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The Profound Junk Science of Climate

excalibur

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And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.

The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.

...

Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.

A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.

One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.

...


 
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And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.
The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.
...
Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.
A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.
One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.
...



And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.
The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.
...
Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.
A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.
One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.
...


The Unabomber: The Psychoses of a Theoretical Mathematician

Despite their GPAs, eco-nerds aren't really intelligent. Their escapist theories, based on the childish way they worshiped the professors who gave them those grades, are simplistically designed to be most attractive to those who have a hard time dealing with the complexities of anything real. They even create models of their fantasies. They are thrilled by all the scare stories about the catastrophes that will occur if they don't get their way, right away. Weakling misfits, they are driven by a desperate desire to be comic-book superheroes who save the world from those "evil practical people."
 

Crepitus

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And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.
The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.
...
Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.
A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.
One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.
...


So all the extra heat is just in your head?
 

ReinyDays

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And it has always been junk science and lies. It is all for power and money, that is all.

Horsefeathers ... there was honest 12-year-old-little-boy glee when these new fangled super fast computers came along ... once we hit megaflops, the die were cast ... why shouldn't we try to model fluid behavior? ... c'mon now, what does your own inner 12-year-old-little-boy say? ...

It's the adults that screwed everything up ...
 

Fort Fun Indiana

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And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.
The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.
...
Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.
A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.
One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.
...


Belongs in the conspiracy theory section, not the science section.
 

Stryder50

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So all the extra heat is just in your head?
That "extra heat" isn't that much and is cyclic, along with the "extra cold";

*Thing is, it is "climate change", and it's a rather cycling process and something largely out of human influence/control (unless we set off all those nuclear weapons that is). These charts should give some perspective. This first one showing on the scale of the past 2.4 billion years (just over half the age of our planet);

ice_ages1-300x117.gif



Here is the time scale from when humans appear, depending on source of science claims, that would be between 200-300,000 years ago.

ice_ages2.gif



Here is an even closer and smaller time scale, covering just the past @5,000 years;

Gtemps480.jpg



And just to give a hint of what Earth looked like about 15-16,000 years ago before the last major Ice Age melted;

63a683abbbd369283337ca2f5848e1e2.jpg
 

Fort Fun Indiana

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That "extra heat" isn't that much and is cyclic, along with the "extra cold";

*Thing is, it is "climate change", and it's a rather cycling process and something largely out of human influence/control (unless we set off all those nuclear weapons that is). These charts should give some perspective. This first one showing on the scale of the past 2.4 billion years (just over half the age of our planet);

ice_ages1-300x117.gif



Here is the time scale from when humans appear, depending on source of science claims, that would be between 200-300,000 years ago.

ice_ages2.gif



Here is an even closer and smaller time scale, covering just the past @5,000 years;

Gtemps480.jpg



And just to give a hint of what Earth looked like about 15-16,000 years ago before the last major Ice Age melted;

63a683abbbd369283337ca2f5848e1e2.jpg
Should be moved to Rubber Room
 

Stryder50

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That is where uneducated slobs who think they have outsmarted experts belong.
So-called "educated" and "experts" are the one's whom produced the data used to make those charts/graphs I presented.

Would seem your the sort whom thought politician Al Gore was "educated" and an "expert" on ACC and AGW.
 

Fort Fun Indiana

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So-called "educated" and "experts" are the one's whom produced the data used to make those charts/graphs I presented.

Would seem your the sort whom thought politician Al Gore was "educated" and an "expert" on ACC and AGW.
You mean, the ones you lied about. Also, your implication that they labor under the ignorance of their own life's work makes you look like lobotomized moron.
 

Crepitus

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That "extra heat" isn't that much and is cyclic, along with the "extra cold";

*Thing is, it is "climate change", and it's a rather cycling process and something largely out of human influence/control (unless we set off all those nuclear weapons that is). These charts should give some perspective. This first one showing on the scale of the past 2.4 billion years (just over half the age of our planet);

ice_ages1-300x117.gif



Here is the time scale from when humans appear, depending on source of science claims, that would be between 200-300,000 years ago.

ice_ages2.gif



Here is an even closer and smaller time scale, covering just the past @5,000 years;

Gtemps480.jpg



And just to give a hint of what Earth looked like about 15-16,000 years ago before the last major Ice Age melted;

63a683abbbd369283337ca2f5848e1e2.jpg
Lol @ "extra cold".

No one with any actual understanding of climate would say anything like that.
 

ding

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Lol @ "extra cold".

No one with any actual understanding of climate would say anything like that.
Pretty sure he was being facetious. He knows more about the earth's climate than you do. He's actually studied the subject.
 

ding

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You mean, the ones you lied about. Also, your implication that they labor under the ignorance of their own life's work makes you look like lobotomized moron.
Given that previous interglacial cycles were 2C warmer than today with 120 ppm less atmospheric CO2, their ignorance of actual climate data is fair game.
 

westwall

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Horsefeathers ... there was honest 12-year-old-little-boy glee when these new fangled super fast computers came along ... once we hit megaflops, the die were cast ... why shouldn't we try to model fluid behavior? ... c'mon now, what does your own inner 12-year-old-little-boy say? ...

It's the adults that screwed everything up ...



No, the models themselves simply aren't that good.

Good models, like those the F1 teams use, cost millions of dollars, and they have a success rate of less than 1 tenth, of one percent.
 

surada

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And it has always been junk science and lies. It is all for power and money, that is all.


Climate change prophecy hangs its hat on computer climate models. The models have gigantic problems. According to Kevin Trenberth, once in charge of modeling at the National Center for Atmospheric Research, “[None of the] models correspond even remotely to the current observed climate [of the Earth].” The models can’t properly model the Earth’s climate, but we are supposed to believe that, if carbon dioxide has a certain effect on the imaginary Earths of the many models it will have the same effect on the real earth.

The climate models are an exemplary representation of confirmation bias, the psychological tendency to suspend one’s critical facilities in favor of welcoming what one expects or desires. Climate scientists can manipulate numerous adjustable parameters in the models that can be changed to tune a model to give a “good” result. Technically, a good result would be that the climate model output can match past climate history. But that good result competes with another kind of good result. That other good result is a prediction of a climate catastrophe. That sort of “good” result has elevated the social and financial status of climate science into the stratosphere.

...

Testing a model against past history and assuming that it will then predict the future is a methodology that invites failure. The failure starts when the modeler adds more adjustable parameters to enhance the model. At some point, one should ask if we are fitting a model or doing simple curve fitting. If the model has degenerated into curve fitting, it very likely won’t have serious predictive capability.

A strong indicator that climate models are well into the curve fitting regime is the use of ensembles of models. The International Panel on Climate Change (IPCC) averages together numerous models (an ensemble), in order to make a projection of the future. Asked why they do this rather than try to pick the best model, they say that the ensemble method works better. Why would averaging worse models with the best model make the average better than the best? This is contrary to common sense. But according to the mathematics of curve fitting, if different methods of fitting the same (multidimensional) data are used, and each method is independent but imperfect, averaging together the fits will indeed give a better result. It works better because there is a mathematical artifact coming from having too many adjustable parameters that allow the model to fit nearly anything.

One may not be surprised that the various models disagree dramatically, one with another, about the Earth’s climate, including how big the supposed global warming catastrophe will be. But no model, except perhaps one from Russia, denies the future catastrophe.

...



Yeah.. They have 12 inches of snow and 100 mph winds in Hawaii.
 

Stryder50

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Belongs in the conspiracy theory section, not the science section.
Says the chap whom when we click on his username and go to his "Profile" page provides no useful information on his credentials and validity to be other than another "username" with no credibility or knowledge on the subject.

Hence why should we consider you anything other than;

iu
 

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