Please, no more YouTube conspiracy videos. Anybody can put up a slick-looking YouTube video.
Science is about DATA.
Science is not about arguing logic.
The YouTube demonstrates that NOAA has altered the record of data.
YouTube is not a source of data. It is source of what some people want you to believe the data is.
Yes it is, it’s used by many reputable bodies to convey information.
Stop attacking the messenger.
YouTube is used by known sources to convey information. That’s because those sources have been pre-vetted by the consumers of the information, who in those cases already knew the sources before the video was posted. That does not described the use made by MonteRCMS. People need to stop searching for support for their conspiracy theories by using YouTube searches. You can confirm literally any hair-brained theory that way.
Clearly, people who check the specific YouTube will learn how and where NOAA altered the historical data.
Start at 1:49
You can also review this week’s findings by Judith Curry:
Watching a video from an un-vetted source, people will learn whatever that source wants them to believe.
No more YouTube conspiracy theory videos masquerading as scientific arguments!
You could simply check it out to see what data you disagree with … [please be specific].
No. The data referred to (when there is data referred to) is not verifiable by me. I have to trust the person on the video. I choose no to do that. Good sources (not YouTube videos) contain links to primary or authorized sources. A guy talking at me of conspiracies does not do that.
I referred to the Cook survey because it is the one I am most familiar with, although it really doesn’t address the claim that the warming is extraordinary. It is a bit of an apples to oranges comparison. I referred to it, however, because if it is not true that “most” climate scientists believe man is largely responsible for what warming we have experienced then it is unlikely that most believe the warming is extraordinary.
Although the Cook survey is loudly touted to have found 97% agreement, here is what that paper actually said:
No AGW position 66.4%
Endorse AGW 32.6%
[Of that 32.6% that expressed an opinion, 97% endorsed AGW]
You made the claim; it would seem to be your responsibility to support it with evidence.
I don’t quite understand how this supports your point, but I do recognize when irrelevant statistics are being thrown around to muddy the waters. The “No AGW position 66.4%” stat has absolutely no bearing on the issue. I argued this with your about 6 years ago, and apparently you have forgotten.
So, to recap, what Cook did was to run an automated program that selected out all possible papers by abstracts according to the presence of certain climate-related keywords, like global temperature. This net was necessarily very wide to made sure they didn’t miss any relevant papers. Then they went through the papers and manually selected only those papers that took a position on global warming. Apparently 66.4% of them did not. But what does that mean, other than the initial automatic screening was too wide? Nothing! The fact that a climate scientist writes a paper that mentions global temperatures but does not take a position on AGW in that paper says nothing about what that scientist believes about AGW. It is just as if you never heard from him. And here we come to an important principle in sampling theory. If you sample a subset of a group for a specific characteristic, and if your sampling method was random or not obviously correlated with the characteristic you are measuring, the results of the sample can be reasonably applied to the whole set. That is why political polling can say what people in a state think about an issue after asking only a small fraction of those people.
So there is absolutely no reason to pollute your calculation of AGW agreement with the irrelevant statistic that was just an artifact of the two-stage method used by Cook. The only relevant statistic is the comparison between number who endorse AGW and those who reject AGW. The graphs you presented above do not give enough low-end resolution to display the tiny “reject” numbers, but it is clear from those graphs that AGW is overwhelmingly endorsed by those who wrote those papers.
Now if you want to claim that those papers are not representative of scientists who do not publish, that would a totally different argument, and I see no evidence of that either.
The fact that the percentage of abstracts that do not take a position on AGW has been going up over the years could be the result of there being more interesting things to write about as the science advances (such as novel instrumentation techniques). Also it could be a consequence of the fact that AGW is seen less and less as something that needs to be stated explicitly. After all, how many modern-day biology papers take an explicit position on the fact that many diseases are caused by microbes? That was big news and hotly debated when it was new. Now it is just assumed to have been taught in high school and need not be mentioned in a modern paper on differential diagnosis of hematuria.
Solar sunspot activity and periodicity since at least 649 BC.
Look up EVERYTHING.
pp 150-151, by the way.
This is a source of data, should you care to look at it. What it alleges is that the NOAA ground station data are becoming ever more divergent from satellite readings. This was back in 2010, and things have not improved in the interim.
NOAA proclaimed May 2009 to be the 4th warmest for the globe in 130 years of record keeping. Meanwhile NASA, UAH and MSU satellite assessments showed it was the 15th coldest May in the 31 years of its record keeping. This divergence is not new and has been growing. Just a year ago NOAA proclaimed June 2008 to be the 8th warmest for the globe in 129 years. Meanwhile NASA satellites showed it was the 9th coldest June in the 30 years of its record.
It is hard to insist that most scientists believe the warming has been extraordinary when it seems there is a significant disagreement on what the warming has actually been.
Science is about DATA.
Bad data = bad science.
Surfacestations project reaches 82.5% of the network surveyed. 1007 of 1221 stations have been examined in the USHCN network. The Google Earth map below shows current coverage.
70.6% of data locations are high by 2ºC OR MORE!
After months of work, our paper has been accepted , read summaries on the paper at these locations:
Dr. Roger Pielke Senior’s website here
Dr. John Neilsen-Gammon’s website here
Anthony Watts website here
Media Resource - download PDF here
Link to the paper (final print quality), Fall et al 2011 here (updated)
Fall et all 2011 supplementary information here
Why are you pointing me to another opinion piece? Point me to the primary authoritative data.
How do you determine how much divergent is significant?
Primary data please. Were they measuring the same thing? I don’t know. I only have your word and the word of Anthony Watts.
YOU MUST DO THE READING.
Do not accept anyone’s word.
Do the reading.
Yes, of those who took a position, most took the AGW side, but the claim is not that “of those who have a position” 97% believe in AGW, rather it is “of all climate scientists” 97% believe. The Cook survey addresses the former, but not the latter. If we found one paper out of 12001 that expressed the belief that sun spots were responsible for all the warming we have experienced while the other 12000 were silent on the issue would anyone really claim 100% of scientists believe the sun spot theory? If 2/3 of the scientists haven’t expressed a specific opinion it is ludicrous to imply they agree with those who have taken a position.
Right. The trend line of those who express belief in AGW is down; the trend line of those who take no position is up…and now we don’t care. If Cook’s methodology was valid then it should be valid now. If you don’t think it valid today then there is little reason to believe it was valid before.
I have done the reading and come to a conclusion. If you expect to convince anyone of a contrary view, you must present the contrary data, not just hint at it.
That’s where standard sampling theory kicks in, as I described.
No, because your example violates the “sufficient size” requirement of sampling theory. Cook did not.
It is not ludicrous. If I asked a random sampling of 1/3 of my neighbors if they though stray dogs have been a problem in our neighborhood and they all agreed, it would not be ludicrous to think that the 2/3 I did not ask also believe that same thing.
No. Only as a fraction of those who write about other things. No matter how you slice it, this “no opinion” stat is irrelevant to sampling theory.