USA Today: Could we be wrong about global warming?

[mobes23]

I'm not refuting anything. That's the point.

You've been refuting the majority of atmospheric/climate scientists who believe there is a correlation between CO2 and global warming. Changed your mind? Or, at the very least, are you willing to admit more data is needed?

 

[PapaG]

You've been refuting the majority of atmospheric/climate scientists who believe there is a correlation between CO2 and global warming. Changed your mind? Or, at the very least, are you willing to admit more data is needed?

Pardon my vulgarity, but the bolded statement is bullshit. I presented other people's evidence, as did Denny Crane, that suggest that there may not be a correlation between man's emissions of CO2 and rising temperatures.

You continue to incorrectly present my position in post after post. Why is that? As for more data being needed, that is the point I have been making. Nice to see you've finally conceded (and even joined) my position.

 

[mobes23]

3. Impact of CO2 on global warming. Glad you brought this up. I'm glad to concede (and I actually already have in this thread) that the impact of CO2 on global warming might not be as large as thought in the past. My point in this thread is that the plot you're hanging your hat on is not nearly strong enough to support it. More data is needed. Is it interesting? Sure, I'm glad to give you that. Do we adjust policy because of it? Absolutely not. Get more data to support it, then maybe the policy goes a different way.

Lol. I beat you to the punch awhile ago on this, PapaG.

 

[PapaG]

Lol. I beat you to the punch awhile ago on this, PapaG.

Um, my entire purpose in this thread has been to introduce the fact that there is data that exists that may not make anthropogenic global warming a reality.

You've been too busy insulting me to actually read the posts, I guess.

 

[Denny Crane]

I'm afraid not. I realize the "science believes in aliens as a religious belief" is your go-to tenet about science, but it's nonsense. "Science" has no position on whether there's intelligent life out there and certainly no model regarding it (Drake's equation is merely a toy to play with, not a model). There are people who search for intelligent life (looking for such a thing is certainly a scientific endeavour) and there are differing opinions on the likelihoods of ever finding intelligent life (or even non-intelligent life). But there's definitely no conclusion about it, because nothing has been observed yet.

This has nothing at all to do with the model of man-made global warming, which is based on actual observations and data. The preponderance of which, most scientists who study the issue believe, suggests man has effect on global temperatures.

Your "decision matrix" is equivalent to Drake's equation. There's nothing scientific about it, just a "fill in your chosen probabilities and results to reach whatever conclusion you want."

There's no model regarding global warming, either. Just really expensive toys to play around with. GIGO. Garbage In, Garbage Out. The ultimate truism about computer models. Just as with Drake's equation, the modellers are plugging in numbers throughout their equations that they pull out of thin air.

I'll give you a small lesson in models and perhaps you'll see why I say these things.

Let's model baseball.

Alex Rodriguez is batting .254. This (in theory) means he'll get a hit 254 out of 1000 times. We have some probability and can make a very simple model. Pick a random number between 1 and 1000; if it's less than or equal to 254 he gets a hit, otherwise an out. Sure enough, we can run simulations 1M times of 1000 at bats and he'll come out at .254.

How realistic is the model? Not very. If he were batting against Jarrod Washburn 1000 times, he certainly wouldn't hit .254. Washburn has a BAA of .223. How about we average them together? We come up with .2385. We can't really do the 1000 thing anymore or we lose the 5 at the end of that fraction. Round up or down and you introduce error. So pick numbers between 1 and 10000 and if <= 2385 it's a hit.

But he doesn't face Washburn every at bat. It's really some sort of aggregate of all the pitchers, some more than others (he may face Washburn only one at bat in a whole season, but he'll face other pitchers 4 times in one game). Washburn averages 6.65 IP/game, but some games he pitches 9 and others he gets bombed out in the 1st. What we can do is figure the Yankees play the Tigers 10 times in a season, and maybe use the Tigers' team aggregate BAA for 16.2 of ARod's ABs.

The model gets more and more complex when you figure out whether a hit is a 2B, 3B, or HR. Does his HR chance go up with men on base? Factor that in. Does Detroit's staff give up many homers? Factor that in.

Now the model isn't really a very good one. It actually is important that ARod does face Washburn in real life. The model isn't modeling that, right? What happens if a fly lands on ARod's nose right as the pitch is coming in for called strike 3? Or if he had trouble sleeping the night before? Or if the sun is in his eyes for a particular AB? Shit happens.

Now I've made certain assumptions and decisions in making this simplistic model. And baseball is far more simplistic a thing to model than the Earth's climate and temperature. My model may come up with some realistic feeling results, but I assure you those are the results I intend for it to come up with. I favored pitcher and batter equally by averaging BA and BAA. See?

At least with my model, I can come really close to modelling the past. ARod in the end will hit .254, no matter how I have to tweak the formulae. Will it predict the future? ARod could get hit by a bus tomorrow. How do I model that? LOL

 

[mobes23]

Um, my entire purpose in this thread has been to introduce the fact that there is data that exists that may not make anthropogenic global warming a reality.

You've been to busy insulting me to actually read the posts, I guess.

Lol. Whatever you say. I'll just take it as a victory that you no longer believe without question that there is no correlation between CO2 and global warming. Huzzah.

 

[PapaG]

Lol. Whatever you say. I'll just take it as a victory that you no longer believe without question that there is no correlation between CO2 and global warming. Huzzah.

When did I say this? A "victory"? Sheesh. Oh well, at least you didn't insult me in the above post. I'll take that as a "victory".

 

[Minstrel]

There's no model regarding global warming, either. Just really expensive toys to play around with. GIGO. Garbage In, Garbage Out. The ultimate truism about computer models. Just as with Drake's equation, the modellers are plugging in numbers throughout their equations that they pull out of thin air.

You're certainly entitled to your opinion that it's all garbage, but you are essentially a duffer. You don't know anything about the science except what you Googled. Learning by Google is a nice way to get a general, superficial overview but it hardly makes you a credible voice of dissent about a scientific field. You assert that climate science is garbage but back it up with no real knowledge. That's not compelling, but it also cannot be refuted. I agree that you think climate science is garbage.

Your model of baseball is essentially equivalent to your understanding of climate science. There is a field of baseball statistical analysis called "sabermetrics" which does much more rigorous modeling, taking into account the variable values of getting on base versus hitting for power, the level of competition faced, etc. Your "model" of baseball hitting is to sabermetrics what your criticisms of climate science are to actual climate science...superficial, using only a layman's ideas, lacking the sophisticated tools of the field.

As to what you had hoped to show with your baseball model, yes, bad models are bad. But you are merely asserting climate models are bad...you don't actually have the expertise to know and demostrate that they are bad.

 

[Denny Crane]

You're certainly entitled to your opinion that it's all garbage, but you are essentially a duffer. You don't know anything about the science except what you Googled. Learning by Google is a nice way to get a general, superficial overview but it hardly makes you a credible voice of dissent about a scientific field. You assert that climate science is garbage but back it up with no real knowledge. That's not compelling, but it also cannot be refuted. I agree that you think climate science is garbage.

Your model of baseball is essentially equivalent to your understanding of climate science. There is a field of baseball statistical analysis called "sabermetrics" which does much more rigorous modeling, taking into account the variable values of getting on base versus hitting for power, the level of competition faced, etc. Your "model" of baseball hitting is to sabermetrics what your criticisms of climate science are to actual climate science...superficial, using only a layman's ideas, lacking the sophisticated tools of the field.

Dude, I kept my model simple, but I did cover sabremetrics aspects:

Does his HR chance go up with men on base? Factor that in. Does Detroit's staff give up many homers? Factor that in.

No matter how rigorous the modelling, you can't get it right. If you could, someone with a great baseball model would be winning sportsbook bets consistently and forever.

It flies in the face of reality and common sense.

If you want to play the "you're a duffer" kind of game, so are you. You still are asking me to accept on Faith (a religious thing) some Truth where there is significant disagreement among the experts.

And I'm not a duffer at simulations and modelling.

 

[PapaG]

You're certainly entitled to your opinion that it's all garbage, but you are essentially a duffer. You don't know anything about the science except what you Googled. Learning by Google is a nice way to get a general, superficial overview but it hardly makes you a credible voice of dissent about a scientific field. You assert that climate science is garbage but back it up with no real knowledge. That's not compelling, but it also cannot be refuted. I agree that you think climate science is garbage.

Your model of baseball is essentially equivalent to your understanding of climate science. There is a field of baseball statistical analysis called "sabermetrics" which does much more rigorous modeling, taking into account the variable values of getting on base versus hitting for power, the level of competition faced, etc. Your "model" of baseball hitting is to sabermetrics what your criticisms of climate science are to actual climate science...superficial, using only a layman's ideas, lacking the sophisticated tools of the field.

As to what you had hoped to show with you baseball model, yes, bad models are bad. But you are merely asserting climate models are bad...you don't actually have the expertise to show that they are bad.

Performance for a given player in a given season is predicted based on sabermetric modeling. How often does this modeling yield an exact result?

Let's take a look at the sabermetric 2009 projections for the Red Sox.

http://www.baseballprojection.com/BOS2009.htm

Compare these results to what the end of the season, or "observation", yields.

Again, yet another poster insulting a skeptic by saying they only know about science from "Googling" it. You pull out the sabermetric card, yet looking at predictions for one team, and clearly very few players will end even close to what is predicted for them, and certainly not at a p-value of less than or equal to 5 across the data set. Weak.

 

[PapaG]

As to what you had hoped to show with your baseball model, yes, bad models are bad. But you are merely asserting climate models are bad...you don't actually have the expertise to know and demostrate that they are bad.

The burden of proof is on the modeler to present their model as accurate. It's certainly not on the person questioning the validity of a model that predicts the future.

 

[Minstrel]

Dude, I kept my model simple, but I did cover sabremetrics aspects

Not really. The point is, you made a purposely bad model to show that bad models are bad. Well done!

No matter how rigorous the modelling, you can't get it right. If you could, someone with a great baseball model would be winning sportsbook bets consistently and forever.

Absolutely. No one is claiming you can get models exactly right. In fact, in a post just a short while ago, I said precisely that:

The "molecular make-up of water" isn't a model. It's a stand-alone empirical fact. All models have some level of uncertainty or conflicting data, because all scientific models are inherently limited by human knowledge, which is not all-encompassing or even close.

The fact there are questions and some conflicting data in the man-made global warming model doesn't mean that it's not solid science. There is always the possibility that it is wrong, and any credible scientist would agree to that...that possibility exists with every single scientific model. What the vast majority of informed scientists say is that the bulk of evidence suggests that man-made effects are amplifying the natural temperature cycle. How much and what the ultimate effects will be aren't conclusively known and the scientific community (Al Gore isn't part of it) doesn't claim that it is known.

If you want to play the "you're a duffer" kind of game, so are you.

Yes, I said exactly that as well in an earlier post. We are both duffers. You know who aren't? Climate scientists, and they overwhelmingly believe that man is affecting global temperatures.

You still are asking me to accept on Faith (a religious thing) some Truth where there is significant disagreement among the experts.

I'm saying that, since you don't know much about the field, you aren't a credible skeptic. I think it's great that some actual climate scientists are skeptics and add their voices to the field. With that, the consensus in the field is what it is. It's not a Truth (science has never been about Truth, it's about the best models our knowledge allows for), it's simply the best information we have from the people who know the issue the best.

And I'm not a duffer at simulations and modelling.

You're a duffer at climate science.

 

[Minstrel]

Performance for a given player in a given season is predicted based on sabermetric modeling. How often does this modeling yield an exact result?

Who cares? Sabermetrics isn't "science" and even scientific models (all of them) have some level of uncertainty, as I pointed out to you in a post earlier this afternoon. I was simply pointing out that there are better and worse models...creating a purposely silly model to show that bad models are useless isn't very insightful.

Again, yet another poster insulting a skeptic by saying they only know about science from "Googling" it.

It's not an insult, it's a fact. You have no education in climate science, all you know is what you Google. As I said earlier, it's fine for a superficial overview, but it hardly takes the place of an actual education and work in the field.

 

[Minstrel]

The burden of proof is on the modeler to present their model as accurate. It's certainly not on the person questioning the validity of a model that predicts the future.

Yes, the burden of proof is on the modeler and the models have been demonstrated to be the best information we have on the subject to the satisfaction of the vast majority in the field.

 

[PapaG]

Who cares? Sabermetrics isn't "science" and even scientific models (all of them) have some level of uncertainty, as I pointed out to you in a post earlier this afternoon. I was simply pointing out that there are better and worse models...creating a purposely silly model to show that bad models are useless isn't very insightful.

So, a model that has to literally encompass the entire globe, and all of its variables, is accurate?

It's not an insult, it's a fact. You have no education in climate science, all you know is what you Google. As I said earlier, it's fine for a superficial overview, but it hardly takes the place of an actual education and work in the field.

Which is why I presented data compiled by people who do have an education in climate science.

We have posters in this thread smearing people who actually work in the field. What is your point, other than to insult one group of posters, yet not insult another group of posters?

Ad hominem attacks are a sure sign of being flustered. I don't need an education in climate science to see that some data doesn't line up with what is being presented to the general public as a fact, do I?

 

[PapaG]

Yes, the burden of proof is on the modeler and the models have been demonstrated to be the best information we have on the subject to the satisfaction of the vast majority in the field.

So, "models" drive climate "science", and observational data is ridiculed. What a joke. Tell me how this isn't politicized.

 

[PapaG]

It's not a Truth (science has never been about Truth, it's about the best models our knowledge allows for), it's simply the best information we have from the people who know the issue the best.

What part of your education makes you an authority to speak for what science is about?

 

[Denny Crane]

You're a duffer at climate science.

But climate science uses models as a large part of their argument that there is man made global warming.

FWIW, I worked for the USGS modelling ground water flow for 3 years. I took graduate courses in computer modelling (and did an NBA simulation for an A+ in one of those). What I really learned is models are a load of crap.

There's a thing called Chaos that breaks your models every time except for the simplest of things (baseball isn't so simple). That's why I also pointed out why they're crap - ARod could get hit by a bus. He could go on a hot streak and hit .500 the rest of the season, and no model would predict that. The govt. budget is a model, but they always seem to go over (Chaos strikes again). The Fed uses a model to model the economy and doesn't get it right - they're always reacting to why their model broke down and trying for "soft landings."

The model I roughly started for baseball could be refined and refined and refined. I tried to illustrate that by adding refinements (like accounting for the pitching). Every refinement costs more computing power. You might do that fist 1000 AB simulation in .1 seconds on a modern desktop. Doing the average of BA and BAA 10000 times might take 3 seconds. The more refinements, the closer you are to needing a super computer to run your model, which is where some of the more sophisticated models are at these days.

But there isn't enough super computer to model something with convincing results. To truly model baseball, you would need to model the weather, and for every microsecond of each at bat. You'd have to model the dust that might blow into the eye of the batter in a small gust of wind. You'd have to model the bacteria on that steak ARod had for dinner the night before (maybe he got a belly ache affecting his performance).

You seem to think you can't learn anything from Google.

Screw that.

http://en.wikipedia.org/wiki/Climate_model

I don't google to learn what I need to know for some message board debate. I google to provide support for something I am speaking from authority on.

Oddly, if you read the above linked page, they sound an awful lot like I do (about the baseball model).

The zero-dimensional model above, using the solar constant and given average earth temperature, determines the effective earth emissivity of long wave radiation emitted to space. This can be refined

The zero-dimensional model may be expanded

 

[PapaG]

(science has never been about Truth, it's about the best models our knowledge allows for)

I had to pull this out to digest it again. Where did you learn this information? It makes no sense.

 

[PapaG]

But climate science uses models as a large part of their argument that there is man made global warming.

FWIW, I worked for the USGS modelling ground water flow for 3 years. I took graduate courses in computer modelling (and did an NBA simulation for an A+ in one of those). What I really learned is models are a load of crap.

There's a thing called Chaos that breaks your models every time except for the simplest of things (baseball isn't so simple). That's why I also pointed out why they're crap - ARod could get hit by a bus. He could go on a hot streak and hit .500 the rest of the season, and no model would predict that. The govt. budget is a model, but they always seem to go over (Chaos strikes again). The Fed uses a model to model the economy and doesn't get it right - they're always reacting to why their model broke down and trying for "soft landings."

The model I roughly started for baseball could be refined and refined and refined. I tried to illustrate that by adding refinements (like accounting for the pitching). Every refinement costs more computing power. You might do that fist 1000 AB simulation in .1 seconds on a modern desktop. Doing the average of BA and BAA 10000 times might take 3 seconds. The more refinements, the closer you are to needing a super computer to run your model, which is where some of the more sophisticated models are at these days.

But there isn't enough super computer to model something with convincing results. To truly model baseball, you would need to model the weather, and for every microsecond of each at bat. You'd have to model the dust that might blow into the eye of the batter in a small gust of wind. You'd have to model the bacteria on that steak ARod had for dinner the night before (maybe he got a belly ache affecting his performance).

You seem to think you can't learn anything from Google.

Screw that.

http://en.wikipedia.org/wiki/Climate_model

I don't google to learn what I need to know for some message board debate. I google to provide support for something I am speaking from authority on.

Oddly, if you read the above linked page, they sound an awful lot like I do (about the baseball model).

In summary, the more variables, the less exact the model. Taking the entire globe as a model? Lots of variables, which is why climate models are continuously adjusted.

 

[Minstrel]

So, a model that has to literally encompass the entire globe, and all of its variables, is accurate?

Accurate enough to pass muster among peer review. Not perfect, obviously.

Which is why I presented data compiled by people who do have an education in climate science.

You don't just present it. You make assertions, like "There is no warming trend over the past decade" (which even the data you present contradicts). The data and observations from those who are actual climate scientists have been presented within the field, and the near-consensus that man is affecting the temperature has taken into account those objections.

There's certainly room to chat about science whether one is qualified or not. It's when people who don't know much about a field start claiming that things in that field are hoaxes, garbage and scams that I think those people are going off the rails.

So, "models" drive climate "science", and observational data is ridiculed. What a joke. Tell me how this isn't politicized.

Scientific models are based on observational data, so I really don't understand what your point is here.

What part of your education makes you an authority to speak for what science is about?

I guess my bachelors and masters degrees in cognitive science, over the course of which I took many of my classes in hard sciences (physics and neuroscience largely). In addition, I've studied various scientific fields on my own simply out of interest. I'm not an "authority," but I think I have a pretty solid understanding of what science is about.

 

[Denny Crane]

In summary, the more variables, the less exact the model. Taking the entire globe as a model? Lots of variables, which is why climate models are continuously adjusted.

Mostly true. It's more true that you cannot refine your model enough, no matter how much time you spend on it (for anything reasonably complicated). There's a lot of room for oversights (oops, I forget to account for X) and near impossible to account for Chaos (I call them chance cards).

There's also the issue of error in the data. If I use .244 instead of .254 for ARod, it sure would spoil the whole simulation for every player and every result.

 

[Minstrel]

But climate science uses models as a large part of their argument that there is man made global warming.

FWIW, I worked for the USGS modelling ground water flow for 3 years. I took graduate courses in computer modelling (and did an NBA simulation for an A+ in one of those). What I really learned is models are a load of crap.

There's a thing called Chaos that breaks your models every time except for the simplest of things (baseball isn't so simple). That's why I also pointed out why they're crap - ARod could get hit by a bus. He could go on a hot streak and hit .500 the rest of the season, and no model would predict that. The govt. budget is a model, but they always seem to go over (Chaos strikes again). The Fed uses a model to model the economy and doesn't get it right - they're always reacting to why their model broke down and trying for "soft landings."

The model I roughly started for baseball could be refined and refined and refined. I tried to illustrate that by adding refinements (like accounting for the pitching). Every refinement costs more computing power. You might do that fist 1000 AB simulation in .1 seconds on a modern desktop. Doing the average of BA and BAA 10000 times might take 3 seconds. The more refinements, the closer you are to needing a super computer to run your model, which is where some of the more sophisticated models are at these days.

But there isn't enough super computer to model something with convincing results. To truly model baseball, you would need to model the weather, and for every microsecond of each at bat. You'd have to model the dust that might blow into the eye of the batter in a small gust of wind. You'd have to model the bacteria on that steak ARod had for dinner the night before (maybe he got a belly ache affecting his performance).

You seem to think you can't learn anything from Google.

Screw that.

http://en.wikipedia.org/wiki/Climate_model

I don't google to learn what I need to know for some message board debate. I google to provide support for something I am speaking from authority on.

Oddly, if you read the above linked page, they sound an awful lot like I do (about the baseball model).

None of that contradicts much of anything that I've said. I don't know how many times I have to repeat that no scientific model is perfectly accurate, or expected to be, before you stop attempting to flog that strawman. The predictive models that are the basis of science are what allow for society to build airplanes and televisions, develop medicines and discover what types of things are swirling in Venus' atmosphere. In other words, scientific models are accepted because they do the best at explaining observable phenomena and provide predictive value. Not because they are "Truth." No scientific models are considered to be absolute truth and the expectation is that models will be replaced by newer, better models as our knowledge expands.

And I never said nothing can be learned from the internet. I said a couple of times that it's good for a superficial overview. It's not good for replacing a proper education at a university.

 

[Denny Crane]

None of that contradicts much of anything that I've said. I don't know how many times I have to repeat that no scientific model is perfectly accurate, or expected to be, before you stop attempting to flog that strawman. The predictive models that are the basis of science are what allow for society to build airplanes and televisions, develop medicines and discover what types of things are swirling in Venus' atmosphere. In other words, scientific models are accepted because they do the best at explaining observable phenomena and provide predictive value. Not because they are "Truth." No scientific models are considered to be absolute truth and the expectation is that models will be replaced by newer, better models as our knowledge expands.

And I never said nothing can be learned from the internet. I said a couple of times that it's good for a superficial overview. It's not good for replacing a proper education at a university.

They don't use models to build any of those things. Or if they do, they find out they're wrong when they send a robot to Venus that samples the atmosphere as it falls to the ground and before it burns up.

And if models were even close to good enough, they'd model car crashes instead of physically crashing cars to see how safe the passengers would be. And that's something simpler to model than baseball.

I build no strawman. The models are a huge element of the argument that there is man made global warming, and sure appear to be generally accepted as some sort of factual evidence by the scientists on that side of the argument.

It goes something like this:
1) Scientists create flawed models
2) Scientists argue the results indicate the sky is falling
3) They tell you about it
4) You believe them without any skepticism.

 

[Minstrel]

They don't use models to build any of those things. Or if they do, they find out they're wrong when they send a robot to Venus that samples the atmosphere as it falls to the ground and before it burns up.

You're a little confused. It's scientific models that allow for the building of the robots, the space probes, etc. All of physics is a model. The theory of gravity is a model. The theory of relativity is a model. All of science is built on models and those models are based on all the observations and measurements that have been made.

The model of man's effect on the temperature is one of those. It's not complete or Truth, because science can never know anything absolutely. It's one of the truisms of science: nothing can ever be proven, because we don't know all the rules. Things can only be proven in math (not science), because math is a man-made construct, so we know all the rules. But even though nothing can be proven, extremely useful predictive models can be built for how molecules behave or how air will flow over a plane.

 

[PapaG]

You're a little confused. It's scientific models that allow for the building of the robots, the space probes, etc. All of physics is a model. The theory of gravity is a model. The theory of relativity is a model. All of science is built on models and those models are based on all the observations and measurements that have been made.

The model of man's effect on the temperature is one of those. It's not complete or Truth, because science can never know anything absolutely. It's one of the truisms of science: nothing can ever be proven, because we don't know all the rules. Things can only be proven in math (not science), because math is a man-made construct, so we know all the rules. But even though nothing can be proven, extremely useful predictive models can be built for how molecules behave or how air will flow over a plane.

Which is where replication in results comes into play in real "science". Results attained consistently yield a "truth", or at least as close to a "truth" that man can achieve. We actually do know the rules in a controlled setting, which is why "science" uses the "Scientific Method".

You seem to be saying that models are more important than results? I offer there are failed models, yet observation + replicable results is very hard to be a skeptic about. Models led to robots? Sure, but there were, many, many failed models, and there still are since robotics continue to advance. You also seem to be under the assumption that because a paper is "peer reviewed" that it means it is some sort of gold stamp of approval. Contradictory arguments are also "peer reviewed"; does that make them any less valid?

Also, why do you capitalize "Truth", and mathematics play a not-so-small role in physics.

 

[Denny Crane]

You're a little confused. It's scientific models that allow for the building of the robots, the space probes, etc. All of physics is a model. The theory of gravity is a model. The theory of relativity is a model. All of science is built on models and those models are based on all the observations and measurements that have been made.

The model of man's effect on the temperature is one of those. It's not complete or Truth, because science can never know anything absolutely. It's one of the truisms of science: nothing can ever be proven, because we don't know all the rules. Things can only be proven in math (not science), because math is a man-made construct, so we know all the rules. But even though nothing can be proven, extremely useful predictive models can be built for how molecules behave or how air will flow over a plane.

I'm not confused. I'm talking about the COMPUTER models that the chicken little crowd are using as concrete proof that global warming is going to flood all the coastal cities, yada yada. Like the ones at wikipedia I linked earlier.

Talk about strawmen

 

[Denny Crane]

Which is where replication in results comes into play in real "science". Results attained consistently yield a "truth", or at least as close to a "truth" that man can achieve. We actually do know the rules in a controlled setting, which is why "science" uses the "Scientific Method".

You seem to be saying that models are more important than results? I offer there are failed models, yet observation + replicable results is very hard to be a skeptic about. Models led to robots? Sure, but there were, many, many failed models, and there still are since robotics continue to advance. You also seem to be under the assumption that because a paper is "peer reviewed" that it means it is some sort of gold stamp of approval. Contradictory arguments are also "peer reviewed"; does that make them any less valid?

Also, why do you capitalize "Truth", and mathematics play a not-so-small role in physics.

The public school system is a model. LOL.

 

[barfo]

Seriously, thanks for the laugh.

Likewise, I'm sure.

One of us knows more about science. You can believe it is you if you want.

barfo

 

[Minstrel]

Which is where replication in results comes into play in real "science". Results attained consistently yield a "truth", or at least as close to a "truth" that man can achieve. We actually do know the rules in a controlled setting, which is why "science" uses the "Scientific Method".

Not all science is done in a laboratory. And we don't know the underlying rules of the universe anywhere, whether it is in a lab or otherwise. Repeatable results give us empirical facts (things that hold up under repeated observation, which is different from an actual "fact") and allow us to build predictive models, which is what science is.

You seem to be saying that models are more important than results?

I'm not saying anything of the kind. Scientific models (like how gravity works, how light behaves, etc) are based on the results of observation and measurement.

I offer there are failed models, yet observation + replicable results is very hard to be a skeptic about. Models led to robots? Sure, but there were, many, many failed models, and there still are since robotics continue to advance. You also seem to be under the assumption that because a paper is "peer reviewed" that it means it is some sort of gold stamp of approval. Contradictory arguments are also "peer reviewed"; does that make them any less valid?

No, being "peer reviewed" doesn't mean it is the end of the debate. My point is that the peer review system subjects all presented theories and models to scrutiny by the scientific community. This includes criticisms of existing theories. Certainly there are failed models...science is after the best model based on current knowledge. It's almost certain that a million years from now (assuming humanity still exists), all our current models will have been replaced, probably many times over, by superior models fueled by more knowledge.

Also, why do you capitalize "Truth"

Because Denny did, to connote some sort of metaphysical absolute truth. I was using it the same way to point out that science doesn't consider its laws and theories to be absolute truth. That isn't what science is aiming for. Science is aiming for the models that best explain the universe.

and mathematics play a not-so-small role in physics.

Mathematics is the language of physics, essentially. It plays a massive role. But it's a separate discipline, and things can be proven within the field of mathematics. Things cannot be proven with the various fields of science.