[kenberg]

I have an honest question here. We can imagine two approaches to predicting from data. I will formulate them ine extreme ways to be clear about the difference. One way is to say "Just ive me the numbers. I don't care if the numbers represent temperatures in the Antartic or the price of McDonalds stock. I will analyze the numbers and predict the future." Another approach is to care very much about what the numbers represent and to bring all of the accumulated knowledge of cause and effect to bear in trying to predict what happens next.

Each approach has it pitfalls. The first ignores influences that might well be relevant, the second brings in beliefs about causality that might if might not be correct. Some sort of combination seems best. The problem is too complicated to expect direct verification such as with relativity in 1919 (and even that needed further work).

Anyway, I am wondering, after we soften the extreme formulation to better match with reality, if this is the distinction being argued over. Or, if that is not the distinction, what is?

Side note: I forget where I read this but supposedly before the 1919 observations were made a journalist asked Einstein what would happen if his predictions were not borne out. He replied "In that case I would feel very sorry for the Almighty, because the theory is correct".

[hrothgar]

kenberg, on 2015-March-31, 05:04, said:

I have an honest question here. We can imagine two approaches to predicting from data. I will formulate them ine extreme ways to be clear about the difference. One way is to say "Just ive me the numbers. I don't care if the numbers represent temperatures in the Antartic or the price of McDonalds stock. I will analyze the numbers and predict the future." Another approach is to care very much about what the numbers represent and to bring all of the accumulated knowledge of cause and effect to bear in trying to predict what happens next.

Each approach has it pitfalls. The first ignores influences that might well be relevant, the second brings in beliefs about causality that might if might not be correct. Some sort of combination seems best. The problem is too complicated to expect direct verification such as with relativity in 1919 (and even that needed further work).

Within the statistics and machine learning community, people distinguish between parametric and non-parametric models.

Regression analysis is a classic example of a parametric model. The techniques pre-suppose a parametric model that describes the relationship between the dependent and the independent variables. There are also any number of "black box" modeling techniques (neural networks, smoothing splines, boosted regression trees, etc.) These techniques do not presuppose any kind of parametric relationship, rather the try to identify patterns found within the data. There are also hybrid techniques such as GAMs (General Additive Models). There are advantages and disadvantages to each of the methodologies. As a rule, people tend to prefer using parametric techniques, especially when you are doing extrapolation rather than interpolation.

What I find amusing about this all is that Daniel is simultaneous decrying the complexity of the IPCC models while stressing the need to adopt purely data driven techniques which require complex, non-parametric modeling. Going back to Daniels own example, he holds up a linear trend with a sinusoidal oscillation as his prototypical data driven technique when this is textbook example of parametric modeling.

The degree of cogitative dissonance is astounding...

[Daniel1960]

kenberg, on 2015-March-31, 05:04, said:

I have an honest question here. We can imagine two approaches to predicting from data. I will formulate them ine extreme ways to be clear about the difference. One way is to say "Just ive me the numbers. I don't care if the numbers represent temperatures in the Antartic or the price of McDonalds stock. I will analyze the numbers and predict the future." Another approach is to care very much about what the numbers represent and to bring all of the accumulated knowledge of cause and effect to bear in trying to predict what happens next.

Each approach has it pitfalls. The first ignores influences that might well be relevant, the second brings in beliefs about causality that might if might not be correct. Some sort of combination seems best. The problem is too complicated to expect direct verification such as with relativity in 1919 (and even that needed further work).

Anyway, I am wondering, after we soften the extreme formulation to better match with reality, if this is the distinction being argued over. Or, if that is not the distinction, what is?

Side note: I forget where I read this but supposedly before the 1919 observations were made a journalist asked Einstein what would happen if his predictions were not borne out. He replied "In that case I would feel very sorry for the Almighty, because the theory is correct".

A little bit of both is needed. The dependence on either varies with the situation. Newton's first law of physics states, "an object in motion stays in motion with the same speed and in the same direction unless acted upon by an unbalanced force." Hence, the prevaling force (trend from the data) will remain in effect until another force acts upon it to cause a change. In a complex system (such as the Earth's climate), several competing forces are acting simultaneously. What we are witnessing is the summation of these forces. Some have tried to consolidate these forces into a simple model, based on a few parameters, on the assumption that the other parameters are either too small to contribute or cancel each other. From a pure numbers standpoint, all these parameters are incorporated into the accumulated the data, and the observed trend is the result.

History (and physics) tells us that nothing will continue indefinitely. There are self-imposed limits. The temperature of the Earth cannot rise forever. Past climates have experienced wide ranges, sometimes ending suddenly. In some cases, we have identified large external forcings as the most likely case. Other times, we simply do not know. Predicting large future changes in such a system is difficult, if not impossible, due to our limited knowledge. Conversely, stating that certain forces are likely to alter the trends slightly, in one direction or the other, based on sound scientific evidence, is reasonable. Our planet has absorbed all the internal and external forces, and returned the current climate situation. Some claim that our planet is precariously perched on a delicate balance of nature, and that the slightest disturbance will throw us over some magical tipping point. Paleoclimatology shows us that this is not the case. Newton's third law states, "for every action, there is an equal and opposite reaction." Natural feedbacks tend to act in an opposite direction to the inital force. While this will not necessarily return to the original scenario, the concept of a given force leading to larger and more numerous positive feedbacks, contradicts most of physics. Otherwise the search for the perpetual motion mahine would have returned several products, by now.

This returns use to Newton's first law. The climate is likey to continue on its current trend, unless acted upon by an unbalanced force.

[kenberg]

hrothgar, on 2015-March-31, 05:54, said:

Regression analysis is a classic example of a parametric model. The techniques pre-suppose a parametric model that describes the relationship between the dependent and the independent variables. There are also any number of "black box" modeling techniques (neural networks, smoothing splines, boosted regression trees, etc.) These techniques do not presuppose any kind of parametric relationship, rather the try to identify patterns found within the data. There are also hybrid techniques such as GAMs (General Additive Models). There are advantages and disadvantages to each of the methodologies. As a rule, people tend to prefer using parametric techniques, especially when you are doing extrapolation rather than interpolation.

Thanks for this. I want to pursue it a bit.

First I should come out of the closet. I am pre-disposed to believe that human activity is a problem for the planet. Immediately maybe, eventually certainly. There are seven billion or so of us and if we all start putting 20K miles a year on an SUV and put air conditioning in our dog houses I don't think that it will work out well.

As to the statistics. Despite my mathematical training I am unfamiliar with modern statistical techniques. Not totally ignorant of them but we are not on close terms. I expect I could learn some of this but more relevantly I think that if I look into it some I will be able to pretty well tell whom I can trust and whom I cannot. Even that would take work, but doable I think.

A question: Does causation fit into your scheme above? Or perhaps I should ask where and how it fits. Regression models, on their own, will not disclose causation, right?

My thinking is that we almost certainly have to do something, and I expect that if I got into this more I would drop the "almost". It's important to be effective, and for this it is important to be as sure as we can about cause and effect.

[hrothgar]

kenberg, on 2015-March-31, 10:15, said:

A question: Does causation fit into your scheme above? Or perhaps I should ask where and how it fits. Regression models, on their own, will not disclose causation, right?

The short, simple answer is "no". Regression techniques are used to describe correlation, not causation.

The longer, more complicated answer is "not really". Regression techniques work by generating a surface that minimized the sum of the squared errors between predicted and actual. Traditional regression techniques associate all of the variance with the Y axis. However, there are other techniques like orthogonal regression that associate variance with both the X and Y axes. Arguable, when you make these sorts of assumptions, you are getting close to ascribing causation.

[Daniel1960]

Kenberg,
A recent paper discusses some of the issues with the global climate models.

http://arstechnica.c...-models-biased/

With some being better than others.

http://phys.org/news...te-accused.html

[mike777]

A report in my local paper today says by 2024 the sea level may rise 10.6 inches off our coast.

The Coastal Resources Commission said there are 2 reasons:
1) ancient geological forces are causing part of the NA continent to subside.
2) Shifts in the speed and position of the Gulf Stream are pushing the seas higher in our region.

[kenberg]

Daniel1960, on 2015-April-01, 09:28, said:

Kenberg,
A recent paper discusses some of the issues with the global climate models.

http://arstechnica.c...-models-biased/

With some being better than others.

http://phys.org/news...te-accused.html

Thank you. I took a quick look at both and I will, I think, get back for a longer look. Climate change is one of many areas where I reluctantly accept a civic obligation to at least try to be informed. It's obviously both difficult and important.

[y66]

kenberg, on 2015-March-31, 10:15, said:

There are seven billion or so of us and if we all start putting 20K miles a year on an SUV and put air conditioning in our dog houses I don't think that it will work out well.

If all of the approximately 4 billion people between the ages of 16 and 65 now put 20K miles a year on an SUV in 2015 and every year thereafter, and their SUVS get 20 MPG now, increasing 2 percent a year in efficiency thereafter, and the driving population grows 0.8 percent a year, the resulting cumulative C02 emissions from SUVs alone will hit 565 gigatonnes sometime in 2030. If you want to quibble with the driving age estimate and the mileage estimates, fine, make it 2030 plus or minus 3 and don't forget to add something for the dogs.

[y66]

What do conservative policy intellectuals think about climate change? by Ben Adler at grist.org.

[blackshoe]

Who is Ben Adler, and why should we care what he says?

[y66]

blackshoe, on 2015-April-06, 17:20, said:

Who is Ben Adler, and why should we care what he says?

I did not know that Libertarians used the first person plural pronoun "we".

[PassedOut]

y66, on 2015-April-06, 16:03, said:

What do conservative policy intellectuals think about climate change? by Ben Adler at grist.org.

It's interesting to see that some other conservatives today don't support a carbon tax, but prefer instead to offer large incentives to (potential) inventors of adaptive solutions. We've gotten to the point where some adaptation will be required, and it might be a good idea to offer such incentives, but I still support a carbon tax as the best way to reduce the amount of adaptation that will be required.

[Daniel1960]

PassedOut, on 2015-April-06, 19:41, said:

It's interesting to see that some other conservatives today don't support a carbon tax, but prefer instead to offer large incentives to (potential) inventors of adaptive solutions. We've gotten to the point where some adaptation will be required, and it might be a good idea to offer such incentives, but I still support a carbon tax as the best way to reduce the amount of adaptation that will be required.

What if adaptation turns out to be the better option?

[mike777]

Daniel1960, on 2015-April-06, 23:05, said:

What if adaptation turns out to be the better option?

that seems to be the debate at this point..


carbon tax will destroy
adaptation will destroy

all roads lead to destruction. aLL ROADS lead to pain, great pain

Often, very often when it comes to pain we have bias TO DELAY

I REFER to Taleb we have a great bias to procrastinate, very often for good reasons

Granted taleb has his view on this one issue.

[PassedOut]

Daniel1960, on 2015-April-06, 23:05, said:

What if adaptation turns out to be the better option?

Then we'd have the benefits of both. But it is too dangerous to put all of our eggs in the adaptation basket.

[blackshoe]

y66, on 2015-April-06, 18:42, said:

I did not know that Libertarians used the first person plural pronoun "we".

I'm not a Libertarian, I'm a libertarian. There's a difference.

[blackshoe]

mike777, on 2015-April-06, 23:50, said:

all roads lead to destruction.

"Whoopee, we're all gonna die!" -- Country Joe MacDonald.

[PassedOut]

Looks like the new pope is making evil-doers nervous: Satan sends a team from Chicago to Rome

Quote

A US activist group that has received funding from energy companies and the foundation controlled by conservative activist Charles Koch is trying to persuade the Vatican that “there is no global warming crisis” ahead of an environmental statement by Pope Francis this summer that is expected to call for strong action to combat climate change.

The smart money, though, expects Satan's team to return with its tail between its legs. Calling in to a popular Roman talk show yesterday, Pope Francis explained, "In the past, whenever the Church has sided with Satan against the scientists, the scientists have always turned out to be right. We've learned."

[mikeh]

blackshoe, on 2015-April-06, 17:20, said:

Who is Ben Adler, and why should we care what he says?

Because he gave a reasonable (at least it seemed to me to be reasonable) summary of the views expressed by those conservatives who have refused to let ideology overrule evidence, at least in terms of global warming issues. For example, he quotes directly from those conservatives whose views he summarizes, and his own bias is sufficiently evident that one can make allowances for it, and look at the intellectually honest arguments advanced by the conservatives.

One can disagree with them. I mean the adaptionists seem content with allowing the widespread destruction of the environment and the mass extinction of most forms of life on earth, beyond the bacteria. I find that morally repugnant, but it seems to be a perfectly valid libertarian attitude, which is basically f*ck everyone and everything else so long as I'm ok.

I appreciate that allowing facts and evidence to drive policy decisions is anathema to libertarians, altho ironically they seem to be blind to that weakness, preferring to posture as realists when in fact they are (twisted) idealists. However, if you are ever inclined to entertain the thought that you are profoundly misguided, you might actually learn something by reading the views of others.

Of course, anyone who thinks that Heinlein is the epitome of philosophical thinking, and that the 'wisdom' of Lazarus Long constitutes real insight is likely to find critical thinking to be difficult. FWIW, I enjoyed Heinlein when I was 18 (I was a young 18), and thought that Lazarus Long was a great character. I like to think I have matured in my thinking a little bit since then