[PassedOut]

mike777, on 2015-March-23, 01:45, said:

Humans are an evasive species

Not always, but pretty often.

[PassedOut]

Daniel1960, on 2015-March-18, 13:32, said:

Let the scientific work be judged on its own merits. Most of the scientifuc research resides in between these two political extremist groups, such that neither truly represents reality.

Could either of the extreme scenarios occur? Sure, science does not exclude any possibility. They are just less probable than others.

Yes, this paper, published in October, 2014, that you recommended earlier in this thread, illustrates the extremes of possible sea level rise by the year 2100:

Quote

Figure 3. Projected global mean sea level rise by 2100 relative to 2000 for the RCP8.5 scenario and uncertainty. Vertical grey bars indicate the 5, 17, 50, 83, and 95th percentiles in the uncertainty distribution.

Although it is possible that sea level rise could be 48 cm on the low end or 180 cm on the high end, these extremes "are just less probable than others." And indeed, that is true; I agree completely.

What I have trouble understanding, then, is why you put forward an even more extreme position on sea level rise:

Daniel1960, on 2015-January-25, 15:59, said:

Assuming their measurement is accurate (3.2 mm/yr), that amounts to another 260 mm (26 cm) by the year 2100. That is less than one foot, which does not worry me.

Representing reality, we have some recent news: Arctic Ice Reaches a Low Winter Maximum

Quote

The winter ice covering the Arctic Ocean has reached its annual peak, but the extent of sea ice cover this winter is smaller than it has been at the end of any winter since 1978, when scientists began keeping consistent satellite records.

And: Global warming is now slowing down the circulation of the oceans

Quote

So far, the study finds, we’re looking at a circulation that’s about 15 to 20 percent weaker. That may not sound like much, but the paper suggests a weakening this strong has not happened at any time since the year 900. Moreover, this is already more weakening than scientifically expected — and could be the beginning of a further slowdown that could have great consequences.

The U.N.’s Intergovernmental Panel on Climate Change, in 2013, said it was “very likely” that the Atlantic overturning circulation would weaken over the course of this century, but gave a gigantic range of from 1 to 54 percent, with best estimates at 11 and 34 percent. We’re already in that window, suggests the new study, and it’s only 2015.

[kenberg]

mike777, on 2015-March-23, 01:45, said:

I think at some point we don't agree with evolution.

Wrong turn at lungfish is an amusing play that explores this view..

[Daniel1960]

PassedOut, on 2015-March-25, 20:09, said:

Yes, this paper, published in October, 2014, that you recommended earlier in this thread, illustrates the extremes of possible sea level rise by the year 2100:


Although it is possible that sea level rise could be 48 cm on the low end or 180 cm on the high end, these extremes "are just less probable than others." And indeed, that is true; I agree completely.

What I have trouble understanding, then, is why you put forward an even more extreme position on sea level rise:



Representing reality, we have some recent news: Arctic Ice Reaches a Low Winter Maximum



And: Global warming is now slowing down the circulation of the oceans

Not sure why you are using short term data to make long term assessments. Why not choose the minimum Arctic or maximum Antarctic value last year? IS it because these would yield results drastically different than you prefer? The satellite measurements of global sea ice area had remained fairly steady until 2001, when it began to fall. The bottom was reached during the northen summer in 2012, at about 2.5 million sq. km below the long term average. This was due to extensive Arctic melt, as Antarctica had been increasing slightly. Since then, the sea ice area has returned to average values, bolstered by increases in both polar regions.

http://arctic.atmos....a.withtrend.jpg

The paper presented shows an extremely high value for global expansion (300 cm) of sea water due to large temperature increases. The estimates due to surface mass balance of the combined Greenland and Antarctic glaciers ranges from -5 to 20 cm, with the Antartic contribution always being negative. The second assumption allows for the possibility of large glacial calving. Without these assumptions, the sea level rise estimate ranges are from 18 - 63 cm, with a best estimate of 32cm. My position of 3.2 mm/yr continuing is right in line with these projections. Unless you beleve that large glacial calving is likely in the near future, then why would you consider it extreme? DO you believe the modeled projections or those based on actual data?

http://www.cmar.csir..._proj_21st.html

The reference concerning slowing down of oceanic circulation is based on models. The following shows no slowdown, and it is based on actual data:

http://www.gso.uri.e...is-not-slowing/

My position is to base future projection of warming, sea level rise, and other climate changes on actual data, and not model predictions. Unless those predictions start to manifest themselves in the data, I see no reason to accept them over the long term research.

[hrothgar]

Daniel1960, on 2015-March-26, 05:37, said:

My position is to base future projection of warming, sea level rise, and other climate changes on actual data, and not model predictions.

How is your "future projection" any different than a "model predictions"?

Oh wait, models are bad and your projections are good...

[Daniel1960]

hrothgar, on 2015-March-26, 06:01, said:

How is your "future projection" any different than a "model predictions"?

Oh wait, models are bad and your projections are good...

So, are you saying that you would base your projections on models over data?

[kenberg]

I may start a thread devoted to the general question of "How do we decide what and whom to believe in areas where we are not at all experts or even particularly well informed?"

Let me take a crack at data versus models, starting with my weight. I can tell you wnat my weight is, or at least what the scale says that it is. I have a rough idea of what it has been over the past year and since I get weighed in the doctor's office I could get some recorded data there. I could say whether over the last several years my weight has gone up or down. This involves data. If I am going to project into the future, I think I need a model. What would happen if I cut out my evening glass of wine? I really like eating dried fruit and nuts, but they have calories so I might consider that. I exercise but I could do more. Exercise really involves some modeling. I have known people who argue that exercise can't help much because it just doesn't burn enough calories unless you maybe bike fifty miles a day or some such. But I think that exercise helps regulate an appetite. . I find that I am less likely, not more likely, to want to eat a Whopper after a nice hike. My tastes change. So we model. Primitively in the above example but still we model.

So it is not a matter of data or a model, if we are to project into the future and look to the likely results of action or inaction, we model. We must.

The distinction can be very useful when we look at criticism of a view. Do we doubt the accuracy of the data, or do we accept the data as accurate but question the realism of a model that projects future results from the data?

Anyway, data, if carefully gathered, can say something of where we are and where we have been. I doubt that data, on its own, can say anything of where we are headed. Even just some simple linear extrapolation is a model.

[hrothgar]

Daniel1960, on 2015-March-26, 07:17, said:

So, are you saying that you would base your projections on models over data?

No, I am saying that you are too stupid to understand that a "projection" is the same thing as a "model" and that both are based on data.

[Daniel1960]

hrothgar, on 2015-March-26, 08:48, said:

No, I am saying that you are too stupid to understand that a "projection" is the same thing as a "model" and that both are based on data.

I think a little introspective action is needed here, as they are not the same. If you were to investigate further, you might find out why. Then again, you refer to others as being stupid, who appear to know more than yourself.

[hrothgar]

Daniel1960, on 2015-March-26, 10:03, said:

I think a little introspective action is needed here, as they are not the same. If you were to investigate further, you might find out why. Then again, you refer to others as being stupid, who appear to know more than yourself.

Webster's defined the word "Projection" as "an estimate of future possibilities based on a current trend". (Webster's offers a number of other definitions, how this is clearly the most appropriate)

http://www.merriam-w...nary/projection

Wikipedia explains "Statistical model" as "A statistical model embodies a set of assumptions concerning the generation of the observed data, and similar data from a larger population. A model represents, often in considerably idealized form, the data-generating process. The model assumptions describe a set of probability distributions, some of which are assumed to adequately approximate the distribution from which a particular data set is sampled."

http://en.wikipedia....atistical_model

Projection is nothing more than an applied use of a model and any kind of projection presupposes some kind of model.

[Daniel1960]

hrothgar, on 2015-March-26, 10:27, said:

Webster's defined the word "Projection" as "an estimate of future possibilities based on a current trend". (Webster's offers a number of other definitions, how this is clearly the most appropriate)

http://www.merriam-w...nary/projection

Wikipedia defines the expression "Statistical model" as "A statistical model embodies a set of assumptions concerning the generation of the observed data, and similar data from a larger population. A model represents, often in considerably idealized form, the data-generating process. The model assumptions describe a set of probability distributions, some of which are assumed to adequately approximate the distribution from which a particular data set is sampled."

Projection is nothing more than an applied use of a model and any kind of projection presupposes a some kind of model.

Reread your definition of a projection. A current trend is based on accumulated data, not a model.

Not that I agree with your definition. A projection could be based on either data, like your current trend or a model, based on deired inputs. Models typically include assumptions as to what the future may entail. This may or may not resemble the past data.

Here is an example showing the difference between projections based on models and those based on data:

http://www.skeptical..._Prediction.png

A model can be made to give any desired result, and is only as good as the selected input. Some models have behaved quite well, others, not so. Economists have a rough time with their forecasts, and the economy is less chaotic than the climate.

http://www.cbsnews.c...wrong-so-often/

[hrothgar]

Daniel1960, on 2015-March-26, 12:11, said:

Here is an example showing the difference between projections based on models and those based on data:

http://www.skeptical..._Prediction.png

Sorry if this comes across as an appeal to authority, but

1. I get paid hundreds of thousands of dollars a year to do statistical modeling
2. Before this, I was product manager for MATLAB's statistics system
3. Before this, I was fifth in my class at MIT
4. Before this, I did a Masters in Mathematical Economics and taught undergraduate statistics
5. Before this, I graduated Wesleyan University, where I was the top student in both the Economics and the Government departments.

I am mentioning this because I am trying to establish that I know a lot about both "modeling" and "data" and how these expressions are used in both professional and academic settings. So, with all due respect, when I say that I find your claims both idiosyncratic and laughable, it probably means something.

Let's take a look at the chart that you choose to illustrate your point:

I assume that the lower of the two dotted red lines is meant to illustrate a projection based on "data".

Guess what? This projection also presupposes a model. In this case, it would appear as if the model is a sinusoidal oscillation around a linear trend.

This is a model. (It's almost certainly a simpler model than the one used by the IPCC, but it is a model none the less and anyone with a background in stats or economics would agree with me)

I have been playing around a bunch in R today. I've been making using of a function called "lm" which can be used to generate trend lines like the one you see in that model. Want to guess what "lm" stands for?

(Here's a hint. The first word is "linear")

[Daniel1960]

hrothgar, on 2015-March-26, 12:52, said:

Sorry if this comes across as an appeal to authority, but

1. I get paid hundreds of thousands of dollars a year to do statistical modeling
2. Before this, I was product manager for MATLAB's statistics system
3. Before this, I was fifth in my class at MIT
4. Before this, I did a Masters in Mathematical Economics and taught undergraduate statistics
5. Before this, I graduated Wesleyan University, where I was the top student in both the Economics and the Government departments.

I am mentioning this because I am trying to establish that I know a lot about both "modeling" and "data" and how these expressions are used in both professional and academic settings. So, with all due respect, when I say that I find your claims both idiosyncratic and laughable, it probably means something.

Let's take a look at the chart that you choose to illustrate your point:

I assume that the lower of the two dotted red lines is meant to illustrate a projection based on "data".

Guess what? This projection also presupposes a model. In this case, it would appear as if the model is a sinusoidal oscillation around a linear trend.

This is a model. (It's almost certainly a simpler model than the one used by the IPCC, but it is a model none the less and anyone with a background in stats or economics would agree with me)

I have been playing around a bunch in R today. I've been making using of a function called "lm" which can be used to generate trend lines like the one you see in that model. Want to guess what "lm" stands for?

(Here's a hint. The first word is "linear")

This is all very nice I graduated over 30 years ago from the University of Michigan. While I cannot compare to your statistical resume, I did take graduate course in statisctics, and use them regularly in my scientific work (chemistry).

I think you are grasping when you refer to every trend as a model. Back when we had to do all our calculations by hand, that may have been the case. Today, modelers have the luxury of computers, which can perform multiple, complicated calculations in the fraction of a second, often changing several parameters simultaneously. Nowadays, the term "model" refers to much more than a simple linear trend.

[Daniel1960]

[quote name='PassedOut' timestamp='1427335756' post='840254']
Yes, this paper, published in October, 2014, that you recommended earlier in this thread, illustrates the extremes of possible sea level rise by the year 2100:


Although it is possible that sea level rise could be 48 cm on the low end or 180 cm on the high end, these extremes "are just less probable than others." And indeed, that is true; I agree completely.

What I have trouble understanding, then, is why you put forward an even more extreme position on sea level rise:



Representing reality, we have some recent news: Arctic Ice Reaches a Low Winter Maximum

Using a projection (see hrothgar's definitiona) based on the current trend for sea level rise (3.2 mm/yr from satellite calculations, less by tidal gauges), the projected sea level rise by 2100 would be ~26 cm. The projections in the linked paper, assumes a thermal expansion equivalent to 32 cm of rise (likely range 25-39 cm). Interestingly, the reference paper they used for their assumptions, calculated a sea level rise of 13 cm by 2100 using CMIP5 models, if warming is kept below 2C, and 28 cm, under worst-case warming scenarios. Jevrejeva, et. al. used the high-end warming only in their calculations. Indeed, this paper shows not a range of potential sea level rise, rather it shows the range of upper limits to sea level rise. You are comparing a likely value of sea level rise based on current trends to an upper limit to sea level rise based on modelled assumptions. By the way, the lower end of their maximum sea level rise is 29 cm.

http://onlinelibrary...012GL052947/pdf

Again, the model is only as good as the data inputted or assumption made.

[hrothgar]

Daniel1960, on 2015-March-26, 14:20, said:

I think you are grasping when you refer to every trend as a model. Back when we had to do all our calculations by hand, that may have been the case. Today, modelers have the luxury of computers, which can perform multiple, complicated calculations in the fraction of a second, often changing several parameters simultaneously. Nowadays, the term "model" refers to much more than a simple linear trend.

I readily admit that the increase in computing power has enabled people to develop more complicated models.
However, expression model still includes naive techniques like fitting a trend line to the data.

Going back to the chart that you original proposed.

A trend line is one possible way to describe the relationship between the dependent and the independent variable
A trend line + a sinusoidal component is another

People need a way to differentiate between these two sets of assumptions.
They use the word model to formally describe the relationship.

As far as I can tell, you use the word "projection" to describe models that you like and "model" to describe models that you don't like.
I don't find this particularly compelling.

[hrothgar]

Daniel1960, on 2015-March-26, 14:20, said:

Nowadays, the term "model" refers to much more than a simple linear trend.

BTW, just so its clear that I am not making ***** up, here is a useful little quote from the R documentation describing how one specifies formula's for linear models.

Quote

The models fit by, e.g., the lm and glm functions are specified in a compact symbolic form. The ~ operator is basic in the formation of such models. An expression of the form y ~ model is interpreted as a specification that the response y is modelled by a linear predictor specified symbolically by model. Such a model consists of a series of terms separated by + operators. The terms themselves consist of variable and factor names separated by : operators. Such a term is interpreted as the interaction of all the variables and factors appearing in the term.

In addition to + and :, a number of other operators are useful in model formulae. The * operator denotes factor crossing: a*b interpreted as a+b+a:b. The ^ operator indicates crossing to the specified degree. For example (a+b+c)^2 is identical to (a+b+c)*(a+b+c) which in turn expands to a formula containing the main effects for a, b and c together with their second-order interactions. The %in% operator indicates that the terms on its left are nested within those on the right. For example a + b %in% a expands to the formula a + a:b. The - operator removes the specified terms, so that (a+b+c)^2 - a:b is identical to a + b + c + b:c + a:c. It can also used to remove the intercept term: when fitting a linear model y ~ x - 1 specifies a line through the origin. A model with no intercept can be also specified as y ~ x + 0 or y ~ 0 + x.

[Daniel1960]

hrothgar, on 2015-March-26, 15:08, said:

I readily admit that the increase in computing power has enabled people to develop more complicated models.
However, expression model still includes naive techniques like fitting a trend line to the data.

Going back to the chart that you original proposed.

A trend line is one possible way to describe the relationship between the dependent and the independent variable
A trend line + a sinusoidal component is another

People need a way to differentiate between these two sets of assumptions.
They use the word model to formally describe the relationship.

As far as I can tell, you use the word "projection" to describe models that you like and "model" to describe models that you don't like.
I don't find this particularly compelling.

No, a projection is a predictor of a future scenario. It may be based on current trends, past data, or mathematical models. A projection is not a model itself. Maybe I am biased against modelers, because I have witnessed too many times when a (computer) model was less reliable than scientific research. Does that satisfy your definition?

[hrothgar]

Daniel1960, on 2015-March-26, 15:24, said:

Maybe I am biased against modelers ... Does that satisfy your definition?

I would agree with the first six words

[Daniel1960]

hrothgar, on 2015-March-26, 15:29, said:

I would agree with the first six words

Would you admit that you are biased against researchers, in favor of modelers?

[hrothgar]

Daniel1960, on 2015-March-26, 16:52, said:

Would you admit that you are biased against researchers, in favor of modelers?

I don't consider the distinction to be salient