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.
Waldo,
Thanks for posting the statistical results as Real Climate. I had been seriously considering doing exactly that, but wasn’t sure how introduce ‘off-topic’ material it into a post.
I’ll respond to any critical comments over there.
Waldo:
“Interestingly, I re-posted his equations above on Real Climate and they were not as impressed with Russ’ T Stats as the good people here are.”
What are the URLs for that thread and comment and what was the specific critique? Or are we again playing those games where the vagueness creates an appearance of something substantial out of nothing?
Found the thread. Of course, Waldo colored the entire topic as “a rather big brewhaha” and of course the first two reactions which Waldo asked to cross-post are knee-jerks instead of substantial critique, but still, my apologies to Waldo. He did indeed post the thread.
For those interested:
http://www.realclimate.org/index.php/archives/2010/08/doing-it-yourselves/comment-page-5/#comments
Waldo’s repost is #209.
Shills:
“And again, you guys have not shown how hindcasting is flawed, you just say it is. Tuning of the sought you guys imply does not happen because it is blatantly unscientific. Any additions to models are made on the basis of the physics understood, not whether it might simply make the fit closer.”
I’m honestly having a hard time seeing a distinction between hindcasting (which you say is good) and tuning (which you say is bad). I apologize if this should be elementary, but could you clarify what you mean, or point me to a good explanation.
Illustrative example: What’s the “physics understood” value for cloud feedback? Last I checked scientists couldn’t confidently determine the sign of this feedback, let alone the magnitude.
When selecting an suitable value for this input variable, what’s the difference between hindcasting and tuning?
Miriam et al,
I’ve followed up on the Real Climate thread with the original context of our discussion, provided all my data and methods for anybody who wishes to dissect them, and have replied to a few early comments.
There have been a number of weak/knee-jerk retorts: (“Nothing of significance can be learned from a mere decade of data… He made a mistake with a number, so he’s an idiot and we should ignore him… He is attacking 1990 and 1995 predictions rather than the 2007 predictions… He is only going back to 1990 and 1995 when there are data to 1980… He didn’t consider the margin of error…)
However, there has been one concern raised that I consider valid (see Brian Dodge, comment #215).
He writes: “Over the period of his analysis – 1995-2010 – CO2 only increased by ~30ppm, from ~360 to 390+ ppmv, at current fossil C emissions of ~7-8 GT/yr. By 2100, under scenario IS92a anthropogenic C emissions will be ~20 GT/yr (see fig 2, p10 of the IPCC report). His extrapolation fails to account for this, and he’s making the same sort of inept (intentional?) mistakes as Monckton, demonstrating the statistical irrelevance of bad analyses.”
If I’m understanding him correctly, I think he’s making a very good point (which I’ve acknowledged over there). The details of Scenario IS92a called for an accelerating increase in CO2 emissions from 1990 to 2100 (and therefore predicted a non-linear increase in temperature, with more of the warming being back-end loaded). As such, it’s inappropriate to test the early years warming against the full-period average prediction.
The simple solution to this would be to find year-by-year warming predictions that can be tested against recent observations, instead of hundred year average. I’m going to dig through IPCC (1990) and (1995) again to see if they provide more detailed warming forecasts that can be appropriately tested. If you are aware of any, please let me know where to find them.
****”I and others asked for non-model evidence that the Earth is going to warm to catastrophic levels. Where is it?”
The. Evidence. Is. In. The. Links. I. Posted.
If you are asking for a non-predictive science, which one cannot do without prediction(which would by its nature need some form of modeling) you will have to find Gandolf or Cthulhu or someone who can look into future magically. Otherwise you will need to do your own homework. Sorry.
Russ, you are touching on a famous debate from two and a half years ago – be sure to read the comments:
http://cstpr.colorado.edu/prometheus/archives/climate_change/001319verification_of_ipcc.html
I am not aware of year-to-year predictions. Gavin Schmidt, in particular, says that long-term predictions “for FAR/SAR/TAR … is all you have”, and it surely sounds from the debate that by “long-term predictions” he really means “long-term trends”.
The central point in the debate, as I see it, are reasons for non-linearity. It can, of course, be argued that the increases in year-to-year CO2 output will grow in the future as that’s how economies normally evolve. But it would also take exponentially more CO2 to double the concentration every time as well. It is not at all clear how it could be argued with such certainty that the first factor will win over the second one, so unless there are other reasons for non-linearity I wouldn’t be so fast to accept it. Right now this looks like an excuse to avoid comparing models to anything prior to 2100 or where this all should end.
It is no doubt very convenient to say that you predict something 100 years forward and then thwart any attempts at fact-checking first on the basis of it being too early, then on the basis of the prediction being non-linear. After some time, you can say that the old prediction is outdated and make a new one, restarting the process (well, it’s too early again).
”I and others asked for non-model evidence that the Earth is going to warm to catastrophic levels. Where is it?”
“The. Evidence. Is. In. The. Links. I. Posted.”
Please cite one of these links and include a paragraph from that link that makes the case.
Otherwise, stop wasting our time and shut up.
****”Please cite one of these links and include a paragraph from that link that makes the case.”
Pick any paragraph you like, Miriam, you obviously can read. I’ll say it one last time: it’s all there. I was helpful and provided the links. The rest is up to you.
****”shut up”
My, my, what would your mother say? No, I don’t think I’ll shut up anytime soon. Again, sorry.
“Pick any paragraph you like, Miriam, you obviously can read.”
Pick any paragraph? OK. I pick this:
“It’s unreasonable to assume that climate science in its current state can predict future temperatures with the level of certainty required for making decisions which might have serious economic ramifications for the entire world.”
It is in the links. Look it up, boy.
Thanks for the link to the debate on Pielke’s site, Miriam. Here is one prediction from there that I am going to believe:
—
In the next IPCC, if temperatures from 2005 to the next report fall below the 2007 IPCC prediction, then the next IPCC will lower its predictions. Similarly, if values fall above that level, then the IPCC will increase its predictions.
****”It is in the links. Look it up, boy.”
Nah, I believe you, girl.
Are the models accurate?
Don’t tell me, argue with this guy.
http://bartonpaullevenson.com/ModelsReliable.html
Thanks to Russ R, Wally, and Real Climate
Russ,
“I’m honestly having a hard time seeing a distinction between hindcasting (which you say is good) and tuning (which you say is bad). I apologize if this should be elementary, but could you clarify what you mean, or point me to a good explanation.”
I don’t know about what waldo means, but there is a very fine line between these two things. I generally see “hindcasting” as a only mildly useful way to test models that can not be tested through experimentation. So for example, in economics, you could create a model based on a few theories of what you think is going on. Then since you only have past data to work with you need to figure out a way to test this model, while not just fitting it to the past data. So one way to do this is to divide up your past data into two groups that should be randomly selected. This would mean instead of having semi-continuous data on a quarter by quarter basis, pool A has data for some random set of time and pool B has the other half. Then you can use one pool to “tune” your model, since even the best theories are going to need to be scaled. And finally you can test your tuned model against the other pool of data.
Now, there are problems with this. One problem would be data sampling and nonindependent data. So for example, if one quarter of GDP can effect the second quarter GDP, then breaking those into two different pools means your two pools are not independent of one another. Thus when you “fit” to one pool, you’re also basically fitting it to the second, meaning your test is not a true test. Also, even though you may think your theories have been arrived at independent of the data being used to “fit” or “tune” the model as well as test the model, that is in the real world highly unlikely, as with all theories, they usually just start with a basic observation of primary, unanalyzed data (which is being used to test/fit your model), then you move on to experimental tests in sciences where this is posible (like say, you observe CO2 concentrations going up with temps, then you do an experiment in the lab to see if it causes warming). Thus, your data has actually been used to create the theory as well. So you’ve gone circular in your hypothesis generation and testing, which results in a model being tested on the data that was used to form it, at least in part.
So, this is a nice little trick, that if extremely well thought out and carefully done, can be useful, but its far, FAR cry from actually being tested on future data, and even further from being test using a controlled experiment.
Thus, “tuning” isn’t really bad or good, its just model creation, not validation. Then hindcasting can run the whole spectrum. It can be a clever way to get around practical limitations, but its very limited itself, and when improperly used it will lead to false confermation of a model’s usefulness. In the end, there really is just no substitute for a controlled experiment. And without controlled experiments, what we know about global climate is going to advance at a snail’s pace compared to the traditional sciences. If in climate science you can only create and test a model or theory every 20 years at minimum, while in my field of basically network genetics, we can create a model and test it often times in under a week, then that would seem to support a 1/1000 relative knowledge advancement pace. And yet despite this CAGW supporters want me to believe that “the science is settled” while my field is basically as old as Mendel or Darwin and many of the most basic issues are still not resolved. For example in evolution, did Birds split from reptiles after reptiles split from mammals, or how about turtles? There is little doubt evolution is true, much like AGW is not greatly debated, but how exactly has evolution progressed is very much an open question and is still being extensively researched 150 years after Darwin’s On the Origin of Species.
****”I don’t know about what waldo means”
Wasn’t me.
Waldo,
“Are the models accurate? Don’t tell me, argue with this guy. http://bartonpaullevenson.com/ModelsReliable.html”
Are you now referencing blog pages? Is Barton Paul Levenson a climate scientist? Was this guy’s work peer reviewed?
Just kidding. If the guy has a valid point and his facts check out, I don’t care about his credentials. Facts are facts.
I’ve looked quickly through his page, and it’s an excellent compilation of research relating to many of the characteristics of AGW which have been modeled by scientists, and observed reality has confirmed (And I should note, I have no argument with). Examples include more warming at the poles vs. tropics, nights vs. days, winters vs. summers, northern vs. southern hemisphere, etc…
It’ll take me a while to go through all of it, but I’ll be focusing on specific global warming predictions vs. the observed temperature record, (and from my first quick skim through his page, I didn’t see any predictions more recent than 1975. Hansen (1988) didn’t make his list.)
Waldo,
One more thing. I’ve been asking you for a while to show me where Hansen admitted his 1988 estimates were too high.
I’ve found it for you. The following quote is from Hansen et al (2006) pg 2:
“Close agreement of observed temperature change with simulations
for the most realistic climate forcing (scenario B) is accidental,
given the large unforced variability in both model and real world.
Indeed, moderate overestimate of global warming is likely because
the sensitivity of the model used (12), 4.2°C for doubled CO2, is
larger than our current estimate for actual climate sensitivity, which
is 3 +/- 1°C for doubled CO2, based mainly on paleoclimate data.”
Since 2006, Hansen’s Scenario A and B predictions have ramped higher, but observed temperatures have not kept pace, turning his “moderate overestimate” into something… well, what’s a word for “bigger than moderate”.
And fortunately, Real Climate has a record of Hansen’s 1988 Scenario A, B & C predictions in data table format, instead of squiggly lines on a chart.
So, for the sake of completeness, I’m going to run those through excel against both GISS and UAH observations since 1988. I’ll post the results for you shortly.
****”I’ll post the results for you shortly.”
Actually, don’t bother for my sake, Russ. I’m sorry, my friend, but (while you have dealt with it with a good deal of humor and some dignity) the response at Real Climate to your earlier work has made me actually even more dubious. Wally is over there now being his usual frustrated, obstreperous self.
Post it if you like and perhaps we will see it on Real Climate also, but don’t try convincing me.
It would appear there was a good deal you didn’t know or take into account. Why, my good buddy, should I listen to you? Don’t post it here anyway–peer-review it. Post it at Real Climate, itself a kind of review.
And I never said Hansen admitted his estimates were too high, but that he said we have a lot to learn yet–I thought it was an op-ed piece. Perhaps I was wrong and it was someone else. What difference does that make anyway?
In reply to Russ R:
I went to this site, and ran your UAH data:
http://www.fon.hum.uva.nl/Service/Statistics/Correlation_coefficient.html
It gave the same 0.184 slope as you got, gave an R of 0.5156, and a t of 9.418
I’m not too impressed by those figures, however. See my reference above to figure 4 in the McShane-Wymer paper.
Those anomalies, -0.003, -0.146, 0.101, 0.011… etc are NON-stationary figures, using them gives bogus high correlations.
Change the series to DELTA changes in temperature, the first term is set to 0.000, the second would be a -.143 drop in temperature,
the third would be a + 0.45 incrase in temp, the fourth a -0.090 drop in temperature, and the significance drops substatially.
Alan,
Sorry, I’m confused. For what two data sets are you calculating a correlation coefficient?
I’ve been comparing slope coefficients to predictions, since I care about the long term trend, and not whether specific year-on-year changes match or not.
Cross posted from Real Climate (I’m not trying to convince Waldo of anything).
——————————-
So, to test Hansen (1988), I’m using the model output data from here: http://www.realclimate.org/data/scen_ABC_temp.data
If anyone can point me to uncertainty values, it would be appreciated.
I’ve seen plenty of back and forth debate over whether Scenario A or B is more appropriate. I’m in no position to choose one over the other, so I’ll test them both (I’ll throw Scenario C in as well, since the data are already in the table).
Using a start year of 1988 and an end year of 2010, I get the following best fit linear regression slope coefficients (deg C / year):
Scenario_A Scenario_B Scenario_C
Slope 0.029844862 0.027396245 0.019274704
I’ll test those against the following GISTEMP and UAH observations from 1988 to present (up to July 2010) available here: http://woodfortrees.org/data/uah/from:1988/to:2010.58/plot/gistemp/from:1988/to:2010.58
I’ve noticed that some evaluations of Hansen (1988) use 1984 as a start date. I’m choosing not to follow that approach, instead only testing predictions against future observations.
Here are the results:
SUMMARY OUTPUT (UAH)
Observations 271
Slope 0.017105791
Standard Error 0.001694254
Scenario_A Scenario_B Scenario_C
Ho: 0.029844862 0.027396245 0.019274704
T Stat 7.518986439 6.073738521 1.280157957
P value 5.52891E-14 1.24966E-09 0.200489589
SUMMARY OUTPUT (GISTEMP)
Observations 271
Slope 0.018145974
Standard Error 0.00137222
Scenario_A Scenario_B Scenario_C
Ho: 0.029844862 0.027396245 0.019274704
T Stat 8.525519713 6.741099703 0.822557306
P value 0 1.57192E-11 0.410759786
Would appreciate any thoughts, guidance, etc.
So, one more summary.
The Pro camp weakly tried to venture that “it is all in the links”, then went home defeated. Cross-posting the thread to RC has taken all their energy.
The Contra camp accepted the dubious “challenge” of discussing the topic of model correctness on enemy’s soil, despite it being heavily censored. The argument from their opponents is quickly transforming into a well-known position that the models either can’t be verified or can’t be said to be wrong because their prediction uncertainty (magic words: internal variation) allows for the Earth to warm, not warm or cool.
LOL at Kreo’s summary. It is funny how the minority on this blog get called ‘trolls’ all the time but I don’t see anyone worse than Kreo these days.
Anyhoo.
Alex said:
I will mention once again that Shills and Waldo are here not to have a meaningful debate, but to mince words. They will say that there is a lot of evidence that the climate is going to warm to unprecedented levels without models,
And I gave model-less evidence for that. Did you not follow the links?
Russ says:
‘I’m honestly having a hard time seeing a distinction between hindcasting (which you say is good) and tuning (which you say is bad).’
So why are you passing judgement on models when you don’t understand them? Most people educate themselves before doing so, no?
Miriam Says:
‘No. Not fine. This is the exact opposite of what I said.’
This is what you said (somehow this is the exact opposite???):
‘As it has been said, the paper arrives at an estimate of climate sensitivity in the range of 1.3 to 2.3. The estimate of climate sensitivity characterizing catastrophic global warming used by IPCC is much higher, 2.0 to 4.5. Saying that the range of 1.3 to 2.3 also suggests…’
And the papers I gave you predicted warming within the IPCC range.
Again, Where in the paper on sea-level rises do they use climate models of any sought? Sure, it uses topographic models but that doesn’t count.
Again, So you guys gonna give us a clear explanation of what CAGW is to you??
@ Waldo,
refreshing move, getting the attention you did from RC. I wonder what it would be like if some of the RC regulars came to this blog site.
@Shills:
“This is what you said (somehow this is the exact opposite???):
‘As it has been said, the paper arrives at an estimate of climate sensitivity in the range of 1.3 to 2.3. The estimate of climate sensitivity characterizing catastrophic global warming used by IPCC is much higher, 2.0 to 4.5. Saying that the range of 1.3 to 2.3 also suggests…’”
Breaking my sentence in the middle is all you can do these days, Shills, it seems. A complete version of the sentence:
“Saying that the range of 1.3 to 2.3 also suggests catastrophic global warming is a bit disingenuous, the argument that warming with a climate sensitivity in that range will be catastrophic has not been made.”
Yes, this is exactly the opposite of your idea and your previous misquote.
You are getting desperate.
You look tired, Shills.
Here is something new for you to ponder:
“Climate: New study slashes estimate of icecap loss”
http://sg.news.yahoo.com/afp/20100908/tts-climate-warming-science-ice-c1b2fc3.html
Miriam,
What are you on about?
You say that the range of climate sensitivity that characterises catastrophic GW is 2. to 4.5. And so I gave you papers that support that range. Perhaps the confusion lies with whether the figure 2. is a mean or a lower limit. Of course, in the context of your argument (that the IPCC uses a range of 2. to 4.5) I meant 2. as a lower limit, not a mean.
I do wonder why you couldn’t have figured this out considering the subsequent papers I gave you used 2. as no more than a lower limit, and because the first paper could fit 2. as a mean nicely enough, and that’s why you didn’t like it.
I cut off the second sentence because it added nothing to your quote that 2. to 4.5 was the catastrophic range. Do you honestly think I would be stupid enough to cut a quote disingenuously when the full text is just a flick above it?
I hope I have figured you out here, but if not, throw me some clues. And don’t be afraid to answer some of my questions…
Kreo,
Pondered. So, if true, this factor helps explain some of the differences between projections and observations that exist in this area. This is a good thing for climate science and a hopeful sign. So yeah… is that it? You don’t think I want the ice to melt do you???
Exactly, the range of climate sensitivity that characterizes catastrophic GW is 2 to 4.5. The central best-guess value used by IPCC is 3. Now please look at how many of the predictions from IPCC use values of climate sensitivity of 2 and 4.5 as opposite to 3.
2.3 does fall into the range of 2 to 4.5. This does not mean you can take predictions made by IPCC and say that if climate sensitivity ends up being 2.3, the future will resemble those predictions with the uncertainty levels assigned to them in IPCC reports.
To tackle this from a slightly different angle, the paper that cites the range of climate sensitivity of 1.3 to 2.3 with 95% certainty would assign the range of 2 to 2.3 (the intersection with the same-certainty range from IPCC) a certainty in the vicinity of no more than 30%, likely around 18-20%. That means that the paper thinks that the lowest estimates made by IPCC (which don’t participate in predictions that you’d call catastrophic, if we delve into the reports) are likely to be still too catastrophic to be real. That’s not a very strong argument in favor of catastrophic global warming.
We’d have a proper argument if this or another study presented its own predictions for temperatures based on these low estimates of climate sensitivity, and these predictions would have been made without the use of models (which is how it all started here), and they would also turn out to be catastrophic. The study does not do that and you haven’t supplied a link to the one that does.
I hope I made myself clear.
By the way, on the paper linked by Kreo, I think he meant to show one more model that had to be scaled down dramatically after touching the reality.
In reply to Russ R:
The 0.184 slope and the 0.5651 correlation was just your UAH table, correlating temperature increase with year. The t number gives an
outrageously high probability that this was not due to chance. The 0.184 IS the long term trend, but my point is, it’s not as
significant as the t number indicates.
From the McShane Wymer paper, plugging in stationary probability figures for non-stationary processes gives nonsense correlations.
If temperature is a random drunkard’s walk, the standard deviation in distance from the 0 axis after N unit steps is the square root of N.
That means, starting from 0, after 100 + or – unit length steps, the average drunk will be 10 steps away from the origin, after 400 steps, the average drunk will be 20 steps away. Also plug in your 1.96 1% factor, and you’ll get 1% of drunks close to 20 steps away after 100 steps,
40 steps away after 400 steps. Take an average drunkard’s walk, run a correlation with time, as you and I did with the UAH data,
and ridiculously high correlations will come up.
Detrend the data, counting only + or – changes from the prior point, and you’ll get a much more realistic probability of the SIGNIFICANCE of the trend.
Just noted this from Waldo:
“Are the models accurate? Don’t tell me, argue with this guy.
http://bartonpaullevenson.com/ModelsReliable.html”
As it was already mentioned, the site does not list models used by Hansen or IPCC and the section on global warming does not list any models after 1975.
But there is a more general pojnt.
If you are going to make an argument that we can believe the output of models used by IPCC, because there have been models whose predictions turned out to be true, you should also count models whose predictions turned out to be false. I bet you any sum of money that the number of models in the latter camp exceeds the number of models in the former camp at least by a factor of 100.
Thanks for clarifying Alan,
I understand the problem now. I will either “stationarize” the data or apply a different regression tool better suited to time-series data.
Appreciate your taking the time to explain it.
As I said, Miriam, argue with him. Or you could concede what I have all along–you don’t know what you are talking about. None of us do.
The debate (such as it is) is best left to the climate scientists, those who actually know what they are talking about. No one here, myself included, sounds particularly knowledgeable or informed. This could be because as a whole we are not knowledgeable or informed, including Mr. Meyer and his parks system.
Wally is over on Real Climate as we speak getting defense as usual (accusing other peeps of ad hominem and belittlement all the while being predictably tone deaf to his own voice and persona), and Russ R is asking for feedback and being given lessons in statistical methodology.
His T-stats, which the peeps here were rather enthusiastic about, are not as solid or as informed as Russ first thought [no Kreo, Wally and Russ were not “math experts” after all]. In fact, it would appear that Russ and Wally did not know as much about climate science and statistical evaluation as they first thought.
If you think there is a “factor of 100” in the fail rate of computer models, go for it, Miriam. But why post it here? Publish it. CS is a fairly safe bet for denialists–you don’t actively challenge each other much. Don’t you want to know how your evaluation measures up?
And by the way, Kreo, I have not slunk anywhere. My heart truly belongs to Climate Skeptic, but, alas, I have other, lesser responsibilities to tend to.
Man, you are dumb. That’s all.
Thank you Alex, for your insightful contribution.
And yes, Waldo, the lessons in time-series statistics are helpful.
Waldoslink: says
“The debate (such as it is) is best left to the climate scientists, those who actually know what they are talking about. No one here, myself included, sounds particularly knowledgeable or informed.”
Realclimate.com is cetainly the site for you. There you can soak up the party line, listen to their chorus of fans and not worry a bit that too many thoughtful contrary comments will get through moderation. They will even warn you about sites that may be too dangerous for you
****”Here is one prediction from there that I am going to believe”
You know, Alex, this is undoubtedly an unintentional revelation on your part, but this little statement speaks volumes about your own scope of intellect and critical thinking skills. I’m glad you can decide what you believe based on what you want to believe — fairly typical for the average denialist I suspect.
And I’m glad you are getting some help, Russ. I thought Real Climate might be able to set you straight.
Apparently, many people do not understand that the “cap and trade” deal is just a starter. The idea is to turn back the clock on fossil fuel consumption by a couple of decades. This represents a fairly modest decrease on fossil fuel use. However, the cap and trade people fail to point out that the models (if they are right) require an 80% reduction in CO2 to stop global warming, thus virtually shutting down modern industry and transportation. The “cap and trade” thing is thus a first step that in itself may be feasible, but the total program of an 80% reduction is not. Hence my earlier comment re destroying our modern industrial economy. If worrying about the affects of an 80% reduction is “over the top”, then I guess I am WAY over the top. Simply criticizing without offering an explanation or solution is way “under the top”.
****”(Here)you can soak up the party line, listen to their chorus of fans and not worry a bit that too many thoughtful contrary comments”
Paul, you do realize that, even if this were true, this likewise describes Climate Skeptic. And you do realize that Wally and Russ have been over there posting “thoughtful comments” for at least 24 hours, right?
Not to mention that Real Climate has people who know what they are talking about.
Waldod says:
“Paul, you do realize that, even if this were true, this likewise describes Climate Skeptic. And you do realize that Wally and Russ have been over there posting “thoughtful comments” for at least 24 hours, right?”
So Waldod, are you telling me that you have attempted to post comments on this blog, only to have them never appear because they were deleted by a moderator? That has been my experience over at Realclimate. About one-half the comments I have attempted to post never appear at Realclimate. Roger Pielke, Jr. has noted that his posts haven’t passed moderation even when the topic being discussed is his own published paper. Steven McIntyre is outright banned from comments from Realclimate. Jeffid from the Airvent blog tells of an experiment he did where he post three dumb critical comments, which immediately appeared in the comments on Realclimate, and then tried posting a serious critical comment, which never passed moderation. Over time, I have read dozens and dozens of accounts by skeptics regarding comments that do not make it through Realclimate’s moderation. If they are so smart and can answer their critics, why do they do they exercise such heavy handed moderation?
As to the comment, “do realize that Wally and Russ have been over there posting “thoughtful comments” for at least 24 hours, right?”, I never said they deleted everything. Perhaps, the moderator thinks their comments have some “mistakes” that can be refuted to the satisfaction of the realclimate groupies?
Just re-read my previous post and realized it might come across as putting down Wally and Russ’s efforts over at realclimate. I just read the thread and I think they are doing a great job. I got a kick out of reading one of the realclimate posts suggest by one of their groupies. The realclimate boys compare projections from AR4, published in 2007 and are impressed that the real trend falls within the 95% confidence band that encompasses significant cooling and significant warming.
Miriam says:
‘I hope I made myself clear.’
Let’s see. You are basically saying that that the 1.3 to 2.3 paper is not a catastrophic prediction because the percentiles that would fit into the IPCC’s range for catastrophic GW amounts to no more than 30%. I know. I get that. 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?
Miriam says:
‘I think he meant to show one more model that had to be scaled down dramatically after touching the reality.’
No. The models have not been scaled down. If anything the measurements of ‘reality’ have been shown erroneous. And so reality now fits the models better. But, this is just one paper and we are yet to see how it is received.
Again, Where in the paper on sea-level rises do they use climate models of any sought? Sure, it uses topographic models but that doesn’t count.
Again, So you guys gonna give us a clear explanation of what CAGW is to you??
Paul, Mr. Meyers does not read the comments, he does not have time; he has admitted as much–that is why there is no moderation here.
And you missed the point anyway, so I’ll make it even clearer. The tenor of dialogue here is, for many, every bit as irrational, dogmatic, uninformed, cultish, and plain old nutso as anywhere on the web outside of, perhaps, an MMA-vs-Kung-Fu forum. Please don’t pretend that somehow you and the Jo Novas and the Anthony Watts of the world are the fair and balanced commentators (both of whom, by the way, banish people with irreverent abandon).
Are you, like Kreo, one of those people who think in terms of “enemy’s soil” when discussing a matter of science which you clearly know very little about?
And Wally and Russ’ “efforts” on RC consist mainly of being schooled in statistical methods (Russ) and being asked to read the actual science involved (Wally).
Ted, where did this paranoia come from? Why do you think “cap and trade” (which looks like a disastrous and doomed bureaucracy to begin with) is only the tip of some Orwellian plan for economic self-destruction? Perhaps you will disagree with him, but since I’ve been checking with RC lately I ran into this commentary by Bob Sphaerica regarding GW and the world economy.
“First, everything I’ve read says that professional economists estimate the cost at between 1% and 3% of GDP, which is pretty minor. No skyrocketing costs. Just retooling, and jobs/economy involved in the process.”
“No free market democracy, no matter what is done, is going to implement policies that strangle the economy and cause the sort of damage you’re describing. In the worst of cases, politicians that try to do so would be voted out of office. That sort of behavior could not come about until climate change itself was so damaging and indisputable that the populace was panicking, which will be too late.”
Perhaps you disagree but these seem like a reasonable analysis.
For what it’s worth,
I haven’t had any problem posting anything to Real Climate. Yes there’s often a few hours delay while my posts have been reviewed by a moderator, but all of them have made it through uncensored.
Now, that could be because I’m sticking to being civil, and sincerely seeking guidance on how to best test model predications against data.
And yes, a few of the folks at Real Climate have been outright rude to anyone with a contrary opinion. However, their rudeness isn’t much different from the way we’ve enjoyed beating up on Waldo and Shills.
A couple of commentators there have been genuinely helpful, pointing out problems with testing a straight-line warming trend for IPCC (1995), and with using OLS regression on time-series data (as was also pointed out by Alan over here). I’ll repost test results as soon as I get settled on the correct tools. It looks like I’ll only be able to test Hansen (1988) and IPCC (1990), since I’m not having any luck finding model output data for IPCC (1995).
Waldo says : “And you missed the point anyway, so I’ll make it even clearer. The tenor of dialogue here is, for many, every bit as irrational, dogmatic, uninformed, cultish, and plain old nutso as anywhere on the web outside of, perhaps, an MMA-vs-Kung-Fu forum.”
That is an interesting perspective. Could you give me a specific example from this thread of a post you would view as “irrational, dogmatic, uniformed, cultish and plain old nutso”
“Are you, like Kreo, one of those people who think in terms of “enemy’s soil” No and did Kreo say something about “enemy soil”?
“when discussing a matter of science which you clearly know very little about?” I see you are picking up the arrogant, condescending tone of the Realclimate groupies that is intended to dismiss skeptics without providing any real content.
“And Wally and Russ’ “efforts” on RC consist mainly of being schooled in statistical methods (Russ) and being asked to read the actual science involved (Wally).” Wally and Russ are doing just fine. There have been many reasonable comments from realclimate and reasonable responses from Wally and Russ, and, as always, many attempts by the groupies to dismiss and intimidate with condescending comments that are devoid of content.
I went through the hassle of changing those tempeperatures to delta temperatures. The the result gave a “t” value of 0.05616, implying that there’s a 46% chance that there might be a “negative” trend. I don’t know how to interpret the slope it gave, so I didn’t bother to write it down. As you said, the actual temperatures were increasing by about 0.184 per decade, but the slope must indicate rate of
temperature change per decade.
Alan,
Thanks for pitching in on this pet project of mine.
I have my doubts about anything more than a trivial probability of a “negative trend” for temperatures over the last couple of decades. The warming was abundantly evident.
Would you mind emailing me your spreadsheet? I’ll send you the version I’ve been working with. My email address is: s21519(at)hotmail(dot)com
“Could you give me a specific example from this thread of a post you would view as ‘irrational, dogmatic, uniformed, cultish and plain old nutso’”
How about–
“condescending tone of the Realclimate groupies that is intended to dismiss skeptics without providing any real content.”
Or perhaps you think you’ve given Real Climate a fair evaluation and the content of their website and its commentary, which is actually filled with a good deal of science-based observations, facts, computer codes, etc. Really, do you consider RC people “groupies” and the CS people…what? model thinkers?
But no matter what, my favorite has always been hunter, who has unfortunately been driven away of late by all the “trolls”:
****”There mental choices leave no room for nuance and distinction. You are either believing there is a looming climate apocalypse or you are a paid shill of big oil, and want to destroy the Earth.”
****”Kreo say something about ‘enemy soil’?”
Yup. Kreo is a rather more articulate and I suspect younger version of hunter.
****”we’ve enjoyed beating up on Waldo and Shills.”
Let’s not get silly here, Russ. Your T-stats were an attempt to shut me down (you’re not the first either) and I outmaneuvered you, essentially proving you wrong by putting you someplace you couldn’t just post an incomplete, uninformed series of equations as an attempt to “convince our friend Waldo” (your words, not mine) to back-down (or whatever you thought would happen).
For whatever it’s worth, I admire your stick-to-it-ivness in this matter, and you are clearly a man of some intellect and articulateness. You will not come up with anything of any real substance, of course, and I have to wonder why you have embarked in this direction when you could use your expertise in finance to actually accomplish something? Why not do an evaluation of the financial burden of fighting GW? Lomborg seems to have (somewhat) reversed direction, perhaps you could explain why to the world, or contradict him? I’d listen to you there and you wouldn’t have to convince me of anything (assuming you are what you post you are)–not that you care of course (although you clearly do). Oh well–
Anyway, I think this thread is dying a lingering death.
Perhaps we shall all meet again. Cheers