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Originally posted by mschmoyer
Originally posted by mschmoyer
Yes, it can and will affect things down the road. Yes, humans have some impact on the climate – that’s how things work. Nothing happens in a vacuum. To what extent though are humans to blame though? Why are people looked at as weirdo conspiracy theorists for wanting more proof that to back up the claims that we're destroying the planet?
What if our impact is negligible, and the temp rise is caused by something else? What if a natural rise in temp is causing CO2 rise, and human activity has nothing to do with CO2 rise (eg. CO2 release from the oceans that are orders of magnitude larger than any anthropogenic source)? What if we go down the wrong rabbit hole because we didn’t fully understand the problem at hand and lose our one shot at doing the right thing?
The overarching point is that temperatures are rising. I get that. Yes, humans are impacting the climate – it’s impossible not to. But by assigning all the blame for a problem directly to humans you open the door to the punishment of humans. Is the science “settled” about temp rise being anthropogenic? In physics it takes 6-sigma confidence (99.99966%) in the data analysis to call something confirmed (eg. The Higgs Boson). In other sciences 5-sigma (99.7%) is acceptable (P = 0.05)
Scientists use p-values to test the likelihood of hypotheses. In an experiment comparing some phenomenon A to phenomenon B, researchers construct two hypotheses: that "A and B are not correlated," which is known as the null hypothesis, and that “A and B are correlated,” which is known as the research hypothesis.
The researchers then assume the null hypothesis (because it's the most conservative supposition, intellectually) and calculate the probability of obtaining data as extreme or more extreme than what they observed, given that there is no relationship between A and B. This calculation, which yields the p-value, can be based on any of several different statistical tests. If the p-value is low, for example 0.01, this means that there is only a small chance (one percent for p=0.01) that the data would have been observed by chance without the correlation. Usually there is a pre-established threshold in a field of study for rejecting the null hypothesis and claiming that A and B are correlated. Values of p=0.05 and p=0.01 are very common in many scientific disciplines.
The researchers then assume the null hypothesis (because it's the most conservative supposition, intellectually) and calculate the probability of obtaining data as extreme or more extreme than what they observed, given that there is no relationship between A and B. This calculation, which yields the p-value, can be based on any of several different statistical tests. If the p-value is low, for example 0.01, this means that there is only a small chance (one percent for p=0.01) that the data would have been observed by chance without the correlation. Usually there is a pre-established threshold in a field of study for rejecting the null hypothesis and claiming that A and B are correlated. Values of p=0.05 and p=0.01 are very common in many scientific disciplines.
Dong a quick search the only climate change data I see that has that that [undocumented] "confidence level" was from the IPCC a few years ago and they said this:
2007
"Most of the observed increase in global average temperatures since the mid-20th century is very likely [90 percent confidence] due to the observed increase in anthropogenic greenhouse gas concentrations
"It is extremely likely [95 percent confidence] more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together."
90% = “Most”
95% = “More than half” (2 sigma)
So,you'd think there would be some easily anayzable and repeatable data to back that up.
In the paper's “Summary for Policy Makers” (no agenda there, right? Here's the entire 375mb / 1552 page report) they very explicitly state:
An integral element of this report is the use of uncertainty language that permits a traceable account of the assessment (Box TS.1). The degree of certainty in key findings in this assessment is based on the author teams’ evaluations of underlying scientific understanding and is expressed as a level of confidence that results from the type, amount, quality and consistency of evidence and the degree of agreement in the scientific studies considered. Confidence is expressed qualitatively. Quantified measures of uncertainty in a finding are expressed probabilistically and are based on a combination of statistical analyses of observations or model results, or both, and expert judgement. Where appropriate, findings are also formulated as statements of fact without using uncertainty qualifier
Sounds a bit bullshitty, eh? If I told you we’re 95% sure that humans have no real impact on global temps, but then had that paragraph in my paper, would you still believe me?
From a dissenting scientist:
In defense of five standard deviations
There’s 32% risk that the deviation from the central value exceeds 1 standard deviation (in either direction), 5% risk that it exceeds 2 standard deviations, 0.27% that it exceeds 3 standard deviations, 0.0063% that it exceeds 4 standard deviations, and 0.000057% which is about 1 part in 1.7 million that it exceeds five standard deviation.
Global climate models have strayed so far from hard science that ALL model projections from 1979 exceed recent temperatures. Furthermore, the model means are now OUTSIDE the two sigma 95% level.
There’s 32% risk that the deviation from the central value exceeds 1 standard deviation (in either direction), 5% risk that it exceeds 2 standard deviations, 0.27% that it exceeds 3 standard deviations, 0.0063% that it exceeds 4 standard deviations, and 0.000057% which is about 1 part in 1.7 million that it exceeds five standard deviation.
Global climate models have strayed so far from hard science that ALL model projections from 1979 exceed recent temperatures. Furthermore, the model means are now OUTSIDE the two sigma 95% level.
If the standard were 2 sigma, particle physics would start to resemble soft sciences such as medical research or climatology and particle physicists would melt into stinky decaying jellyfish, too. (This isn’t meant to be an insulting comparison of climatology to other scientific disciplines because this comparison can’t be made at all; a more relevant comparison is the comparison of AGW to other religions and psychiatric diseases.)
So why do we have to rely on a “consensus of scientists”, each of whom wrote separate papers and have their own personal agendas, good or bad, when the data should be able to speak for itself? Where’s the definitive, peer reviewed paper that tells us the statistical correlation between human activity and global temp rise? With this many people on the case you'd think that would be available if "the science is settled."
With the massive amounts of policy and money transfer associated with a conclusion on this shouldn't the data lead to an irrefutable conclusion? A ton of people accept "scientists say ___!" but just winning over the that portion of the population does not change the [il]legitimacy of the conclusion. Someone needs to prove it and stop saying "oh, but these guys agree!" (even though it's been shown that "97%" statistic is patently false and many researchers attributed to that report have gone so far as to sue to have their names removed from it)
Again with the disclaimer: I'm still open to the idea that we're the cause of all this shit, but the entire discussion here was started because there is no definitive answer so instead they use a guy chosen for his nostalgic appeal to the demographic with the loudest voice in politics these days to host a slanted episode of a Netflix special... In my opinion.
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