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Posted (edited)

What does this list have to do with this thread?

 

All pollutants identified as not cool that were vigorously defended by business interests, segments of the public, and experts who collectively paid off the government and contributed to dissuade the science that showed the problems with their use. They were all banned or curtailed - and in spite of the warnings and wailings that society and business simply could not survive without them - both society and business turned out to better without them.

 

@wacka - Not a liberal - worse - I am an engineer

Edited by baskin
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Posted

 

All pollutants identified as not cool that were vigorously defended by business interests, segments of the public, and experts who collectively paid off the government and contributed to dissuade the science that showed the problems with their use. They were all banned or curtailed - and in spite of the warnings and wailings that society and business simply could not survive without them - both society and business turned out to better without them.

 

@wacka - Not a liberal - worse - I am an engineer

 

 

DDT ban has led to dirt bags spreading bed bugs.

 

CO2 ban would lead to all trees dying.

Posted

Sorry, you are only permitted to cite "cause and effect" when you are complaining about "Climate Change",

 

 

not when you are evaluating their solutions........................

 

 

 

 

.

Posted

Sorry, you are only permitted to cite "cause and effect" when you are complaining about "Climate Change",

 

 

not when you are evaluating their solutions........................

 

 

 

 

.

No one in the climate change argument cites "cause and effect." They cite "correlation," and mistake it for cause and effect.

Posted

No one in the climate change argument cites "cause and effect." They cite "correlation," and mistake it for cause and effect.

 

 

I stand corrected.

 

 

.

Posted

Defense of DDT is laughable.

 

What you see as correlation most see proven as cause and effect.

 

If increased CO2 from 220 to 400 ppm in a controlled environment causes raised temperatures in a controlled environment under UV (proven) - one really would almost have to disprove that the same isn't happening in atmosphere...

Posted

Defense of DDT is laughable.

And malaria's a good thing...

 

 

What you see as correlation most see proven as cause and effect.

 

No, most see it as correlation. Have you even read any research on it? There's not a credible researcher on the planet that calls it anything but correlation.

 

 

If increased CO2 from 220 to 400 ppm in a controlled environment causes raised temperatures in a controlled environment under UV (proven) - one really would almost have to disprove that the same isn't happening in atmosphere...

 

No, that's not proven. In no small part because it's not even correct - you don't even know how the greenhouse effect works. :wallbash: You are either ignorant on this topic, or ignorant and stupid. What the hell kind of an engineer are you? A sanitation engineer?

Posted

Forget it Tom................the two aquarium experiment equation has spoken.

 

$_35.JPG

 

 

We rich countries simply must start sending our wealth to poorer countries.

 

The health of Mother earth hangs in the balance.

Posted

Millions die of malara in Africa because of ban on ddt but there only Africans who cares? Where were the Sharptons of the world on this one? No where because it was one liberal broad that pushed for the ban so it's all good.

Great article on it here

http://www.discoverthenetworks.org/viewSubCategory.asp?id=1259

 

It's unfair to blame the ban solely on Rachel Carson and Silent Spring. It was certainly a contributing factor, at the very least in creating the modern environmental movement with the modern tactics of sensationalism and fear-mongering. But Carson herself wasn't for banning DDT as much as she was for responsible use of it and against the profligate overuse.

 

Plus, malaria control collapsed well before the ban on DDT, when Congress idiotically defunded the program.

Posted (edited)

Let's get this out of the way right away: I'm a idiot.

 

K...

 

Now, how does technology play a role in all this? Say data collection points, calibration of instruments, etc... Are they "better" now, more accurate than say in 1850. I would think they are, but then again the good tech back then could have pretty damn close? Weren't the British only about 12 feet off when they shot the level run from the sea to Mt. Everest? That's using levels, rods and steel chains, through jungles, mountains, and all kinds of temperature swings. That''s a pretty long level run using steel chains and temperature springs. On top of it all, they didn't even get to the peak until Hillary reached it.

 

What's the adjustment here with tech and more & more data being collected every year. I was surprised to find out that Great Lakes ice coverage (in the modern sense) only traces back to 1973. Before that, just flyovers. Even after 1973 to the satellite age... How accurate were the pilots vs. satellites?

Edited by ExiledInIllinois
Posted

Let's get this out of the way right away: I'm a idiot.

 

K...

 

Now, how does technology play a role in all this? Say data collection points, calibration of instruments, etc... Are they "better" now, more accurate than say in 1850. I would think they are, but then again the good tech back then could have pretty damn close? Weren't the British only about 12 feet off when they shot the level run from the sea to Mt. Everest? That's using levels, rods and steel chains, through jungles, mountains, and all kinds of temperature swings. That''s a pretty long level run using steel chains and temperature springs. On top of it all, they didn't even get to the peak until Hillary reached it.

 

What's the adjustment here with tech and more & more data being collected every year. I was surprised to find out that Great Lakes ice coverage (in the modern sense) only traces back to 1973. Before that, just flyovers. Even after 1973 to the satellite age... How accurate were the pilots vs. satellites?

There's a bunch of different factors involved in measurement and there's some "fudge factor" involved especially when "urban heating" is brought into play.

Posted

There's a bunch of different factors involved in measurement and there's some "fudge factor" involved especially when "urban heating" is brought into play.

 

There's always "fudge factors" involved in sciences. That's because there's always some noise in the data, and you have to somehow account for the noise to experimentally verify theory. It's called "massaging the data" (which is a term I always hated). It's also why there's a 95% confidence interval, because it's nearly impossible to get a 100% match between theory and experiment. It's also why repeatability is a big deal in science - repeated experiments "average out" noise in the data. And why skepticism is a important in science - healthy and informed (as opposed to blind) skepticism leads to further tests of theory and strengthens or refines them (or sometimes, overturns them - Lee and Yang won a well-deserved Nobel Prize in the '50s for demonstrating that the universe itself can tell left from right.) And that goes doubly for a science largely based on computer modelling, which by definition is of limited accuracy (a model with perfect accuracy isn't a model, it's reality.)

 

But in climate change, you can't question how they account for noise (Noise? What noise? CO2 measurements are exact.) Confidence interval and repeatability is replaced by consensus. And God forbid you should express any skepticism, because the science is "settled."

Posted

 

There's always "fudge factors" involved in sciences. That's because there's always some noise in the data, and you have to somehow account for the noise to experimentally verify theory. It's called "massaging the data" (which is a term I always hated). It's also why there's a 95% confidence interval, because it's nearly impossible to get a 100% match between theory and experiment. It's also why repeatability is a big deal in science - repeated experiments "average out" noise in the data. And why skepticism is a important in science - healthy and informed (as opposed to blind) skepticism leads to further tests of theory and strengthens or refines them (or sometimes, overturns them - Lee and Yang won a well-deserved Nobel Prize in the '50s for demonstrating that the universe itself can tell left from right.) And that goes doubly for a science largely based on computer modelling, which by definition is of limited accuracy (a model with perfect accuracy isn't a model, it's reality.)

 

But in climate change, you can't question how they account for noise (Noise? What noise? CO2 measurements are exact.) Confidence interval and repeatability is replaced by consensus. And God forbid you should express any skepticism, because the science is "settled."

THANK YOU... I knew you could explain it, God forbid my scattered idiot azz could. Sorry for the lead in.

 

Eagerly waiting relpy from the "Church of the Science is Settled" (CSS) side.

Posted

THANK YOU... I knew you could explain it, God forbid my scattered idiot azz could. Sorry for the lead in.

 

Eagerly waiting relpy from the "Church of the Science is Settled" (CSS) side.

 

For some of the measurements, too, they have standard methods for "accounting for" measurement era across different eras. You see it a lot with temperature readings over centuries-long time frames, where they apply some standard factor to adjust historical temperatures (because there wasn't complete geographical coverage, or instrumentation was less accurate, or some such). Part of the problem there is that most of the studies use the same method. It's understandable, because you want to use a published method that's repeatable and has been demonstrated. But a side effect is that, if the model has any inaccuracies, then ALL the studies based on it reflect that inaccuracy. It kind-of throws a great big monkey wrench into the idea of "scientific consensus" - a consensus based on error is still wrong. (Ice cores are a great example - there's a consensus that they're accurate, based on the standard method of interpreting them. But that standard method doesn't account for differential diffusion of gasses in ice. And that has a potentially significant impact - any measurable diffusion can significantly impact the accuracy of ice core data, rendering any consensus somewhere between "moot" and "ridiculous." No one's studied that yet, by the way.)

 

For measurables like Great Lakes ice coverage...sometimes they extrapolate, from current data and historical anecdote. Usually, they just ignore it, and pretend a 40 year baseline is relevant.

 

An easy way to recognize bad science is artificial precision. You see a statement like "Atmospheric CO2 levels have been increasing by 1.55ppm per year for the past half-century," and you ask yourself "Why not 1.54? Or 1.56?" Or "the upper safety limit for atmospheric CO2 is 350ppm" and ask "Why not 349? Or 351?" That's usually an easy way to distinguish between the real science and the bull **** marketing - artificial precision is sales, not science.

 

That first example, by the way, is taken from NASA. The second is taken from the CO2 Now web site, which has an even worse example on their home page: the preliminary monthly average for CO2 for December of 2014 was 398.78ppm as of January 6, 2015. Five significant digits. Really? Not 398.68? Not 398.88? And a December average as of the first week of January? What the hell does that number even mean, a monthly average to five significant digits?

Posted

 

For some of the measurements, too, they have standard methods for "accounting for" measurement era across different eras. You see it a lot with temperature readings over centuries-long time frames, where they apply some standard factor to adjust historical temperatures (because there wasn't complete geographical coverage, or instrumentation was less accurate, or some such). Part of the problem there is that most of the studies use the same method. It's understandable, because you want to use a published method that's repeatable and has been demonstrated. But a side effect is that, if the model has any inaccuracies, then ALL the studies based on it reflect that inaccuracy. It kind-of throws a great big monkey wrench into the idea of "scientific consensus" - a consensus based on error is still wrong. (Ice cores are a great example - there's a consensus that they're accurate, based on the standard method of interpreting them. But that standard method doesn't account for differential diffusion of gasses in ice. And that has a potentially significant impact - any measurable diffusion can significantly impact the accuracy of ice core data, rendering any consensus somewhere between "moot" and "ridiculous." No one's studied that yet, by the way.)

 

For measurables like Great Lakes ice coverage...sometimes they extrapolate, from current data and historical anecdote. Usually, they just ignore it, and pretend a 40 year baseline is relevant.

 

An easy way to recognize bad science is artificial precision. You see a statement like "Atmospheric CO2 levels have been increasing by 1.55ppm per year for the past half-century," and you ask yourself "Why not 1.54? Or 1.56?" Or "the upper safety limit for atmospheric CO2 is 350ppm" and ask "Why not 349? Or 351?" That's usually an easy way to distinguish between the real science and the bull **** marketing - artificial precision is sales, not science.

 

That first example, by the way, is taken from NASA. The second is taken from the CO2 Now web site, which has an even worse example on their home page: the preliminary monthly average for CO2 for December of 2014 was 398.78ppm as of January 6, 2015. Five significant digits. Really? Not 398.68? Not 398.88? And a December average as of the first week of January? What the hell does that number even mean, a monthly average to five significant digits?

This place is gr8!

 

Gr8 post... Now, can you get me to vacate my final determination on the red-light cam bogus crap? Besides being extorted for 200 bucks and my license/credit not hanging in the balance. J/K... I will be fine. ;-)

 

Oh... You absolutely don't want to know how non-discretionary water usage accounting is handled (@ work). It's been "wrong" for so long... It's "right." Oh my!

 

To quote Thomas Dolby: "Science!"

Posted (edited)

 

For some of the measurements, too, they have standard methods for "accounting for" measurement era across different eras. You see it a lot with temperature readings over centuries-long time frames, where they apply some standard factor to adjust historical temperatures (because there wasn't complete geographical coverage, or instrumentation was less accurate, or some such). Part of the problem there is that most of the studies use the same method. It's understandable, because you want to use a published method that's repeatable and has been demonstrated. But a side effect is that, if the model has any inaccuracies, then ALL the studies based on it reflect that inaccuracy. It kind-of throws a great big monkey wrench into the idea of "scientific consensus" - a consensus based on error is still wrong. (Ice cores are a great example - there's a consensus that they're accurate, based on the standard method of interpreting them. But that standard method doesn't account for differential diffusion of gasses in ice. And that has a potentially significant impact - any measurable diffusion can significantly impact the accuracy of ice core data, rendering any consensus somewhere between "moot" and "ridiculous." No one's studied that yet, by the way.)

 

For measurables like Great Lakes ice coverage...sometimes they extrapolate, from current data and historical anecdote. Usually, they just ignore it, and pretend a 40 year baseline is relevant.

 

An easy way to recognize bad science is artificial precision. You see a statement like "Atmospheric CO2 levels have been increasing by 1.55ppm per year for the past half-century," and you ask yourself "Why not 1.54? Or 1.56?" Or "the upper safety limit for atmospheric CO2 is 350ppm" and ask "Why not 349? Or 351?" That's usually an easy way to distinguish between the real science and the bull **** marketing - artificial precision is sales, not science.

 

That first example, by the way, is taken from NASA. The second is taken from the CO2 Now web site, which has an even worse example on their home page: the preliminary monthly average for CO2 for December of 2014 was 398.78ppm as of January 6, 2015. Five significant digits. Really? Not 398.68? Not 398.88? And a December average as of the first week of January? What the hell does that number even mean, a monthly average to five significant digits?

003.50

 

Or, I suppose it's actually 3.5234...because I said so. It's my number that I made up, try to disprove it!

 

Anyway, good posts. As I have been saying, things are far from settled, and these people have a lot more work to do, and a lot less talking to do, if they truly want to move this forward scientifically. But....they don't want to do work. Work gets them nothing more than a $40k grant. Talking gets them on TV, gets them book deals, etc.

 

I have been saying all along, I highly doubt finishing the work was ever the true goal. This was never about science, or hard work. This was about getting just enough evidence to create (now extremely tenous) support for the AGW theory, taking that to the leftist politicians, and them turning on their big, propaganda-->$-->power-->propaganda, perpetual, BS machines. These "scientists" saw 1st class for the first time in their lives, because some of that $ got kicked back to them.

 

Now? All of that $ is gone. Sure, you get the odd clown and his $100 million in campaign funds to Ds who towed the watermelon line(green on the outside, red in the inside). The problem? That $100 million was pissed away, as all the D Senators it was intended to help are now out of office. The scientists saw none of that $100 million. The big time is over for these people.

Edited by OCinBuffalo
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