Scientists discover that climate-change skeptics are bozos

[Peregrinator]

As long as we're bashing religiosity and the right...


Michael Barone, NRO

Care to comment on the fact that with this post you c&ped an ad hominem attack and signed on to it?

 

[4est_4est_Gump]

has anyone said why if Anthro climate change is bullshit scientists keep insisting it's real. what's in it for them?

Ca$h money, government grants, a cowed and worshipful following ready to Crusade, to do good, to join that noble cause of saving all of humanity.

Government can use the fear to humiliate and enslave us and once society is stripped of all religious moral, then any moral will do and soon you have a self-feeding cycle, Government plunders, Science partakes, and everyone is proud of their efforts for they have set for themselves a morality and a nobility in what they do.

As Perg as said many times, even if they're wrong, what the hell is wrong with trying to clean up the planet? You see even in this an ends justifies the mean mentality and usually the best way to produce this mentality is an irrational fear stoked by the infallible omnipotent and unquestioned expertise of the Priesthood.

That's what Christians say to me all the time, A_J, you heathen Atheist, what could be wrong with believing? There's no downside to being wrong and a huge upside to being right...

"When plunder becomes a way of life for a group of men living together in society, they create for themselves in the course of time a legal system that authorizes it and a moral code that justifies it."
Frédéric Bastiat

 

[4est_4est_Gump]

Care to comment on the fact that with this post you c&ped an ad hominem attack and signed on to it?

It's only ad hominem if it's not true.

The movement has adopted the methods and trappings of religion.

This is an a priori observation to even the most slow among us. You yourself act as devout as any member of any congregation that has tried to convert me over the course of 50+ years to the "truth" of their particular belief system. There are a ton of them out there that you have no problem in denigrating as sheer ignorance, yet somehow, it's not the least bit possible that you too could fall sway to a powerful, seductive and charismatic movement, oh, no, perish that thought for you are a free thinker, a man of enlightenment, of letters and many, many experts for friends who constantly give you good reason for your surety...

It's gone long past Science. Science does not crusade; followers, Hoffer's True Believers, they crusade in the name of Science.

 

[Peregrinator]

It's only ad hominem if it's not true.

The movement has adopted the methods and trappings of religion.

This is an a priori observation to even the most slow among us. You yourself act as devout as any member of any congregation that has tried to convert me over the course of 50+ years to the "truth" of their particular belief system. There are a ton of them out there that you have no problem in denigrating as sheer ignorance, yet somehow, it's not the least bit possible that you too could fall sway to a powerful, seductive and charismatic movement, oh, no, perish that thought for you are a free thinker, a man of enlightenment, of letters and many, many experts for friends who constantly give you good reason for your surety...

It's gone long past Science. Science does not crusade; followers, Hoffer's True Believers, they crusade in the name of Science.

1) It's not true. Retract it or admit your hypocrisy.

2) The scientists are not crusading. Well, most of them aren't. The scientists are trying to muddle through the smokescreen set up by assholes like the author of your ad hominem piece. I'm not "devout" about this any more than I'm "devout about gravity, evolution, genetics, solution chemistry, or any of a million other things that other people figured out before me and told me about.

3) Your ad hominem c&p contains two paragraphs with factual errors. Do you care? Did you notice?

 

[where]

Money, lots of money, and power. That's what it's all about.

Ishmael

Ca$h money, government grants, a cowed and worshipful following ready to Crusade, to do good, to join that noble cause of saving all of humanity.

Government can use the fear to humiliate and enslave us and once society is stripped of all religious moral, then any moral will do and soon you have a self-feeding cycle, Government plunders, Science partakes, and everyone is proud of their efforts for they have set for themselves a morality and a nobility in what they do.

As Perg as said many times, even if they're wrong, what the hell is wrong with trying to clean up the planet? You see even in this an ends justifies the mean mentality and usually the best way to produce this mentality is an irrational fear stoked by the infallible omnipotent and unquestioned expertise of the Priesthood.

That's what Christians say to me all the time, A_J, you heathen Atheist, what could be wrong with believing? There's no downside to being wrong and a huge upside to being right...

"When plunder becomes a way of life for a group of men living together in society, they create for themselves in the course of time a legal system that authorizes it and a moral code that justifies it."
Frédéric Bastiat

ridiculous. Scientists get funding and cuts in funding all the time. There is more financial benefit to saying it doesn't exist than saying it does.

you will both have to be a lot more convincing than scientists want to keep the funding.

 

[richard_daily]

Money, lots of money, and power. That's what it's all about.

Ishmael

For once in your life, you're actually right about something.

Unfortunately, you don't understand that the money and power that you're referring to is the money and power of the oil and gas companies lobbying and fighting against anything that would cause their destructive behavior to change.

 

[trysail]

I don't make a habit of attempting to convince the unconvinceable. It's usually a mistake to do so.

__________________



There aren't enough hours in the day to explain to someone that a computer model of an already imperfectly understood, immensely complex, multi-variate, NON-LINEAR system is a farce from the git-go.


If you don't understand that, you're already beyond help— you're gullible and a computer model can be manufactured that will get you to believe damn near anything.


If you have not looked at NASA GISS ModelE, if you have no experience with attempting to program computer simulations of highly complex, multi-variate, non-linear systems, you'll never understand what's going on.






The now infamous "HARRY_READ_ME.txt" file:
http://www.anenglishmanscastle.com/HARRY_READ_ME.txt

Brief excerpts therefrom:

...
Loading just the first program opens up another huge can o' worms. The program description reads:

pro cal_cld_gts_tdm,dtr_prefix,outprefix,year1,year2,info=info
; calculates cld anomalies using relationship with dtr anomalies
; reads coefficients from predefined files (*1000)
; reads DTR data from binary output files from quick_interp_tdm2.pro (binfac=1000)
; creates cld anomaly grids at dtr grid resolution
; output can then be used as dummy input to splining program that also
; includes real cloud anomaly data

So, to me this identifies it as the program we cannot use any more because
the coefficients were lost. As it says in the gridding read_me:

Bear in mind that there is no working synthetic method for cloud, because Mark New
lost the coefficients file and never found it again (despite searching on tape
archives at UEA) and never recreated it. This hasn't mattered too much, because
the synthetic cloud grids had not been discarded for 1901-95, and after 1995
sunshine data is used instead of cloud data anyway.

But, (Lord how many times have I used 'however' or 'but' in this file?!!), when
you look in the program you find that the coefficient files are called:

rdbin,a,'/cru/tyn1/f709762/cru_ts_2.0/_constants/_7190/a.25.7190',gridsize=2.5

And, if you do a search over the filesystems, you get:

crua6[/cru/cruts] ls fromdpe1a/data/grid/cru_ts_2.0/_makecld/_constants/_7190/spc2cld/_ann/
a.25.01.7190.glo.Z a.25.05.7190.glo.Z a.25.09.7190.glo.Z a.25.7190.Z
crua6[/cru/cruts] ls fromdpe1a/data/grid/cru_ts_2.0/_makecld/_constants/_7190/spc2cld/_mon/
...
So.. we don't have the coefficients files (just .eps plots of something). But
what are all those monthly files? DON'T KNOW, UNDOCUMENTED. Wherever I look,
there are data files, no info about what they are other than their names. And
that's useless.. take the above example, the filenames in the _mon and _ann
directories are identical, but the contents are not. And the only difference
is that one directory is apparently 'monthly' and the other 'annual' - yet
both contain monthly files.
...

http://www.edge.org/documents/archive/edge219.html#dysonf

… I have studied the climate models and I know what they can do. The models solve the equations of fluid dynamics, and they do a very good job of describing the fluid motions of the atmosphere and the oceans. They do a very poor job of describing the clouds, the dust, the chemistry and the biology of fields and farms and forests. They do not begin to describe the real world that we live in. The real world is muddy and messy and full of things that we do not yet understand. It is much easier for a scientist to sit in an air-conditioned building and run computer models, than to put on winter clothes and measure what is really happening outside in the swamps and the clouds. That is why the climate model experts end up believing their own models.

Freeman Dyson, Ph.D.
Professor of physics at the Institute for Advanced Study, in Princeton. His professional interests are in mathematics and astronomy. Among his many books are Disturbing the Universe, Infinite in All Directions Origins of Life, From Eros to Gaia, Imagined Worlds, and The Sun, the Genome, and the Internet. His most recent book is Many Colored Glass: Reflections on the Place of Life in the Universe.






Do you know what derivatives are? Do you know what a CDO-squared is? It was computer simulations of these comparatively simple( by comparison to the climate system ), single variable, NON-LINEAR securities that enabled the rocket scientists ( literally, as Wall Street employed Ph.D. mathematicians to build the models ) to bamboozle not only themselves but their employers, the ratings agencies, the banks, the pension funds and the entire financial system into their self-inflicted destruction. The rocket-scientist-modelers fooled themselves into believing their own models.

The models and their simulated outcomes gave a patina of "science" to what were essentially incomprehensible and unknowable results.

The history of humanity is full of people who were absolutely dead-set sure, and completely wrong.

Climate models are not evidence: they are imperfect “simulations” of the climate, not the climate itself. Our global atmosphere is a messy algorithm, with oceans, clouds, rain, water vapor, solar wind, magnetic fields, forests, ice-cover, glaciers, volcanoes, heat from below, and moving dust clouds of soot. It’s just not possible to simulate the real atmosphere without making assumptions, estimates or decisions on which parts to simplify or omit. Since all those things rely on the opinions of the modelers, no matter how well intentioned or educated they are, a model is a glorified opinion.
-Joanne Nova
http://joannenova.com.au/2010/01/is-there-any-evidence/

_________________________





By comparison to the climate system, this was a trivial problem.


http://noir.bloomberg.com/apps/news?pid=20601110&sid=ay4tFTEBKCE8


Taleb Says Investors Should Sue Nobel Panel for Losses
By Stephanie Baker

Oct. 8 (Bloomberg) -- Nassim Nicholas Taleb, author of “The Black Swan,” said investors who lost money in the financial crisis should sue the Swedish Central Bank for awarding the Nobel Prize to economists whose theories he said brought down the global economy.

“I want to make the Nobel accountable,” Taleb said today in an interview in London. “Citizens should sue if they lost their job or business owing to the breakdown in the financial system.”

Taleb said that the Nobel Prize for Economics has conferred legitimacy on risk models that caused investors’ losses and taxpayer-funded bailouts. Sweden’s central bank will announce the winner of this year’s award on Oct. 11.

Taleb singled out the Nobel award to Harry Markowitz, Merton Miller and William Sharpe in 1990 for their work on portfolio theory and asset-pricing models.

“People are using Sharpe theory that vastly underestimates the risks they’re taking and overexposes them to equities,” Taleb said. “I’m not blaming them for coming up with the idea, but I’m blaming the Nobel for giving them legitimacy. No one would have taken Markowitz seriously without the Nobel stamp.”

Markowitz, a professor of finance at the Rady School of Management at the University of California, San Diego, didn’t return a phone call seeking comment. Miller, who was a professor at the University of Chicago, died in 2000 at the age of 77.

“People used the theory and assigned numerical forecasts to the algebra,” said Sharpe, a professor of finance, emeritus, at the Graduate School of Business at Stanford University, in a telephone interview. “But I’m not going to take the blame for the numbers they put in.”

Probability Models
In his 2007 bestseller “The Black Swan: The Impact of the Highly Improbable,” Taleb described how unforeseen events can roil markets. He warned that bankers were relying too much on probability models and disregarding the potential for unexpected catastrophes.

“If no one else sues them, I will,” said Taleb, who declined to say where or on what basis a lawsuit could be brought.

The Nobel prizes in physics, chemistry, medicine, peace and literature were established in the will of Alfred Nobel, the Swedish inventor of dynamite who died in 1896. The first awards were handed out 1901. The Swedish Central Bank founded the economics award in 1968 in memory of Nobel. Previous winners of that prize include Milton Friedman, Amartya Sen, Paul Krugman, Robert Merton and Myron Scholes.

A former derivatives trader, Taleb is a professor of risk engineering at New York University and advises Universa Investments LP, a Santa Monica, California-based fund that bets on extreme market moves.

 

[Peregrinator]

While there are uncertainties with climate models, they successfully reproduce the past and have made predictions that have been subsequently confirmed by observations.

http://www.skepticalscience.com/images/Hansen_2005_Model.gif
Figure 2: Global surface temperature computed for scenarios A, B, and C, compared with two analyses of observational data (Hansen 2006).

http://www.skepticalscience.com/climate-models-intermediate.htm





If the models successfully reproduce the past and make predictions that are confirmed by observation, no amount of argumentation, spin, and technojargon will make them wrong.

The models successfully reproduce the past and predict the observable. Think about it.

 

[Sonny Limatina]

Look, the study is obviously driven by ideology and bandwagoning, anyone can tell that without even reading it.

Don't give me the 'Koch helped fund it and anti's are in on the study too' bullshit. Everyone knows the media is controlled by freedom-hating liars.

At this point, I won't even believe the study exists until I see it with my own eyes, which I'm not going to do, since it's obviously wrong.

 

[phrodeau]

(edited)
I don't make a habit of attempting to convince the unconvinceable. It's usually a mistake to do so.

__________________



There aren't enough hours in the day to explain to someone that a computer model of an already imperfectly understood, immensely complex, multi-variate, NON-LINEAR system is a farce from the git-go.


If you don't understand that, you're already beyond help— you're gullible and a computer model can be manufactured that will get you to believe damn near anything.


If you have not looked at NASA GISS ModelE, if you have no experience with attempting to program computer simulations of highly complex, multi-variate, non-linear systems, you'll never understand what's going on.

Well then, of the few people who do understand what's going on (in your opinion), how many are deniers and skeptics?

 

[JohnnySavage]

I would like to contribute to this thread with some graphs.

Thus:

http://3.bp.blogspot.com/_RBGVNzE33VE/SgN2FbAUGNI/AAAAAAAAAN0/ICUJWZDvOVs/s400/us_post_causes_global_warming_lrg.jpg


/thread
/issue
/AGW

 

[Sean]

[



There aren't enough hours in the day to explain to someone that a computer model of an already imperfectly understood, immensely complex, multi-variate, system is a farce from the git-go.

So we should stop designing aircraft, then? You do know that non-laminar flow over aircraft wings is chaotic, right? Bernouilli's theory notwithstanding?

 

[cjh]

that graph, indeed, is compelling.

maybe jenn should add that to her USPS screed.

 

[JohnnySavage]

The facts don't lie.

 

[Sean]

that graph, indeed, is compelling.

maybe jenn should add that to her USPS screed.

LOL. Usually I don't bother, it's science v corporate true believers. And I wouldn't even have seen the Trysail post if it wasn't quoted.

 

[mercury14]

You are also pretty damned sure that I should not be using it for economics, but there is one problem with that attitude, American Thinker has been a lot closer to reality than Turbo TIMMAH! and friends...

Detailed weather records from 20,000 years ago...

Was that Barney Rubble's job?

That's right, you shouldn't get your economics or your climatology from the American Thinker or Glenn Beck.

 

[mercury14]

I missed that post earlier. Trysail, what other huge swathes of science are primarily computer-modeled or not reproducible? Do you routinely castigate them, too? Cuz it seems to me that could get problematic pretty fast.

He'll just dodge your question, as he did when I asked the same thing a few pages back.

Well, he might, but I think he actually likes me, which might make a small difference.

Did he ever get around to answering your question? Or did he hide from you exactly as I predicted?

 

[trysail]

So we should stop designing aircraft, then? You do know that non-laminar flow over aircraft wings is chaotic, right? Bernouilli's theory notwithstanding?

Congratulations. In a rare demonstration of posting virtuosity, you actually managed to post nonsense within a non sequitur.

 

[Sean]

Congratulations. In a rare demonstration of posting virtuosity, you actually managed to post nonsense within a non sequitur.

Um, no. Just because you didn't understand it doesn't mean it's nonsense. But it looks like we've pegged your level of scientific understanding now, doesn't it? Back to ignore you go, font boy. You really weren't worth taking off.

 

[trysail]

Climate Model Uncertainty: Part I
by William M. Briggs
http://wmbriggs.com/blog/?p=2067

Would you check the results of a model with another model? Before you answer, be sure you know what the question is.

A model—whether it is physical, statistical, mathematical, or some combination—is an algorithmic device designed to make predictions about some observable thing. You want today to know that price of tomorrow’s Dow Jones Industrial Index? There are models for that; usually statistical models.

You want today to know whether it will rain in Detroit tomorrow so that you can decide whether to plant your crops in the old lots that used to contain houses? There’s a model for that; a physical-statistical weather model called MOS (model output statistics; see Part II).

Now, how would you, assuming you are not an expert in these matters, check the accuracy of your model? Would you (a) compare the model’s predictions with what actually happened, or (b) produce another model and check the results of the first model against the predictions of the second?

The right answer is (a), of course, but the problem is that there are two ways to interpret “what actually happened.” You probably thought it meant “what happened in the future.” Now, it is the great shame in the field of statistics—both in the dismal way it is taught and the worse way it is practiced by most—that (a) is nearly always is interpreted to mean “what happened in the past.”

Nearly all—the exceptions to this are rarer than sober Paul Krugman columns—statistical models, and many physical models, are checked against the data that was used to fit, or create them. Since it is an elementary theorem that any model may be made to fit perfectly—not just closely, perfectly—to any set of historical data, to claim that your model is good because it fits old data well is a hollow boast.

This is the reason for the great overconfidence of experts who build and use models. And don’t think it doesn’t matter, because it does. People in charge of us makes decisions and set policy based on these models frequently. We are at the mercy of bad statistics.

Weather and Climate Models

But it’s not all bad. It is to the great glory of meteorological models that they are usually—in practice, I mean—checked against what happened in the future. Weather models have the advantage of a constant stream of model predictions and future observations. Discrepancies between the two are noted quickly and used in tweaking the models so that they perform better in the future.

Anybody who cares to look will discover that the performance of meteorological models has improved dramatically over the last thirty years. Of course, people’s expectations of accuracy has also increased, so that the level of grousing about weatherman has remained constant. Human nature.

Climate models are in a different category. So far, all they can boast about is how well they fit the data used to build them, which we have just seen is no great shakes. This being true, those who use climate model output should be humble, they should be cautious, even timid about their prognostications. And that’s just what we see in practice, right?

Actually, it’s still worse, because climate modelers—and in their development stages, weather modelers—answer (b) to that question above. They check their models against the output of other models. How could this be?

The Analysis

Climate/weather models take current observations as input and produce forecasts of future observables as output. But these physical models cannot take observations raw, like statistical models can. They must first process those observations so that they fit into the model environment. This assimilation is called an analysis. Analysis is a model itself.

Climate/weather models are run on grid-like structures, but observations come irregularly: we do not have equally spaced observations over the surface of the Earth and through the atmosphere. To operate, the observations have to be placed on the model grid. The analysis, then, is a sort of interpolation that does this. This is not a detriment; it is a necessary step to get these models to run.

Once the analysis is complete, the model is integrated forward in time to produce a forecast. OK so far? Because it’s about to get tricky. At that future point—the time of the forecast—come new observations. Ideally, the climate/weather model’s output would be checked against these actual observations, at only the irregularly spaced sites where they are taken. These observations are, are the truth, the whole truth, and the only truth.

But that’s not what happens. Instead, these new observations are read into the model in a new analysis cycle. This interpolates these new observations to the model grid. Then the old model integration is checked against this new analysis.

Thus, the model’s accuracy is checked with another model.

Climate Model Uncertainty: Part II
by William M. Briggs
http://wmbriggs.com/blog/?p=2069

The Analysis (cont.)

Two problems arise when comparing a model’s integration (the forecast) with an analysis of new observations, which are not found when comparing the forecast to the observations themselves. Verifying the model with an analysis, we compare two equally sized “grids”; verifying the model with observations, we compare a tiny number of model grid points with reality.

Now, some kinds of screwiness in the model are also endemic in the analysis: the model and analysis are, after all, built from the same materials. Some screwiness, therefore, will remain hidden, undetectable in the model-analysis verification.

However, the model-analysis verification can reveal certain systematic errors, the knowledge of which can be used to improve the model. But the result is that the model, in its improvement cycle, is pushed towards the analysis. And always remember: the analysis is not reality, but a model of it.

Therefore, if models over time are tuned to analyses, they will reach an accuracy limit which is a function of how accurate the analyses are. In other words, a model might come to predict future analyses wonderfully, but it could still predict real-life observations badly.

Which brings us to the second major problem of model-against-analysis verification. We do not know actually how well the model is performing because it is not being checked against reality. Modelers who rely solely on the analysis model-checking method will be—they are guaranteed to be—overconfident.

The direct output of most climate and weather models is difficult to check against actual observations because models makes predictions at orders and orders of magnitude more locations than there are observations. Yet modelers are anxious to check their models at all places, even where there are no observations. They believe that analysis-verification is the only way they can do this.

This is important, so allow me a redundancy: models make predictions at wide swaths of the Earth’s surface where no observations are taken. At a point near Gilligan’s Island, the model says “17oC”, yet we can never know whether the model was right or wrong. We’ll never be able to check the model’s accuracy at that point.

We can guess accuracy at that point by using an analysis to make a guess of what the actual temperature is. But since model points—in the atmosphere, in the ocean, on the surface—outnumber actual observation locations by so much, our guess of accuracy is bound to be poor.

MOS

Actual observations can be brought into the picture by matching model forecasts to future observations and then building a statistical model between the two. This is called model output statistics, or MOS. The whole model, at all its grid points, is fed into a statistical model: luckily, many of the points in the model will be found to be non-predictive and thus are dropped. Think of it like a regression. The models’ output are like the Xs, and the observations are like the Ys, and we statistically model Y as a function of the Xs.

So, when a new model integration comes along, it is fed into a MOS model, and that model is used to make forecasts. Forecasters will also make reference to the physical model integrations, but the MOS will often be the starting point.

Better, MOS predictions are checked against actual observations, and it is by these checks which we know meteorological models are improving. And those checks are also fed back into the model building process, creating another avenue for model improvement. MOS techniques are common for meteorological models, but not yet for climatological models.

Measurement Error

MOS is a good approach to correct gross model biases and inaccuracies. It is also used to give a better indication of how accurate the model—the model+MOS, actually—really is, because it tells us how the model works at actual observation locations.

But MOS verification will still given an overestimate of the accuracy of the model. This is because of measurement error in the observations.

In many cases, nowadays, measurement error of observations is small and unbiased. By “unbiased” I mean, sometimes the errors are too high, sometimes too low, and the high and low errors balance themselves out given enough time. However, measurement error is still significant enough that an analysis must be used to read data into a model; the raw data measured with error will lead to unphysical model solutions (we don’t have space to discuss why).

Measurement error is not harmless. This is especially true for the historical data that feeds climate models, especially proxy-derived data. Proxy-derived data is itself the result of a model from some proxy (like a tree ring) and a desired observation (like temperature). The modeled—not actual—temperature is fed to an analysis, which in turn models the modeled observations, which in turn is physically modeled. Get it?

Measurement error is a problem is two ways. Historical measurement error can lead to built-in model biases: after all, if you’re using mistaken data to build—or if you like “inform”—a model, that model, while there is a chance it will be flawless, is not likely to be.

Plus, even if we use a MOS-type system for climate models, if we check the MOS against observations measured with error, and we do not account for that measurement error in the final statistics (and nobody does), then we will be too certain of the model’s accuracy in the end.

In short, the opportunity for over-certainty is everywhere.

 

[Peregrinator]

http://www.skepticalscience.com/climate-models-intermediate.htm




Skeptics argue that we should wait till climate models are completely certain before we act on reducing CO2 emissions. If we waited for 100% certainty, we would never act. Models are in a constant state of development to include more processes, rely on fewer approximations and increase their resolution as computer power develops. The complex and non-linear nature of climate means there will always be a process of refinement and improvement. The main point is we now know enough to act. Models have evolved to the point where they successfully predict long-term trends and are now developing the ability to predict more chaotic, short-term changes. Multiple lines of evidence, both modeled and empirical, tell us global temperatures will change 3°C with a doubling of CO2 (Knutti & Hegerl 2008).

Knutti and Hegerl 2008: http://www.iac.ethz.ch/people/knuttir/papers/knutti08natgeo.pdf

 

[patrick1]

Maybe it's just because I'm a diffident science-loving Brit but here are some things I find puzzling about this whole debate:

- why rudeness and anger and emotive rhetoric are thought to aid enlightenment
- why so many articles cited in this debate do not reference their sources. A simple set of brackets and a link within them would do. For instance, that article by Briggs: I am interested in the follies of forecasting by modelling, indeed I have not the slightest faith in forecasters, one book I would like to write but never will is the comedic History Of Forecasting - but I immediately distrust Briggs's article because it fails to quote sources. That makes it look ideological, not a seeker after truth.
- how politics became entangled in science in this way. I am a leftist in politics, but am used to finding common ground with people all across the political spectrum on scientific matters. Why, in respect of climate change, does politics matter so much?
- conspiracies...the 'right wing' view seems to imagine there is some sort of 'left liberal' conspiracy involved here. I can't fathom the core of this supposed conspiracy. A bunch of academics earning middling to low salaries are conspiring together...for why? I just don't follow it. Do explain to me what they are all gaining and why it's worth risking their intellectual reputations.
- uncertainty and scepticism...I feel the core of science is doubt. Our knowledge is the sum of hypotheses that have not yet been disproved. Why, are the sceptics in this debate so unsceptical about their own views? They seem so certain they are right, I can't fathom how that fits with the notion of the scientific method, and a belief in scepticism.
- trust is I suppose the key thing here. Nobody who posts here is a climate scientist: we are all making judgments as to whether we trust expressed opinions.

For myself, I doubt the worst of the forecasts. But it seems to me wise to act as if they might be true, and make some precautions: in low-lying islands and places like Bangladesh, say; in the greater provision of energy by renewable sources.

In left field, I wish we didn't use petroleum for energy at all: if we saved it to create materials, we could make it last hundreds of years longer, saving lives and enabling more fun in the process!

Well, there you are.

Patrick

 

[4est_4est_Gump]

1) It's not true. Retract it or admit your hypocrisy.

2) The scientists are not crusading. Well, most of them aren't. The scientists are trying to muddle through the smokescreen set up by assholes like the author of your ad hominem piece. I'm not "devout" about this any more than I'm "devout about gravity, evolution, genetics, solution chemistry, or any of a million other things that other people figured out before me and told me about.

3) Your ad hominem c&p contains two paragraphs with factual errors. Do you care? Did you notice?

Let us, then, examine how you approach the topic. You know it's true, for a fact. Anyone who says it is not true is a denier, a skeptic, has been discredited, is not qualified to make a judgement or has an agenda. It's classic good-guy bad-guy stuff. Anything offered as possible cause is rejected out of hand, "everyone knows it's not the sun," as if the sun has nothing to do with temperature in the solar system. This is the parallel of Lovelynice. Lovelynice is a wacadoodle when it comes to the religion of 9-11 Trutherism. Lovelynice is very concerned about righting that wrong.

Those of us who disagree with you don't have our facts straight, don't have the proper educational credentials to discern the facts of climate change and are under the sway of powerful (rw Christian [even the Atheist A_J]) forces with an anti-Science agenda. Never mind that a lot of us that you disagree with have degrees in Science that are more advanced than yours or have worked in meteorology (*ahem* *ahem*), we are irrelevant because we haven't read the important papers (sacraments) and we don't engage in ongoing conversations with experts in the field (the Priesthood) as you do. This obviates your need to have an advanced degree in Science and qualifies you to discern the absolute truth of the matter. This parallels that Hassan chap, who did his reading, spent time studying under experts, reached his conclusions and then shot up Fort Hood in the name of doing right for his religion.

When models are proven to be fixed hoaxes, then the retreat is the Rather-esque, "So what if the document is forged, the story is still true" we have other models, we fixed that model, they all say the same thing, what qualifies you to even discuss models even though you created them for the banking and telecom industries as you finished your degree, you just have a right-wing agenda coupled with a lot of ignorance...

Then, finally, you get to the level of U_D and merc where everything is an ad hominem, facts are taken out of context or cherry-picked in the manner of the fallacy of unquestionable "expertise and we're just bad, ignorant people of no compassion or concern for the environment (again good-guy bad guy stuff, our greed cases dirty air and water).

I have freely admitted many times that I think you are indeed a good person who very much loves nature and cares deeply about the environment, unfortunately, sometimes your love, devotion and good intentions border on zealotry to the point that you are willing to trade off my current (economic and literal) liberty for some promised future security, which, in all honesty, will never come because even as we deal ourselves a death-blow in the name of Gaia, China, India and Islam are having none of it; they think it's nuts and they will profit off of us as long as we are profitable and then they will discard us.

I think Karen Armstrong put in best in her book "Holy War" and she ended with the [paraphrase] conclusion that even as we put Christian Crusading behind us and put Christianity down, we did not change our culture, we just picked new Crusades and new methods of carrying them on.

We are still self-righteous moral busybodies who would be better off just minding ourselves instead of the affairs of others.

 

[4est_4est_Gump]

Good gawd...

When modeling fails, double down on it perg.

Those linear models predicting a chaotic system are very bit as sophisticated as the economic models used by the Obama Team to prove that three trillion in spending would keep the unemployment rate under 8%. I think we can keep that dramatic and drastic temperature under three degrees by spending no money on it at all...



PS - You know, in the Bibles I grew up with the infallible word of gawd was always printed in red...

 

[4est_4est_Gump]

Those who label us "Bozos" in a nutshell...

The next battle over President Obama’s job-killing regulations may take place on the Atlantic Coast, where fishermen, and the senators and congressmen who represent them, are voicing mounting frustration at the Obama administration’s “catch-share” rules for the fishing industry.

The Republican senator from Massachusetts, Scott Brown, on Saturday stood with fishermen in Gloucester and called on Mr. Obama to fire the administrator of the National Oceanic and Atmospheric Administration, Jane Lubchenco.

But the frustration at Ms. Lubchenco, who also serves as under secretary of commerce for oceans and atmosphere, extends well beyond Republican, Tea Party-backed senators or libertarians for whom the idea of a federally enforced “share” program sounds like some nightmare out of an Ayn Rand novel.

A surprising and growing number of Democratic elected officials are also expressing annoyance and outright opposition. Sen. Kerry, the Democrat of Massachusetts who was his party’s presidential nominee in 2004, said Friday, “Because of federal regulations limiting fishing in our waters, a lot of our fisherman have been put out of business or pushed the brink.” Also last week, he sent a stern letter to Ms. Lubchenco, warning her, “tensions between federal regulators and the fishing community have reached a boiling point beyond anything I’ve ever witnessed in my 26 years in the Senate.”

...

The story hasn’t yet hit The New York Times, Politico, or the Drudge Report. But when it does, it won’t be pretty. At the center of the storm is Ms. Lubchenco, whose official biography fits what to the Obama administration’s critics will seem like a familiar pattern. Like President Obama himself and like Mr. Obama’s initial economic adviser, Lawrence Summers, Ms. Lubchenco has an advanced degree from Harvard. Like Mr. Obama and Mr. Summers, Ms. Lubchenco has little private sector experience, but spent a lot of time teaching at a university—in her case, more than 20 years at Oregon State University. When President Obama nominated her to the NOAA job, she was vice chairman of the board of the Environmental Defense Fund, an environmental advocacy group that promotes catch shares, which are kind of like a cap-and-trade emissions scheme transferred to fishery management. When her appointment was announced, EDF’s president, Fred Krupp, praised her by saying, “her depth of understanding of climate change is unmatched.”

Her official biography also notes that she is a recipient of 14 honorary doctoral degrees and of one of the MacArthur Foundation’s “genius” awards.

...

Partly it is by displaying a kind of arrogance towards those not blessed with her genius. She reportedly minimized the job losses under catch-share by describing them as “marginal jobs where people are squeaking by.”

http://reason.com/archives/2011/10/24/obama-fishing-czar-divides-dem