The difficulty is that once you decide that you can selectively ignore facts because of a huge conspiracy to falsify data, it becomes impossible for any amount of information to ever change your mind. So, the NASA data is falsified? And, the NOAA data, that's falsified too. And the University of East Anglia, of course. And the Berkeley data-- that was done specifically to address the problems people had with the NASA and NOAA data-- http://berkeleyearth.org/ That's faked too.? How about the Japanese data? http://ds.data.jma.go.jp/tcc/t... Also faked? The Australians-- fake too?

Once you conclude everything that disagrees with you is fake, your opinion is incontrovertible-- since nobody can confront it.

Right; there are both positive and negative feedbacks.

If you really want to know about the various climate feedbacks, try the summary in section 8.6 ("Climate sensitivity and feedbacks") of the the IPCC Fourth Assessment Report: https://www.ipcc-wg1.unibe.ch/... (the section starts on page 629)

It would be helpful here if everybody pointed to a common data set, so we all knew that we were talking about the same thing.

Here's the NASA-NOAA, showing NOAA (in blue) and NASA (in red) 's values for average temperature since 1880: http://www.wired.com/wp-conten...

You can see the "hiatus" in the far right of the graph: the curve to right of about 2000. If you blow up just this portion of the graph, and leave out everything to the right of 1998, you can make a graph which makes it appear that global warming has stopped.

So: the deniers look at this graph and say "warming stopped in 2002". People skeptical of the deniers say "There's a clear upward trend with random fluctuations; there's nothing statistically significant in the data after 2002; it's well within the range of variation in the record."

Or, you can say "There's a clear long-term rise. However, superimposed on that long-term trend are shorter term variations; these shorter term variations are also data, and the study of the causes of these variations may be a valuable subject for research."

Here's the Berkeley Earth graphic, with temperatures going back to 1870:
static.berkeleyearth.org/graphics/figure9.pdf

(also comparing models to measured data)

The link between solar activity and weather is discussed in great detail in the IPCC Working Group 1 report, with voluminous references to the literature; have you read it? You can find it here: http://www.ipcc.ch/pdf/assessm... The analysis is chapter 2.7, Natural Forcings, section 2.7.1 "Solar Variability."

Another effect discussed in the same report: section 2.7.2 "Explosive Volcanic Activity"

The key point is that we measure the sun, and we record volcanic activity. There haven't been changes in the sun or in volcanic eruptions that are sufficient to account for the temperature trend.

The 1991 Mt. Pinatubo eruption was an important event, because its effects were well measured.

One of them. NASA was established by the National Aeronautics and Space Act of 1958. In the list of what NASA was established to do, the first item is:
  (1) The expansion of human knowledge of phenomena in the atmosphere and space;

(building space vehicles was number 3 on the list)

Teledesic.

http://3csysco.com/Pubs/Telede...
https://www.isoc.org/inet96/pr...

In terms of greenhouse warming, it doesn't make much of a difference what altitude it's at. Slightly less pressure-broadening of the spectral line, I guess.

No, that's not true-- formally, they have only to show that a crime occurred. (That's called corpus delicti-- which, despite popular misconception, does not require a corpse.)

However, what they do have to show is how they know that the defendant is the one who did the crime. If understanding how they know this means they need to explain an internet investigation unmasking Tor anonymization, they may very well need some technical explanations.

Not according to the references I can find.
from http://newsoffice.mit.edu/2014...

"...methane is a potent greenhouse gas, as well as a significant byproduct of using natural gas — advocated by many as a “bridge” to a lower-emissions future. But a direct comparison between methane and carbon dioxide, the most abundant greenhouse gas emitted by human activities, is complicated: While the standard figure used for emissions trading and technology evaluation says that, gram for gram, methane is about 30 times as potent a greenhouse gas as CO2, scientists say that’s an oversimplification.

''As reported in a paper published today in the journal Nature Climate Change, authored by MIT assistant professor of engineering systems Jessika Trancik and doctoral student Morgan Edwards, this conversion factor (called the global warming potential, or GWP) may significantly misvalue methane. Getting this conversion factor right is challenging because methane’s initial impact is much greater than that of CO2 — by about 100 times. But methane only stays in the atmosphere for a matter of decades, while CO2 sticks around for centuries. The result: After six or seven decades, the impact of the two gases is about equal, and from then on methane’s relative role continues to decline."

Or, if you prefer Wikipedia as a source: https://en.wikipedia.org/wiki/...

No, worse than that. They're not taking random noise (it's an unpowered CCD array). They're saying that maybe a different CCD array is receiving the same photons, because if you measure one ccd array, some of the photons it sees might have hit the unpowered one. ...And the random noise that they're not taking isn't making any images, because the energy of cosmic background radiation isn't high enough to produce an electron hole pair in a silicon CCD.

And that's why we have more detailed models.

But it ends up being a no-win situation, when the objective is to criticize rather than to understand. If the model is simple, they say "that model's too simple! The real world is complicated! You need to include X Y and Z!". And if the model is modified to include X, Y, and Z, they say "The model is too complicated! You can't believe any complicated models like that!"

The actual answer is, you start simple, understand the simple models, and progressively add complexity. This is the way science is done. Planets don't move in uniform elliptical orbits. Nevertheless, starting with Kepler's laws and then adding peturbations is a good way to analyze planetary motions.

As for comparing models to reality, and asking what we know and how we know it, there isn't really time for me to go through this model by model since 1967 (since I do have other things to do). I'll again suggest as a start reading the WG-1 summary report, it goes into detail on this (and has references for more details). The one I'm more familiar with is the fourth: https://www.ipcc-wg1.unibe.ch/... (although there seems to be a more recent one, fifth, here:
http://www.climatechange2013.o... )

According to the link, this is from "The report by Japan Society of Energy and Resources (JSER) ... the academic society representing scientists from the energy and resource fields".

This is something I've noticed. While climate scientists mostly agree with the physics models, whenever you see a headline about a group of scientists who disagree, when you look at the details, you usually find it's commissioned by the energy industry. There was a headline article in Forbes a year or so back, similar: the headline was "here's a poll of hundreds of scientists who aren't sure about global warming," and when you looked at the details, it was a survey of the people working in the Alberta coal and petroleum extraction industry.

When you look at the details here, nothing seems to be new. People have been looking for a connection between solar activity and climate for a hundred years; this has been studied a lot, and as far as I know, nobody has found a correlation large enough to drive climate. At a top level, the issue is summarized in the IPCC WG-1 report: http://www.ipcc.ch/pdf/assessm... (There's a fifth assessment report out now, but the one I'm familiar with is the fourth, so that's what I link to.) A summary is in section 1.4.3, (Solar Variability and the Total Solar Irradiance); and the more detailed analysis is chapter 2.7, Natural Forcings, section 2.7.1 "Solar Variability."

(I'll also note that solar forcing tends to have a different signature from the greenhouse effect warming. Solar forcing tends to increase day/night temperature differences; the greenhouse effect tends to reduce them).

On the subject of the Japan Society for Energy and Resources critique, this is the page from the Japan Meteorological Agency: http://ds.data.jma.go.jp/tcc/t...
So the 2009 criticism by the Japanese Society for Energy and Resources doesn't seem to have made any influence to the actual people in Japan studying climate.

Right.

By present-day standards, the Manabe and Wetherald model is very simple. This was indeed the criticism at the time-- "but the model doesn't account for XXX effect"-- and all of the present-day models basically work on adding in the various feedback effects you mention.

The simplicity is both a flaw, but also a virtue. Basically, Manabe and Wetherald is a model of the greenhouse effect, and nothing but the greenhouse effect: while there are a hundred more sophisticated models these days, now all of the criticism is "but how do you know that you didn't get XXX feedback effect wrong?" Well, Manabe and Wetherald didn't have all the bells and whistles-- it was the first real greenhouse effect model that incorporated real-world, measured infrared absorptions, accurate radiative transfer, and convective equilibrium, but that's all.

This is typically the way science is done. First you make the back of the envelope models, then the simple models, then you progressively add more refinements.

Surprisingly, the other effects matter less than you might think. Clouds was the first criticism made (and all modern models have cloud effects)-- but clouds aren't actually a huge effect. If clouds blocked visible and infrared light equally well-- and to first order they do-- cloud cover would have little effect on average temperature: the infrared radiation scattered downward heats the planet, the albedo scattering cools the planet, and in the simplest model the two balance out. Of course, the real world isn't the simplest model, but in some places clouds can actually increase the temperature (you see this in models of carbon dioxide clouds on early Mars.) What clouds mostly do is tend to equalize the daytime and nighttime temperatures. This is actually a good way to separate cloud effects from infrared absorption effects. (Another way is to look at vertical profiles).

As for the constant relative humidity assumption-- well, what would you suggest would be a better input assumption? Again, it's a good simple assumption. It does implicitly include a feedback effect, but it's pretty much the most transparent way to incorporate it. Most importantly, note that by assuming constant humidity, there aren't any adjustable parameters. If you worry that models have been "tweaked" to make the output match the data, well, there isn't any feedback to tweak here.

With the advent of supercomputers in the 70s, models got more detailed. The next good summary of models would be the U.S. National Academy of Sciences report 1979, by which time the report could look at and compare several models. The '79 NAS report is a good go-to reference for models of the '70s; and is still a bit before the politically-motivated attacks started muddying up the conversation. That still gives 35 years of data that can be compared to prediction -- a long enough run to average out some of the year-to-year variation and compare the models to reality. I graphed (but haven't yet added the most recent data, 2014, yet) and, yes, the measured temperatures fit inside the error bars of the NAS models.

After that, models got much more sophisticated very quickly (and so did the attacks on the models, resulting in a fast evolution as ever more sophisticated models addressed ever more complicated critiques). Today there are hundreds, and probably thousands of models being run. Comparing them to measurements is more like looking at statistics than looking at an individual model. There's some good graphs comparing models to reality in the IPCC working group 1 report, if you're interested in tracking them down.

Manabe and Wetherald 1967.