One of the defenses often used by climate modelers against charges that climate is simple to complex to model accurately is that “they do it all the time in finance and economics.” This comes today from Megan McArdle on economic forecasting:
I find this pretty underwhelming, since private forecasters also unanimously think they can make forecasts, a belief which turns out to be not very well supported. More than one analysis of these sorts of forecasts has found them not much better than random chance, and especially prone to miss major structural changes in the economy. Just because toggling a given variable in their model means that you produce a given outcome, does not mean you can assume that these results will be replicated in the real world. The poor history of forecasting definitionally means that these models are missing a lot of information, and poorly understood feedback effects.
Sounds familiar, huh? I echoed these sentiments in a comparison of economic and climate forecasting here.
@Shills:
“That is why I gave you two other papers that had ranges of sense. at 2.3 to 4.1, and 2. to 4. And both are model-independant. Have you seen them?”
Yes, I have seen them as I read them a few years earlier. Not all numbers in these papers are model-independent (eg, Tung and Camp have only been able to avoid using models for establishing their lower bound and are borrowing a model-independent upper bound from another study), but together with other papers there is enough to say that there are model-independent estimates for climate sensitivity of the scale used in IPCC reports.
Now we come to the gist of the argument. You said that even if the models did not exist, we would still have a ‘catastrophic warming camp’ as there is a lot more evidence besides the models. The thing is, yes, there is some understanding of some of the processes, and there are model-independent estimates for some of the key parameters, like climate sensitivity, but we are still asked to take action based on predictions, and these predictions *are* based on models. It has been the argument of IPCC that there’s just no escaping models when you want to say that 30 years from now it will be warmer. So, no, if the models did not exist, we would not have a ‘catastrophic warming camp’.
I admit it would have been more fair to state the above right when the debate started to save you the time spent looking for references. The argument, however, has a point. Since there’s no escaping models, the quality of these models play a central role in deciding whether or not the climate is going to change in catastrophic proportions. If predictions made by these models do not hold, we don’t know whether the climate is going to change in catastrophic proportions. If predictions can’t (yet) be verified, we don’t know that either. If predictions hold, but are too vague (eg, they would have held even if the Earth was not warming, to take the extreme), it was silly to have such a model in the first place and we still don’t know ™. In my view, all models that we currently have fall into one of these three camps. Which is sad.
I hope this clears it a bit and you can better see why people like me, Wally and Russ participate in these debates, even those where the hopes of having a sensible discussion are limited.
Miriam,
The model-less estimates of climate sensitivity together with emissions scenarios and the already observed effects of warming on ice, biology, ocean acidity, and drought (the now famous RC comment page has some stuff relevant here) would be evidence enough for many scientists to conclude that very bad things could happen if warming were to continue. The uncertainty is huge sure, but if, hypothetically, all we had (so no models) was the knowledge that the present warming was causing minor damage now, the idea that more warming later would cause worse problems is not irrational. So, instead of this so called catastrophic camp being the mainstream view, it might be a more contentious view, but it would still exist.
You say:
‘In my view, all models that we currently have fall into one of these three camps. Which is sad.’
Well in my view, if you have such condemning criticisms of something then you must surely have some credibility on the subject, thus can discuss it in the scientific arena, which would be great because than you can correct all the scientists. But unfortunately you probably haven’t because they are all still going around, blindly unawares, using these apparently dodgy models, which is sad.
Shills says: “The uncertainty is huge sure, but if, hypothetically, all we had (so no models) was the knowledge that the present warming was causing minor damage now, the idea that more warming later would cause worse problems is not irrational.”
Unfortunately, efforts to stabalize CO2 concentrations are enormously difficult. Roger Pielke, Jr. has written a book on the topic and posts regularly at his blog on this issue. A recent post is illustrative of the problem. http://rogerpielkejr.blogspot.com/2010/09/twenty-five-wedges-or-more.html#links
@Shills:
“But unfortunately you probably haven’t because they are all still going around, blindly unawares, using these apparently dodgy models, which is sad.”
And this is where we ultimately differ.
I might be mistaken, and if so, I apologize in advance, but you seem to have decided for yourself that you won’t ever be able to decipher what is it that the experts are talking about, or maybe you decided that you don’t care enough. Thus you take the fact that they are “still talking” about catastrophic global warming to be sufficient evidence that the models are OK and do predict enough to take action.
My position is different. I did care enough to read papers and studies for a few recent years, as well as educate myself on the subject. My math degree helped. I feel I can at least tell something real from a fluke (your opinion might be different, but, well, the proof is in the pudding, bring some real points and we’ll talk) and so I see messing around with dodgy models for what it is – messing around with what you have for lack of something better.
As to the inevitable advice to go ahead and have it with the experts, thanks, I am doing what I can in my spare time, but climate science is not the only thing that interests me and I am unlikely to change careers.
Russ and Wally:
Lucia at the Blackboard, http://rankexploits.com/musings/
regularly posts on issues involved in comparing model projections to actual temperatures. She has a search feature on her blog that will generate a long list of entries on this topic. I believe she is an engineering professor who has taken an interest in climate issues. She describes herself as a “lukewarmer” Her posts are informative and contain much analysis of the issues involved, along with extensive discussions in the comments from a variety of perspectives.
Shills, dear…
“The model-less estimates of climate sensitivity together with emissions scenarios and the already observed effects of warming on ice, biology, ocean acidity, and drought (the now famous RC comment page has some stuff relevant here) would be evidence enough for many scientists to conclude that very bad things could happen if warming were to continue. The uncertainty is huge sure, …”
Models happen between the first and second sentence. No models, no predictions, no uncertainties, no camp.
Paul, thanks for the link, I’ll check it out.
By the way, I love the thread on RC.
#276 (camp Pro): 10 paragraphs of talk about GDP, its growth and federal spending. A-OK.
#277 (camp Contra, Wally): 4 paragraphs of talk on the same matters in response. A note from the admin of the forum – “Completely OT, no more please. Jim”
#280 (camp Pro): 2 paragraphs of more economy talk in response to Wally. OK.
#281 (camp Pro): 2 more paragraphs on economy. OK.
#282 (camp Pro): 3 more paragraphs on economy. OK.
#283 (camp Pro): 8 paragraphs on nuclear ban, malnutrition in India and futility of efforts to educate Wally on anything because he just won’t listen. OK, of course.
#284 (camp Pro): another reply to Wally’s post, 6 paragraphs, economy and pointing where Wally should go. OK. Why wouldn’t it be OK, right?
Pure fun. 🙂
I bet at least one of Wally’s posts have already been stopped. Any takers? Don’t mess with settled science, guys.
Alan, after thinking through your idea of detrending the data, I’m still wondering why we’re doing that if we want to compare a model’s predictions to actual results. I understand the autocorrelation issue. That being that temperature at time 1, T(1) heavily influences temperature at time T(2), thus your data points are not fully independent of one another. However, what you purpose does not get around that problem any better than a least squares method, both methods are finding the first direvative, just through a different process.
What you’re having us do is get the delta value for each data point, then use those data points as independent samples, and run a T-test as normal right? But that is little different from what the regression analysis will end up doing anyway. The mean of what you’re going to get is the average slope. But the regression is going to give you a least squares estimate of the same thing. Which as you probably know just means the weighting of each data point is different, and the least squares method effectively weights things farther away greater than a simple average.
So when you go to test the confidence in the line generated by the regression, you’re using the sum of the squared residuals from the line. Then in your method you doing the same thing but from the mean delta. They are quite similar, and I don’t think you get around auto correlation is either case, as even your delta is reduced thanks to it.
Secondly, what we’re ultimately trying to do is test the actual data against slope of the model projections, which at realclimate I believe someone correctly brought up we should make sure to test the slope for the right time periods, as the predictions are not linearly for the whole 100+ years. So, the test we’re doing is T = beta(found)-beta(predicted)/SEbeta(found).
So, I suppose what you’re suggesting is that we instead use T=ave.delta(found)-ave.delta(predicted)/SEave.delta(found). Is that right? And I may be wrong, but I’d guess ave.delta(predicted) and beta(predicted) are going to be the same thing.
I honestly don’t think you’re going to find substancially different results with either method, nor do I think one method gets around this autocorrelation problem any better than the other. I’m interested to see this issue discussed further however, do you have a good link for a more indepth analysis? Basically, I’m not finding the reasoning for using a simple mean over a least squares method.
Waldo: You describe everything I say as paranoia. I did not dream up the 80% reduction in CO2 required to stop global warming (according to the models). The other stuff you quote (1-3% reduction in GDP) for the first cap and trade step is not the point. This is certainly doable. The 80% thing has been published repeatedly. Why start on the first cap and trade part if we abe not prepared to continue to 80% reduction? The Obama administration and all the other AGW believers talk about an 80% reduction by 2050. Are you saying that such a reduction is feasible without wrecking the economy? If you have some explanation, I would be delighted to hear it.
I am not an anti AGW zealot. I don’t know if CO2 is as bad as the AGW enthusiasts say. Until we are sure, have alternative energy schemes in hand, and have the Chinese and Indians on board, it is premature to embark on the first step in reducing CO2 by 80%. Also, what are the alternatives? Rather than wreck the economy, maybe everyone could move a couple of hundred miles north. Many people moved south with the advent of A/C.
The cap and trade blogs are at least honest (some of them). They point out that there is no viable alternative energy scheme, but the CO2 cap will force people to find such schemes. Thus, we should jump out of the airplane and hope somebody invents an earth softener before we hit the ground. Wouldn’t it be better to do it the other way around?
RE: Hansen (1988) – Autocorrelation issue.
Wally et al,
I spent a few hours last night reading up on the various approaches for identifying and correcting autocorrelation in time series data.
Here are a handful of good references:
http://www.statsoft.com/textbook/time-series-analysis/?button=3
http://www.docstoc.com/docs/27442875/Autocorrelation-in-Regression-Analysis
http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc44.htm
http://userweb.port.ac.uk/~judgeg/INEMET/e255_l13.pdf
http://www-stat.stanford.edu/~jtaylo/courses/stats203/notes/time.series.regression.pdf
Since I don’t have access to professional statistics software with GLS tools, I’m limited to excel-based OLS methods. I’ve settled on the AutoRegressive (AR) approach, which basically runs a standard OLS regression twice – first regressing the data against 1-period lagged observations to identify and strip out auto-correlation, and second to regress the residuals against the date to identify trend and significance.
Here’s a summary of the preliminary results:
Hansen’s temperature projections (1988-2010)
Scenario: Scenario_A Scenario_B Scenario_C
Slope: β = 0.029844862 0.027396245 0.019274704
(Source: http://www.realclimate.org/data/scen_ABC_temp.data )
UAH data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.834750724
(Source: http://woodfortrees.org/data/uah/from:1988/to:2010.58/plot/gistemp/from:1988/to:2010.58 )
GISTEMP data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.760693177
(Note the higher autocorrelation coefficient for the UAH data.)
UAH AR(1) autoregression
Observations: n = 270
Intercept: α = 0.022953044
Lag-1: β = 0.838341028
GISTEMP AR(1) autoregression
Observations: n = 270
Intercept: α = 0.097138485
Lag-1: β = 0.76108575
Both data sets were stripped of autocorrelation as modeled above, and the residuals used for the next stage of regression.
UAH Residuals regression
Observations 270
Slope 0.019506406
Standard Error 0.006566299
Scenario: Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 1.574472273 1.2015656 -0.035286678
Pvalue (2 tail) 0.115378307 0.229531876 0.971851146
GISTEMP Residuals regression
Observations 270
Slope 0.01920112
Standard Error 0.004669017
Scenario Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 2.279653399 1.755214024 0.015759938
Pvalue (2 tail) 0.022628253 0.079222706 0.987425909
Conclusions: As expected, the T-stats are lower than before. Due to the higher degree of autocorrelation in the UAH data, they only give us 77% & 88% confidence that we can reject the predictions for Scenarios A & B respectively. The GISTEMP data show a significant difference between predictions and observations with 98% and 92% confidence.
As always, please let me know if you have any concerns with the method, and I’m happy to email the spreadsheet I used to anyone who’d like it.
If the above checks out, I’ll repeat with IPCC (1990).
RE: Hansen (1988) – Autocorrelation issue.
Wally et al,
I spent a few hours last night reading up on the various approaches for identifying and correcting autocorrelation in time series data.
Here are a handful of good references:
http://www.statsoft.com/textbook/time-series-analysis/?button=3
http://www.docstoc.com/docs/27442875/Autocorrelation-in-Regression-Analysis
http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc44.htm
http://userweb.port.ac.uk/~judgeg/INEMET/e255_l13.pdf
http://www-stat.stanford.edu/~jtaylo/courses/stats203/notes/time.series.regression.pdf
Since I don’t have access to professional statistics software with GLS tools, I’m limited to excel-based OLS methods. I’ve settled on the AutoRegressive (AR) approach, which basically runs a standard OLS regression twice – first regressing the data against 1-period lagged observations to identify and strip out auto-correlation, and second to regress the residuals against the date to identify trend and significance.
Here’s a summary of the preliminary results:
Hansen’s temperature projections (1988-2010)
Scenario: Scenario_A Scenario_B Scenario_C
Slope: β = 0.029844862 0.027396245 0.019274704
(Source: http://www.realclimate.org/data/scen_ABC_temp.data )
UAH data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.834750724
(Source: http://woodfortrees.org/data/uah/from:1988/to:2010.58/plot/gistemp/from:1988/to:2010.58 )
GISTEMP data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.760693177
(Note the higher autocorrelation coefficient for the UAH data.)
UAH AR(1) autoregression
Observations: n = 270
Intercept: α = 0.022953044
Lag-1: β = 0.838341028
GISTEMP AR(1) autoregression
Observations: n = 270
Intercept: α = 0.097138485
Lag-1: β = 0.76108575
Both data sets were stripped of autocorrelation as modeled above, and the residuals used for the next stage of regression.
UAH Residuals regression
Observations 270
Slope 0.019506406
Standard Error 0.006566299
Scenario: Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 1.574472273 1.2015656 -0.035286678
Pvalue (2 tail) 0.115378307 0.229531876 0.971851146
GISTEMP Residuals regression
Observations 270
Slope 0.01920112
Standard Error 0.004669017
Scenario Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 2.279653399 1.755214024 0.015759938
Pvalue (2 tail) 0.022628253 0.079222706 0.987425909
Conclusions: As expected, the T-stats are lower than before. Due to the higher degree of autocorrelation in the UAH data, they only give us 77% & 88% confidence that we can reject the predictions for Scenarios A & B respectively. The GISTEMP data show a significant difference between predictions and observations with 98% and 92% confidence.
As always, please let me know if you have any concerns with the method, and I’m happy to email the spreadsheet I used to anyone who’d like it.
If the above work checks out, I’ll repeat with IPCC (1990).
RE: Hansen (1988) – Autocorrelation issue.
Wally et al,
I spent a few hours last night reading up on the various approaches for identifying and correcting autocorrelation in time series data.
Here are a couple of good references:
http://www.statsoft.com/textbook/time-series-analysis/?button=3
http://www.docstoc.com/docs/27442875/Autocorrelation-in-Regression-Analysis
http://www-stat.stanford.edu/~jtaylo/courses/stats203/notes/time.series.regression.pdf
Since I don’t have access to professional statistics software with GLS tools, I’m limited to excel-based OLS methods. I’ve settled on the AutoRegressive (AR) approach, which basically runs a standard OLS regression twice – first regressing the data against 1-period lagged observations to identify and strip out auto-correlation, and second to regress the residuals against the date to identify trend and significance.
Here’s a summary of the preliminary results:
Hansen’s temperature projections (1988-2010)
Scenario: Scenario_A Scenario_B Scenario_C
Slope: β = 0.029844862 0.027396245 0.019274704
(Source: http://www.realclimate.org/data/scen_ABC_temp.data )
UAH data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.834750724
(Source: http://woodfortrees.org/data/uah/from:1988/to:2010.58/plot/gistemp/from:1988/to:2010.58 )
GISTEMP data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.760693177
(Note the higher autocorrelation coefficient for the UAH data.)
UAH AR(1) autoregression
Observations: n = 270
Intercept: α = 0.022953044
Lag-1: β = 0.838341028
GISTEMP AR(1) autoregression
Observations: n = 270
Intercept: α = 0.097138485
Lag-1: β = 0.76108575
Both data sets were stripped of autocorrelation as modeled above, and the residuals used for the next stage of regression.
UAH Residuals regression
Observations 270
Slope 0.019506406
Standard Error 0.006566299
Scenario: Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 1.574472273 1.2015656 -0.035286678
Pvalue (2 tail) 0.115378307 0.229531876 0.971851146
GISTEMP Residuals regression
Observations 270
Slope 0.01920112
Standard Error 0.004669017
Scenario Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 2.279653399 1.755214024 0.015759938
Pvalue (2 tail) 0.022628253 0.079222706 0.987425909
Conclusions: As expected, the T-stats are lower than before. Due to the higher degree of autocorrelation in the UAH data, they only give us 77% & 88% confidence that we can reject the predictions for Scenarios A & B respectively. The GISTEMP data show a significant difference between predictions and observations with 98% and 92% confidence.
As always, please let me know if you have any concerns with the method, and I’m happy to email the spreadsheet I used to anyone who’d like it.
If the above checks out, I’ll repeat with IPCC (1990).
RE: Hansen (1988) – Autocorrelation issue.
Wally et al,
I spent a few hours last night reading up on the various approaches for identifying and correcting autocorrelation in time series data.
Since I don’t have access to professional statistics software with GLS tools, I’m limited to excel-based OLS methods. I’ve settled on the AutoRegressive (AR) approach, which basically runs a standard OLS regression twice – first regressing the data against 1-period lagged observations to identify and strip out auto-correlation, and second to regress the residuals against the date to identify trend and significance.
Here’s a summary of the preliminary results:
Hansen’s temperature projections (1988-2010)
Scenario: Scenario_A Scenario_B Scenario_C
Slope: β = 0.029844862 0.027396245 0.019274704
(Source: http://www.realclimate.org/data/scen_ABC_temp.data )
UAH data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.834750724
(Source: http://woodfortrees.org/data/uah/from:1988/to:2010.58/plot/gistemp/from:1988/to:2010.58 )
GISTEMP data set (1988 – 2010.58)
Observations: n = 271
Slope: β = 0.017105791
Autocorrelation: ρ = 0.760693177
(Note the higher autocorrelation coefficient for the UAH data.)
UAH AR(1) autoregression
Observations: n = 270
Intercept: α = 0.022953044
Lag-1: β = 0.838341028
GISTEMP AR(1) autoregression
Observations: n = 270
Intercept: α = 0.097138485
Lag-1: β = 0.76108575
Both data sets were stripped of autocorrelation as modeled above, and the residuals used for the next stage of regression.
UAH Residuals regression
Observations 270
Slope 0.019506406
Standard Error 0.006566299
Scenario: Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 1.574472273 1.2015656 -0.035286678
Pvalue (2 tail) 0.115378307 0.229531876 0.971851146
GISTEMP Residuals regression
Observations 270
Slope 0.01920112
Standard Error 0.004669017
Scenario Scenario_A Scenario_B Scenario_C
Ho: Slope ≠ 0.029844862 0.027396245 0.019274704
TStat = 2.279653399 1.755214024 0.015759938
Pvalue (2 tail) 0.022628253 0.079222706 0.987425909
Conclusions: As expected, the T-stats are lower than before. Due to the higher degree of autocorrelation in the UAH data, they only give us 77% & 88% confidence that we can reject the predictions for Scenarios A & B respectively. The GISTEMP data show a significant difference between predictions and observations with 98% and 92% confidence.
As always, please let me know if you have any concerns with the method, and I’m happy to email the spreadsheet I used to anyone who’d like it.
If the above work checks out, I’ll repeat with IPCC (1990).
Kreo says:
‘Models happen between the first and second sentence. No models, no predictions, no uncertainties, no camp.’
The emissions scenarios? They are not climate models. Besides, we don’t even need the scenarios to predict that society would likely pump out heaps more Co2 in the future.
Kreo says:
‘I bet at least one of Wally’s posts have already been stopped.’
Lame anomaly hunting. both sides have received warnings.
Miriam says:
‘My position is different. I did care enough to read papers and studies for a few recent years, as well as educate myself on the subject. My math degree helped. I feel I can at least tell something real from a fluke (your opinion might be different, but, well, the proof is in the pudding, bring some real points and we’ll talk)…’
Precisely and, in science, where is the most delicious pudding of em all? peer-reviewed lit. Anything you write is practically fiction until you take that step. And you are the one criticising the established opinion, you need to bring the points to the table.
Shills: “Precisely and, in science, where is the most delicious pudding of em all? peer-reviewed lit. Anything you write is practically fiction until you take that step. And you are the one criticising the established opinion, you need to bring the points to the table.”
This is B.S. There is plenty of peer-reviewed lit. that is of poor quality and plenty of non-peer reviewed lit. that is helpful for laymen to gain an understanding of climate issues.
There are many insights that can be presented on blogs that are helpful to evaluating climate science, but which do not warrant publication in the journals.
There are many people without credentials outside of the field of climatology who have interesting things to say about climate science. It is a bit much to ask them to put aside their own professional endeavors and personal time to publish in journals that will not pay them or advance their careers.
Shills, if you want to make peer-review the gatekeeper for everything worth reading on climate science that is your choice. Why do you then spend time reading blog comments?
opps, that should be in the fourth paragraph in my post above, “there are many people with credential outside of the field of climatology who have interesting things to say about climate science.”
You know, this “you have to be climate scientist, or pass peer review to have anything important to say about climate science” argument is getting quite tiring. For the population as a whole to act, especially in a way that will impede their lifestyle, these climate scientists need to be able to put forth a rational and convincing argument that can be understood by lay people, or at the very least, even especially, the well educated in other fields. Often times its those well educated in other fields, that can provide the most inciteful criticisms, at least that’s what I’ve found to be true. Those in one particular field can often end up getting somewhat myopic and burried in the details or minutia of their very small niche, while the outside observer can bring a new perspective from a different angle and provide a bit of a refreshment to the field. This is why, I believe, that many of the biggest break throughs in science come from young scientists or from those moving between fields. Its that influx of new ideas and perspectives that helps the science evolve. So, in no way do we need to already be experts to have somethign valuable to say about a given field. As, at one point in time, every current expert would not have been considered expert, yet through some valuable contribution to the field, they became known as an experts. And if you just repeatedly shout down criticisms because those leavying the criticsms are not experts, you’re just impeeding the progress of knowledge.
We owe it to climate science to have this discussion between the “skeptics” and “believers,” because in doing so, we’ll likely reveal issues not thought up by either side. Ulitmately science does not care if you’re an expert or if you passed peer review. It cares about the quality of the data, analysis and logic contained in the argument. It doesn’t matter if it comes from a Jr. High student, a Ph.D. student, a established researcher with 200 peer review publications to his name, or a similar researcher but with those publications in a different field.
Speaking of business models, you should all be familiar with the “black swan” effect, where events with supposedly 1 in a million or 1 in a billion chance of happening occur more often than one might calculate.
Here are some papers showing how these correlations are miscalculated:
http://www2.owen.vanderbilt.edu/bobwhaley/Research/Publications/jf97.pdf
http://www.class.uidaho.edu/psy586/Course%20Readings/Babyak_04.pdf
http://management.uta.edu/Casper/MultiStat/Bobko%20-%20Multivariate%20-%20Handbook%20Chapter.pdf
Sure, I agree with what you guys are saying. There is nothing wrong with sincere and honest criticism of climate science. I’m sure the climate scientists welcome that. And if that is what you guys see yourselves as doing, well, unfortunately everyone else sees it (so far) as stale denialist ranting. Now, who is to say that you guys aren’t sincere and that the Climate scientists are actually in the wrong?
Well, ask yourself this: Just like how scientists in other fields would welcome new perspectives, why wouldn’t climate scientists?
Also ask yourself: how quick was I to convict those in the climategate scandal and with what evidence?
And until we find a better way to sift the wheat from the chaff, peer-review is the hurdle anyone with a scientific claim needs to jump if you want to be taken seriously. Of course published non-fiction could have an impact but how often does that happen?
“unfortunately everyone else sees it (so far) as stale denialist ranting.”
I am curious who you would classify as a “denialist”. It is my impression that nearly everyone on this forum would agree with these propositions: 1) the average global temperature is increasing; 2) c02 is a greenhouse gas and adding greenhouse gases to the atmosphere will cause warming; and 3)human emissions of CO2 have contributed to the increase in global average temperatures.
Where people here might disagree with some climate scientists concerns the climate’s sensitivity to a doubling of CO2 concentrations. Most people here would believe that the likely climate sensitivity is in the low end of the range proposed by the IPCC. The consensus opinion as expressed in the IPCC is that there is great uncertainty is the estimation of climate sensitivity.
So I am curious as to what specific beliefs one must hold to be classified by you as a “denier”?
Shill also says: “Also ask yourself: how quick was I to convict those in the climategate scandal and with what evidence?” Well, it depends on what you think climate scientists were convicted of. For anyone paying attention, there wasn’t anything particularly surprising in the climategate emails.
Its not just creating new scientific knowledge that is the issue however, its also accepting what has been done to be true by the “learned” community at large, and what to do about it. Both those aspects fall well outside of peer review. And besides that, something passing peer review does not make it gospel. I’ve seen plenty of crap published in my field, even in some of the top journals. We need to think of peer review journals as a way to communicate more than a way to absolutely prove something true.
True pauld, I don’t know anything about you in particular. But I’m pretty sure most peeps here think the the ipcc range is still to high. That is Meyer’s arg. anyway. And, if you think the clim. sens. is close to 2., aren’t you worried about that? After all, it is the level seen by the IPCC as the 50/50 mark of avoiding CAGW, I’m pretty sure.
And if you were not sold on the climategate incident, I assure you, you don’t speak for the rest of em here.
“And if you were not sold on the climategate incident, I assure you, you don’t speak for the rest of em here.”
The notion of being “sold” on the climategate incident is such a vague statement that I have no idea what it means. Much of what was said in the popular media and internet was wrong. On the other hand, michael mann’s “trick” and the “hide the decline” graph had already been identified and discussed at climateaudit.org long before the emails were released. The difficulties that climate scientists who did not towe the party line had long before been noted by Dr. John Christy, Dr. Roy Spencer, Dr. Roger Pielke, Sr. and Dr. Richard Lindzen, among others. So to the extent that the climategate emails discuss keeping skeptical articles out of the science journals, the only thing surprising was to see it in writing.
Most of the comments on this blog discuss the validity of the AGW theories and models. However, there is very little discussion re practical implementation of a major CO2 reduction and dealing with its consequences.
Let’s assume that EVERYBODY agrees that the AGW theory and models are correct. Then what? The models indicate that an 80% reduction in CO2 emmissions is needed. How do we do this? Until there is a method to reduce CO2 by 80%, including dealing with everything involved (alternative energy, political and economic issues, poverty, etc.) we have nothing useful. All of the schemes for CO2 sequestering, alternative energy, etc. that have been suggested or investigated are impractical, wildly uneconomical, or plain nonsense. Furthermore, Indian government officials have made it clear that a country where 80% of the people earn less than $2 per day is not going to give up their industrialization program.
We need a completely thought out program, not just verifying or debunking the AGW theories.
If anyone has seen such a comprehensive program laid out, I would be interested in seeing it.
As would I Ted. And you’ll surely find people that would give you their plans, especially at a place like realclimate, but not many of them would qualify as “completely thought out.”
Wally, be truthful, are you really a scientist?
I don’t mind discussing policy, but that is not often the subject of the main post on this blog. If you want to talk policy, you should check out these blogs.
1) http://rogerpielkejr.blogspot.com/ Pielke, Jr. writes extensively on the policy implications of climate science and posts often of the subject. His comment section is lively, and has participants with a wide diversity of views.
2. http://www.masterresource.org/ . This blog addresses policy issues frequently and critiques current alternative energy technology. There is an interesting series of posts right now on wind power. Although the blog has great articles, and appears to receive alot of traffic, there is seldom much discussion in the comments.
Pauld: I agree. However, if the science must be followed by a practical program, then it is incumbant on the scientists to have a viable implementation program in mind.
The points I raised are not policy questions, but engineering questions. As a retired chemical engineer, I have been following the AGW arguments with interest from the point of view of practical implementation. Nothing I have seen re alternative energy, C sequestering, etc. is remotely feasible on a large scale. If there is no workable way to deal with the consequences of an 80% reduction in CO2 emmissions, then who cares whether AGW theories are true or not? We cannot do anything about them other than move north.
Policy decisions would come in when there is more that one feasible way to deal with CO2 reduction, one of which must be selected. At present, there are none.
You mention wind power. This is only viable when the amount of wind power is small relative to the large thermal power system, which can act as backup. If a large part of the power was generated with wind (or solar), dedicated standby power facilities would have to be be provided. Even without this need, with wind power getting “freebees” re standby costs, large subsidies are required to get wind farms built. There is a study (in Australia) which works out all the details of a wind/standby system, with alternatives and costs.
One thing that disturbs me about the Feds getting involved in this: Professors are seeking government research grants for all sorts of crazy schemes, which any engineer could debunk in an afternoon’s investigation. No study of the research proposal seems to be made by the Feds. They just push money out the door as an indication of progress. The object of the professors is to get grant money which endears them to the university administration. Without this distortion, I am sure research effort would be much more intelligently directed. Research has gone on for centuries without government intervention. Other than military stuff, I am sure it is a better way.
Ted Rado: I think we are on the same page and I cannot say I disagree with anything you have written above.
The posts at MasterResource regarding wind power make a strong case that wind power is not now nor ever likely to be a viable alternative source of powergrid energy and, in fact, will not substantially reduce CO2 emissions. I think you will find an ally at that website.
I think that Roger Pielke, Jr. would also agree with your conclusion that there are now no feasible technologies to rapidly reduce CO2 emissions. Although he believes that we need to reduce our reliance on carbon-based fuels, he would agree that many of the proposed policies to acheive this goal are based on unrealistic “magical” thinking. He has written an entire book soon to be released on what policies are politically feasible and will move things in what he perceives to be the “right” direction. I, as a “luke warmer”, disagree with much of what Pielke writes on the state of climate science, but I do think he is a serious thinker whose ideas are worth considering. Ultimately, I think he argues that decarbonization of the economy is a good idea independent from global warming concerns.
If you are interested in issues regarding decarbonization, his site is good place to engage in a discussion on this issue.
Waldo, what would be my motivation for such a lie? To help convince some annonymous DB in the comments section of a blog of something that is probably impossible to convince him of anyway?
Also the mear fact that you feel the need to ask such questions in evidence of your homerism.
I’m sorry, Wally, I would not impugn you personally, but there have been several people who have made claims about their scientific pedigrees on this very blog which evaporated upon closer inspection (An Inquirer and netdr, for instance) and so I’ve become suspicious. Why these people make spurious claims is beyond me. You clearly have some scientific background…but I’ve just been checking over at Real Climate from time to time and noticed that one of the commentators had some doubts…I guess that is between you and them.
I suppose you’d be much more convincing if you could peer-review your opinions. They’re not doing so well over at RC but maybe a panel of scientists would find your insights about which experiments climate scientists should conduct very interesting.
I do totally dig that you used the word “homerism,” however–that is very cool.
Pauld: Thanks for your comments. I have, among lots of other things related to the AGW thing, studied up on CO2 removal. At one time, I was involved in a commercial plant to recover CO2 from flue gas for use in an industrial process. This recovery is very energy intensive. You reduce power plant electrical output by about 30% due to steam used in the process rather than in the turbine. To generate the same amount of power, you use approx. 40% more fuel, which means coal will be depleted that much faster, and you will have more CO2 to recover. Also, what do you do with the 900 psi. liquid CO2? There are proposals to inject it into deep wells, and various other schemes, which create even more problems as well as huge cost.
Having voiced my concern about how to implement a CO2 reduction plan, there is non-the-less a long term need to completely revise out energy production and use system (all aside from our fear of depending on foreign oil). In a very few hundred years, we will be out of low cost fossil fuels, so CO2 will disappear of its own accord. Electrity can be generated in nuclear plants, but what about transportation fuels, ag chemicals, farming, etc? I have done some conceptual studies of cities built around nuclear power plants, using low pressure extraction steam for heat and A/C. Small electric cars could be used for neighborhood travel. Lots of questions remain about fuel for farming, air travel, production of chemicals, etc. I guess we could go back to plowing with a mule, and electric train travel. Those who say we have plenty of natural gas are speaking in terms of 120 years or so. To me (82 years old) that is not a long time. Where are the studies of this long term problem? I have seen none, yet it in 100 plus years, it will be a real issue, regardless of AGW.
Perhaps some of the current studies to do away with fossil fuels will suggest ways of dealing with the long term fossil fuel depletion problem. I am a bit astonished that people seem to think we have plenty of gas and coal. Unless man dies out before the fossil fuel does, we are in deep trouble. The lay people keep saying “science will come up with something”. Unfortunately, the laws of thermodynamics are hard to circumvent.
On this latter subject, I was astonished that some scientists are seriously proposing to react CO2 with nuclear-produced H2 to make hydrocarbons. I ran some calcs, and found that the overall energy efficiency is about 1% vs 35+ % for a nuclear energy plant. You would have to build 35 nuclear plants to get the same usable energy as you get from one!!! And people put out this stuff seriously. Does anybody do a few engineering calcs before running off with this kind of nonsense?
Waldo: “I suppose you’d be much more convincing if you could peer-review your opinions.”
Why do you spend time reading blog comments, if the only things you find convincing is peer-reviewed articles?
Waldo,
But what does it mean for my comments to not be received well in an obviously hostile environment, like that of realclimate?
From my very first comment I’ve had multiple post attack me and my arguments with pretty much the full gamate of ad hominems. I’ll admit that at times I may resort to such things, but those that post to realclimate seem to have an addiction to such behavior.
Also, someone asked a while back if my comments had been censored. Thus far they have not. However, when it takes all day for your posts to show up, while comments critical of your posts show up almost instantly, it makes for a pretty good deterrent to a fair debate. I’ve had posts that I made in the morning, still awaiting moderation in the late evening, while the conversation has continued, not to see my posts up for everyone to see until the following morning. So, they are quite obviously flagging posts for further review, which in “blog-time” is taking forever. Eventually I will give up in frustration, which I’m sure is by design, and the realclimate moderators will have “won.”
Which leaves us with the natural question: Why does realclimate, which so adamantly believes they have the truth on their side, feel the need censor posters such as myself?
Wally, I just want you to know that I – and I believe many others here – greatly appreciate your efforts on RC. You really have the patience of a saint.
****”Why do you spend time reading blog comments, if the only things you find convincing is peer-reviewed articles?”
I find the denialist mentality fascinating.
****”I’ve had multiple post attack me and my arguments with pretty much the full gamate of ad hominems”
Not from what I’ve read, Wally. They take you to task for your lack of knowledge, your math, and your methodologies. They have provided you with multiple links and references to things you either do not know or did not think about. My favorite is when you suggested greenhouse experiments to judge rice yields based on temperature only to be reminded that such experiments have gone on for a hundred years or so. Comments like that make me wonder if you are trying to fool us about who and what you are. You have also gotten in the habit of accusing everybody who disagrees with your scientific opinions of ad hom.
****”Thus far they have not. However, when it takes all day for your posts to show up, while comments critical of your posts show up almost instantly, it makes for a pretty good deterrent to a fair debate.”
Seems a little unlikely to me. I’ve had to wait several hours the couple of times I posted things — once my post waited almost an entire day. There is in you, Wally, the need to see some sort of systematic, institutionalized inequity in the conversation — and this is a very one-sided observation on your part.
****”Eventually I will give up in frustration, which I’m sure is by design, and the realclimate moderators will have ‘won.'”
Would you feel the same way if, for instance, Anthony Watts bans or holds comments? Again, Wally, this is akin to paranoia and rationalization. You are talking to an erudite, scientific crowd over there, and they are not impressed. Perhaps you think that’s ad hom.
****”Wally, I just want you to know that I – and I believe many others here – greatly appreciate your efforts on RC.”
Homerism. What a great word.
****”One thing that disturbs me about the Feds getting involved in this: Professors are seeking government research grants for all sorts of crazy schemes, which any engineer could debunk in an afternoon’s investigation.”
Could you debunk one of these for us?
****”No study of the research proposal seems to be made by the Feds.”
Really? Who do you think these “feds” are?
****”They just push money out the door as an indication of progress. The object of the professors is to get grant money which endears them to the university administration.”
Which professors?
”I’ve had multiple post attack me and my arguments with pretty much the full gamate of ad hominems” – “Not from what I’ve read, Wally.”
Who cares about what *you* think, Waldo? You are a troll. All you are doing is trying to “own” the discussion. Nobody tries to convince you of anything.
Wally:
I think you have done a great job at RC, but I do question whether it is worth the effort. Although you have been fortunate not to have any posts deleted in moderation, having long delays in your post, while posts critical of your position go through right away, makes it impossible to have a reasonable discussion.
What is especially frustrating for me with the delays on posts I have written, is that the delayed posts are inserted back where they would have been had they been posted immediately. Thus anyone who is trying to follow the discussion needs to re-read the entire series of posts every time to see whether something new has been added. Of course, most readers either won’t do that or are not aware of the need to do that. This is particularly frustrating on very active threads where there may be several hundred new posts between the time my comment is submitted and the time it appears.
I personally don’t bother to post at RC because of the moderation policy. I also take everything they write with a huge grain of salt because 1) on topics with which I have personal knowledge, they frequently provide a slanted and unbalanced perspective; 2) one topics with which I don’t have personal knowledge, I don’t trust that they will allow their critics an opportunity to respond.
There was a great series of posts one time at the Air Vent blog where he asked people about their backgrounds and how they came to be skeptical of CAGW. A large number of people responded who had engineering and advanced science degrees. A surprisingly large percentage of people got started questioning CAGW because of the experience they had over at Real Climate.
Ted Redo:
I thought this recent post at Pielke, Jr’s blog would be of interest to you. http://rogerpielkejr.blogspot.com/2010/09/miniscule-effects-of-european-ets-on.html#links
A summary paragraph:
“In The Climate Fix, I present data suggesting that Europe’s rate of decarbonization was essentially unchanged before and after implementation of the Kyoto Protocol, up to the period covered by the Sandbag analysis. The Sandbag analysis suggests that this finding holds to the present. The strong implication is the that EU ETS has not accelerated BAU decarbonization in Europe.”
****”Who cares about what *you* think, Waldo?”
Strangely, a surprising number do. Like you.
Here is an interesting report on the climategate inquiries that I picked up from the link at wattsupwiththat. The full report is here: http://www.thegwpf.org/images/stories/gwpf-reports/Climategate-Inquiries.pdf
I’ve taken a quick look at it and it looks good. Although much of what was written in the popular press and in some blogs was incorrect, this report outlines the issues and their implications correctly. It does a good job of putting “hide the decline” in its proper context and shows why the attempts of the various inquiries to paper over the flap are disingeneous. I am, of course, looking forward to reading the reply from realclimate.org
Pauld: Thanks for the heads up on Pielke. I read his stuff regularly. Apparently, many industries in Europe have obtained a reprieve from their governents on CO2 as they would be driven out of business or forced to move to India. There is endless, very interesting, commentary on this subject. The Australians have dumped the idea of cap and trade (aka move to India or China). Even many of the lay politicians are beginning to get real (see Copenhagen). Many countries, such as Canada, have not come anywhere near meeting their Kyoto pomises.
Bottom line: Nobody has figured out how to reduce CO2 without reducing industry as well (as per our previous exchanges).
Waldonation: You asked me to debunk a couple of statements:
1) No study of the research proposals seems to be made by the Feds.
Most of the money passed out by the Feds is through the DOE as reaearch grants. In industry, an idea for a new process is passed throuth the engineering department. The idea is first assumed to be absolutely workable. A flow sheet, heat and material balance, and capital and operating cost estimates are made (again without questioning the validity of the idea). In 99% of the cases, the idea is found to be flawed for various reasons, such as the product being worth less than the raw materials, the fuel value of the product is less than the energy input to the process, costs far exceed the value of the product, etc. In this way, research is only done on those ideas that, if they are found to really work, are doable on a large scale. The idea is not to waste money that could be spent on potentially useful R&D. The DOE should do this, or require those seeking grants to submit such a study with their research proposal.
2) Which professors?
One professor has a grant to study use of calcined eggshells to make lime, which is then used in a process to absorb CO2 out of the process. Obvious questions: Eggshells are calcium carbonate, which is the same as limestone. Rather than collect 90 billion eggshells per year from around the country, why not just mine a few thousand tons of limestone, at abviously a tiny fraction of the cost? Also, when you calcine the eggshells (or limestone) you drive off the same amount of CO2 that you will absorb later, plus the CO2 from the duel you use. Where does this go?
I won’t give you the name of the prof because I have no desire to make him look rediculous.
The Feds themselves are a wonderful source of kooky schemes. Two researchers at Los Alamos are working on a scheme to remove CO2 from the air (rather that from flue gas) by setting up lime absorbers all over tho country. They state that with a million of these, they could remove a billion tons/yr of CO2. Obvious question (see eggshells above): To make the lime, you have to calcine limestone and drive off CO2, then ship the lime to the many absorbers, change out the spent lime, etc. How much CO2 is generated by the trucks carrying lime? Where does the CO2 from the lime calcination go?
Honest, I am not making this crap up. If you want to have a really hilarious time, go to the DOE website and read up on their sponsored R&D.
Any chemical engineer I know could quickly put a stop to this nonsense by requiring the DOE to use well established engineering practise in approving research proposals. The current DOE head is a scientist, not an engineer. The DOE head in the Bush era was a finance man, who bragged about how much money they were pushing out the door. Go figure!
The professor(s) (their are several working on this problem, including a dissertation) are all at Ohio State University, no? My question to you, my friend, since you understand this problem better than the good professors, why don’t you let them know what they are doing wrong?
Likewise, it appears that there are three scientists at the Los Alamos National Laboratory working on the problem described above.
Everyone’s email and contact information is readily available online. I found them within a minute or less.
Shoot them a line. Explain what they are doing wrong.
Likewise, since “Any chemical engineer I know could quickly put a stop to this nonsense by requiring the DOE to use well established engineering practise in approving research proposals. The current DOE head is a scientist, not an engineer.”
You will undoubtedly also want to explain this to Dr. Steven Chu.
I did notice that these “feds” had some pretty stellar credentials.
You have not debunked anyone yet.
Waldo,
“Not from what I’ve read, Wally. They take you to task for your lack of knowledge, your math, and your methodologies.”
Lets take a look at what some people have said:
Ray: “The fact Russ is declaring the models dead without having even done a 5 minute search suggests he isn’t really serious. This isn’t that hard.”
This is just hugely ridiculing. First, Russ never even declared the models dead, just that they came in high. Why does Ray feel the need to create a hyperbole in a ridiculing manner to make a case? Second, Ray has no idea how much time Russ may have been “searching.” Its should have been pretty obvious that Russ put a decent amount of time into those regression analyses he did. Further, he’s casting an appeal to motive with this “isn’t really serious” claim. Russ only has his hyperbolic statement to fall back on as evidence for Russ’s “seriousness.” Then of course he casts that ridicule that “this isn’t that hard.” These are the kinds of things people say when they don’t have anything of real merit to bring up.
Next from Ray: “Do you have any idea how tiring it is to have neophytes/trolls (one cannot tell the difference) come on here every 2 months or so claiming to disprove climate change based on a very simple, WRONG statistical analysis? And the mistakes are always the same.”
Here he’s obviously suggesting Russ and/or I are neophytes/trolls. If he wants to claim Russ’s statistical analysis is WRONG(!) why doesn’t he just show why? Instead I’m supposed to be convinced because Ray is tired? Yawn.
Ray in a post to Russ: “I really think that your time would be better spent learning the science rather than trying to assess predictions you don’t understand. ”
More ridicule and the rest of the post has little to nothing of substance.
From CM to me: “Feel free to suggest a better way to test the projection that does not involve time travel, psychic powers, or substituting a straight line of your own fancy for the model projection.”
More hyperbole constructed as a ridicule…
Then there’s lots of stuff like this from Hank floating around:
“The science assumes some statistics; if you don’t have that background or, like me, learned it a third of a century ago, it’s helpful to read at least something like Grumbine on trends for the basic idea.
A lot of resources on using Excel for climate point to old topics at Tamino’s blog that are currently unavailable, for example this page:
http://processtrends.com/toc_trend_analysis_with_excel.htm (which is still worth a look; I just found it this minute, not a recommendation yet).
I see some readers at Tamino’s have found and maybe archived some of the missing material. That will help.”
So a poster starts by suggesting someone go take stat 101 as an obvious ad hominem. Now Hank wants to somehow defend such idiotic arguments, by tell someone to go look at some general regression analysis toolkit, without actually pointing out what’s wrong or what specific someone might want to actually brush up on. This is quite common at realclimate. They tell you you’re wrong because of some vague reason in one or two sentences, then give you several links that are supposed to illuminate why. That’s not how arguments go. You need to point out what specifically is wrong and where specifically to look for further answers. Don’t just tell people to go read a stat book. In the end those kinds of arguments just function as, you guessed it, ad hominems.
Another example from Didactylos: “If your “null hypothesis” is a constant warming (which is a really stupid thing to do, which is why the scientists didn’t use that as a null) – but assuming you are that stupid, then do you understand that this means that you have just assumed that the world is constantly warming, and that you have no explanation for why?….Looking through your rambling post, I’m struggling to find any position of yours that isn’t based on a misconception. Get the facts straight, then the conclusion follows easily.”
What facts? The strawman that we’re testing against constant warming? Did Didactylos not read Russ’s posts?
That only takes us through about half the conversation thus far, but if you are a nonbiased reader, I think you have probably gotten the point. The abuse has been on full bore since your first copy/paste of Russ’s post. Its come in a variaty of forms, from constructing hyperbolic strawmen and using it as a tool to ridicule the author, or out right insults such as didactylos shows above.
I won’t put myself up as being perfect in avoiding ad hominems, but the abuse thrown at respectful, even if flawed, counter arguments over at realclimate is shocking.
Oh and Waldo, I rarely read Watts up with that, please don’t attribute my thoughts to someone else, even if they had the same thought, without knowing damn well that’s where it came from.
Waldoe: As regards the Ohio State professors working on the eggshell thing, I am embarassed to say that I am an OSU alumnus. A friend of mine (also an old Chem. E.) who is an Illinois grad, and I shake our heads at this stuff. The eggshell thing simply reinforces a point I made before: much of the seeking of research grants is to get money from the Feds. It completely corrupts the intellectual process. If you can get a million dollars from the government to study how many angels can dance on the head of a pin, why do research that is not encouraged by the government for free? I have personally been in a meeting where the chairman stated that we all knew that the process to be studied was nonsense, but the government had set aside 300 million for grants, so let’s get our share. It was hard to keep my lunch down! Which raises the obvious question: In what way are politicians, none of whom are engineers as far as I know, qualified to determine what areas of R&D to support? Their advisors are all lobbyists or political hacks. Note also that by diverting R&D effort to nonsense, the resources for working on really useful things is deminished. Thus, the Feds get the opposite effect of what they are presumably seeking: solutions to scientific/technical problems.
As to Dr. Chu, I am sure that he is a fine scientist. In industry, scientists and engineers have seperate roles. They work closely together for the reasons I have already explained. Together, they develop processes that are not only scientifically sound, but are amenable to practical implementation. Very few scientists I have encountered are capable of determining the practical feasibility of a scientific idea on their own. Ideas from the scientists are sent to the engineers for evaluation as to their feasibility, as I described earlier. If the idea is sound, the scientists and engineers work in harmony to perfect it.
As to contacting anybody re my misgivings, that is a waste of time. In the case of scientists/engineers, it will simply result in an argument (look at this blog, for example). In my 66 years since I started studying chemical engineering, I have found relatively few people with whom a professional and useful discussion is possible. Most people have a strong opinion, and refuse to discuss the subject with an open mind (also see this blog). The person with whom one can have a productive discussion is a pearl beyond price. Fortunately, in industry someone is put in charge (project manager), thus ending arguments. If this person is wrong and the comany loses money, he gets fired. Thus the system works and is self-correcting, albeit sometimes painfully.
As to the politicians, have you tried to get anything listened to by your congressman or senator? You either get no reply or a handout describing their own views.
Wally:
The point of the ad homien arguments and condescending attitudes over at Real Climate is two-fold: 1) It convinces people like Waldo, who don’t know better, that their critics can be easily dismissed without actually responding to their arguments; and 2) it eventually discourages critics from posting at all since it is rather pointless.
If a critic keeps going in spite of the hostile environment, the moderator starts deleting their posts in moderation or delays posting them for an inordinate time. Eventually, people give up after they have the experience of devoting substantial time to carefully write a post, only to have it deleted in moderation. Or when they are subjected to cheap shots and have their responses deleted.
While these tactics protect people like Waldo from being exposed to dangerous ideas, they alienate a substantial number of people who have the background and take the time to actually understand what is being discussed, thus adding to the skeptic’s camp daily.