Al Gore--environmental saboteur?

[I AM NOT THAT GUY 5,715]

Feel up to defending your argument that atmospheric CO2 levels have no real impact on the earth's temperature?

Did I make that argument? My only concern is as to the magnitude of the anthropomorphic (sic) contribution to an otherwise naturally occurring process.

Edited February 23, 2010 by Lone Ranger

[one...two...tree 2,762]

Did I make that argument? My only concern is as to the magnitude of the anthropomorphic (sic) contribution to an otherwise naturally occurring process.

Is it not logical to conclude that if we can accurately measure the atmospheric levels of CO2 and we know that measurement has gone up dramatically over the last 50 years, and we know that man made CO2 levels also have gone up dramatically over the last 50 years and those levels coincide with the increase in atmospheric levels, that it is a cause and effect relationship?

[I AM NOT THAT GUY 5,715]

Is it not logical to conclude that if we can accurately measure the atmospheric levels of CO2 and we know that measurement has gone up dramatically over the last 50 years, and we know that man made CO2 levels also have gone up dramatically over the last 50 years and those levels coincide with the increase in atmospheric levels, that it is a cause and effect relationship?

If all is as you say it is, that would be a prima facia case. But to be absolutely certain, you would have to demonstrate which activities are causing that rise. For instance, besides CO₂ emissions, you might also want to look at whether the system's ability to utilize, or remove CO₂ has been comprised by either human, or natural causes, and what measures should be instigated to mitigate those as well.

Further, much depends on whether, or not, a natural cycle is overwhelming the human contribution, and whether, despite our best efforts, the inevitable is going to happen anyways, as historical evidence would suggest.

[one...two...tree 2,762]

If all is as you say it is, that would be a prima facia case. But to be absolutely certain, you would have to demonstrate which activities are causing that rise. For instance, besides CO₂ emissions, you might also want to look at whether the system's ability to utilize, or remove CO₂ has been comprised by either human, or natural causes, and what measures should be instigated to mitigate those as well.

Further, much depends on whether, or not, a natural cycle is overwhelming the human contribution, and whether, despite our best efforts, the inevitable is going to happen anyways, as historical evidence would suggest.

There are numerous scientific studies that have addressed just that. Granted, there are many variables, like natural carbon sinks such as the oceans that absorb over half of the CO2 in the atmosphere. The ice polar regions create a circulation effect that allows for the absorption to take place, however, as the polar ice caps melt, less circulation occurs, thereby lowering the ocean's ability to absorb more CO2. A snow ball effect if you will. If we know that through fossil fuel emissions, a certain amount of metric tons of CO2 is released into the atmosphere, we can see a direct relation to the rise in atmospheric CO2 levels, as well as measure the levels of CO2 which are currently being absorbed by the oceans. What ever variations or variables, the consequence of change is accurately measurable.

[I AM NOT THAT GUY 5,715]

There are numerous scientific studies that have addressed just that. Granted, there are many variables, like natural carbon sinks such as the oceans that absorb over half of the CO2 in the atmosphere. The ice polar regions create a circulation effect that allows for the absorption to take place, however, as the polar ice caps melt, less circulation occurs, thereby lowering the ocean's ability to absorb more CO2. A snow ball effect if you will. If we know that through fossil fuel emissions, a certain amount of metric tons of CO2 is released into the atmosphere, we can see a direct relation to the rise in atmospheric CO2 levels, as well as measure the levels of CO2 which are currently being absorbed by the oceans. What ever variations or variables, the consequence of change is accurately measurable.

I am with you until the last part, which is where the debate should lie.

We are relying on trends, and extrapolating from those trends. The "hockey stick" has disappeared from the projections, yet if you look at many websites for the proponents of Global Warming, they still offer that chart as proof. As any student of Numerical Analysis would know, it is hard to fit a curve to a dynamic system. Small errors in measurements can have radical effects on projections, especially when dealing with small variances in a multi-dimensional model.

[one...two...tree 2,762]

I am with you until the last part, which is where the debate should lie.

We are relying on trends, and extrapolating from those trends. The "hockey stick" has disappeared from the projections, yet if you look at many websites for the proponents of Global Warming, they still offer that chart as proof. As any student of Numerical Analysis would know, it is hard to fit a curve to a dynamic system. Small errors in measurements can have radical effects on projections, especially when dealing with small variances in a multi-dimensional model.

The emphasis should be on the macro and not the micro (forgive my lack of technical terms). For example, if you went on a weight loss program, measuring your weight over a period of time would be an accurate way to determine or project what your weight would be at a future point. However, if you step on a scale several times throughout the day, you'd see your weight fluctuate within a certain range. That fluctuation, however, doesn't negate the importance of the slope or decline of your weight over time which would indicate a trend, particularly if that trend coincides with a trend of decreasing your caloric intake. There are also many variables that can have an impact on your weight, some of which are beyond your control, however, the variables that you can control are worth modifying if you hope to achieve the desired result. I believe this is called a 4th order polynomial curve, which is used in science all the time. It's not something that climatologists concocted.

[w¡n9Nµ7 §£@¥€r 123]

... 4th order polynomial curve, which is used in science all the time. It's not something that climatologists concocted.

sounds liek fuzzy math to me

[I AM NOT THAT GUY 5,715]

The emphasis should be on the macro and not the micro (forgive my lack of technical terms). For example, if you went on a weight loss program, measuring your weight over a period of time would be an accurate way to determine or project what your weight would be at a future point. However, if you step on a scale several times throughout the day, you'd see your weight fluctuate within a certain range. That fluctuation, however, doesn't negate the importance of the slope or decline of your weight over time which would indicate a trend, particularly if that trend coincides with a trend of decreasing your caloric intake. There are also many variables that can have an impact on your weight, some of which are beyond your control, however, the variables that you can control are worth modifying if you hope to achieve the desired result. I believe this is called a 4th order polynomial curve, which is used in science all the time. It's not something that climatologists concocted.

Exactly! However, we are not talking about a simple polynomial here, but a series of simultaneous equations. Engineering problems mostly deal with x³ for static systems (dead load) and x⁴ for dynamic systems (live load). But, in the climatological models, you may be dealing with 100 or more dependent (variables that vary with the value of other variables) variables. Simplified weather equations can dependent on three or four variables, measured against time, and then the complexity of the model increases as you add more and more of those data sets. For instance, how many different locations do you want to place your sensors over a geographical area?

As an example, a simple 210 ft weather tower used to target incoming MRV's has wind speed, direction, barometric pressure, and temperate sensors at five different heights. That's 20 variables right there for a "linear" launch system.

Edited February 23, 2010 by Lone Ranger

[Hilarious Clinton 452]

I dare anyone with an open mind to compare human prosperity during the Medieval warming period to the devastation of the little ice age wich followed.

[Wei&Shu(Joe) 2]

You don't think it's import that Algore has a following similar to David Koresh, Jim Jones, and that guy that cut everybody's nuts off before they committed suicide waiting for to the comet to take them to Jupiter?

Not really skilled at staying on point, eh? BTW, you left Jesus off the list.

[one...two...tree 2,762]

Exactly! However, we are not talking about a simple polynomial here, but a series of simultaneous equations. Engineering problems mostly deal with x³ for static systems (dead load) and x⁴ for dynamic systems (live load). But, in the climatological models, you may be dealing with 100 or more dependent (variables that vary with the value of other variables) variables. Simplified weather equations can dependent on three or four variables, measured against time, and then the complexity of the model increases as you add more and more of those data sets. For instance, how many different locations do you want to place your sensors over a geographical area?

As an example, a simple 210 ft weather tower used to target incoming MRV's has wind speed, direction, barometric pressure, and temperate sensors at five different heights. That's 20 variables right there for a "linear" launch system.

Bill, have you ever stepped on a scale that you know was slightly off by a few pounds? Regardless of it being off by a few pounds, if we keep measuring your weight from that same scale over a period of time, we will be able to accurately detect a change in weight, even if the overall weight might be slightly off. According to what I've read, we only need about 50 - 100 reasonably distributed temperature stations around the globe to accurately measure the changes in the earth's temperature. Now I don't know how many temperature stations there are actually, but the logic is there and in plain view as to how the earth's mean temperature can be measured. Again, these aren't methods of measurement unique to climatology, nor are such predictions exclusive to climate change. The modern scientific processes that we've come to rely on for so many aspects of our lives are what are being used in studying climate.

[I AM NOT THAT GUY 5,715]

I dare anyone with an open mind to compare human prosperity during the Medieval warming period to the devastation of the little ice age wich followed.

That is another facet of the argument: Maybe all this global warming is not a bad thing!

Not really skilled at staying on point, eh? BTW, you left Jesus off the list.

And your point is?

[I AM NOT THAT GUY 5,715]

Bill, have you ever stepped on a scale that you know was slightly off by a few pounds? Regardless of it being off by a few pounds, if we keep measuring your weight from that same scale over a period of time, we will be able to accurately detect a change in weight, even if the overall weight might be slightly off. According to what I've read, we only need about 50 - 100 reasonably distributed temperature stations around the globe to accurately measure the changes in the earth's temperature. Now I don't know how many temperature stations there are actually, but the logic is there and in plain view as to how the earth's mean temperature can be measured. Again, these aren't methods of measurement unique to climatology, nor are such predictions exclusive to climate change. The modern scientific processes that we've come to rely on for so many aspects of our lives are what are being used in studying climate.

Ah, but they are! These are the complex models the climatologists are using to make their predictions. There is not a linear, polynomial, or even exponential relationship between the two variables, average CO₂ levels in the atmosphere and mean surface temperatures, exclusive of all other variables in the system. Why do you think these "predictions" are constantly subject to revision? When you rely on empirical data to determine trends, you fall into a logical trap, that something will occur, and often does occur, that just blew your theory out of the water. Hopefully, once you understand the mechanism, you can make better predictions, but in the end, science is often no better than astrology when it comes to predicting future events.

[one...two...tree 2,762]

Ah, but they are! These are the complex models the climatologists are using to make their predictions. There is not a linear, polynomial, or even exponential relationship between the two variables, average CO₂ levels in the atmosphere and mean surface temperatures, exclusive of all other variables in the system. Why do you think these "predictions" are constantly subject to revision? When you rely on empirical data to determine trends, you fall into a logical trap, that something will occur, and often does occur, that just blew your theory out of the water. Hopefully, once you understand the mechanism, you can make better predictions, but in the end, science is often no better than astrology when it comes to predicting future events.

The way by which you are measuring is linear (temperature stations). Even if you went and weighed yourself on 100 different scales, all giving you slight variations of measurement, as long as you kept record of your weight from each on of them consistently, that would be linear, would it not? Now suppose that other people using those same scales might throw the baseline off, you would still see a constant, linear change of weight over time. In other words, it matter less your actual weight than the actual change in weight which will be accurate within a margin.

[Wei&Shu(Joe) 2]

Exactly! However, we are not talking about a simple polynomial here, but a series of simultaneous equations. Engineering problems mostly deal with x³ for static systems (dead load) and x⁴ for dynamic systems (live load). But, in the climatological models, you may be dealing with 100 or more dependent (variables that vary with the value of other variables) variables. Simplified weather equations can dependent on three or four variables, measured against time, and then the complexity of the model increases as you add more and more of those data sets. For instance, how many different locations do you want to place your sensors over a geographical area?

As an example, a simple 210 ft weather tower used to target incoming MRV's has wind speed, direction, barometric pressure, and temperate sensors at five different heights. That's 20 variables right there for a "linear" launch system.

That makes a lot of sense. If you have good data but too much of it, your little head becomes confused, so it isn't good data anymore. If you have a good model that takes into account a large number of variables that actually effect global climate, it is too complex for your little mind to comprehend so it must be wrong. Of course, this type of complex (accurate) modeling couldn't be done without the help of computers so then you will make some derogatory comment about computer models and call it a day. It has always been interesting to me that denialists scoff at the impossibility of modeling the many variables accurately but then also tend to latch on to suggestions that none of the variables matter except solar activity or cloud cover or isohaline flow. It is an amazingly inconsistent religious belief system.

The point that you really really work hard to ignore, in order to save your ideological beliefs, is that the test of the models is not

1) Whether you think they are too complex or not complex enough

2) Whether the variables exceed some number that you decide is "manageable"

3) Whether you can confuse weather with climate enough to create a straw man to argue to

The only measure of the models is whether or not they predict reality as measured objectively by scientific standards. What can be said is that they do predict the rise in mean global temperature quite well, although they are less accurate at predicting the year to year variations. as to the consequences of warming, they sadly seem to be underestimating the impact fairly dramatically as things are happening now which the models would have placed many years in the future.

What level of scientific training do you have that allows you to arrogantly proclaim that the accuracy of the model is moot if YOU FEEL there are too many variables in the model? As most denialists do and as all people arguing for their religious beliefs do, you skip over the simple facts about the models and the data in order to create bogus arguments that are only intended to create space for you to insert your religious beliefs/conspiracy theories about climate change. You seem to repeatedly make the same point (and I find this point being made by every denialist I've ever spoken to) that the accuracy of the models at predicting reality is completely irrelevant and that whether or not you personally can comprehend modeling such a complex system (without study or experience) is actually the basis for measuring science.

AND I would bet that any of you who do this would not even accept the same arguments from your children. If your kid was pouring milk and kept pouring until the cup overflowed and there was the milk cascading down the side of your table and there was your child saying

1) It isn't my responsibility because many factors may have been involved in affecting the "fullness" of the cup. Consider that a sudden shift in barometric pressure might have effected the density of the air that was being displaced. A decrease in solar activity could have cooled the cup causing it to contract and decreasing the size of space I had to pour into. Why it might have even decreased the size of some of the porous areas of the material that would have held some of the milk I poured. How could you possibly create a model of milk pouring that would possibly let you conclude that my pouring of milk into the cup was the major cause of milk leaving the cup? There are just too many variables for you to ever be sure! Even if you use a computer! Kids have been spilling milk ever since time began and there's been no problem! I dare you to compare the economic conditions after the great medieval milk spillings and the little milk drought that followed because that would be entirely relevant to your consideration of what to do about my milk spillings.

2) If I was responsible for pouring the milk, then how do you know for sure that it won't be a good thing? Maybe this table material will be substantially rejuvenated by the milk bath, maybe little Billy is calcium and vitamin D deficient and his life will be saved by licking at the floor, maybe an entire colony of beneficial microorganisms will grow on the floor and create better health for all of us. You have to look beyond all the cleaning up of my mess and highly likely negative consequencesto see the unlikely, implausible, yet remotely possible benefits of my even now continuing to pour the milk into the full cup.

What is your response? "Good point"? "I'm glad you've been listening to me discuss climate change and caught on"? "That's my good little Sophist"?

What you return to repeatedly is not an evaluation of the actual models or their accuracy but a discussion of whether individual denialist's without specific training or knowledge of climate science "buy it". You evaluate climate science based on its concordance with your belief system and not on its concordance with reality. In doing so you sound like the Bishop who declared to Galileo that to believe that the Earth orbits the Sun is as incomprehensible as if one were to believe that Jesus was not born of a virgin. The comparison is to your beliefs and not to the actual science or to reality. I would presume that there are many people in less developed areas of the world who would be surprised and amazed if we told them that we take kidneys from one person and put them in other people who don't have functioning kidneys. Many of them would probably disbelieve us because it doesn't fit with their worldview. Does their disbelief change the fact that we do kidney transplants? Does it make it impossible? Of course not. Your beliefs have no greater power than theirs.

So, if you feel that I have mischaracterized your stance, then please, give us the reference to the paper describing the specific published model that you believe is inaccurate and let's all have a chance to review it and then you tell us specifically and with reference to reality and not beliefs, why you think that model is inaccurate. You can show us that you are correct about how many variables can be modeled and you can explain for us why the model anomalously predicts reality when there is no way that it could. That discussion would actually be helpful rather than hearing the sad, ignorant denialist belief system recanted again.