for this. We have been burning enough forests, etc. to explain this CO2, but these forests grew 200 million years ago, and we’re burning them as fossil fuels.

    And, the temperature increase is consistent with what we would have expected for adding that much CO2. Logically, this is not “proof,” it is “confirmation.” Just one step among many in accepting or rejecting a hypothesis.

    Bottom line here: temperature drives CO2 in the short term; this is well understood and not controversial. But in the long term, no such natural explanation exists; we just haven’t lost enough plants, and the AGW explanation works.

  96. JazzyT:

    You conclude your post at January 25, 2013 at 1:37 am saying

    the AGW explanation works

    No. The AGW explanation fails in ALL its predictions; e.g.
    missing ‘hot spot’
    missing ‘Trenberth’s heat’
    missing ‘committed warming’
    lack of accelerated warming in both polar regions
    lack of global warming for 16+ years despite continuing increase to atmospheric
    etc.

    Richard

  97. NASA graph 1920 -.2
    40 years later 1960 0
    20 years later 1980 .1
    10 years later 1990 .2
    10 years later 2000 .4
    10 years later 2010 .6

    Recognize exponentiality?
    The chart doesn’t graph at a 5 year mark. But I would venture to guess 2015 will mark the .8 derision and 2020 would peak at 1. Looking at a historical chart for a global temperature index that goes back to 1986 is blatantly ignorant. Good luck. Pretend like this isn’t happening.

    Americans should be preparing for a global food shortage. In 2011 60% of corn was rated good to excellent. In 2012 only 26% of corn was rated good to excellent. It is all on the department of agriculture’s website. You are talking about a 50% crop loss due to an unstable environment. Arizona just lost 70,000 acres of lettuce due to freezing temperatures. The global environment is becoming unstable, not just warming.

  98. I forgot to mention this chart is in celsius the overall difference in fahrenheit:
    31.64
    32
    32.18
    32.75
    33.08
    33.44
    33.8
    Again demonstrating the exponential increase. It took 40 years to increase by .36 degrees F. Which is the exact amount it increased in 10 years from 2000 to 2010. Cut that in half again and it will follow my opinionated model. An increase in .36 degrees fahrenheit but in half the time. There is also increasing acidity levels in the ocean that are hindering shellfish from creating an exoskeleton which are the bottom of the food chain. The global production of food needs to increase by 3.5 percent to keep up with the increase in population at its current rate. Due to the instability in the environment there is a massive threat to that equation. Late frosts, drought, flooding. We dont have to worry about an ice age or water world because we will not make it that far . We need to pay attention to crop loss due to instability and prepare for starvation.

  99. I forgot to mention the jackasses talking about phytoplankton. They are getting ready to become extinct due to the acidification of the oceans. Which are the basis of the food chain and deliver half the Earths oxygen through photosynthesis.

  100. Sincitylivin:

    re your post at January 25, 2013 at 6:55 am

    Climate varies. It always has and it always will, everywhere. People adapt: they have to.

    As for global temperature measurements over time, well look at this

    That is scary and it is completely man-made.

    Richard

  101. Sincitylivin says: January 25, 2013 at 7:46 am

    I forgot to mention the jackasses talking about phytoplankton. They are getting ready to become extinct due to the acidification of the oceans. Which are the basis of the food chain and deliver half the Earths oxygen through photosynthesis.
    ============================
    This is the usual score talk that is propagated by the global warmers. The oceans are alkaline and will be for the next bilion years or so. Don’t let the global warmers make you wet your britches.

  102. Philip Shehan says: January 24, 2013 at 7:34 pm

    mpainter, I can assure you that “noisy data” is not a term limited to the dscussion of the last 16 years of temperature data. It is a term I have regularly used and encountered in over 3 decades of research experience in the physical and biomedical sciences.

    It refers to the difficulty of detecting the real “signal” in the presece of background “noise”. Thus the term signal to noise ratio, which has a mathematical formulation. A low ratio can be described as a noisy signal or noisy data.
    ==============================
    How much noise does a thermometer put out? That is my point. The fidelity of the temperature record is certainly a question but the problems are mis-characterized when referred to as noise instead of fidelity, IMHO. For example, Anthony Watts work in station siting and the effects on the fidelity of the data is hardly a question of signal noise.

  103. Sincitylivin says: January 25, 2013 at 7:29 am

    “…. There is also increasing acidity levels in the ocean that are hindering shellfish (which are the bottom of the food chain) from creating an exoskeleton ….”

    Sorry Sin, that story was a complete beatup … the dissolving shells turn out to be perfectly natural phenomenon if they go to too deep or if water currents bring up deep carbonate corrosive water – in normal seas the poor old shellfish can’t possibly even tell the changes in pH which have occurred to date.

    Worth going back and reading the original article and seeing in fact that all it says is the scientist harvested shellfish damaged by this ‘normal upwelling’, but they expect this sort of thing will become a lot more common when (no ifs about it of course!) in the future!

    eg http://www.antarctica.ac.uk/press/press_releases/press_release.php?id=1976

    Carbonate Compensation Depth is the depth below which carbonate shells cannot exist (about 4000 m) . The article is about the natural upwelling of this ‘shell corrosive’ water. The researchers simply applied some forecast pH and temperature data to this via modeling and come to the rather obvious conclusion that the process would become worse(?)/more common if pH and temperature increase in the future.

    Although, perhaps it is not quite so obvious: “…The exact value of the CCD depends on the solubility of calcium carbonate which is determined by temperature, pressure and the chemical composition of the water – in particular the amount of dissolved CO2 in the water. Calcium carbonate is more soluble at lower temperatures and at higher pressures….” http://en.wikipedia.org/wiki/Carbonate_compensation_depth

  104. JazzyT says:
    January 25, 2013 at 1:37 am

    You are preaching a storyline which has been assumed and taken on a patina of scientific respectability by repetition alone. But, it is discredited by the evidence before us. Stop regurgitating cant, and get those neurons firing.

  105. JazzyT says:
    January 25, 2013 at 1:37 am

    BTW, your WoodForTrees link is to my chart comparing the CO2 derivative with temperature. Nice correlation, eh? You cannot fail to see my point.

    Now, try to correlate absolute CO2 levels with temperature – can’t be done.

  106. JazzyT says:
    January 25, 2013 at 12:49 am

    “That’s not so obvious if you’re willing to look at all the data.”

    Which you obviously didn’t do. Because, if you look at the rates of change, you see immediately that there is no match at all between absolute CO2 and temperature.

  107. Bart,

    Jazzy is not the only one playing games, but thanks for calling him on it. He says:

    “Bottom line here: temperature drives CO2 in the short term; this is well understood and not controversial. But in the long term, no such natural explanation exists; we just haven’t lost enough plants, and the AGW explanation works.”

    Wrong. Changes in CO2 follow changes in T on all time scales, from years to hundreds of millennia. There are plenty of charts showing that same cause-and-effect relationship. But there are no charts showing that T follows CO2, and doing a bogus overlay of T/CO2 does not show cause-and-effect. This does, just like the 400,000 year chart.

    “Adjusting” the y-axis to overlay T allows nefarious people to claim that CO2 causes warming, but upon cursory examination it does no such thing. Jazzy’s fabricated overlay does not show cause and effect. It merely shows short term coincidence.

    Jazzy is just playing games with charts. In fact, the correlation is entirely coincidental, and it only lasted for a couple of decades out of the temperature record.

  108. D.B. Stealey says:
    January 25, 2013 at 11:26 am

    Yes, DB. And, I just want to remind people that, modulo an integration constant, the information in the derivative is entirely equivalent to the information in absolute quantity. If you cannot match the derivative, then there is no match.

    The derivative of CO2 has a marked trend which is not observable in the derivative of temperatures. They do not match on that level. Only when you take the derivative of CO2, and compare it to the temperature, do you get a match.

  109. Bart says…..
    >>>>>>>>>>>>>>>>>>>
    Bart, Thanks for the CO2 derivative information. It is the first I have seen it.

  110. This chart shows that CO2 has no measurable effect on temperature.

    The entire “carbon” scare is being falsified by the ultimate Authority: Planet Earth herself. Anyone contradicting that is asking us to believe them, instead of what our planet is telling us.

  111. I just noticed “Sincitylivin’s” comments. It really gets tedious deconstructing all the nonsense that one person can bring here, after they load up on their talking points at an unreliable alarmist blog.

    While I find some links showing that ‘ocean acidification’ is unscientific nonsense, Sincitylivin can use this to help him get over his climate fright.

  112. No amount of positive examples proves a theory correct. However, a single contrary example proves a theory wrong.

    The current lack of warming shows that AGW theory is wrong in its present form (CO2 is the basis for AGW). No amount of positive examples can overcome this. This is the scientific method.

  113. Bart says:
    January 25, 2013 at 10:03 am

    You are preaching a storyline which has been assumed and taken on a patina of scientific respectability by repetition alone. But, it is discredited by the evidence before us. Stop regurgitating cant, and get those neurons firing.

    The graphs you’ve shown suppress low-frequency, long-term information–that’s what a derivative does. In electronics, a differentiator circuit can be used as a high-pass filter; you could literally boost the treble and supress the bass in your stereo with it. So, once you’ve taken the derivative, your signal has little to say about long-term trends.

    As you’ve noted, the information is still in there, but it’s been suppressed so much that you can’t hope to see anything about long-term trends on a noisy signal by eyeballing a couple of lines on a graph. In fact, taking a derivative is a pretty good recipe for preventing any information about long-term trends from being noiticed.

    Bart says:
    January 25, 2013 at 10:08 am

    BTW, your WoodForTrees link is to my chart comparing the CO2 derivative with temperature. Nice correlation, eh? You cannot fail to see my point.
    Now, try to correlate absolute CO2 levels with temperature – can’t be done.

    And so it was. Thanks for letting me know. [Mod: Thanks for fixing the other formatting problem too; my apologies for that as well.] Here is the link that I meant to post:

    http://www.woodfortrees.org/plot/esrl-co2/mean:24/scale:0.0095/offset:-3.1/plot/gistemp/from:1959/mean:24

    Absolute CO2 actually does correlate well with temperature in the long term. Of course, with that sort of short-term fluctuations in temperature, a graph, by itself, does not indicate which is cause and which effect, or whether both stem from a common cause, or whether it is mere coincidence. Those who believe that CO2 is driving temperature expect this due to greenhouse gas theory, and use graphs like the one linked above for confirmation.

    Correlations between the rate of change of CO2 vs. temperature are interesting, not least because what you find is exactly what you would expect from some known mechanisms opperating on an annual timeframe (with variations lasting several years). But the whole idea of scary AGW is that it should operate over much longer timeframes, and your efforts will run into a brick wall whenever a believer brings up the short-term vs. long-term issue, and points out that you’re looking only at short-term changes when it’s long-term changes that they fear. Especially because the known mechanisms for short-term changes won’t work for the long-term ones.

  114. A claim has been made that “adjustment” of the y scale by” nefarious people” to produces the following plots:

    http://www.woodfortrees.org/plot/rss/from:1979/plot/rss/from:1979/trend/plot/esrl-co2/from:1979/scale:0.008/offset:-2.81

    http://www.woodfortrees.org/plot/hadcrut4gl/from:1958/mean:12/plot/esrl-co2/from:1958/normalise/scale:0.75/offset:0.2

    The slopes of the latter two plots in degrees C / CO2 concentration (in parts per thousand) are:

    The WFT plot 1979 to the present 8 C/ppt

    The WFT plot from 1958 9 C/ppt

    It is claimed that the following plots represent the real situation, but no is given as to why the selection of the y-scaling of CO2 concentration not entirely arbitrary:

    http://www.woodfortrees.org/plot/rss/from:1995/plot/rss/from:1996.83/trend/plot/esrl-co2/from:1996.83/normalise

    And in fact the arbitrariness is demonstrated by the fact that the slopes of the latter two plots are.

    The WFT plot from 1997 30 C/ppt

    The slope for the wordpress plot from 1980 13 C/ppt

  115. “So, once you’ve taken the derivative, your signal has little to say about long-term trends.”

    As can be plainly seen, there is still a trend in the derivative of CO2. That trend integrates into the curvature of the absolute CO2. And, that curvature is what falsifies significant contribution from human sources. I’ve written extensively about all of this above. Please familiarize yourself with the argument before going any further.

    “Absolute CO2 actually does correlate well with temperature in the long term.”

    No, it doesn’t. This is the flip side of your argument above: integrating suppresses higher frequency information. So, all you’ve got is a similarity in very low frequency, which is very easy to match on a superficial level when you are allowing yourself to pick and choose the offset and linear terms.

    “…your efforts will run into a brick wall whenever a believer brings up the short-term vs. long-term issue…”

    There is no issue. The dCO2/dt relationship with temperature integrates precisely into the observed CO2 and matches all the variation as well as the longer term trend and curvature. Occam’s Razor then kicks in.

    To do what you are proposing, there would have to be implausibly complicated mechanisms in place which high pass filter the temperature contribution, and low pass filter the human contributions, and match the two outcomes precisely in phase so that it looks like temperature only is all that is needed. Which is more likely? Such fantastic processing of the signals to make it look just like it would when it is only temperature driving it, or in fact that it is only temperature which is driving it?

  116. When talking of temperature it is useful to remember the record has been diddled and the error bars large. … the CRU computed sampling (measurement) error… start at 0.5°C, which is the mark where any indication of global warming is just statistical noise and not reality. Most of the data is in the +/- 1°C range, which means any attempt to claim a global increase below this threshold is mathematically false.

    ‘KevinUK’ does a great job working in collaboration with Verity Jones on ‘mapping’ possible global warming/cooling in both the NOAA and GISS GCHN raw and adjusted datasets for different time segments and presenting a visual representation of these adjustments.

    A graphic representation of the station drop out problem from diggingintheclay by Verity Jones (check out the posts on either side for a lot more information)

    On the “march of the thermometers” @ WUWT

    “E. M. Smith, aka “chiefio“, who has been aggressively working through the data bias issues that develop when thermometers have been dropped from the Global Historical Climate Network… the GHCN station dropout Smith has been working on is a significant event, going from an inventory of 7000 stations worldwide to about 1000 now, and with lopsided spatial coverage of the globe. According to Smith, there’s also been an affinity for retaining airport stations over other kinds of stations. His count shows 92% of GHCN stations in the USA are sited at airports, with about 41% worldwide. “

    There are 69 posts by ChiefIO starting here that go into detail on the ramifications of the station dropout by country.

    Verity Jones also did a lot of work on the issue in this section of her blog:

    http://diggingintheclay.wordpress.com/2010/02/25/of-missing-temperatures-and-filled-in-data-part-1/

    http://diggingintheclay.wordpress.com/2010/03/02/of-missing-temperatures-and-filled-in-data-part-2/

    http://diggingintheclay.wordpress.com/2010/03/14/no-more-cold-turkey/

    http://diggingintheclay.wordpress.com/2010/03/21/climate-syndrome-china-meltdown/

    and many more

    Mike McMillan put together flick graphs of ALL the USHCN individual stations for Iowa

    http://www.rockyhigh66.org/stuff/USHCN_revisions_iowa.htm

    and all USHCN stations in Wisconsin

    http://www.rockyhigh66.org/stuff/USHCN_revisions_wisconsin.htm

    and Illinois

    http://www.rockyhigh66.org/stuff/USHCN_revisions.htm

    This is for the 2009 ‘raw V1′ and 2010 ‘raw V2′ data.

    The real killers are Jo Nova’s posts

    Australian temperature records shoddy, inaccurate, unreliable. Surprise!
    The BOM say their temperature records are high quality. An independent audit team has just produced a report showing that as many as 85 -95% of all Australian sites in the pre-Celsius era (before 1972) did not comply with the BOM’s own stipulations. The audit shows 20-30% of all the measurements back then were rounded or possibly truncated. Even modern electronic equipment was at times, so faulty and unmonitored that one station rounded all the readings for nearly 10 years!… It’s doubtful they can justify one decimal place, let alone two….
    …. The audit team were astonished at how common the problem was. Ian Hill and Ed Thurstan developed software to search the mountain of data and discovered that while temperatures of .0 degrees ought to have been 10% of all the measurements, some 20 – 30% of the entire BOM database was recorded as whole number, or “.0″.

    as a result of the above findings… Threat of ANAO Audit means Australia’s BOM throws out temperature set, starts again, gets same results and the New Zealand temperature record is running into similar problems: Don’t mention the Peer Review! New Zealand’s NIWA bury the Australian review otherwise known as The Goat ate the Data a similar problem to Phil Jones “The Dog ate the Data” and the worst Data Tampering: GISS Caught Red-Handed Manipulating Data To Produce Arctic Climate History Revision This leaves no doubt the ‘adjustments’ that always favor CAGW are intentionally bias.

    IMHO the surface temperature data recorded is so messed up and shoddy there is no way to find a real warming trend. The actual raw temperature graph as it should be presented.

  117. Well, Gail, I have to disagree. I think the CO2 measurements offer corroboration of the adjustments, as the correlation between the adjusted temperatures and the CO2 derivative is readily apparent.

    That temperatures and CO2 should be so correlated I explain here. I think the keepers of the records are not fraudsters, merely not up to the job of drawing the correct inferences from the data.

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