The environmental debate thread

[Dak]

Now there's a paragraph the other side could never get away with, and a perfect demonstration not only of the fact that this is indeed a political argument, but of which side of this political argument is politically acceptable on this forum, and which side is not.

 

and then two mods came along, and the invective mysteriously stopped and we started discussing the science

[Cap'n Refsmmat]

Indeed. Please stay on topic.

[Realitycheck]

Can anyone tell me why a .2 C difference in average temperature makes a bunch of gigantic ice shelfs break off into the ocean and start melting away?

 

I have been somewhat of a casual global warming proponent and the graphs that swanson provided seem to be good evidence to back up global warming claims for the past 30 years. However, when we cross-reference this with the global CO2 output chart, we don't find this surge in CO2 output, which leads me to believe that other factors are contributing to the temperature surge from 1976-2007. Of course, this does not prove that global warming is not occurring either.

 

http://cdiac.ornl.gov/trends/emis/glo.htm

[SkepticLance]

You need to remember that the 0.5 C warming over the past 30 years is a global average. In the Arctic, the warming is 3 times that, or +1.5 C. This has little effect in the Arctic winter, when temperatures are well below minus 1.5. However, in summer, a lot of the sea temperature is slightly positive. An extra 1.5 C is enough to cause melting of sea ice. It even melts some ice on the fringes of the land, but not ice any distance from the sea.

 

Of course, this means that in other parts of the world, warming has been a lot less than 0.5 C. The United States saw 0.4 C warming. In the tropics, it was much less than that.

[Chris C]

Can anyone tell me why a .2 C difference in average temperature makes a bunch of gigantic ice shelfs break off into the ocean and start melting away?

 

I have been somewhat of a casual global warming proponent and the graphs that swanson provided seem to be good evidence to back up global warming claims for the past 30 years. However, when we cross-reference this with the global CO2 output chart, we don't find this surge in CO2 output, which leads me to believe that other factors are contributing to the temperature surge from 1976-2007. Of course, this does not prove that global warming is not occurring either.

 

http://cdiac.ornl.gov/trends/emis/glo.htm

 

I would spend a bit less time looking at emissions, since concentration is what matters. I haven't kept up with emission numbers lately, whether they have leveled off, declined a bit, or what have you. I know that since around the 2000 mark they have accelerated a bit, and are showing growth now (see http://www.pnas.org/cgi/reprint/0702737104v1 ). In any case, we're still adding CO2 to the climate system, throwing the carbon cycle a bit out of balance and *concentration* is increasing since it is being put in faster than the oceans can remove, and it is the rise in concentration that promotes a warming planet. Infrared radiative transfer isn't too concerned with emissions.

 

For your first question, the number is around 0.8 C now, which still may look rather small, but globally averaged it is rather significant. Remember that since the last ice age around 10,000 years ago, the global temperature has not fluctuated by any more than + or - 1 degree C, and the rate of rise is pretty quick now (which matters for adaptation purposes). The "average temperature" includes the oceans, which take a lot longer to heat up, so on land the number is actually larger, and the poles (especially northern hemisphere) you get significant effect as well. For perspective on the numbers, you only need to reduce global temperatures around 3-4 C to get an ice age, so rapid fluctuations of a degree (and projected 3 C at doubling of CO2) is significant. -- chris

 

P.S.

 

For those who have followed my posts, or are just interested, I have a blog up at http://chriscolose.wordpress.com/ if you'd like to respond to any of the posts. I'm working on part 3 of the "Basic Radiative models/Earth’s climate system analysis" series now, which may be useful as a general overview of how our climate system works (see Pt. 2 for what happens when you add greenhouse gases)

[SkepticLance]

To Chris C

 

Your figure of 0.8 C warming. Can you tell me what time period it refers to? I assume it is average global temperature change?

[waitforufo]

Generally speaking a model is a mathematical expression used to first describe observed phenomena and to then predict future phenomena. The process goes something like this. A person has data from an event or experiment. A curve fit is performed and from that curve fit a mathematical expression is defined. That mathematical expression is a model. Generally further experiments are then conducted to prove the model.

 

For example, if I have a cannon, a barrel of powder, and a large supply of cannon balls, I can come up with a mathematical expression for ball distance traveled based on variables such as powder charge, firing angle, cannon ball weight. That model will work well as long as the cannon is well made, the balls fit well, and powder can be made with uniform performance.

 

I can develop the model above without knowing anything about gravity, air drag, chemistry, metallurgy, etcetera. All I have to have is the data from a large number of experiments and the ability to define a function from curve fit to the data taken. With this model I can determine accurate firing solutions.

 

Modelers in fact don’t need to know much science. For example, people developed models of an earth centered universe that were very accurate at predicting the location of stars and planets. These models are still in use today for navigation. Bad science, but good models.

 

Now, some scientist may come along one day and explain how my cannon model works based on scientific principals of gravity, air drag, chemistry, metallurgy, etcetera, but I don’t need to know any of these things to develop my model. In fact, such knowledge may hinder the modeling process if I were trying to make known science match the data taken. Modelers fall into this trap all the time.

 

Now what happens if the cannon is not well made, the balls don’t fit well, and powder can not be made with uniform consistency? Well, I can still eye ball a curve fit and develop a mathematical model but I might not be able to hit much. At least I will have to take more shots. Let’s hope the target isn’t moving.

 

So what about models of natural systems? Let’s say I’m a pharmaceutical manufacturer. I develop a new chemical compound that I think will help control diabetes. Now I could test the effects of the chemical compound on human health with a computer model. If I created such a computer model perhaps much could be learned about human health. But, my guess is most people would not take the drug unless it was first tested in animals, and then monitored human trials. Most people would not trust a computer model. They would be skeptics. Too many of the variables are just unknown for a good computer model of the human system.

 

Climate models are even worse. At least in the pharmaceutical example above, animals and human volunteers can be used for testing. How is this done with the climate? The IPCC publishes a chart showing the uncertainty of various known global warming and cooling forces. These uncertainty ranges appear to be quite large. So based on limited set of forces of which we have limited knowledge, as show in the IPCC uncertainty charts, I’m to accept changes in my standard of living. Sorry, but I have a snowmobile I want to ride for no other reason but recreation.

[iNow]

To Chris C

 

Your figure of 0.8 C warming. Can you tell me what time period it refers to? I assume it is average global temperature change?

 

 

Wow. Glad to see that it matters to you too. Maybe he'll ignore you and you can ask him six times for this information, at which point he can come back and tell you check wiki.

 

 

 

 

 

Climate models are even worse.

Tell us specifically which models you challenge and why.

 

 

The rest of your post about changing how you live is really rather selfish and short sighted, but let's talk about the specific models you think fail. Drawing a mental picture of modelling difficulties does not prove we cannot model complex systems. Precisely which model(s) do you challenge and why?

[jryan]

The Mann model of 1998 comes to mind as a model that is poorly designed (the famous "hockey stick"). It has been shown that his normalization methods are such that his model will return a hockey stick graph even with random data.

 

It is also troubling to me to see an overlay of "proxy data" models that only seem to coincide when the average global temperature is fairly well determined, but vary dramatically when projected into the past.

 

Furthermore, as I read these studies on current and furture warming, the often used "urbanization" adjustment also is fairly troubling. I wish that I could find the studies that I used in a previous debate, but in one study there was a calculation for "urbanization" with regard to global temperature, and a second follow-up study that barrowed the urbanization calculation, but had to adjust it because the barrowed calculation would have resulted in "cooler than expected" measurements. So in essence they changed the calculation to produce warmer readings. That just struck me as odd at the very least.

 

Finally, for now, it bothers me that from theory to collection to evaluation many studies seem to be done "in house" rather than using a double blind methodology to evaluate data correlations. There was a study done some time ago where it was shown that even absent direct manipulation of data, statisticians have a 75% chance of supporting a correlation when they know the expected result, whereas it is fairly even when the expected result is unknown. This is why the medical field requires double blind studies when producing medication. It would seem even more important to conduct double blind studies in a field where their is a "consensus" in the exptected outcome.

 

I have little doubt that the Earth has gone through a warming trend, I am less convinced of the scale, and even less convinced of the abnormality of the current increase in forcings, or the warming trend for that matter.

 

We can take politics out of the discussion all we want, but the simple fact remains that a huge amount money and political capital has been and will be spent on what is currently seen as an oncoming anthropogenic catastrophe. In that light, I would like the information to at least be accurate.

 

Also, a warming trend of the last 30 years in not entirely accurate, as for the last 6 years the temperature has remained fairly stable. Claiming thirty years of warming is like me claiming that the Washington Redskins have been a Superbowl calibre football team for the last 30 years... even though that stopped being the case in 1991.

[iNow]

The Mann model of 1998 comes to mind as a model that is poorly designed (the famous "hockey stick"). It has been shown that his normalization methods are such that his model will return a hockey stick graph even with random data.

While the methods of the 1998 Mann et al. paper have been challenged, the results align quite well with other studies. These other studies did not suffer the problem in methods that the 1998 Mann et al. paper did, and they remain accurate and unchallenged. In other words, if we ONLY had the 1998 Mann et al. data on which to rely, and that data was flawed, THEN your comments would have greater merit, but since we don't, they don't.

 

 

 

 

 

Furthermore, as I read these studies on current and furture warming, the often used "urbanization" adjustment also is fairly troubling. I wish that I could find the studies that I used in a previous debate, but in one study there was a calculation for "urbanization" with regard to global temperature, and a second follow-up study that barrowed the urbanization calculation, but had to adjust it because the barrowed calculation would have resulted in "cooler than expected" measurements. So in essence they changed the calculation to produce warmer readings. That just struck me as odd at the very least.

 

 

I'll just show you this, and indicate that the above is of too little relevance to worry (emphasis mine):

 

 

http://www.skepticalscience.com/argument.php?a=32

This confirms a peer review study by the NCDC (Peterson 2003) that did statistical analysis of urban and rural temperature anomalies and concluded "

Contrary to generally accepted wisdom, no statistically significant impact of urbanization could be found in annual temperatures

... Industrial sections of towns may well be significantly warmer than rural sites, but urban meteorological observations are more likely to be made within park cool islands than industrial regions."

 

Another more recent study (Parker 2006) plotted 50 year records of temperatures observed on calm nights, the other on windy nights. He concluded "temperatures over land have risen as much on windy nights as on calm nights, indicating that

the observed overall warming is not a consequence of urban development

".

 

 

 

 

Finally, for now, it bothers me that from theory to collection to evaluation many studies seem to be done "in house" rather than using a double blind methodology to evaluate data correlations. There was a study done some time ago where it was shown that even absent direct manipulation of data, statisticians have a 75% chance of supporting a correlation when they know the expected result, whereas it is fairly even when the expected result is unknown. This is why the medical field requires double blind studies when producing medication. It would seem even more important to conduct double blind studies in a field where their is a "consensus" in the exptected outcome.

Now this is actually quite humorous. How do you suppose we prevent the climate from knowing whether or not it was in the control group?

 

You are correct that double-blind studies are generally viewed as more stringent and less prone to bias, but can you explain how this approach could be applied to climate research?

 

 

 

 

I have little doubt that the Earth has gone through a warming trend, I am less convinced of the scale

Have you seen the historical trends? The scale is abundantly clear. What is it that is preventing you from being convinced?

 

Instrumental record: http://www.ncdc.noaa.gov/paleo/globalwarming/instrumental.html

 

 

 

 

Also:

 

Past 2,000 years: http://www.ncdc.noaa.gov/paleo/globalwarming/paleolast.html

Prior to 2,000 years ago: http://www.ncdc.noaa.gov/paleo/globalwarming/paleobefore.html

 

 

 

 

 

 

 

We can take politics out of the discussion all we want, but the simple fact remains that a huge amount money and political capital has been and will be spent on what is currently seen as an oncoming anthropogenic catastrophe. In that light, I would like the information to at least be accurate.

Precisely with which data do you challenge the accuracy?

 

 

 

Also, a warming trend of the last 30 years in not entirely accurate, as for the last 6 years the temperature has remained fairly stable.

Fairly stable in it's increase, perhaps.

 

 

 

 

 

 

 

 

Why is it that doubters never seem to have specifics or data to support their claims, just a bunch of hand-waving?

 

 

 

 

 

Here, they can present their position, and any evidence/data/references that they might have to support their position. While we can go on and either verify or debunk their claims.

 

Have you noticed a lack of data and evidence, or is it just me?

[jryan]

I also would like to insert the following study into the debate:

 

http://www.ecd.bnl.gov/steve/pubs/HeatCapacity.pdf

 

I found his conclusion rather interesting, as it appears to be rather moderate in it's estimates.... not coming off as a full fledged skeptic, nor one that you could include in the AGW camp.

 

In this study Wilson found that the total final warming due to anthropogenic doubling of CO2 (currently expected around 2100 AD) to be roughly 1.1 degrees K, 0.7 of which has already occurred.

[Chris C]

To Chris C

 

Your figure of 0.8 C warming. Can you tell me what time period it refers to? I assume it is average global temperature change?

 

I was referring from pre-industrial time; sorry, I should have been specific.

[iNow]

I found his conclusion rather interesting, as it appears to be rather moderate in it's estimates.... not coming off as a full fledged skeptic, nor one that you could include in the AGW camp.

 

In this study Wilson found that the total final warming due to anthropogenic doubling of CO2 (currently expected around 2100 AD) to be roughly 1.1 degrees K, 0.7 of which has already occurred.

 

Thanks for the link, but in that paper he expressly states that his analysis rests on a simple single-compartment energy balance model and it is not representative of the overall climate system since it is an analysis based on a simplified model.

[jryan]

While the methods of the 1998 Mann et al. paper have been challenged, the results align quite well with other studies. These other studies did not suffer the problem in methods that the 1998 Mann et al. paper did, and they remain accurate and unchallenged. In other words, if we ONLY had the 1998 Mann et al. data on which to rely, and that data was flawed, THEN your comments would have greater merit, but since we don't, they don't.

 

And again I have to question a these models as they only seem to correlate when the temperature was fairly well known. It appears more that the measured temperature is informing their model soley... but when left to the proxy data, they begin to vary.

 

The issue is not that these models can't model a period of time where the data is already fairly well known... it is that we are supposed to be using the current trend and measuring it against a historical period in which anthropogenic CO2 was NOT a forcing medium. It is in THIS stage of the evaluation that the models fail. We don't really know from these models whether the current anthropogenic assited GW is even abnormal, as we can't really determine what "normal" is.

 

We then want to take these same models and project them into the furture and pretend that their seeming agreement for a scant 100 years or so out of their full 1200 years qualifies them as a good predictor. And at least on of those studies varies greatly from Mann.. and it happened to be the study done as a contemporary to the Mann study.... so I am left wonder how it could be that the later studies agree with the Mann study that was critically flawed, and so divergent from the Jones study.

 

Again, it would seem that expectation may be driving the modeling, and the expectations, until recently, were weighted heavily on the Mann study.

 

 

Now this is actually quite humorous. How do you suppose we prevent the climate from knowing whether or not it was in the control group?

 

You are correct that double-blind studies are generally viewed as more stringent and less prone to bias, but can you explain how this approach could be applied to climate research?

 

You don't need to use the "weather" as the control group. You might as well ask "how can you tell the illness that it is a control group?". We are talking about correlations of proxy data and temperature, and of modeled temperature -vs- actual measured data. In a way, you can see the effect of the double blind study in that Mann comparison chart above. For the most part, the various studies agree when they knew what the outcome actually was, but disagree when nobody is certain. Were these studies done completely through double blind methodology, you would more likely see just as much divergence in results even during the periods where the "answer" was already known.

 

But again, we want models that can project into the unknown... right now they can't agree on that historically, so why trust them on future data?

 

 

 

 

 

Have you seen the historical trends? The scale is abundantly clear. What is it that is preventing you from being convinced?

 

Again, what are you claiming with that graph? That the Earth is warming? No convincing needed.... now show me where that graph is supposed to convince me that that trend is something out of the ordinary.

 

 

Ok, now look at that graph for a second and tell me what I am supposed to be seeing.

 

What I am seeing is that based on this particular study, the entire mid-holocene period is completely unlike the previous interglacial. It seems to cap lower in "degrees change", and plateau, rather that drop "abruptly" (in terms of a graph that measures in 10,000 year incriments). But this anomoly, if you can call it that, is something that is shown as being the case for over 10,000 years... and not unique to our minute period of industrialization. So I don't see what that chart really does to prove or disprove anthropogenic global warming (AGW).

 

 

Precisely with which data do you challenge the accuracy?

 

See: Everything you have posted. It doesn't meet the criteria for proving AGW... or at the very least, AGW as an impending global catastrophe that requires trillions of dollars spent.

 

 

 

 

Fairly stable in it's increase, perhaps.

 

 

 

 

Actually, no. Look at the chart again. The last 5 years, given the (well, what I assume to be) standard error from the black brackets shows no statisticaly discernable variance in that time.

 

That isn't a chart of the average increase for each year, rather the variance from the norm. So they may have been hotter than previous years on that chart, but that doesn't show continued warming.

 

Why is it that doubters never seem to have specifics or data to support their claims, just a bunch of hand-waving?

 

The kinds of data that you are tossing out is really all I need to make my point.

 

 

Have you noticed a lack of data and evidence, or is it just me?

 

All I really need to do is wait for data to be posted, and ask questions. That is the beauty of being a skeptic. I am not here to prove that global warming doesn't exist. That is a scientific impossibility even if it actually doesn't exist. Where it is needed, I will provide studies and evidence to support my claim, but when my job is to disecting global warming studies, you can just provide them for me.

[swansont]

The Mann model of 1998 comes to mind as a model that is poorly designed (the famous "hockey stick"). It has been shown that his normalization methods are such that his model will return a hockey stick graph even with random data.

 

It is also troubling to me to see an overlay of "proxy data" models that only seem to coincide when the average global temperature is fairly well determined, but vary dramatically when projected into the past.

 

Furthermore, as I read these studies on current and furture warming, the often used "urbanization" adjustment also is fairly troubling. I wish that I could find the studies that I used in a previous debate, but in one study there was a calculation for "urbanization" with regard to global temperature, and a second follow-up study that barrowed the urbanization calculation, but had to adjust it because the barrowed calculation would have resulted in "cooler than expected" measurements. So in essence they changed the calculation to produce warmer readings. That just struck me as odd at the very least.

 

Finally, for now, it bothers me that from theory to collection to evaluation many studies seem to be done "in house" rather than using a double blind methodology to evaluate data correlations. There was a study done some time ago where it was shown that even absent direct manipulation of data, statisticians have a 75% chance of supporting a correlation when they know the expected result, whereas it is fairly even when the expected result is unknown. This is why the medical field requires double blind studies when producing medication. It would seem even more important to conduct double blind studies in a field where their is a "consensus" in the exptected outcome.

 

I have little doubt that the Earth has gone through a warming trend, I am less convinced of the scale, and even less convinced of the abnormality of the current increase in forcings, or the warming trend for that matter.

 

We can take politics out of the discussion all we want, but the simple fact remains that a huge amount money and political capital has been and will be spent on what is currently seen as an oncoming anthropogenic catastrophe. In that light, I would like the information to at least be accurate.

 

Also, a warming trend of the last 30 years in not entirely accurate, as for the last 6 years the temperature has remained fairly stable. Claiming thirty years of warming is like me claiming that the Washington Redskins have been a Superbowl calibre football team for the last 30 years... even though that stopped being the case in 1991.

 

Many claims, and not a single citation. Learn from the examples of others here: make a claim, back it up.

[Chris C]

I also would like to insert the following study into the debate:

 

http://www.ecd.bnl.gov/steve/pubs/HeatCapacity.pdf

 

I found his conclusion rather interesting, as it appears to be rather moderate in it's estimates.... not coming off as a full fledged skeptic, nor one that you could include in the AGW camp.

 

In this study Wilson found that the total final warming due to anthropogenic doubling of CO2 (currently expected around 2100 AD) to be roughly 1.1 degrees K, 0.7 of which has already occurred.

 

Thanks for the link. This is a very simplified model of climate, and amounts to something like representing Earth’s climate as a single entity, with one time scale (ex. the oceans and land have a single heat capacity).

A "short timescale" does not allow for "in the pipeline warming" (our current warming is not at a 380 ppmv like atmosphere). Meanwhile, there is no heat exchange between the atmosphere and ocean and land (and the water heats up as quick as the ocean). In reality, an atmosphere heats quickly then slowly toward equilibrium. Of course this means the atmosphere's "time scale is short" which may or may not be applicable to the oceans. In other words, you can stop the accumulation of greenhouse gases and still get warming that we've already commited ourselves to (about half a degree C).

 

You can allow "one time constant" for simplified climate models, but not for the real world. In that sense, Schwartz is probably a good first step at understanding climate sensitivity, but will not be accurate in a climate system with multiple timescale responses to a forcing.

 

See this...

http://www.jamstec.go.jp/frsgc/research/d5/jdannan/comment_on_schwartz.pdf

 

Right now, one can easily calculate the temperature response for doubling the amount of CO2 with all other things equal at 1.2 K on basic physical principles. see my blog post at http://chriscolose.wordpress.com/2007/12/25/basic-radiative-modelsearths-climate-system-analysis-pt-2/ (part 1 may help as well). But, you do have feedbacks in the climate system, notably water vapor, clouds, the presence of a lapse rate which the greenhouse effect depends upon, ice-albedo, etc. There are more uncertanties here, especially for cloud paramterization, but there is a range of ΔT(2x CO2) = 3.0 (+ 1.5; - 1) K. From real-world observations and paleoclimatic analogs, there is really no physically plausible way to stretch this to a really low or a really high climate sensitivity, despite the existence of uncertainty. Unfortunately, that uncertainty leaves much more room for bad things to happen on the high side than it does for the warming to be much lower than the "mean" estimate.

[jryan]

Thanks for the link, but in that paper he expressly states that his analysis rests on a simple single-compartment energy balance model and it is not representative of the overall climate system since it is an analysis based on a simplified model.

 

He isn't dismissing his own study by admitting that. He is taking a new angle at determining global temperature and tolerances and he is concluding that more studies should be done using a more elaborate form of his method. His findings diverge drastically from current models, while at the same time supporting the findings of studies such as Lyman who observed rapid heat loss in the oceans between 2001 and 2005, which would not be supported by current models.

 

I'm fairly certain he didn't do all that work just to say "Here is what I found, but my study is unimportant because the others are more complex".

 

Many claims, and not a single citation. Learn from the examples of others here: make a claim, back it up.

 

I tend to save citations for things that I figure others here may not be aware of. I assumed you would know about "urbanization" or "urban heat island" or "UHI".

 

But if you don't know about UHI you can read a study that uses it here.

 

You can also do a search on Realclimate to obtain several discussions about is usage.

 

As for the rest of it, it is my opinion. I could link you back to the post if you like.. but I fail to see the point in that.

[iNow]

And again I have to question a these models as they only seem to correlate when the temperature was fairly well known. It appears more that the measured temperature is informing their model soley... but when left to the proxy data, they begin to vary.

 

The issue is not that these models can't model a period of time where the data is already fairly well known...

I ask you again... specifically which models do you challenge and where?

 

 

 

You don't need to use the "weather" as the control group. You might as well ask "how can you tell the illness that it is a control group?". We are talking about correlations of proxy data and temperature, and of modeled temperature -vs- actual measured data.

My comment implied that you did not fully understand the double-blind methodology, and you haven't addressed my question which pertained to how this methodology can be applied to climate research.

 

 

 

In a way, you can see the effect of the double blind study in that Mann comparison chart above. For the most part, the various studies agree when they knew what the outcome actually was, but disagree when nobody is certain. Were these studies done completely through double blind methodology, you would more likely see just as much divergence in results even during the periods where the "answer" was already known.

Again, will you please elaborate on how the double blind methodology could be applied in this instance?

 

 

 

But again, we want models that can project into the unknown... right now they can't agree on that historically, so why trust them on future data?

They do agree. Did you miss my previous post on this?

 

 

To your comments on the charts I shared, they were in response to your argument that we cannot model climate. I ask you where precisely you challenge them or their accuracy.

 

 

 

See: Everything you have posted. It doesn't meet the criteria for proving AGW... or at the very least, AGW as an impending global catastrophe that requires trillions of dollars spent.

Again, I did not share those charts as proof of anthropogenic global climate change. That issue is well argued and agreed upon elsewhere. I shared the charts in response to your broad sweeping generalizations regarding our understanding of past climate and our modelling ability.

 

 

 

 

 

Actually, no. Look at the chart again. The last 5 years, given the (well, what I assume to be) standard error from the black brackets shows no statisticaly discernable variance in that time.

 

Here's a different one, then:

 

 

 

 

 

As you can plainly see, the slope on the trend line is clearly positive.

 

 

 

I'm fairly certain he didn't do all that work just to say "Here is what I found, but my study is unimportant because the others are more complex".

 

I agree. Why are you arguing this point with me?

 

 

 

To your comments that you don't need to share data to support your claims, I advise you start. This is, after all, a science forum.

[Realitycheck]

According to the data presented on this page, the correlation between CO2 levels and temperature is quite straightforward. For some reason, I have never seen it displayed like this. I wonder if there is something questionable about the data. Notice how, on the second chart at the end, CO2 levels are rising above 375 currently. Doesn't CO2 start getting toxic for humans around 380? The first chart runs through 1999 while the second chart runs through 2007.

 

http://www.freewebs.com/fyiglobalwarming/

 

 

[jryan]

See this...

http://www.jamstec.go.jp/frsgc/research/d5/jdannan/comment_on_schwartz.pdf.

 

 

I removed most of the quote for simplicity. Thanks for the link... but I am not sure I entirely agree with that comment by Foster et al either. As was said earlier, Schwartz admits that he is using a simplified model, and that further study is called for, but in reading that comment, I can't agree with the method used.

 

Essentially the study comment appears to not disagree with Schwartz on his assumtion that a simplified time scaling model is potentially useful.

 

What he DOES do is completely alter the model as presented by Schwartz, inserts his on time scales, selects one he thinks would be most advantageous to Schwartz, and reruns the model. Is it just me that finds this approach strange? Further he dismisses the 5+/-1 y Time scale, and then runs a model designed to treat incidental measures as trending on monthly data. This also seems strange.

 

Am I reading this wrong or has Foster et al simply said: "We can't dismiss his assertion of a single time scale out of hand.. so here is his model with a bunch of changes we made and it doesn't work."

 

According to the data presented on this page, the correlation between CO2 levels and temperature is quite straightforward. For some reason, I have never seen it displayed like this. I wonder if there is something questionable about the data. Notice how, on the second chart at the end, CO2 levels are rising above 375 currently. Doesn't CO2 start getting toxic for humans around 380?

 

http://www.freewebs.com/fyiglobalwarming/

 

No, it would need to be significantly higher. We are current at about 383ppm, I believe the toxicity begins at a few thousand ppm, but you will get a better answe here I am sure.

 

I ask you again... specifically which models do you challenge and where?

 

THis again? I have already pointed to the models posted in response to my comment on Mann, if you want to know, go back the response, and my response to it. Note that those models listed only correlate well when the temperature is already known.

 

I commented on your own cited studies:

 

 

So to answer your question: Briffa, Esper, Mann, Jones and Mann, and Jones. If you want to know what issue I have with them based on your citation, go read what I wrote.

 

My comment implied that you did not fully understand the double-blind methodology, and you haven't addressed my question which pertained to how this methodology can be applied to climate research.

 

Well, first of all, it can be applied to the gathering and vetting of proxy data. If the theory of correlation between ice cores, tree rings, et al are accurate and reliable, then a double blind study could and should be used to correlate that data, but at the moment it isn't. The same people that collect the data do the correlations.

 

Secondly, it is entirely possible to model temperature without actually knowing that you are modeling "temperature". If you have established sound proxy data, sound direct observation, and you submit that data for analysys, it wouldn't matter if you called a given variable "anthropogenic CO2" or "potato", technically the statistical model would be the same.

 

Are you assuming that the modelers, and statisticians MUST know the data is for temperature forcings, and global temperature before they can do analysis? Numbers are numbers, are they not? Or are you suggesting that the site studies that gather ice cores MUST know that they are collecting data for a GW study, and that "oh yeah, most people think you should find *this*" and shown then the projections from a model?

 

 

 

They do agree. Did you miss my previous post on this?

 

To your comments on the charts I shared, they were in response to your argument that we cannot model climate. I ask you where precisely you challenge them or their accuracy.

 

They only really agree duiring the period where the outcome was already measured. Pardon me for not being wowed by a models that get it mostly right when we know what right is, but diverge when they all try to model a period where the outcome is not known.

 

So, I challenge their accuracy for the periods prior to the 1900s, because the further back in time you go from that point, the less they agree on the Y axis.

 

Again, I did not share those charts as proof of anthropogenic global climate change. That issue is well argued and agreed upon elsewhere. I shared the charts in response to your broad sweeping generalizations regarding our understanding of past climate and our modelling ability.

 

And again, how can the point be so well agreed upon (are you saying it isn't open for debate???) when your very own models don't agree? I would have to assume that the models are pretty accturate when they knew what accruate was... so they will become accurate in the future? I'm not buying it.

 

 

Here's a different one, then:

 

As you can plainly see, the slope on the trend line is clearly positive.

 

And as you can plainly see, you are arguing against a point that NOBODY HERE IS ARGUING. I am not saying that the data does not show a warming trend. Can you get that, please? Reread that last statement as many times as it takes to sink in.

 

No I ask you, how much of that is AGW? Obviously some. But how much? And more to the point, how abnormal is this 150 year trend compared to previous periods? The trouble is that we don't actually know the answer to that question, yet we want to make decisions on the future as if we do. And those furture decisions revolve around models that we can't even get to agree on historical projections..

 

 

To your comments that you don't need to share data to support your claims, I advise you start. This is, after all, a science forum.

 

 

So what, I am not allowed to question your sources based on my own observation? What you propose is not "science" as much as it is rival fans arguing the merrits of their favorite teams. If I have a question about a source of yours, I will ask you.... and I don't need a source to verify that I have a question. That is as much science (or moreso) as just wrote linking to skepticalscience.org.

[Realitycheck]

Some interesting numbers here, also, though it still adds up to pollution in the end.

 

Carbon dioxide is released to the atmosphere by a variety of natural sources, and over 95% percent of total CO2 emissions would occur even if humans were not present on Earth. For example, the natural decay of organic material in forests and grasslands, such as dead trees, results in the release of about 220 gigatonnes of carbon dioxide every year. This carbon dioxide alone is over 8 times the amount emitted by humans.

 

http://en.wikipedia.org/wiki/Carbon_dioxide_in_the_Earth's_atmosphere

[Chris C]

I removed most of the quote for simplicity. Thanks for the link... but I am not sure I entirely agree with that comment by Foster et al either. As was said earlier, Schwartz admits that he is using a simplified model, and that further study is called for, but in reading that comment, I can't agree with the method used.

 

Essentially the study comment appears to not disagree with Schwartz on his assumtion that a simplified time scaling model is potentially useful.

 

What he DOES do is completely alter the model as presented by Schwartz, inserts his on time scales, selects one he thinks would be most advantageous to Schwartz, and reruns the model. Is it just me that finds this approach strange? Further he dismisses the 5+/-1 y Time scale, and then runs a model designed to treat incidental measures as trending on monthly data. This also seems strange.

 

Am I reading this wrong or has Foster et al simply said: "We can't dismiss his assertion of a single time scale out of hand.. so here is his model with a bunch of changes we made and it doesn't work."

 

 

 

No, it would need to be significantly higher. We are current at about 383ppm, I believe the toxicity begins at a few thousand ppm, but you will get a better answe here I am sure.

 

A simple example will show the problem with the Schwart inference: the time response of the surface after a volcano is not indicative of an overall time constant of the system. See a paper in Nature for example (http://www.nature.com/nature/journal/v439/n7077/full/439675a.html )

 

Abstract- "This huge eruption slowed sea-level rise and ocean warming well into the following century.

 

We have analysed a suite of 12 state-of-the-art climate models and show that ocean warming and sea-level rise in the twentieth century were substantially reduced by the colossal eruption in 1883 of the volcano Krakatoa in the Sunda strait, Indonesia. Volcanically induced cooling of the ocean surface penetrated into deeper layers, where it persisted for decades after the event. This remarkable effect on oceanic thermal structure is longer lasting than has previously been suspected and is sufficient to offset a large fraction of ocean warming and sea-level rise caused by anthropogenic influences."

 

I do understand that simple models are good for understanding something even if they don't reflect complex real-world behavior, and I don't think the Schwartz paper is "useless." The problem is if you take some time-constant "mean" and apply a whole system into a "single cell" when in fact there are multiple interacting cells. That is, the lag response time of the land/atmosphere/ocean.

 

As for CO2 at "deadly" concentrations, you do need to get into whole number percenatages by volume, which 380 parts per 1,000,000 is not. Not near that, so I'd be much worried about warming before suffocating.

 

Some interesting numbers here, also, though it still adds up to pollution in the end.

 

 

 

http://en.wikipedia.org/wiki/Carbon_dioxide_in_the_Earth's_atmosphere

 

Indeed, the carbon cycle is also a beautiful thing.

[jryan]

Some interesting numbers here, also, though it still adds up to pollution in the end.

 

http://en.wikipedia.org/wiki/Carbon_dioxide_in_the_Earth's_atmosphere

 

 

Here is another somewhat painless avenue for reducing CO2 emissions:

 

Put out all the coal fires.

[iNow]

No I ask you, how much of that is AGW? Obviously some. But how much?

Most of your post was just strawmanning and logically fallacious appeals, and additionally you have still failed to supply evidence in support of your claims, nor supplied any specifics on where the supposed inaccuracies exsit. So... I'll just share more data in support of my position, specifically, here are two more sources to address your specific point above graphically:

 

 

 

http://solar-center.stanford.edu/sun-on-earth/glob-warm.html

 

 

 

 

 

 

http://ipcc-wg1.ucar.edu/wg1/Report/AR4WG1_Print_Ch02.pdf

 

[SkepticLance]

To iNow

 

Take a look at your graph of calculated forcings. Note how the net cooling of 1940 to 1976 is not explained by that graph. Note how the warming of 1910 to 1940 is not explained by that graph. Note how the line showing solar forcings is almost a straight line (ignoring minor fluctuations) for much of the time, in spite of our knowledge of relatively massive changes in sunspot activity. Note how there is no line representing the effect of variations in cloud formation.

 

Conclusion : Predictions based on these figures will be poor.