For those who don't know how science works:

it works with datasets. The data are never perfect, for example you can measure 20 degrees on one spot and a person a little further will measure 21 degrees. This gives a distribution of data... many measurements will be around 20 degrees and some a little higher, some a little lower. Suppose this set of measurements has 10% error.

Now we have a different dataset, for example the amount of CO2 in the atmosphere. Suppose this also has 10% uncertainty.

Now we have yet another dataset, for example the average oceanic water level. Suppose we have 30% uncertainty here.

The next step is to fit all of this to some model. Science works with theoretical models. These models include everything we know about natural processes and are as accurate as possible. It shouldn't get too perfect, because we cannot recreate reality, it should only be just as complex enough to be able to describe what we see around us.

Now... if we take the model and try to predict one dataset, we'll get a model with say a 10% uncertainty.

Now we take another dataset and apply it to the same model. We find that this model is also a good match to that other dataset. It now matches both datasets. The resulting uncertainty isn't 10%, but it's less, because we've fitter to BOTH datasets. The uncertainty is less, for example it's 5% due to the relative sensitivity of the model to the different datasets.

Now we take the 3rd dataset and apply it to the same model. We find that the model is also a good fit to those data. Because the data are independent, it gives us an additional constraint and reduces the overall uncertainty in the model even more, for example down to 3%.

If we repeat this for more and more datasets, we reduce the uncertainty each time. The more types of data we add, the less the resulting uncertainty.

In other words... noise in the data is reduced. We can distinguish noisy parts of on type of data better with the help of other data.

That's the beauty of IPCC and climate models. They gather information from various fields and while each field doesn't know for certain, the combination of all the knowledge will give a lot of confidence about the model.

That's how science works.

There's one caveat: models can be made such that they'll fit any data... that's the tricky part to avoid. However, models are tested for their sanity and robustness, and by now there are a pretty lot of data type that have to be fitted and this kind of eliminates this threat.

And this gives us the best possible state of knowledge we have at the moment. It's a culmination of all types of data and all our knowledge of how natural systems work.

To just disregard such knowledge because of a bit of noisiness, that's a bit crude to say the least and doesn't do justice to a major effort.

I've actually learned a lot over the course of this thread. I was initially kind of surprised so many people here doubted AGW - but I guess that was my own preconceptions. Many of the comments over the course of 30 pages reinforced the fact that for many people, quality of science and quality of information does not matter when it comes to matters that have a political, ideological, or religious aspect. There is actually a recent study that looked at this: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2319992

Essentially, people will actually change their view of facts/data/reality once it is presented in a political/ideological context. Where the facts/data were seen clearly and accurately before, once the lens of ideology is applied, they change their opinion. The study shows that emotion and ideology have a much more powerful hold over people compared to objective data/facts. Political views distort the truth so that people start from a conclusion and then simply seek out anything (no matter how spurious, as this thread has demonstrated) that supports their view.

It's the weight of atmospheric CO2. The rest of your tale is too weird to even respond to. 

No, it doesn't. Conducting scientific studies, analyzing data, submitting for publication, undergoing peer review, having everything scrutinized by thousands of scientists from various countries and academies does not have anything to do with ideology. The entire point of the scientific method is to rule out our biases as much as possible. It certainly isn't perfect, but it's far superior to any alternative way of understanding the world.

What I was describing knows no political boundaries either. Most Americans probably know who Bill Maher is - I think he is generally described as "liberal". He makes exactly these same mistakes. On the one hand he talks about climate change and AGW and the science that supports it but then the ideological glasses go on when it comes to looking at genetically modified foods. Then science goes out the window and it's Monsanto is evil, therefore GMOs are dangerous for consumption. It's the same with people who deny AGW. They start with some ideological/emotional premise like "I don't like the UN" or "No commie government is going to carbon tax me!" and then somehow that means that the science of AGW is flawed...

You guys are just obsessed with peer reviewed science.

Peer review has failed to show quality control.  Reviewers are more likely to find grammar errors than scientific errors.  BMJ(British Medical Journal) did a study using their own peer review process and none of their reviewers even caught all the errors they inserted into a work.  They also found that a single experienced editor worked just as well as peer review for judging the quality of work.

Peer review also doesn't check data.  Which is how SurfaceStations.org and U.C. Berkley both have peer reviewed analysis of the USHCN while one claims the alterations for time of observation bias and location changes resulted in accurate alterations, and the other says they've screwed the pooch and corrected unbiased stations and historically biased stations to match the trends of the more recently biased.  One or both of them have to be wrong, but peer review doesn't do anything about it because the reviewers are only checking the claims against the supplied information, not the accuracy of the information supplied.

Peer review gets you all kinds of idiocy.  Intelligent Design is peer reviewed, rather extensively considering how recent it is, not to mention derided.  Eggs being bad for you and good for you are peer reviewed, same with coffee, bacon, most of what we eat really.

Sodium cyclamate and saccharin causing bladder cancer are peer reviewed science.  They're both still illegal in various countries despite the absurdity of the claim.  It's physically impossible to consume as much of the stuff in food products as they were giving to rats, and people don't get bladder stones from it no matter how much they take.

You, like the thousands of scientists that have done work based on them and reviewed work based on them, assume the alterations of historical climate data by a small group of political appointees to be accurate.  I checked for myself, they were lying through their teeth ten years ago.  They've gotten better at lying in the interim, and they've had to make major corrections in some of the things they were caught on, but they're still fudging the old numbers.

It's why they still haven't had a single model accurately run future climate trends, they can't even get them right five years out.  They're working off data that says we've warmed more than we actually have, when the mythical acceleration doesn't present itself, they fail to trend with it.  The models you keep talking about are all wrong.  Hence the fact that they can't explain the lack of warming, every model they had showed an accelerated rise in temperature over the last decade, not a drop.

As expected. No model to challenge the current consensus, so what do you do? Tear down more of the foundation. If the process is flawed, the science upon which it is based must be as well, right?

When I was doing "post grad" training at Stanford, I was fortunate enough to work with two Editor-in Chiefs of one of the major medical journals. One of them is a good acquaintance of mine, who actually has a small bit of pop culture fame. My friend was EiC when one researcher was accused of falsifying data. Normally he is the nicest guy in the world...he excoriated that researcher when the fraud was discovered. In any walk of life you will find people who will be wrong: inadvertently or for secondary gain, etc. In his professional life, after caring for patients, nothing is more important to him (him being my EiC friend)than protecting the integrity of the Journal he was hired to head.

Here is what the peer-review process affords science-From Wiki "Peer review is the evaluation of work by one or more people of similar competence to the producers of the work (peers). It constitutes a form of self-regulation by qualified members of a profession within the relevant field. Peer review methods are employed to maintain standards of quality, improve performance, and provide credibility. In academia peer review is often used to determine an academic paper's suitability for publication." http://en.wikipedia.org/wiki/Peer_review

Is the peer review without weakness? NO. The peer review can be gamed, both by the researcher submitting the study (falsifying data) and the referee (who will reject a study based on good science because of personal bias, etc). But this is where things like repeatability of the experiment come into play.

Beyond that, however, I see the same tactics-cherry pick ("The peer review process is junk because a paper said that silicone breast implants cause fibromyalgia when in fact they don't. All peer reviewed studies are therefore nonsense") then deride but offer no alternative solutions that could improve the situation (just as you deniers...no you are not skeptics...do NOT do with offering an alternative theory and model to AGW).

It's all from the same playbook...identify a weakness in the foundation (today it is the peer review), then instead of finding a way to shore it up/offering a better solution, you declare the whole structure condemned. Thankfully, scientists do not listen to you guys.

And you are STILL harping on ten year old data...H E double hockeysticks, huh?

^^This. So saith the Frog 

I was also once on the side of AGW, and well... 

WTF 

Take screenshots and upload to a free image hosting service, or supply a link to the pdf.

to late, I seen that mile long headache maker 

So for the record: Give us a %. How much?

NP, I realize that. was kinda funny after I could focus again. 

From my post #657

Your question is an important one and yes, of course it does matter because if human activity was only responsible for a small percentage of global warming then that would be much better news. Unfortunately that isn't the case. You really should read the IPCC report summary at least (it seems most people in this thread haven't actually done so) if you are interested in the topic though as this is discussed. For example, in terms of surface temperatures only:

"It is extremely likely that 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."

http://www.climatechange2013.org/images/uploads/WGIAR5-SPM_Approved27Sep2013.pdf

The IPCC is fairly conservative here as other studies have concluded about 3/4 of climate change is man-made.

http://www.scientificamerican.com/article.cfm?id=three-quarters-of-climate

On the other hand, warmer temperatures are good for the economy. http://nextbigfuture.com/2013/10/an-unbiased-economic-scorecard-shows.html 

1)A good model will predict the future AS WELL AS THE PAST (the general theory of relativity predicts the effects of gravity for black holes as well as Mercury's orbit. Newtonian physics cannot describe black holes). A good model works in BOTH DIRECTIONS.

2)The overall TREND is upward. Nuff said (as has been said many times over by others in this thread).

Tactics-Cherry pick and then use the one cherry to try to destroy the whole orchard.