The term is “autocorrelated” not “autocorrected” and here is the Wikipedia page on autocorrelation. “Autocorrelated data” is not bad per se, but the essential idea is that traditional statistical analysis usually assumes each data point is an independent measurement so if this is not the case because there is significant autocorrelation then you, in a sense, have fewer data points than you think you have, which can then make a difference in test of statistical significance of trends or correlations.
intention can say where I’ve gone wrong and fill you in from there (e.g., on the issue of long-term vs. short-term persistence of the autocorrelation). It is not a topic I have ever had to study in any detail whatsoever.
Oh, good, now it’s my motives that are being questioned. Foolish me, I was under the impression you wanted to talk about the science. I have asked the question about the IPCC review process, and the shabby science inherent in that. No answer. I have asked the question about the use of PPP instead of MER, and how you justify that. No answer.
Heck, I’ve even talked at length about the McKitrick paper, which you seem to think I have accepted uncritically … but within which you have not found any scientific problems. Even NASA says there’s no way to measure SAT, and there’s not even any universally accepted correct answer as to what SAT is, and that different methods of figuring the average temperature give drastically different results, which is exactly what McKitrick said. I’ve discoursed at length about the difference between extensive and intensive variables here, and we had a long discussion about the McKitrick paper on that thread … but now you’re quite willing to claim that I haven’t investigated the question in detail, that I have “uncritically embraced” the claims. Nonsense. I invite the interested reader to peruse the thread where you and I discussed the question.
But that’s all a side issue, whether I’m too critical or too uncritical. The real issue is that instead of answering the scientific questions, you want to talk about the tobacco companies, and some Republican strategist I’ve never heard of, and libel my motives, and accuse me of not being critical enough … which, as you point out, is a good strategy … but doesn’t address the scientific issues.
This is Great Debates. Stop dodging, and talk about the science. Start with the statistical problems ignored by the IPCC that I have documented. Move on to a discussion of the fact that the IPCC has refused to stop using the MER, despite the fact that no other major organization on the planet uses it. Not the rest of the UN. Not the World Bank. Nobody. Then explain why, since their statistics suck and their economics doesn’t work, and since they have been notified of both of these problems and have refused to fix them, we should trust the IPCC at all.
When we’re done with that, I’m happy to discuss Republican strategists or tobacco executives over in MPSIMS if you wish.
Well, a few people in this thread seem to be questioning my qualifications to have an opinion on AGW. What would I need to read so that those people would withdraw their objections on that issue?
Well, you’ll likely think I’m nuts, but I would suggest statistics … there are so many studies out there that are based on abysmally bad statistics, it would help you throw out a whole lot of bogus results without further ado. In particular, you need to understand the statistics of autocorrelated series.
Which reminds me, someone asked what an autocorrelated series is. “Correlation” measures the similarity of two datasets. These might represent anything — say CO2 levels and temperatures. Correlation is measured by a number which varies between 0 (no correlation) and 1 (two identical datasets).
Autocorrelation, on the other hand, measures if a data series is similar to itself. For example, a hot day is often followed by another hot day, and a cold day is often followed by another cold day. If our dataset contains daily observations, the similarity of one day to the previous day is called “lag-1 autocorrelation”, meaning a one day lag. “Lag-2” autocorrelation would be if a days temperature is related to the temperature two days ago, and so on.
A random dataset has no autocorrelation. In an autocorrelated dataset, extreme trends are more common than in a random dataset. This is because, since a hot day is more likely to be followed by another hot day, we can get a long trend of hot days (or cold days) over time, a trend that would be very unlikely with a random dataset.
Often, a climate dataset will have “long term” correlation. This means that there may be a long string of wet years, for example, or dry years. Again, in a random dataset these would not happen as commonly. Most climate time series, such as temperature or rainfall records, contain both long and short term autocorrelation.
The lack of understanding of the statistics of autocorrelated series leads us to think, for example, that the recent warming is unusual. It is not. Nature contains trends, trends of a surprising length and strength, trends that can last for decades. The fact that the world has warmed for the last 20 years is not at all abnormal or unusual. Statistically, the recent warming is not distinguishable from the warming of 1920-1945, a warming which almost everyone agrees was almost entirely natural.
Anyhow, that’s my $0.02 worth about what to read …
You should read enough so that you can cite specific articles and discuss problems behind the science. And to understand those articles, you will most likely need to read some other articles cited there. Of course by “articles” I mean refereed journal articles.
At least, that what it would take for me to take your opinions seriously.
I am sorry that you seem to be offended but let me answer you this way:
(1) Extraordinary claims require extraordinary evidence…and certainly considering more ordinary possibilities. As Kimstu has noted, you are making the extraordinary claim that a whole field of physical science has somehow been corrupted. You are making further extraordinary claims such as the claim that the National Academy of Sciences, an organization whose charter is to advise the U.S. government on scientific issues, cannot be trusted in this case, nor can the analogous bodies in Britain, Canada, France, Russia, India, China, Germany, Italy, … I think it is perfectly reasonable to consider the more ordinary possibility that in fact what is going on is that there are a few contrarian scientists and others who, because of their own biases, are not entirely objective. (In fact, it is expected that individual scientists will have their own individual biases. It is the process of science that is designed in order to minimize the effect of this on the progress of science as a whole.) And, in fact, a little research on these scientists indeed reveals that many have connections that would likely make them biased in the direction of being particularly skeptical of the AGW hypothesis. You seem to believe that you yourself are totally objective. However, I am skeptical of any individual scientist being totally objective and, in your case, quite frankly the evidence that I have seen does not lead me to believe that you have any unique characteristics that make you different from others in this way.
(2) I have consistently said that the place where science should be debated is in the peer-reviewed literature, not on messageboards. I am willing to engage in discussions on science to a certain degree as my time and energy permit but, quite frankly, I don’t have the bandwidth to address every point that is raised on the ClimateAudit website such as PPP vs. MER accounting or long-term persistence in autocorrelated data.
(3) The previous comment notwithstanding, I did note that coming into the MER vs PPP exchange rate issue completely on square-1, I was able to find in a 5-minute google search two papers that presented the issue quite differently than you have presented it. [Just to fill everyone else in, the debate is how the IPCC converts between different currencies in constructing their economic scenarios for what different possible paths the world might take in development and hence emissions. MER = market exchange rate, i.e., using the conversion between currencies that you get at the bank whereas PPP = purchasing power parity is, I presume, correcting, e.g., for the fact that many things tend to be cheaper in Third World Countries as travellers there know.] One of the papers notes that, far from being settled which is the better system to use, the debate is very much open:
The second paper notes that in the actual application here, the difference likely does not turn out to matter much to the results anyway:
A final note is that predicting the future economic course of the world is, of course, far from an exact science and the IPCC scenarios were never meant to be precise predictions of what will happen but simply a plausible set of “storylines” that encompass a range of possible futures. To argue excessively about which accounting practice to use seems to me sort of like arguing on whether to keep 4 or 5 significant figures on your estimate of the gravitational constant obtained from timing a ball dropping out a window and measuring the seconds by counting “one, one thousand, two, one thousand, …”!
Contrary to what you claim, I have found significant scientific problems with the McKitrick paper. The basic scientific problem is that they have not demonstrated any relevance whatsoever to the real world. Yes, global temperature is not something that has a rigorous thermodynamic definition. However, that does not mean that it is not a reasonable metric to use. (If you want to get technical, temperature is only defined in thermodynamic equilibrium and NO real system is truly ever in thermodynamic equilibrium and yet we still find temperature to be a useful metric.) And, NASA might note too the difficulties in measuring temperature but they do so in a constructive way, i.e., in order to find a useful metric and not as just a way of saying, “Whoa is me! I guess we don’t know anything about whether or not the earth is warming!” or other such nonsense. What NASA argues is that a much better metric to use is temperature anomalies because a temperature anomaly field is much more slowly varying in space than a temperature field. For example, if you have stations that are close in space but one is at the top of a mountain and one is in the valley, they will measure very different temperatures and thus it would make a significant difference which one you use. However, if you look at the temperature anomalies of both over time, they will be much more similar and hence it will not make such a significant difference which one you use.
The only attempt that the McKitrick paper made to relate their conclusions to the real world of global temperature trends was the contrived example shown in their Figures 2 and 3 where they claimed to show how with a 12 station sample of temperatures, they could get a very different result for the average temperature trend depending on how they performed the average. For example, in Fig. 2, their different averages consisted of summing different powers r of the temperature and then taking the rth root. Thus, r=1 is the standard arithmetic average while r=2 is what is called the root-mean-squared average. And, if you look at their Fig. 2, it does indeed seem like they can get dramatically different results for the temperature trend. However, what you have to realize is the scale of the x-axis where they have taken r to range between -125 and 125. So, what they do is raise the temperature to absurdly high powers, which in effect creates an “average” which just chooses the temperature that is the lowest or highest (depending on whether r is negative or positive, respectively) of the the 12 stations for each month. Does this sound like any sort of reasonable average to you? [And, in fact, one finds that if one sticks to a reasonable range of “r” values that one can likely find any sort of physical justification for using, say r between 0 and 4, then the resulting temperature trend changes very little…by only a few percent as I recall. My guess is that this change in trend would be even smaller with a larger data set than 12 stations although I haven’t verified this.]
Thus, their whole paper rests on the proposition that if you can’t give something like global temperature a completely rigorous thermodynamic definition, then any way of doing an average is as good as any other one (including, apparently, one that gives all the weight to just one station each month). This is the sort of logic that might get you by in a freshman philosophy class but it surely isn’t going to fly in the scientific community.
[The one piece of credit that I would give to McKitrick is that he practiced what he preached in terms of making all the data he used available (and even the code, I believe, although it was written in something that was useless to me). This allowed me to directly check his calculations and check that choosing very large positive and negative r’s was indeed doing what I thought it would and to see what the temperature trend is over the more reasonable range of r’s that gets compressed to almost nothing when you look at their graph showing the range -125 to +125!]
I’m not claiming that a whole field of physical science has been corrupted. I’m claiming that:
a) a consensus on climate science does not exist, as demonstrated by a variety of polls and signed statements. You don’t like the fact that 60 climate scientists in Canada signed a statement saying they don’t agree with the consensus, so you have made your usual ad hominem attack on their motives or their funding — but the fact remains that they are climate scientists who don’t agree with the consensus. Deal with it.
b) most climate scientists are not statisticians, and many of them have made extremely important (and often ludicrous) statistical errors, errors which have either been ignored or not noticed or blown off by the IPCC and the National Academies of Science you seem to think so much of. I have demonstrated this in many postings … you have ignored it.
c) the surface data is much less accurate than many climate scientists seem to think. See surfacestations.org for details. AGW supporters say “but this doesn’t affect the trends” … this may be so, but it is the responsibility of those scientists to establish that fact before building a worldview around it. Instead, the surface record has accepted by them without question … this is part of the science that you say requires “extraordinary evidence” to overthrow, but it has been accepted by AGW scientists without any evidence at all. Now that the evidence is finally coming out, we see that the “high quality” network of surface stations is nothing of the kind. I’ll take ordinary evidence over no evidence any day, nothing extraordinary is required to overthrow the idea that the surface record is reliable.
d) politics and noble cause corruption have biased some scientists points of view, on both sides of the issue.
e) the IPCC is a highly politicized body which has not fulfilled its responsibilities to summarize the science. Again, I have given a number of citations and examples.
f) far too many scientists have a vastly inflated opinion of the untested, unproven climate models’ ability to project future climates.
g) Error estimates and confidence intervals have been routinely underestimated by the AGW supporters, making their claims look much more scientific than they actually are. I have provided citations and examples for this as well.
I am not making the claim that “a whole field of physical science has been corrupted”. (In passing, I notice you’re not even claiming that I said that, but blaming it on Kimstu, so you have perfect deniability.) I am saying, as are many climate scientists, that our understanding of the climate is far from the point where we can make 100 year forecasts, or ascribe causes to all or any part of the 300 year warming of the globe.
You seem to think that it is somehow “extraordinary” that science could be wrong … where in fact, that is how science progresses. Einstein showed that Newton was wrong, Wegener showed that the scientific world’s belief in static continents was wrong. For thirty six years, the scientific consensus was that there were 48 human chromosomes … until Tjio and Levan noticed in 1956 that the count wasn’t right, and that scientists the world over had simply accepted an erroneous count for years, and never bothered to count themselves. The nature of science is proving that previously held scientific beliefs, the previous “scientific consensus”, is wrong.
It seems to me that you are stuck in some 20th century ideal, where scientists are noble and wear white coats and always tell the truth. In the 21st century, as Stephen Schneider points out, they are all too often hucksters, people with an idea to sell and no compunction about lying to sell it. Schneider says the issue is to decide how much to lie while selling the “science” … do I find it surprising, or extraordinary, that all too many scientists have bought into some of the lies that Schneider says are a necessary part of science? Not a bit. Do I find it strange that climate scientists seem to have forgotten how to say “I don’t know”? Not at all.
OK, fine, it’s your call. But in that case, I won’t debate the science with you here. I’m tired of you breaking off the discussion with these types of excuses for not continuing to participate whenever the scientific tide starts flowing against you.
jshore, I have enjoyed our discussions, but they have all proven very frustrating to me because at the end of the day, when the questions get tough, you “don’t have the bandwidth”. Which is fine, I understand that every person’s time is limited, but like I said, it’s frustrating.
It’s especially frustrating because you portray yourself as knowledgeable on the subject, you make all of these very definitive statements about how the IPCC can be trusted, you seem to think that, as in Emerald City, we should ‘pay no attention to that man behind the curtain’ … then when I show you how the IPCC blows off one of the most important, fundamental statistical questions in the field, a question that affects all of their results and claims, suddenly you’re out of bandwidth.
jshore, you strike me as basically an honorable person, you have always provided scientific citations for your claims, and I have benefitted from our interaction. You obviously believe what you are saying, and other than your unending ad hominem attacks on people whose scientific conclusions you don’t like, and your claims that the statements of the IPCC and the NAS carry great scientific weight despite not being the “peer-reviewed literature” you claim to espouse, you have generally stuck to the science and avoided the press releases.
I will not, however, answer any further posts from you about science. I’m tired of getting sucked in to an interesting discussion, only to have you bail out. To paraphrase Harry Truman, “if you can’t stand the bandwidth, get out of the kitchen.”
And yet again Jshore you come back to the “science by consensus” position. Every thread you trot out this idea that we should take a vote on the facts, and every thread you retreat from it as soon as challenged, and then the next thread you advance the same position.
Quite simply science is not achieved by consensus. We do not take votes on the facts. It doesn’t matter if large collections of sicentists are saying something. Within our liftetimes large collections of scientists have said that continental drift couldn’t occur and that gastric ulcers were caused by stress. That didn’t make them right. Large collections of sicentists are just as cabpable of being wrong as individuals.
Either the hypothesis is predictive, replicable and consistent with the observations or it is not. “We should listen to large groups of scientists” is nothing but an argument from popularity, and a particularly blatant one.
Well if you can present some references to support that claim then it wil have some legs in GD. Until then we shall be free ignore it.
I won’t report you this time, but don’t try this rubbish again in GD.
You are still trying to impose the same double standard. No scientist understands the physics, statistics, jargon of all AGW papers.
When you show me some evidence that an average forester or benthic hydrologist can understand that paragraph then you will have a point. The fact is that I don’t understand that paragraph as you posted it, and I have worked in this field and been published in GCB.
CITE.
Seriously, show us you evidence that climate scientists have read a good proportion of the peer reviewed information regarding AGW?
Once again you don’t seem to understand just how broad the peer reviewed science is. Let’s consider 10% to be a good proportion. You are claiming that all climate scientists have read 25% of the papers in forestry, savanna ecology, bethic hydrology, palaeobotany, and so on and so forth across the fields of physics, economics, sociology, chemistry, gology and so forth.
Do you have any idea how many papers that would entail reading each day. Seriously, tell us how many papers relating to AGW you think appear in each issue of an average/typical peer reviewed journal. And then tell us how many such journals you think are published every month? Then we’ll look at the contents of some journals and see how close you are.
Dude nobody in the world has the time to have done what you claim. Nobody. Your claim that any climate scientist has read a good portion of the peer reviewed literature on AGW is total bunkum. Even if they had read them lacking any education in forestry or economics or bentholgy they couldn’t possibly understand them.
Oh, yeah. jshore cited some peripheral papers claiming that using MER in place of PPP makes no difference, that either one is OK. To quote from Ian Castles:
So, given that the PPP system was adopted in 1993, and was approved by the UN Statistical Commission fourteen years ago, and forms part of the internationally agreed “System of National Accounts”, and is used by everyone from the UN to the EU to the World Bank, why did the UN IPCC use MER? Anyone’s guess. The two most probable reasons are 1) they didn’t know better, or 2) because it increases projected CO2 emissions.
And given that they have continued to use MER, after being notified by Castles and Henderson, and the Economist journal, and a host of other people that their use of it is a very large error, explanation 1) no longer is applicable.
In any case, I don’t know which explanation makes the IPCC look worse … and in either case, it clearly shows that in this most important regard, the IPCC is not scientific in the slightest.
scr4, you have asked for a citation for this statement:
The rate of increase is also known as the trend. Now it depends on how long a trend we are talking about. Let me use a thirty year trend, as thirty year averages are usually thought of as climate rather than weather. I will use the HadCRUT3 data (covers 1850 to present) for the global temperature.
The two largest thirty year trends in the record occurred during the years 1916-1945, and 1974-2003. The earlier trend was 0.17°C/decade, and the latter trend was 0.18°C per decade. Can we say, then, that because the recent trend is larger, it is not a natural fluctuation?
To say whether these trends are different, we need to use the concept of the confidence interval. This is used with a percentage, such as a “95% confidence interval”, and it means that we can have 95% confidence that the true value is between the two values given as a confidence interval. Statistically, two values are said to be significantly different if their 95% confidence intervals don’t overlap.
The 95% confidence interval for the 1916-1945 trend is from 0.13° to 0.21° per decade. This means that, given the data we have, there is a 95% chance that the true value is somewhere in that interval.
For the recent (1974-2003) trend, the 95% confidence interval is from 0.13° to 0.23° per decade. Since this overlaps (almost completely) with the earlier 1945 range, we cannot say that they are different. In fact, the true trend could easily be smaller in the recent warming, we simply don’t know. All we can say is that the confidence intervals overlap, so the trends are not significantly different.
The rise in CO2 forcing in the later period was 4.6 times the rise in forcing during the earlier period … but despite that, the trends for the two periods are almost identical (0.18° vs 0.17°/decade). In other words, we have absolutely no evidence that the latter trend is anything other than natural.
Finally, note that these numbers do not include the underlying error estimate for the HadCRUT3 data itself. These errors, from bias, number of stations, site changes, instrumentation changes, and the like, make the trends even more uncertain.
A wiser man than I once said “Before we waste too much time trying to explain the nature of a phenomenon we should first confirm that the phenomenon exists.” This is nowhere truer than in climate science. Before we try to explain “anomalous” or “unnatural” warming, we should first confirm that unusual warming exists. In the case of the global temperature warming trend … it doesn’t.
Thanks for an interesting question,
w.
PS - Is there a peer reviewed article that says this? I doubt it, because this is entry level stuff, the kind of thing that scientists are supposed to do before they write the peer reviewed article.
However, you can do this for yourself, that’s the beauty of the internet. Download the HadCRUT3 dataset, and do the math yourself. The recent trend is in no way unusual or different from historical trends.
Is that all? Brazil84 just said that the current temperature trends can be validly attributed to natural variation.
Oh well, if that’s all you are chasing refernces for, allow me.
“These results suggest that 20th Century warming trends are plausibly a continuation of past climate patterns. Results are not precise enough to solve the attribution problem by partitioning warming into natural versus human-induced components. However, anywhere from a major portion to all of the warming of the 20th Century could plausibly result from natural causes according to these results.”
Loehle, C. 2004; “Climate change: detection and attribution of trends from long-term geologic data.” Ecological Modelling, 171:4
Jeez it’s not like Brazil84 has said anything novel or controversial, which is probably why he had trouble seeing what you were requetsing evidence for. According to our best science the current temperature trends are quite plasuibly attributable to natural causes. Even the IPCC doesn’t dispute this, admiting that there is a anything up to a 40% chance that the majority of the current temperature increase is natural.
Thank you for the informative posts, intention and Blake.
I think scr4’s point was that I made the claim about natural fluctuation without personally reading and citing scholarly articles on the subject. And that therefore my opinions about AGW in general should not be taken seriously.
But you did make those statements without citing any references. If you can’t explain what your opinion is based on, then that opinion lack credibility. That’s all I’m saying.
I’m just attempting to answer your question: “What would I need to read so that those people would withdraw their objections on that issue?” (“That issue” being your qualifications.) My answer is that you need to have read enough so that you can cite references for your own position, and discuss them.