Excellent news. Some climate scientists have started a blog called RealClimate, something sorely needed to correct the disinformation put about by Tech Central Station and the like. I hope they can do for climate science what T…
Let me be frank. While I’m hopeful about the realclimate.org effort I’m not especially optimistic that it will work.
[Response: Thanks. We need just this kind of constructive criticism at this early stage of the site’s development ;)
This article reinforces my fears. For instance, while this article has text that appears to critique some of McKitrick’s work, the following quote appears to corroborate it:
“Benestad (2004) repeated their analysis using a a different statistical model (linear and generalised multiple regression model), and found coefficients of similar magnitude for the factors McKitrick and Michaels proposed as important.”
I am guessing there is some qualifier missing above. As it stands, I find it hard to place this in the semantic context of the article. This tends to indicate that the article was assembled with insufficient care.
To make matters worse, we have this:
“In their reply to my comment, McKitrick and Michaels (2004b) note that I do not dispute their choice of data or their methodology. While that is true, they should not confuse this with my vouching for their approach. I have not commented on their choice of methodology or data simply because that is beside the point.”
This is perfectly coherent in a logical way, but not everyone reads with precision. Many people, reading casually as web users are wont to do, will see “I do not dispute” to mean “I agree”. The following sentences will then be lost in the shuffle
in ways that they would not be in apurely academic environment. It would be better to say something like:
“McKitrick and Michaels (2004b) misleadingly cliam that I do not dispute their choice of methodology. A methodology is only valid when correctly applied, and this M&M 2004 have egregiously failed to do.” (Or something like that, presuming that I take the meaning correctly.)
[Response: Again, thanks for your constructive criticism. We have revised the posting significantly to address, among other things, the various issues you’ve raised. Please see our revised version as of 12-14-04.]
Worst of all, even though I work in the climate field at a major and well-endowed university, I have no access to the journal in question, and am therefore unable to make much of the argument without going to considerable effort. Consider how much
more difficult this will be for the general readership.
[Response: Well, this we can’t do much about. However, we have linked to a pdf version of the Benestad (2004) article (we don’t have access to the other articles cited).
Something like this article may belong in the journal in question, but the purpose of this site is outreach to the general public, both directly and through journalists. This article does not succeed in this effort.
I appreciate that the effort is finally being made, (and for what it’s worth I’m willing to help) but one should have no illusions that the task is easy. I hope that in future even the primary contributors will not simply allow but demand some editorial input to ensure that their contributions are appropriate for a general audience. More articles like the current one will reduce realclimate.org to just another professional mailing list with negligible impact on public discourse.
[Response: Again, we hope you find the revised version of our posting an improvement over the original. We would certainly like to encourage you to consider contributing guest postings if you feel so inclined. And, again, we appreciate very much your helpful feedback on the current content of the site.
It is interesting that McKitrick and Michaels would not account for the effect of correlations between nearby stations on the size of confidence intervals and on statistical significance, since Ross McKitrick lectured me (quite correctly) several years ago on the similar effect of autoregressivity in temperature time series.
I hate to be blunt and mean: You guys are wasting your time. No one who doesn’t agree with you is going to fight through your essays as currently writen. You are fighting the good fight — but you’ve no chance of winning.
I used the readability tool in MS Word to check your entry “Are Temperature Trends Affected by Economic Activity.” Your piece is less readable than journal articles in Harvard Law Review. Your piece is slightly easier to read than the average insurance policy.
Clarity and efficiency in writing is important on the web and in email. More important than on the printed page. Computer screens cause substantially more eye-fatigue than do printed pages. So people scan to compensate.
For clarity of writing on the web I’ve found the work of Dr. Rudolf Flesch helpful. He developed a formula back in the 40’s for readability. I’ve begun using it for my own web writing and email and noticed real improvement in audience comprehension.
[Response: (to James Acres)
I understand your comment, and yes, this piece is very technical indeed. It also discusses several points, which makes it even more complex. I felt it was important to include the technicalities in order to convince. By popularising the piece, the article loses its edge. I guess that there is a similar reason why articles in Harward Law Review are not popularised either. Maybe I can write a more understandable ‘translation’ for the lay person? Or re-cap in one sentence: the analysis by MM04 can be thought analogous to conducting a survey, where 10 individuals are asked the same question 100 times and then presenting the results as a statistical sample from 1000 independent polls. -Rasmus]
I find some of the work on this site to be a challenge to read and it takes some work to understand the technical references, however the information and the broadening of my understanding through this effort make it well worth the investment. The time and thought that you have put into this effort are greatly appriciated. Thank you and plesae keep it up!!!
[Response: Thank you for bringing my attention to the paper by De Laat and Maurellis (DLM04) and the URL. After having read their paper, I must admit that I’m left with a number of unanswered questions. DLM04 argue that there is a correlation between industrial actiivty (local CO2 emission) and temperature trends, and it may therefore seem to support MM04. I noticed, however, that their Fig. 2 showed a systematic difference between the trend in the global climate models (GCMs) corresponding to the regions where the CO2 emissions are higher than the given threshold value and those where they are lower (henceforth referred to as ‘above’ and ‘below’ curves). I presume that the CO2 emission data are the same as for the real world. The GCMs from IPCC (2001) do not, unless I’m very mistaken, account for the urban heat island effect. Hence, I see their results as supporting the contention by Benestad (2004) that the overlap between the economic activity and temperature trends was coincidental and misleading due to high spatial correlation.
I also find it hard to fit the conclusion of DLM04 into the broader picture: the SST trends are still positive and not affected by local industrial effects, and there was a strong temperature trend in Russia even after the collapse of the old Soviet that also affected their industry. If DLM04 were correct, then should not the temperature trends there drop after 1990? On the contrary, and MM04 proposed that the strong trends here were due to a deterioration of the quality of the stations.
One would expect an urban heat island to produce a local warming, but it is difficult to see physically how the industrial activity can lead to an ongoing warming trend unless the activity grows quite dramatically. Why should there be an ongoing trend with if there is a stable level of heat spillage?
I have also some possible misgivings about the analysis and the figures in the DLM04 paper:
(a) I find it hard to reconcile the curves for below and above the thresholds because why doesn’t the gap between these two increase with the level of CO2? Fig 1a in DLM04 shows how the mean surface temperature trends (y-axis) vary with different threshold values for the CO2 emissions (x-axis), and even over several orders of magnitude (0.01 … 30GT/year), the trends only change by ~0.1 according to their figure! To me, it seems like the trends are not all that sensitive after all to the changes in the CO2 threshold!
(b) Why do the trends for the lower tropospheric MSU trends (Fig.1b) increase so much rapidly with the threshold values above 2GT/year than the surface (Fig.1a)? It is almost tempting to draw the conclusion that (locally) the enhanced greenhouse effect is important after all according to observation (i.e. that the lower troposphere warms more rapidly than the surface)!
(c) The trends in the temperatures from the GCMs (Fig. 2 in DLM04) are strangely insensitive to the CO2-threshold (x-axis). Presumably the way the analysis is done, the CO2-thresholds are represented by different regions for which the industrial activity differs. The GCMs tend to produce temperature trends that vary geographically, and I would expect to see at least some changes in the trend estimates when the fractional surface area becomes small. I find it a bit suspicious that all of the GCMs produce a constant trend level for all different intervals and yet there are clear differences between the ‘above’ and ‘below’ curves.
Finally, I note that DLM04 observes that “Bengston et al  have shown that model-predicted surface temperature trends are much larger (by about a factor of two) than what has been observed over the last two decades” but do not discuss the fact that the observed and simulated surface trends in Fig 1a (0.19 K/decade) and Fig 2 (NCAR-DOE-PCM: ~0.2K/decade) seem to agree very well (and even the surface trend from ECHAM-OPYC3 suggests ~0.3 K/decade). Furthermore, DLM04 argue that there are important differences between the real world and the GCMs in terms of how the trends change with the x-axis, but do not mention the similarities in that both GCMs and real world data iindicate higher trends for the ‘above’ curves. rasmus-]