Quote of the Week #3

Hello, MarkT !! Having followed Lindzen for a decade, my take on this is his attempt to inject humility to both sides, not a subtle jab. Humility is key IMHO. One has to realize that the “science is never settled” and either side has the potential to be proven wrong, always. It is a hard pill to swallow if you are convinced you are right. We must fully understand the oppositions point of view in order to dismantle it, and I expect the same from their side. It makes me wonder that sites like RC and DeSmog are so insecure, that they cannot allow the slightest refutation to their position. I find I strengthen my position when I am forced to question the validity of my viewpoint. Ted Clayton mentioned contrarians in a very good post about their importance to a quality debate. Truer words were never spoken. The fact that I am deleted from posting on RC and DeSmog should tell you all you need to know about their position. Cheers and Happy Easter to all, …….

to Lamont:
“That is only “implausible” if the models are assumed to a priori be incorrect. If the models are, in fact, in the process of being proven correct then the data should trend towards supporting the models, and the corrections to bad data should be more in line with models than against them. This is exactly the behavior that would be expected if the models are right.”
Huh? And how does “data” become ‘bad’ data? Don’t tell me, let me guess — it’s when it doesn’t agree with “the model”.
Rubbish – the only thing ‘a priori’ is that data is real and models are, well, models — and proper science follows the data, it doesn’t ‘fix’ the data.
The quote from Dyson, about getting outside in the mud, is very appropriate — whereas tinkering with the data to save the models is the very definition of “Game Boy” science.

Re good models and bad data.
There is considerable experience of adjusting data, where a model has previously been shown to be robust and accurate. As just one example, this occurred years ago (late 1980’s) in a company for which I worked. The products we developed and sold were a suite of sophisticated computerized simulators. One simulator in particular had been tested and proven accurate in several live applications with modern manufacturing plants owned and operated by sophisticated clients. Their data was very good.
Then we began selling that proven simulator to other clients in slightly less advanced countries. The simulator did not match one client’s data, when run in predict mode. The client was understandably unhappy, and viewed the simulator as a bunch of junk. So we began the delicate task of investigating their data collection and measurement systems. In the end, the simulator was proved correct, and the client found some data errors that they corrected.
The climate models are not anywhere close to being at a point where one should adjust data to match the models’ predictions. First, one must adjust the model so that there is good agreement between model predictions and carefully validated data.
The company I worked for was in the field of chemical kinetic simulations, with highly non-linear simultaneous equations, but the lessons learned there are applicable in any simulation / data field.
Do the climate scientists not know this? Do they not realize there is an entire body of knowledge, and practitioners from many fields that know this? Do they not realize what laughingstocks they are, when they adjust data to match a demonstrably unverified model?
Is this the new scientific method?
One can only imagine what Richard Feynman would have to say about this…

Tom (16:20:04),
Thanks for checking my french on climate-feedback. I have familiarity with feedback application & study, in engineered systems, but would like to get on a better footing with it, in natural systems – especially climate. Can you point me to sources I can use to get it down pat?

I don’t see the big deal. Clearly sometimes reality is wrong, and needs to be adjusted to values that will keep the government dollars flowing.
Now, some will claim that reality should not be defined by what governments are willing to pay for, but these denialists are ignoring hundreds of government-funded studies to the contrary.

Lee Valentine (16:59:15) and (17:13:41),
I searched Google using ‘co2 plant respiration’.
“High Carbon Dioxide Boosts Plant Respiration, Potentially Affecting Climate And Crops”
http://www.sciencedaily.com/releases/2009/02/090209205202.htm
and
http://news.illinois.edu/news/09/0209co2.html
” Plants draw CO2 from the atmosphere and make sugars through the process of photosynthesis. But they also release some CO2 during respiration as they use the sugars to generate energy for self-maintenance and growth. How elevated CO2 affects plant respiration will therefore influence future food supplies and the extent to which plants can capture CO2 from the air and store it as carbon in their tissues.
While there is broad agreement that higher atmospheric CO2 levels stimulate photosynthesis in C3 plants, such as soybean, no such consensus exists on how rising CO2 levels will affect plant respiration. [emph. added]
“There’s been a great deal of controversy about how plant respiration responds to elevated CO2,” said U. of I. plant biology professor Andrew Leakey, who led the study. “Some summary studies suggest it will go down by 18 percent, some suggest it won’t change, and some suggest it will increase as much as 11 percent.” ”
The transpiration of water you mention is a different effect, but related and possibly connected.

This comment reminds me that everything I hear about AGW is Baaaaddddd, not a single good thing is ever mentioned.

Ted Clayton (18:34:35):
While there is broad agreement that higher atmospheric CO2 levels stimulate photosynthesis in C3 plants, such as soybean, no such consensus exists on how rising CO2 levels will affect plant respiration. [emph. added]
Correlation is 2:1, i.e. plant respiration consumes in average 50% from the carbohydrates they produce by cell respiration. The rate varies with species, age and season.