Exploring Hydrocarbon Depletion
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Lore wrote:Fishman wrote:Er, I had to struggle with the math
A bat and a ball cost 110 cent together and the bat costs one dollar more than the ball. How much does the ball cost?
x + Y = 110, Y= 100 + x. Y=110- x 110-x = 100 +x 2x= 110 - 100 2x = 10 x = 5.
However, the "science " presented at the NC legislature is not quite so algebraic. Its a model, based on data, that had not fit the model so far. My preference is for a bit more data that fits the model, or a model that better represents the data. Asking "are we moving toward a fact-free future" based on ill fitting models, is manipulation of data. Not a fact-free future.
The models have a basis in historical evidence and accepted scientific theory. To ignore them is to ignore those facts. They need not be perfect, as most projections are not, to indicate a reliable certainty as to the outcome.
It's more correct to say that the models are based on fundamental governing equations much like those of Maxwell. You can chose not to believe in Maxwell's equations or the Navier-Stokes equations. But then you would be a loon who thinks, for example, that gravity is an opinion and not an objective fact.
We then tried a so-called “encompassing” test, which asks if each of the 22 GCMs does such a good job explaining the climate data that the socioeconomic data can be ignored, or vice versa. In all 22 cases the probability that you could leave out the socioeconomic data was computed as zero. But only in three of 22 cases did the data say you should keep the GCM, and in one of those cases the fit was negative (opposite to the observed patterns), so it didn’t count. So, again, only two of 22 climate models demonstrated enough explanatory power to be worth retaining, but in all 22 cases the data gave primary support to the socioeconomic measures the IPCC insists should not be used.
Then we estimated a weighted combination of the two types of models and asked if the socioeconomic data should be given all the weight, some, or none at all. The data never rejected the option of giving all the weight to the socioeconomic model, and always rejected giving it none.
Finally, we used Bayesian methods to check if the climate models might work better in some new super-model consisting of an unknown linear combination of some or all of the 22 GCMs, with a linear combination of some or all of the socioeconomic variables. Our data set yields 537 million such combinations, so we employed a computational method that searched over the entire model space and estimated the probability that each of our variables belongs in the overall, best model.
This approach identified the optimal combination as consisting of three of the seven socioeconomic variables and three of the 22 GCMs. The rest, it said, could be ignored. Redoing the encompassing tests confirmed that these variables contained all the relevant information in the data set. So we conclude that a valid model of the pattern of temperature changes at the Earth’s surface requires both measures of data contamination induced by regional socioeconomic variations and some climate-model processes.
The public perception of the climate problem is somewhat schizophrenic. On the one hand, the problem is perceived to be so complex that it cannot be approached without massive computer programs. On the other hand, the physics is claimed to be so basic that the dire conclusions commonly presented are considered to be self-evident. Consistent with this situation, climate has become a field where there is a distinct separation of theory and modeling. Commonly, in traditional areas like fluid mechanics, theory provides useful constraints and tests when applied to modeling results. This has been notably absent in current work on climate. In principle, climate modeling should be closely associated with basic physical theory. In practice, it has come to consist in the almost blind use of obviously inadequate models.
“The sciences do not try to explain, they hardly even try to interpret, they mainly make models. By a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work - that is correctly to describe phenomena from a reasonably wide area. Furthermore, it must satisfy certain esthetic criteria - that is, in relation to how much it describes, it must be rather simple.”
― John von Neumann
seahorse3 wrote:I find it hard to believe so many got the simple math problem wrong. I'm terrible at math but immediately knew the answer, so not sure I believe the "fact" that 50% of MIT students got it wrong. Can we fact check that please?
Pops wrote:His example of believing the NWS on weather records may not be the best because I'd think there are other observations to review,
People who have encountered a similar problem before may have retained a problem solving pattern that they can grab for a quick solution.
Others may instinctively realize that anything that seems so simple in the context the problem is presented is likely to have a hidden issue and slow down and think carefully about where the trick may lie.
But most will look quickly, think they recognize the problem and apply a simple pattern to solve it freeing their mind for the next problem to come along.
Supercomputers will achieve one human brain capacity by 2010, and personal computers will do so by about 2020.
Before everything went sideways, what was the general consensus back in the 90's for an explanation of the unusual climate phenomenon observed? Is there an alternate climate model than AGW which better fits the empirical evidence? If so, do you have any suggested reading on it? I am not really interested in sources that merely poke holes in AGW, but rather an alternate theory that fits the data.rockdoc123 wrote:Depends on what your definition of climate change is. If it adheres to Pielke Sr’s definition which is basically the fact that , well climate changes and there are a host of controlling factors then yes I agree with you….but if you are suggesting a definition that equates climate change with AGW then you are dead wrong. In fact there is a host of empirical evidence that points to major discrepancies between what that model would predict versus what has happened and is happening with climate. As I’ve pointed out numerous times there is no direct evidence for AGW, it is all modeled based on theory and those models produce non-unique solutions which means they can not be proofs.
In each of the cases you spoke of scientists continued to test the theories and continued to refine them….there was no huge swell of scientists arguing the science was settled it was business as usual for the scientists involved….theorize, test, re-theorize and test again. This was in fact the way climate science progressed up until the late nineties when it all went sideways.
AgentR11 wrote:quod erat demonstrandum
Before everything went sideways, what was the general consensus back in the 90's for an explanation of the unusual climate phenomenon observed? Is there an alternate climate model than AGW which better fits the empirical evidence? If so, do you have any suggested reading on it? I am not really interested in sources that merely poke holes in AGW, but rather an alternate theory that fits the data.
Also, I assume you agree with the observed data listed in my initial post from NASA. The point of contention is that you are arguing that it could be caused by a host of factors other than AGW?
I am trying to stay out of this and not turn an interesting thread into yet another rerun of the same tired old arguments.rockdoc123 wrote:Arctic ice is thinning partly due to warming of ocean waters but also do to adverse wind patterns. It shouldn't be surprising that ice would be retreating as we are still coming out of a glaciation.
smiley wrote:So how do we get out of this?
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