Bill Glasheen wrote:Why must I build a mathematical model, fraught with limitations and assumptions? It's much easier to do a cross correlation between CO2 levels and temperature through history. It goes beyond a simple statistical correlation. It shows that temperature leads CO2 levels, and not the other way around.
What, YOU are taking the easy way out?!?! Now I really am disillusioned!
Seriously though, there are a lot of assumptions going on in the approach you are taking, not the least of which is that the timing data of both are accurate. But more importantly you are focusing on a single tree, in this case a single graph, and not the forest of evidence. This chart of model results for example supports the dominant theory that observed temperature changes are being influenced by both natural and human causes:
Here is a version that separates the three model results:
ALL scientists are on "your" side, eh? NOT! But nice try. I like your debating style.
What is interesting about your debating style Bill is your frequent use of distraction and diversion techniques to move a debate away from certain areas, when you do not ignore those areas all together that is. As you know, my statement had nothing to do with sides.
Pray tell, what in life has "no negative effects"? Certainly no treatments in medicine, and yet many treatments with potential side effects in a large population are considered evidence-based and state-of-the-art.
When a system's parameters change, the system changes. Change is associated with positives and negatives. There are winners and losers. The only questions are how much, to whom, and the net effect.
Yes but we cannot always bury our heads in the sand and wait to see what happens, particularly given what is at stake in this case. And we cannot make decisions based only on what helps the rich. In all likelihood some corporations and investors will benefit greatly from the decreased Arctic ice cap in the future, but at what cost to the native Arctic peoples and wildlife, the coastal peoples flooded out, the island nations that disappear, etc. Climate change has global impacts, it affects everyone, and is too big to be left only to the market or those who get rich off of the market to decide.
To use your example, think of curbing climate change as a medical treatment, with benefits to the many but potential negative side effects to the few.
... the mathematical models used by environmental scientists. Quite the contrary, Glenn, I'm highlighting that.
Take for instance the recent BP-induced Gulf Oil Spill. Who would have predicted that natural forces would rid us of much of the spilled oil? We didn't, but it happened.
Our environment is robust in ways that we can't quite fully understand yet. We mathematicians write wonderful models that work well in narrow ranges. But violate the assumptions or go outside the bounds that the equations in the model "behave" and all bets are off. Truth be told, mathematicians are great at linear models, and suk at modeling a nonlinear world. And some nonlinear phenomena (a.k.a. a system in mathematical chaos) are predictably unpredictable (a.k.a. the butterfly effect).
Furthermore, you can't build a mathematical model which accounts for principles and processes you aren't aware of.
And finally... Climate Change happens. It has happened to extremes long before humans started sending stored carbon dioxide back into the atmosphere where it came from.
You of all people know we have to start somewhere. You build models based on what is known, and modify or build new models as more information becomes available. Highlighting the simplicity of models is one thing, working to improve them is on a different level, and what the scientists are attempting.
And again, sending things back where they came from, particularly in a period of time that at best moves the decimal place five places to the left, is not automatically a good thing.
A good read when you get the chance.
It speaks to the problems that exist when presenting new and/or "unpopular" ideas.
I read it, first ~25 years ago for a history of geography course and then again last year for a political science course. It models a particular period in the history of physics, and as you say it works well within that range but has been critiqued for being too broadly applied. The picture you used is of the second edition, I recommend the third edition where Kuhn himself rejects some of the interpretations and applications of his ideas. Elsewhere Kuhn is quoted as saying "I am not a Kuhnian!" as another statement of rejecting how some 'followers' were using his ideas.
But to your point, the counter-claim that anthropogenic influences on climate do not exist is hardly a new one, it is the null hypothesis after all, and almost everyone would like it to be true so it is not particularly unpopular. It simply is not supported by the evidence...maybe someday though.
And there is your problem. Where there is money, there is corruption. Academia - so dependent on grants and publishing - isn't immune to a disease of the unwashed masses living at the foot of the ivory tower.
I think one factor here is that you have a hard time believing people willingly choose career-paths for reasons other than money. Discovering something new and the thrill of the chase is what drives most academic scientists, particularly in something like climate research...it certainly is not for wealth. The grants enable them to go where they could not otherwise go. For example my university has a strong Arctic program and the researchers travel there to take measurements, test their models, see first hand what is happening, and talk to the people directly affected, in other words they get out of the ivory tower to better model the real world. Grants enable that kind of science. But even with that, in general most academic publications do not come from grant-supported research (it varies depending on the field of course, your field of training probably has a higher association between grants and publications due to the nature of the research and the technology requirements...not to mention there simply is a lot of money thrown at medical and engineering research). I am a good example of this, my master's thesis was not grant supported, my dissertation research is not grant supported, and I am currently working on two publications unrelated to my dissertation work that are also not grant supported.
The biggest flaw with your corruption hypothesis is tenure. Once a faculty person makes tenure he or she is no longer dependent on grants or publishing and could conceivably coast until retirement. I have yet to meet anyone who has done that however, because everyone I know enjoys research. My advisor is 70 and has yet to talk about retiring, and he is very active teaching, researching, presenting at conferences, and publishing. He simply loves it. Another professor I work with on some outreach got his PhD in the early 1970s and says he wanted to work in a field that tackles big problems, and he ended up choosing climate research because he also wanted to work in something that was not controversial (little did he know how that would change a decade later). He too is close to 70 and still travels to the Arctic every year. He simply loves it. And even those who retire usually do so as emeriti, continuing to research and advise but no longer teach in a classroom. People who are intimately aware of the evidence, and the strengths and weaknesses of that evidence, and are no longer dependent on anything still support the model that fits that evidence. Think about that.