New comment by Antonio Regalado of WSJ – reporter not editorial writer – is here.
-
Tip Jar
(The Tip Jar is working again, via a temporary location) -
Pages
-
Categories
-
Articles
-
Blogroll
- Accuweather Blogs
- Andrew Revkin
- Anthony Watts
- Bishop Hill
- Bob Tisdale
- Dan Hughes
- David Stockwell
- Icecap
- Idsos
- James Annan
- Jeff Id
- Josh Halpern
- Judith Curry
- Keith Kloor
- Klimazweibel
- Lubos Motl
- Lucia's Blackboard
- Matt Briggs
- NASA GISS
- Nature Blogs
- RealClimate
- Roger Pielke Jr
- Roger Pielke Sr
- Roman M
- Science of Doom
- Tamino
- Warwick Hughes
- Watts Up With That
- William Connolley
- WordPress.com
- World Climate Report
-
Favorite posts
-
Links
-
Weblogs and resources
-
Archives
Climate Audit 
60 Comments
You’d think the reporter might have spent some time at the Climate Audit site to see what the real issues are…and why Steve’s not “moving an inch.” It’s a fluff story…one that doesn’t actually report anything of real importance or significance.
May I add my comment?
… “the Canadians’ critique may have limited significance.”
“… “while there is a statistical snafu in the hockey-stick math, it may not strongly affect the graph’s accuracy.”
My, how is it that we all are asking permission for something to happen? It seems we need a “may” each time we claim something is having almost no effect.
The next commenter may now add his own comment.
Jaime
I worry that Steve will just get his head down and get bogged down with these tendentious tussles. For instance, the Huybers comment seems like at core a semantic argument about what “conventional PCA” means and how to best replicate an undisclosed method of Mann’s. I worry that he is not pushing forward new analyses in the urge to defend his views.
Also, it’s unfortunate that the quote from the reporter implies that Steve is just being intransigent, rather than that the comments on his paper do not shift his criticisms of the Mann work. I think a short clarifying letter to the editor would be appropriate (and would be published, given the interest in this story).
I second TCO’s idea. A nice short pithy letter (with references to the weblog, of course), would be a good course of action.
TCO, I’m working away at new material. However, it’s hard not to engage in controversy because (1) the Comments do not rebut our arguments and it’s important to convey that point; (2) most climate scientists want the Comments to be right and will not pay much attention to the Replies; (3) if you lose your reputation, it gets hard to get an audience for further work. (4) This would be especially irritating if, as in the present case, the criticisms do not rebut our critique or revive MBH.
I think if you have more material, it will help your overall standing. Also, that someone will always be able to find a tendentious slant and you will never get complete satisfaction. So sure, make sure that you argue the point. But don’t expect satisfaction or get too wrapped up. And certainly if any of the criticism of your work is relevant or is additive, make sure to acknowledge it.
Off topic a bit, but over at Roger Pielke Sr’s blog (http://climatesci.atmos.colostate.edu//) he has an interesting Q&A about climate models up, which pertain to discussions threading elsewhere on this site. There’s an interesting quote there from Gavin Schmidt towards the end, taken from a Q&A on realclimate. He (GS) says: “On a final note, an implicit background to these kinds of questions is often the perception that scientific concern about global warming is wholly based on these (imperfect) models. This is not the case. Theoretical physics and observed data provide plenty of evidence for the effect of greenhouse gases on climate. The models are used to fill out the details and to make robust quantiative projections, but they are not fundamental to the case for anthropogenic warming. They are great tools for looking at these problems though.”
This next paragraph uses a bit of musical notation, namely the repeat sign.
||: The hockey stick is wrong, but it is not that important to the case for anthropogenic warming because there’s other evidence– the model predictions. Except they’re not predictions, they’re just projections, since models have irreducible uncertainties and limitations. But in any case the models are not fundamental to the case for anthropogenic warming, because there’s other evidence from fundamental physics. Except the fundamentals only give you infrared absorption, and to predict the outcome in the actual atmosphere the fundamentals involve turbulence and fluid dynamics and other things that can’t be solved directly so that’s why the models don’t use the fundamentals, they use parameterizations. But that’s OK because the numerical solutions aren’t fundamental to the case for anthropogenic warming, instead we have signal detection studies. Except the signal detection studies use signals generated by climate models, and thus rely on the assumption that the models are generating exact projections of natural variability and responses to natural forcings. So the models are fundamental to the signal detection papers, but that’s OK because the signal detection studies aren’t fundamental to the case for anthropogenic warming since we have the temperature data. Except the temperature data is subject to all the known problems of incomplete sampling, inhomogeneities, UHI’s, uncertainty about MSU calibration etc., but that’s OK because any one specific temperature data set is not fundamental to the case for anthropogenic warming since we can look over the whole lot and see that there’s almost always a slight upward trend. And we know the upward trend is historically unusual, indeed unprecedented in the past 1000 years, because we have the hockey stick. Except : ||
oops, the blog converted the end-repeat sign, colon-line-line, into a face. It should signal, go back to ||:
In considering how I would point Antonio Regalado to the core issue of why the comments of VZ and Huybers do not answer the problems of the hockey stick, I cannot find a clear statement in all of the discussion on this website or in your articles. I would propose a summary of the problem thus: “The problem with PCA is that if there are 99 proxies that have no ‘temperature signal’ at all in them, and there is one proxy series that is correlated with 20th century surface temperature data, then PCA will put extrordinary weight on this single series, while making it seem as if all 100 series are being used to ‘explain’ climate history. With VZ and Huybers, correcting the PC methodology errors of MBH does not change the fact that the last 1000 years of climate history is being explained by a handful of bristlecone pines in the Western US. The authors of the studies reporting on the recent growth of these pines specifically rejected the idea that the recent high growth was related to temperature. As a result, the ‘hockey stick’ is based entirely on a small fraction of the data that the authors purported to be ‘using’, and that small fraction of the data has been rejected as related to global warming.”
Steve
I wrote a message. Pressed “Submit Comment”.
You said E-mail address invalid
I pressed “Back” to correct.
You wiped out my message.
It would be nice if I didn’t have to retype my message.
jim w
Steve
Re #7
Except we have the Hockey Stick, but we know it has mistakes, but the mistakes don’t matter, because we have other studies that match the Hockey Stick, except the other studies can’t be replicated. The other studies can’t be replicated, but that’s OK because there’s a scientific consensus, and though some people disagree with us, the people who matter think that what we have done is valid, and even if it’s not quite valid, there’s a press announcement of a new study which confirms our earlier results….
This comment could go on for hours, possibly days.
McKitrick said: “…but that’s OK because the signal detection studies aren’t fundamental to the case for anthropogenic warming since we have the temperature data. Except the temperature data is subject to all the known problems of incomplete sampling, inhomogeneities, UHI’s, uncertainty about MSU calibration etc. …”
This is the weakest point of the chain of connectivity. The temperature data since 1850 is consistent with hindcast modeling, based on first principles; the UHI has been shown to be of little significance; the MSU data is aligning with the observed surface and predicted atmospheric trends, etc.
The problem with the uncertainties surrounding past global climate states (which is core to the proxy estimation issue central to the controversy) is that the magnitude of what is being observed now — which is difficult to deny — cannot be reliably compared to what has happened in the past. The lack of that comparison capability doesn’t reduce the importance of what is happening now, but it would be nice to have an agreed-upon accurate comparison to allow full evaluation of the Earth system climate “context”. And refinement of the proxy climate data would also improve the climate sensitivity parameters in current models.
Steve
I think MBH will fight you forever. Their reputation is at stake.
I’ve followed this blog for many months. It seems to me that the width of tree rings is an unreliable way to measure temperature. There are too many factors:
Fertalization
Tree age
Precipitation
“U” shaped temperature effect
Trees only grow in the summer
Accuracy of width measurement
Carryover from year to year
Reliance on statistics to fish out a temperature trend
A tree’s distance from its tree line
I doubt that one can measure the ring widths and detect a temperature trend of 1oC per 100 years.
I think you may have the data you need to show how unreliable tree rings are as a measure of temperature.
I suggest that if you write papers that demonstrate this unreliability you will make a major scientific contribution.
Best Wishes & keep up the good work.
Jim W
But the temperature data since 1850 is controlled and unknown “adjustments” are made before this fundamental data is published by Phil Jones at the CRU. So before the models can be calibrated the fundamental data must be checked, but the fundamental data cannot be checked because the data is proprietary, but even if you got permission from the authors, Dr Jones would not give it out because “We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try and find something wrong with it.”…
And now a song on the state of climate science, sung in the key of “Grrr”
“There’s a hole in the bucket, dear Liza, dear Liza. There’s a hole in the bucket, dear Liza, a hole…”
John A.: I wasn’t thinking of CRU, I was thinking of NCDC. It goes back to the 1800s too. (Not to be confused with either BC/AD or AC/DC…)
Re #13: I’m less optimistic about the temperature data, but if I grant for a minute that it’s all OK, then your second point states nicely what I had in mind. A trend only proves something is amiss if you expected no trend, or if you have reason to believe the trend is historically unusual. Which gets us back to the hockey stick argument.
Man, I wish all reporters were as straightforward and responsive as Antonio. I wrote:
Antonio replied:
I responded:
There it stands … my thanks to the gentleman. Maybe he could give classes to the other reporters …
w.
It is not the model uncertainties that turns the IPCC’s work into pseudoscientific “projections,” rather than scientific (i.e., falsifiable) predictions.
It is simply the fact that the IPCC KNOWS their “projections” are nonsense. Therefore, when the “projections” don’t come to pass, the IPCC can say, “Well, they were just ‘projections,’ not predictions.”
This is EXACTLY the same leftist pseudoscientific hackdom engaged in by the authors of the “Limits to Growth,” and “Beyond the Limits” series of books. (Hilariously, I think that series is up to it’s forth incarnation…though I haven’t seen fit to even pay for a used version of number 3 and number 4.)
P.S. Wigley and Raper actually published probabilistic “projections” in Science, after the IPCC’s Third Assessment Report (without probabilities) was published:
http://www.sciencemag.org/cgi/content/citation/293/5529/451
However, even Wigley and Raper can claim that they are not doing “predictions,” because their probabilistic analysis is based on the (hilariously unscientific!) assumption that all the scenarios (aka, “stories”) have the same probability of occurrence.
P.P.S. I used Wigley and Raper’s “50 percent probability” “projections,” and an eyeballed similar procedure for methane atmospheric concentrations, CO2 emissions, and CO2 atmospheric concentrations, to contrast my own *predictions* with the IPCC TAR’s (via Wigley and Raper) “projections.”
I challenged any primary or secondary author of the IPCC TAR to bet me that their projections were more accurate than my predictions:
http://www.longbets.org/181
So far, no takers. 🙂
P.P.S. I even bet that *Michael Crichton’s* projection for temperature in 2100 would be more accurate than the IPCC TAR projection, in Long Bet #180.
And I specifically DARED William Connolley to put his money where his mouth is, and bet against me on that (see Discussion for Long Bet #180). So far, he has weaseled out. 🙂
http://www.longbets.org/180
Willis–if Antonio takes your advice, reads up, and blows the lid off of the weak case for AGW, then who will he talk to at work? The WSJ news staff is made up of the same liberal jouralism grads as the NYT and WP. It has been oft-noted that the news side and the editorial side at the WSJ are worlds apart.
Ross,
Re: 7
I just traded a couple emails with William Connolly after he told me that I missed the point in a one of my posts on Realclimate. I had simply stated that I thought that “theoretical physics and observed data” would have been used to create climate models. They do not stand on their own. William answered my emails. His conclusion was that I had not looked at the real picture.
People often knock on my door and try to convince that their way is better than mine using that sort of logic.
Re #9,19: John, I spoke by phone to Regalado yesterday afternoon (he also interviewed Steve) and made that very point about the bristlecones to him, and summarized the other issues succinctly. I also followed up with a brief email. It evidently didn’t fit the storyline he wanted to tell.
I have done countless interviews over the past 4 years, for TV, radio & print, and it has been for the most part like trying to reason with a herd of buffalo. But in a few cases I’ve found the effort of talking to media paid off. Steve and I put considerable effort in explaining the issues to Marcel Crok, and when the light went on he rewrote his article and produced an outstanding expose. We also invested a lot of time in Regalado back in the winter, and by the end he understood the story well enough to get past the cliches and see through Mann’s position.
As for why he published this snarky little piece, I don’t know. I’m disappointed in it, but not surprised. The job of the WSJ is to sell papers, and controversy sells, so the article emphasizes themes like us “being attacked” and Steve “not budging an inch” and whatnot. We weren’t “attacked”, von Storch and Huybers commented on our paper, and we replied. But saying that won’t sell a stack of papers.
Nor can I get very exercized about the fact that some people will form their entire views on the matter from this article. The only people whose views matter to me are those who make the effort to read and understand the comments and our replies. I fully expect we will win the verdict with them.
Re: 13, Jack, thanks for your post. You say:
Not sure what the “etc.” refers to, but the previous three statements are not correct:
1) Hindcast modeling has not been shown to be skillful, except in the most limited way. The results produced by the models are neither lifelike, nor achievable without massive tweaking and the introduction of “adjustments”. Yes, they might reproduce the past in a clumsy way. However, if you’d done as much modeling as I have, you’d realize that this means nothing about either the fideltiy of the models or their ability to forecast. See, for example, Dynamical downscaling: Assessment of value restored and added using the Regional Atmospheric Modeling System (RAMS). J. Geophys. Res. – Atmospheres, 110, No. D5, D05108, doi:10.1029/2004JD004721, or take a look at http://blue.atmos.colostate.edu/publications/pdf/R-271.pdf, for further information.
Among other problems, there are forcings such as changes in the suns magnetic field, cosmic ray variations, temperature-albedo feedback, plankton-cloud feedback, and variations in the earth’s magnetic strength which are not included in the models. In fact, we don’t even know which of the forcings and feedback are relevant, nor their sizes and in some cases even their sign.
Finally, it is meaningless to say that “the models” are anything. Some of them, frankly, are so bad as to be humorous. In addition, they all predict different futures. It is very difficult to say anything true about two models, one of which forecasts radical warming and one mild warming, other than to say that one or both of them has to be wrong. Knowing that, any positive statement about both of them (and all the rest as well) is very suspect.
2) Nothing has been shown about UHI, how could it be? Jones continues to hide the data, so unless he’s secretly revealed it to you and you’ve done the math, no one knows whether UHI is a confounding factor or not.
3) The MSU tropospheric temperature data, even with the RSS adjustment, is still a long ways from being in alignment with the surface. All the models say the troposphere should warm faster than the surface, but none of the incarnations of the MSU data (MSU+RSS adjustments or straight RSS) show that happening.
w.
Willis,
Your item 2.
The Realclimate people may be referring to Parker’s piece as evidence that the UHI is a non-issue.
I have corresponded with Parker concerning his piece in Nature which claims that UHI effects are not a factor in historic instrument data. Parker claims that higher temperatures on windy nights disprove that UHI is an issue. In my opinion his claim does not take both night time radiative and convective cooling into account. I also feel that depending on the locations of the stations used in his article, warm windy nights may support the importance of the UHI effect.
Parker has provided data to Warwick Hughes and to me.
Dear Willis Eschenbach,
Thank you for your informed commentary.
Regarding point 1: please comment on:
http://www.grida.no/climate/ipcc_tar/wg1/450.htm#fig127
Regarding point 2: please comment on:
Parker, “Large-scale warming is not urban”, Nature 432, 290, doi:10.1038/432290a.
and
Peterson, “Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found”, J. Climate, 16, 2941-2959.
Regarding point 3:
Please comment on:
Santer et al., “Amplification of surface temperature trends and variability in the tropical atmosphere”, cience, Vol 309, Issue 5740, 1551-1556, 2 September 2005 [DOI: 10.1126/science.1114867]
from which I excerpt:
“The RSS T2LT, T2, and TFu trends are physically consistent (all three layers warm as the surface warms), whereas the UAH data show trends of different sign in the lower- and midtroposphere. These results support the contention that the tropical warming trend in RSS T2LT data is more reliable than T2LT trends in other observational data sets. This conclusion does not rest solely on comparisons with climate models. It is independently supported by the empirical evidence of recent increases in tropospheric water vapor and tropopause height (26, 36), which are in accord with warming but not cooling of the free troposphere.”
Re # 22. Ross, I have had a lot of experience talking to reporters who were doing stories on the economy. I got a lot of calls when I was at the Fed, and later I did economic forecasting and got calls whenever new data was released. Your comment about cutting through the cliches is well stated. These reporters are pleasant people and many are smart, or at least good writers. But they only hear what they want to hear for the story du jour. If they think the economy is going in the tank because the leading indicators declined this month, then you can tell them all day about how the evidence is for a growing economy. They will say, yes, but is it POSSIBLE that the economy could be going downhill? And if you admit the possibility, then that is the only thing that will be quoted.
Re: #25, Jack, thank you for your questions. Let me take them in order, repeating my statement first.
1) I said that climate models are not skillful in reproducing observational data.
Your IPCC reference shows the results of the runs of four different climate models forced by “natural”, “anthropogenic”, and “all” forcings. Given the number of models available from which to select four models to average, I don’t find these results at all surprising.
As I have stated elsewhere on this site, the results of GCMs are not evidence. How could they be? Each model gives different results. Yes, the averaged results of these four four models seem to make sense, but why have they used four models? And how did they pick these particular four models? Why not use just two models? Why didn’t they use them all?
Had they picked four other models, or just used two of the four chosen models, or used all of the models, their results would have been very different. How could they not be, since all of the GCMs give very different results by all measures (average, standard deviation, trend over any given period, IQR, autocorrelation, etc. ad infinitum).
Nor, in fact, did they use the models to generate the figures. They first had to fudge them. The notes say “Changes in cloud brightness (the first indirect effect of sulphate aerosols) were calculated by an offline simulation (Jones et al., 1999) and included in the model.” Oh, that raises the credibility level.
So these are not model results, they are model results as adjusted by Jones … and we all know that Jones would never play fast and loose with the facts … but I digress.
I guarantee you that among the IPCC models I could find four models which when averaged will give a result as bad as the four cherry-picked models were good. Would this prove to you that global warming is not happening? Of course not, because the results of GCMs are not evidence. Nor are they skillful, especially when one considers that the data had to get Jones’d in order to get the results they desired.
I find it astounding that the only requirement for inclusion of a GCM in the IPCC results is that it has to be big. Some of the models give a variety of results (e.g. year to year changes) that have never been observed on Earth, but they still get as much weight as any other model, and you still think the model results are a skillful representation of reality. What’s up with that?
2. I said we don’t know what the effect of the UHI is on global temperature records.
Curiously, your references prove my point. These papers hypothesize that there is absolutely no UHI bias at all in global temperature records. I can’t find complete copies of these on the web, so it’s hard to comment on them directly.
Regarding the Jones data, of course, we can make no determination of the truth because Dr. Jones has taken his toys and gone home. The other main datasets are the GISS data and the USHCN data. Both of these datasets are adjusted (in theory) for the effects of UHI. The IPCC also says that the UHI effect is real … and you are telling me that these papers show that the GISS, the USHCN, and the IPCC are all wrong.
Not to mention a variety of other solid, peer reviewed studies showing that UHI in some places (e.g. Atlanta, called “Hotlanta”, and Barrow, AK) is both quite large, and is not necessarily related to the size of the “urb”. Barrow, for example, is a very small town (pop 4600), but the UHI is as much as 6° C at times. (Int. J. Climatol. 23: 1889–1905 (2003), THE URBAN HEAT ISLAND IN WINTER AT BARROW, ALASKA, Hinkel et. al.)
Unfortunately, it is extremely difficult to say how big the UHI effect actually is. This is because the phenomenon is misnamed. Although the phenomenon is know as an “urban heat island”, in fact it is not limited to the urbs. A variety of changes around any given temperature station can change the local microclimate in significant ways.
The majority of these changes (e.g. increased fuel use in the area, increased foliage around the site, increased traffic by the site, increased buildings, paving of adjacent areas) increase rather than decrease the recorded temperature. Since these changes are site specific, there is no way to remove the effects without visiting all of the sites individually, and getting their history.
So you say there is no UHI effect on global temperatures. IPCC, GISS, and USHCN all say there is such an effect. My statement, that we don’t know, seems to be proven by this conflict.
3) I said that the models all show too high a rise in tropospheric temperature.
You cited the Santer paper in opposition to this statement. The Santer paper was extraordinary, and I have analysed it very carefully. They compared model results with tropospheric observational data from both the UAH and the RSS, with balloon observational data, and with sea temperature observational data from NOAA and HadCRUT2v. They found that the models don’t agree with the data. Their conclusion was … believe it or not … THE OBSERVATIONAL DATA IS WRONG.
Right …
They showed nine models, which all give extremely different results. The modelled surface temperature trends, for example range from a low of 0.04° per decade (virtually none) to nine times that large. Some of the models show clearly impossible results. One has the temperature heating and cooling at unheard of year by year rates, and another hardly varies at all from year to year.
Their models don’t correctly predict, or even closely resemble, any of the observational datasets, neither surface, balloon, UAH, or RSS. They don’t show the timing or size of any of the known swings in the surface and atmospheric temperatures. They don’t even agree with each other.
And the conclusion from this is that the models are right and the data is wrong?
Riiight …
Perhaps you believe that models whose results are different by up to an order of magnitude, both from the other models and from the data, in everything from trend to annnual change, can be used to prove or disprove anything … I don’t.
Since you agree with the paper, perhaps you can explain how models that are so radically different from both each other and from the observational data can prove anything. The fact that this paper passed peer review, while very revealing about the level of review that actually occurred, says nothing about the validity of the conclusions. The idea that the results of 9 wildly differing climate models can overthrow observational data is a chilling statement about the current quality of climate “science”.
All the best,
w.
ross, you said “I have done countless interviews over the past 4 years, for TV, radio & print, and it has been for the most part like trying to reason with a herd of buffalo.”
after reading through this site, and posting in for some mind numbing fun over at realclimate, i must admit you are incorrect. it is not like reasoning with a herd of buffalo, rather, a herd of cats.
mark
re 27
If UHI is such a big problem, why is it that tropospheric and surface data only disagree over the ocean where water temperatures are used as a substitute for air temperatures?
ref:
Douglass, David H., Benjamin D. Pearson, S. Fred Singer, Paul C. Knappenberger, and Patrick J. Michaels, 2004. Disparity of tropospheric and surface temperature trends: New evidence. Geophys. Res. Lett., 31, L13207, doi:10.1029/2004GL020212, July 9, 2004
http://arxiv.org/pdf/physics/0407075
Hans, it could also be that the basic GH theory is right & the MSU (troposphere) data is showing an upward trend, but the REAL surface trend (if UHI were correctly accounted for) in northern latitudes is less than MSU.
Interesting article. I’ve thought for some time that people interested in temperature series should spend more time on SST data than they were doing. The weird bucket adjstments deserve a little more attention than they are getting. Fred Singer suggested recently that there has been a major changeover in primary SST data source from vessels to floating buoys and hypothesizes that the floating buoys sample higher than vessels, leading to an upward bias in SST values as sampling methods change.
Someone could do a very easy, discrete experiment/publication to prove/disprove this. Just show the thermocline of the top 30 feet of water. Do some actual sampling over time in a couple places with different methods. And maybe publish some initial info on the distribution of SW injection hights for vessels.
You don’t have to take the whole story apart or slay the dragon one way or the other. Just do a good initial experiment. And publish the findings with a neutral title and conclusions. But the thing is…you start the process of validating/criticizing the method.
Willis,
Re: 27
Yesterday, I submitted a brief and polite question to Realclimate. Mike seems to have lost it. My follow up question as to what became of my last post was also lost.
The question was: “Can you please provide a link to Jones’ data?”
Why should questions about data be such an anathema to many people in climate science?
I think that Singer has submitted a funding proposal for this very experiment. NSF will probably reject it.
Re: #33
Brooks, the link he provided (reply to post 40, ref in post 23) was to the 2004 article:
Click to access JonesMannROG04.pdf
I think you will (unfortunately) have to be more precise in wording your question, as the link to the JM2004 paper would superficially seem to answer your request.
In reply to #27, Willis:
Recall that I originally said:
This is the weakest point of the chain of connectivity. The temperature data since 1850 is consistent with hindcast modeling, based on first principles; the UHI has been shown to be of little significance; the MSU data is aligning with the observed surface and predicted atmospheric trends, etc.
You provide a description of potential uncertainties in GCMs. There is no doubt that GCMs differ (if they didn’t, there would be little point in comparing their results for purposes of refinement), and there is also no doubt that modeling uncertainties remain. Nonetheless, we would be hard pressed to find any GCMs which, using known climate forcing factors, do not provide an output which shows a rising temperature trend since the mid-1800s.
The models are compared to the observational temperature data. This observational data, too, shows an increasing temperature trend (and it is also necessary to point out that ocean water column temperatures ALSO show an increasing trend). The Peterson paper is seminal partly because Peterson is the person in charge of USHCN data integrity, and also because it shows that divisions of the data into rural, semi-urban, or urban show essentially the same increasing temperature trend. There is no amplification in urban stations, nor is there a decrease in the rural stations.
A quick google search on the combination “Peterson urban rural temperature” provided several online references. This in particular seemed quite informative; I am providing it unlinked because it is a Powerpoint presentation requiring download:
http://www.ncdc.noaa.gov/oa/rural.urban.ppt
(Peterson’s comments regarding site history, which exists for every USHCN station, should interest you.)
Note that in Peterson et al. 1999, the increasing temperature trend for rural stations only was actually greater than for the full dataset (rural, urban, and in-between).
It is therefore difficult (verging on impossible) to say anything regarding the instrumental surface temperature record other than it clearly shows an increasing trend since the mid-1800s.
Finally, regarding the Santer et al. paper:
The paper, in general, finds better agreement with the RSS MSU analysis than the UAH. The paper shows how there are differences between the observational data and the model results (this forum is limited in discussing model differnces; the results were available because of the IPCC assessment process), and points out why there are potential problems with the satellite observational data. [For some reason, you place great stock in the satellite data (which is based on several different satellites, and one of the main problems has been intercalibration and “splicing” of the data from the different satellites) while being far less certain about the reliability of surface data.] And rather than saying that the observational data are wrong, it indicates that one satellite data analysis generally gets it right.
In summary, my original statement is correct (and I could have added more to the “etc”, such as the oceanic water column warming trend). While I admire Mr. McIntyre’s efforts to force better accountability and transparency in the paleoclimate proxy temperature field, which will hopefully result in a better understanding of how accurately past climate states can be determined, what he is doing does not significantly affect the assessment of what is happening now. Even such an esteemed global warming skeptic as Dr. Patrick Michaels fully admits the existence of the current warming trend, while discounting future amplication — this is where insights from paleoclimate studies would be particularly valuable.
I would hope that avid skepticism such as is evinced on this site would be enhanced by an acknowledgment of basic facts. This would certainly contribute to a more insightful process.
Thank you again for your replies on this topic.
“Even such an esteemed global warming skeptic as Dr. Patrick Michaels fully admits the existence of the current warming trend, while discounting future amplication ”
He also does not agree with the magnitude of the current warming trend attributed to anthropogenic causes, an important qualifier.
Jack, you wrote:
I don’t think that most of the skeptics think there’s an issue with the apparent warming trend existing. What is in question is the reason for that trend. Why is the earth warming? Is it because we’re coming out of the LIA? Is it because of a natural cycle of earth and sun? Is it because of human activity? Is it a mix of some of the above or other reasons we’re not aware of?
I also don’t think that knowing the temperature since the mid 1800’s means we understand past climate states. Isn’t climate a long view of “weather”? I don’t think present science is able to accurately show what past climate is (and isn’t this part of the debate we’re having, too?). We’re just beginning to understand the complexities and how the various issues relate. I’ll repeat that…we’re just beginning to understand the issues. It appears climate science is still in an embryonic stage, not yet even in its infancy. Paleoclimate science isn’t too different, either.
What Steve is doing does affect what is happening now…politically (Of course, Steve’s efforts will not change the climate, or the weather). Too many people are hanging their hats on bad science, suspect data and faith. As has been pointed out, climate has become a political tool. Steve’s efforts are necessary to help remove climate from the politician’s tool box.
I am content that the late 20th century is warmer than the 19th century for a variety of a reasons. I am not convinced that it is warmer than the MWP based on the multiproxy papers. It may be, but the multiproxy guys haven’t provided evidence that convinces me. I am not very impressed by the attribution papers. Again that doesn’t prove the reverse.
One of the original formulations of the UHI hypothesis [Oke] was that the UHI varied as log(population). It’s more complicated than that, but this formulation would require examination of population growth rather than population. I would expect that there would be more change in some suburban/”rural” settings than in a city like Vienna with a stable population and a relatively stable footprint. However, it’s not a topic that I’ve examined closely.
****** Jack writes:
Note that in Peterson et al. 1999, the increasing temperature trend for rural stations only was actually greater than for the full dataset (rural, urban, and in-between).
******
Could be that many of the, ahem, “rural” stations are incurring unrecognized UHIEs.
In response to #36 “[For some reason, you place great stock in the satellite data (which is based on several different satellites, and one of the main problems has been intercalibration and “splicing” of the data from the different satellites) while being far less certain about the reliability of surface data.]”
Yes, these are possible problems with the satellite data. Now multiply the exact same problems by at least one thousand for the ground based weather station measurements. This is a network of thousands of weather stations which was never designed to measure the global temperature, has spotty,varying, and limited coverage, no quality control, unknown calibration, inconsistent recording procedures, and of course, the dreaded Urban Heat Island effect.
See Roger Pielke, Sr’s web site for an article with an extensive discussion of the problems with weather stations. http://climatesci.atmos.colostate.edu/. Also Warwick Hughe’s discussion at http://www.warwickhughes.com/climate/. There used to be a link at John-Daly.com to another discussion of surface temperature but it seems to be broken.
re: #36
I looked at the slides and wasn’t too impressed. Of course the text that went with the slides isn’t there so I might have missed important things, but it seems the author(s) was trying to say there is no UHI to speak of. He starts off essentially saying that it’s all a figment of our imaginations that it’s warmer in cities than in rural areas and then later shows it is warmer. I don’t get exactly what he was going for! Best I can figure is that he thinks as long as you put thermometers in the right spot you don’t need to worry about UHI. This doesn’t work for me since 1. it’s the growth around an area which counts. 2. He was working with clusters of stations which almost by definitions they’re all in one urban area and therefore both ‘rural’ and ‘urban’ stations in the area are going to become more and more urbanized as the area grows.
I’ve conducted my own “UHI” experiment. Using two thermometers, I’ve found that the temperature on the north side of my house is usually 5 deg F warmer than the temperature on the north side of a tree 100 yards away. I’ve seen that the local radio station 3 miles away “in town” is almost always warmer than my house and the airport almost 10 miles away.
Of course, we have elevation differences (no more than 50′-60′), orientation, thermometer differences, calibration issues, etc.
The more you know the more you realize you don’t know…
Re post 25
Is Jack around ?
Re Jack’s question quoting Parker, “Large-scale warming is not urban”, Nature 432, 290, doi:10.1038/432290a.
I have just posted in Coolwire 13, scroll down at;
http://www.warwickhughes.com/cool/cool13.htm
and you can see how I have exposed one major fallacy in Parker’s paper.
What checks are made before Nature publishes this stuff ?
Jack also asks about Peterson, “Assessment of urban versus rural in situ surface temperatures in the contiguous United States: no difference found”, J. Climate, 16, 2941-2959.
I have asked TCP for his time series data for his urban rural clusters.
He has sent me only station ID’s and suggests his time series are not where I should be investigating, so I have a lot of digging to do yet.
I am just one unfunded guy who prefers this investigative work to fishing.
The research I am looking into is produced in multi-million $ taxpayer funded IPCC compliant orgs where people have massive computing budgets and no doubt all manner of junior help eager to do their bidding.
The few poor old sceptics have little hope of keeping up with the deluge of papers.
But Jack, this paper too is being looked into.
Best wishes to all, Warwick Hughes
Dave Dardinger,
I couldn’t find a discussion of the problems with weather stations on Pielke’s blog. Do you have a pointer? What I do read from Pielke (Sr.) indicates that while he is interested in calibration problems for global temperature datasets, he doesn’t appear to think that the observed trends are invalidated because of them.
Regarding the USHCN data, you may wish to read:
USHCN: Quality Control, Homogeneity Testing, and Adjustment Procedures
and
Global historical climatology network (GHCN) quality control of monthly temperature data
Warwick, thanks for the effort. Good luck. Lots of data to go through.
By the way, if you can also explain why spring thaws of rivers and lakes are about 9-10 days earlier, and winter freeze-up of rivers and lakes is about 9-10 days later, than in the late 1800s — without invoking a surface warming trend — I’d be interested in that, too.
Re 45 by Jack.
I have listed many errors in the V2 GHCN, scroll down at;
http://www.warwickhughes.com/climate/quality.htm
these are just examples I have come across by accident.
What could be found if little me had the computing power to SEARCH for errors.
There are many more here from USA data;
http://www.warwickhughes.com/climate/ghcn.htm
Once again, just kicked my toe on these as I worked on my Jones et al urban / rural comparisons.
I just get a bit sceptical of people quoting the GHCN as tho it is one of mankinds sublime creations.
Re 46 by Jack.
Try rebound from the Little Ice Age (LIA).
Best wishes, Warwick Hughes
RE 46
I think there is a need to investigate the effects of detergents and waste heat on the freezing of lakes and streams. For example, detergents contain alcohol which lowers the freezing point of water, so they would melt earlier and freeze later. I am not sure if this is the cause, but do think people don’t consider any other explanations except global warming for many observations.
Salt on roads being washed into streams would have the same effect.
re #45 Why are you asking me about Pielke? I don’t recall citing him. Certainly not in my last message.
I believe I’ve read both the links you have before. The trouble is that reading them doesn’t really help. Look, for instance at the first link. You read it and get down to the last step where they mention adjustment for UHI. Do they tell you how they do it? No! They reference another paper which is not (apparently) available on line. So what have I gained? Nothing. I think when I complained about this a few years ago someone sent me an electronic copy of the paper, but I don’t know where it is now. And if I recall, it didn’t really help anyway. It gives you a schematic version of how it’s to be done, but the actual steps aren’t given. The fact is that what’s actually done should be given in detail and examples shown and then let people look at it and see if it makes sense and try it themselves on some data. This would not be this difficult in this day and age and people who are expecting us to accept their policy recommendations should be willing to, and be required to, provide means for the intelligent reader to reach conclusions without having to spend years learning the biz and gathering obscure papers from multiple sources.
It’s bad enough here to try following the trail of something you want to learn, where everything is available and Steve is even available to help people who get lost. Why isn’t a similar site available for those who have their doubts about the conventional wisdom? They have tons more money and are trying to convince us and our representatives to introduce extremely expensive policies. I want some effort shown to provide what’s needed to the line of argument as deep as a person desires without hitting brick walls.
It does amaze me that the warmers have reached the stage where they are trying to prove that the urban heat island effect (UHIE) does not exist.
The phenomenon was first identified nearly 200 years ago in London. It has been the subject of hundreds of studies since. Anyone can verify the effect with simple experiments such as those Paul describes.
There are myriad infrared satellite photos with huge urban islands shown.
http://www.warwickhughes.com/climate/uhi2.htm
There are dozens of studies comparing cities with rural neighbours that show the cities warming faster, and there are at least three major studies which correlate UHIE magnitude with population (sure it’s not the only factor, only a proxy, so the correlation is not perfect). See esp. page 10 and references here: http://www.warwickhughes.com/climate/seoz_uhi.pdf
What is going on with Peterson’s study, and does it really challenge the view that long-term weather station aggegates do not have UHIE bias?
First, notice that Peterson’s raw data do show evidence of UHIE: the cities are warmer. He then makes various adjustments including for “siting” factors. These are the very factors that constitute the UHIE, i.e. proximity of buildings and other heat sources. Once he removes the siting and other non-climatic factors, he finds no discrepancy between “urban” and “rural” temperatures. What does he expect? He has taken out the UHIE and is then surprised that he can’t find the UHIE.
Second, consider the influence of Peterson’s focus on the USA. Even his “raw” data only show small UHIE effects. But why is this? Peterson correctly points to leafy urban weather stations, e.g. Central Park. Sure the weather instruments there are a long way from buildings. But how many cities in the rest of the world have their weather equipment in parks the size of Central Park?
Third, remember all the adjustments Peterson makes. By contrast, the vast majority of stations in long-term global aggregates like Jones’ are used “raw”. Even if Jones were serious about trying to make adjustments as extensive as Peterson’s, he could not do so. There is little or no metadata on most GHCN sites, especially in the three quarters of world land area covered by developing countries. Nor has Jones done station-by-station inspections to assess the influence of “siting” factors.
[Actually, Jones often takes a rather cavalier attitude to “inhomogeneities”. Sometimes he even splices together records from two different stations. For Sydney, Australia, his data take a dive in 1971 when he switches from the Observatory Hill site to the airport — but then warm up rapidly as the airport grows like topsy up to the 2000 Olympics:
http://www.warwickhughes.com/climate/sydney.htm ]
Remember too that Peterson’s study is a snapshot, not a time series. What he has shown is that he can account for the difference between current temperature readings at different sites by examining the factors that influence the readings. That is not the issue. It is the physical changes associated with population growth, not absolute population at a moment in time, that leads to warming trends in temperature aggregates.
A more relevant test than Peterson’s for assessing the validity of the trends in temperature aggregates would be to compare data from “dark” nightlight sites with those from moderately or brightly lit sites. Jim Hansen did this in 2001. The unlit US sites showed cooling of 0.05 degrees over the 20th century, whereas the bright sites showed a quarter of a degree of warming.
Hansen should have conceded that this showed that long-term temperature aggregates had warming trends from UHIE. Instead, he “adjusted” all the stations, but especially the unlit ones, using similar techniques to Peterson (who was a co-author). He managed to conclude that the United States had warmed a third of a degree in the 20th century:
http://pubs.giss.nasa.gov/docs/2001/2001_HansenRuedyS.pdf, page 20
So the cities showed warming when the countryside didn’t, but the “real” warming was higher still. Quite a performance! Perhaps Peterson’s observations about preconceptions influencing data treatment could be applied to his own side too.
“By the way, if you can also explain why spring thaws of rivers and lakes are about 9-10 days earlier, and winter freeze-up of rivers and lakes is about 9-10 days later, than in the late 1800s ”
Is that the overall trend, or a local impact somewhere? Are you comparing latest thaws of 1800 to earliest thaws of the past twenty years?
As a data point, I personally saw Ice on Lake Champlain this year in late May, this is roughly 20 days later than I normally see it there. Though admitedy my observational time frame is sporadic.
I just haven’t seen a real complete data set for what your are talking about (global, not local), so far as I know there is only good data for one area in Alaska where people have been betting on it for like 75+ years. I know of no comprehensive study going back that far.
But I honestly would like to see the data, data that is up to date of course. I’e seen a lot of data for the northeast that snowfall is less now than it was in the 1970’s (same with lake, ice). However that data ends in 2000, those of us that live in the Northeast realize that the years from 2000 to 2005 have seen abnormally large snowfall, incluiding the winter of 2003-2004 where we had eight months of snow at least one day a month. And who can forget the snow in Las vegas last year.
Re. 45, see this.
Item 1 has link to problems with weather station sites.
Jack wrote: (Peterson’s comments regarding site history, which exists for every USHCN station, should interest you.)
The PowerPoint viewer seems not to display such comments.
One pertinent comment about the USHCN station history file may be that the first of this month was the eleventh anniversary of the most recent update to it.
Check out Parker’s and Peterson’s studies on the Urban Heat Island and you will discover that there is no significant difference between rural and urban weather stations.
Also, this article was in the WSJ, not in some, what you would say, “liberal” paper. That the WSJ seems to indicate that skeptics are mistaken, it shows that the proof of the occurrence of human-induced climate change exists.
re 54: The Wall Street Journal’s opinion proves that human-induced climate change exists??? How foolish of me not to realize that the question had been settled.
I mean, I’d heard that scientific results about the climate were submitted to the journals … but I didn’t realize they meant the Wall Street Journal. In that case, we can all go home, move along, folks, there’s nothing to see here, party’s over …
w.
RE: #55, “The Wall Street Journal’s opinion proves that human-induced climate change exists???”
I did not say that. I said that if the WSJ is featuring columns which say climate change is happening and that it is humanity’s fault, at least in part, then the proof must be there.
Even the WSJ wouldn’t smokescreen an issue if it were clear that it was true.
Re: #51, from ET Sid Viscous:
This is the paper:
Magnuson, J. J., Robertson, D. M., Benson, B. J., Wynne, R. H., Livingstone, D. M., Arai, T., Assel, R. A., Barry, R. G., Card, V., Kuusisto, E., Granin, N. G., Prowse, T. D., Stewart, & K. M., Vuglinski, V. S. 2000. Historical Trends in lake and river ice cover in the Northern Hemisphere. Science 289: 1743- 1746.
John J. Magnuson’s Web site
I apparently was misremembering the trend in this data; it’s 5-6 days earlier (for thaw) and later (for freeze). The 9-10 days is probably for a different phenological trend.
Re: #42, from Dave Dardinger:
Sorry, my response was for Paul. I didn’t make the attribution correctly.
Re: #47 from Warwick Hughes
Regarding rebound from the LIA: sure, that’s fine, but there is a warming trend. That would be global, wouldn’t it? [I still think that current observations indicate greenhouse warming as part of the cause, and I think that the ocean water column warming is probably the most unassailable data set demonstrating it. My point in the original “weakest link in the chain of connectivity” was to note that a variety of data types evince a warming trend which is consistent with basic physics and models containing them. Tim Barnett of Scripps made some considerably stronger statements regarding his recent paper.]
Regarding urban heat islands, in general:
The main issue seems to be whether or not UHIs significantly affect global temperature trends. UHIs of some kind certainly exist; I offered papers which indicate how their climate effect has been assessed. To show that UHIs are a primary rather than a peripheral factor in global climate change would require rebuttal of these assessments, and demonstration of how the UHI signal propagates into the full climate system. In particular, I think that it would take effort to show how UHIs affect ocean temperatures at depth, and how they are the main factor in Hansen’s “global energy imbalance”.
Finally, if UHIs are indeed a primary warming factor: cities aren’t going away.
Re 57, Jack, thanks for posting. A couple things.
As you point out, a main issue is the influence of the UHI on the recorded trends. Until Jones et. al. gets off their “my data! mine! you can’t see it! it’s mine! mine!” kick, we won’t find out.
However, UHI is likely not a “primary warming factor” as you state. The cities likely are not warming the world appreciably, but they may be warming the temperature record significantly, which is very different.
w.
Re #57,
Jack, the warming of the oceans since 1955 doesn’t resemble the increase of GHGs in any way. See the sinusoidal curve at Levitus ea., with a cooling 1980-1985, while GHGs were increasing fast. Hansen linked the 1993-2003 warming to the increase of GHGs in that period, but did not include the previous periods…
Moreover, Barnett proved that models don’t capture natural variability. See Fig. S1 of the supporting online material which shows that the models and the observations significantly differ for any periodic events between 10-60 years, which includes the 11/22 and longer sun cycles.
Further, the change in heat content, corrected for ocean surface area/volume, shows that the NH oceans warm much faster (some 50%) than the SH oceans, while GHGs are more evenly distributed, but aerosols are emitted (and stay there) for 90% in the NH. Aerosols, according to current climate models, have a large cooling effect…
Last but not least, there is a huge discrepancy between the supposed radiative heat balance at the surface, according to Barnett, and the heat storage, as follows from the ocean findings, according to Levitus, based on NOAA data (fig. S2 in the Levitus paper need to be corrected for ocean area to be comparable to the Barnett findings at http://www.sciencemag.org/cgi/content/full/309/5732/284/FIG4 ).
Re: #59, Ferdinand Engelbeen,
Sorry for the delay in reply. I saw that you posted a similar discussion on RealClimate.
Jack, the warming of the oceans since 1955 doesn’t resemble the increase of GHGs in any way. See the sinusoidal curve at Levitus ea., with a cooling 1980-1985, while GHGs were increasing fast. Hansen linked the 1993-2003 warming to the increase of GHGs in that period, but did not include the previous periods…
I don’t see why the ocean warming should resemble the increase in GHGs. Temperature changes in the climate system are non-linear and spatially diverse, ocean circulation is variable, and ocean/atmosphere systems like the PDO and NAO have specific phase characteristics that don’t have much in the way of intermediate “positions”.
Levitus et al. 2005 discusses non-uniform oceanic temperature response in paragraph 11, with an interesting reference to the Indian/Asian brown cloud.
Moreover, Barnett proved that models don’t capture natural variability.
That’s unsurprising, particularly because they can’t effectively capture the size, duration, or frequency of ENSO events, though they do have them. That’s why ensemble results are preferred over single run results. Am I missing something more subtle?
Further, the change in heat content, corrected for ocean surface area/volume, shows that the NH oceans warm much faster (some 50%) than the SH oceans, while GHGs are more evenly distributed,
Barnett says that the warming signal in the northern and southern Atlantic penetrates deeper due to convection. Warming of the Indian Ocean appears to have been suppressed by aerosols (though I don’t know how far south this effect extends). Also refer to the last sentence of Levitus et al. 2005 paragraph 11.
Last but not least, there is a huge discrepancy between the supposed radiative heat balance at the surface, according to Barnett, and the heat storage, as follows from the ocean findings, according to Levitus,
I looked at both papers side-by-side and cannot find a specific mention of this. However, Levitus et al. 2005 indicates that ocean warming may actually be under-estimated (end of paragraph 10). If that’s the discrepancy, it’s not in the direction I would prefer it to be.