Oranges may be natural medicine, but they're not homeopathy.

The theory of homeopathy is that you cure a disease with a drug that reproduces the symptoms of that disease (that's the prefix "homo" in homeopathy-- "same"). So, oranges would only be useful as a homeopathy remedy if eating oranges gives you the symptoms of scurvy. ...and then homeopathy takes that drug and dilutes it until not a single molecule originating in an orange is in the drug. The homeopathy cure for scurvy would be "take a drink of water from a glass of water that was filled from a glass of water that was filled from a glass of water that had one drop of orange juice in it.

Nice back of the envelope calculation! but you're off by a factor of 6.

Solar irradiance is absorbed by the disk area of the earth, pi r^2. But the earth's surface area is 4 pi r^2. And the solar energy absorbed is multiplied by the (1-albedo). So you're off by 4/(1-a), where a is about 0.30 to 0.35.

... and then you're assuming the difference between zero solar activity, and current solar activity. But over the time scale over which the global warming we're discussing occurs, the change in TSI isn't that high. Here's a graph of the historical Total Solar Irradiance:
http://lasp.colorado.edu/home/...
and the variation between 1900 and 2015 is considerably less than that.

We know that it doesn't explain the warming this century.

With no actual evidence, you are assuming ideological and institutional bias as in input assumption. You're assuming NOAA is biased. NASA is biased. The National Science Foundation is biased. The National Climatic Data Center is biased. The Berkeley Earth Surface Temperature project is biased. The British Met office (formerly the Meteorological Office) is biased. The Climate Research Unit is biased. The Japanese Meteorological agency is biased. The Australian Bureau of Meteorology is biased. The Commonwealth Scientific and Industrial Research Organization is biased. The Centre National de la Recherche Scientifique is biased. The Max-Planck-Institut für Meteorologie is biased

These have all made models and measurements confirming the greenhouse effect. ...isn't it slightly stretching credibility that all of these institutions-- and many others-- on four continents, all happen to be biased, and all biased in exactly the same way?

But, yes, if you assume that pretty much everybody who has ever studied the field is biased, and you can ignore their work... well, yes, you can ignore a heck of a lot of data, yes indeed.

While there is indeed a higher total solar irradiance (TSI) with higher solar activity, that variation in irradiance is plus or minus one tenth of one percent. If, as you suggest, this is driving the observed warming, then there is a huge amplifier in the system.
But if there's a huge amplifier in the system, you have to explain why this doesn't amplify the contribution of infrared re-radiated by greenhouse gasses. Why would some input forcing get amplified, and other input forcing not amplified?
We measure all of this. When the scientists say "this effect can't account for the warming," this is because they are dealing with measured quantities.

(I will also note that TSI has a different warming signature from greenhouse effect: the greenhouse effect changes increase night time temperatures much more than TSI)

Basically, what you're saying boils down to "I won't pay attention to what the scientists actually say, and I haven't done a back of the envelope calculation showing it's plausible that they might be wrong, but I just refuse to believe them."

And I'm a scientist. I look at the data.

One tenth of one percent.

I hate to keep harping on the same things, but the effect of solar variability has been analyzed in mind-numbing detail in the last few decades, and it just isn't there. Try the summary in chapter 8 of the WG-1 report
http://www.ipcc.ch/report/ar5/...

So, what you're now saying is that the little ice age is not due to the Maunder minimum, but you're hypothesizing that it might have been due to some other sunspot minimum for which we have only proxy data.

Unfortunately,
(1) proxy data on solar activity is somewhat harder to interpret (see, for example, review article here: http://solarphysics.livingrevi... )
  (2) nobody looking at the record of proxy reconstruction has been able to find a firm correlation to global climate (although there are some regional climate correlations),
(3) there still isn't any accepted mechanism connecting sunspot number to climate,

This analysis looks like you have a result you want, and you're going back through the data trying to select data to try to fit the result. If this were actual science, you would need a correlation coefficient. How well does the variation in (proxies for) sunspot number fit the variation in (proxies for) climate?

All of the scientists doing the actual studies of this sort say the effects seen are far too small to explain the current warming trend: see, for example Solanki et al. 2004 study of sunspot numbers over the past 11,000 years and climate: http://www.nature.com/nature/j... "we point out that solar variability is unlikely to have been the dominant cause of the strong warming during the past three decades", or the review of dozens of studies here: http://www.skepticalscience.co...

But, returning to the topic, we seem to agree: the little ice age cannot be attributed to the Maunder minimum.

And when you dismiss all data that doesn't agree with you-- which is what you're doing-- then it is completely impossible to ever overturn your conspiracy theory that all the science ever done on climate happens to be wrong.

In fact, it's not. This is currently the best hypothesis that fits the data, including the dates. There may be a better hypothesis later. This is the way science is done; you gather data, make a hypothesis that fits the data, and see if later work confirms or overturns the hypothesis.

Paleoclimate resesearch, and most specifically modelling the climate variations in the late middle ages is indeed difficult, because not only don't we have contemporary measurements of all the input parameters, we don't have good measurements of the temperature, either. (Modelling contemporary climate is much more accurate-- we have lots of data on both the input (the solar output is well measured) and the climate (not just average temperatures, but diurnal variation, seasonal variation, latitude and longitude variation, etc. all of which must fit the modelling, although the AGW debaters only ever look at the year-by-year changes.)

The paper referenced, however does use a pretty convincing proxy for temperature change in the little ice age: they looked at the dead flora preserved in the Arctic ice cap. This dates the little ice age to a start in 1375-1400, with a second cooling period around 1450 AD. That is about the time when the Vikings abandoned their settlements in Greenland (they kept Church records; the last document in Greenland (a marriage certificate) was dated 1408.)

Unfortunately, this is THREE HUNDRED YEARS before the Maunder minimum. So it's really hard to think that the Maunder minimum caused the little ice age.

So, here's the summary.
1. There is no well-understood mechanism connecting sunspot numbers to climate.
2. The only connection between the Maunder minimum and the little ice age is a rough coincidence in timing.
3. But the more detailed examination of timing shows that the little ice age started much earlier.

Well, except nobody knowns whether the Maunder minimum even had anything to do with the little ice age, except for the coincidence of timing. The best understanding at the moment is that the little ice age was due to volcanic eruptions: http://news.agu.org/press-rele...

People have been looking for a solar cycle-weather connection for years, but not really finding one.

About plus or minus 0.1% change in total solar irradiance between solar maximum and solar minimum:

http://science.nasa.gov/scienc...

Well, except that every solar cycle since I can remember, I've heard somebody predicting that the next solar cycle is about the start a new Maunder minimum, and it will mean mini ice age. Every one.
This one is a prediction based on fitting a model only to the last three cycles. i'm not impressed.
For reference, here's the MSFC page on solar cycle modelling: http://solarscience.msfc.nasa....

Apollo 6 had two engines shut down early, but the upper stage burned longer to compensate, so the vehicle still made orbit.
The S-IVB didn't restart in orbit-- but since that was after it already made orbit, that counts as an in-space propulsion failure, not a launch vehicle failure.

Apollo 13 had a second-stage engine shut down early, but, again, the other engines burned longer to compensate, and the launch was a success. Launch wasn't the problem with Apollo 13.

So, I'd rate Saturn-V at 100% success rate as a launch vehicle, if the criteria for success is "getting the payload successfully into orbit".

Of course, with only 13 launches, it's not had as long a record as many other vehicles.

Nice video here: http://gizmodo.com/watch-all-1...

Well, that reason is certainly not reliability-- Russian rockets have been pretty failure prone lately.
http://spacenews.com/proton-fa...
http://spacenews.com/progress-...
http://spacenews.com/russian-s...

Atlas-V and Delta-IV been doing pretty good, though: so far both have had a 100% record for reaching orbit, although each one has had one launch with an underperforming upper stage that put it into lower-than-planned orbits.

Yes, that's what they said.

However another explanation of the data is that many products fail early, and thus many of the people who buy products early in the release cycle ("early adopters") will buy many products that will fail. Is the set of "early adopters who adopted products that then failed in the market place" a set that can predict future failure in the marketplace? Well, they didn't show that.

It's easy to predict the past.

# of flops chosen (position in set)

Those particular numbers (one in four, two in four, two in three, >2/3) are indicative: the study set consists of people who made only three or four choices. (If it were larger numbers, the cut points wouldn't be such even numbers)

This is not significant.

And, more significantly, that's way too few to tell if membership in a set is predictive.

Certainly some early adopters pick products that don't take off, and mathematically some of these will have done it multiple times.
But the article claims that some people are actually predictors-- that their product choices have predictive value for product failure.
Is this actually true? It's easy to select out a set of people who have bought failed products, and then cull out of that set the ones who have not also sometimes bought successful products. But is this group statistically able to make future predictions?
I'm doubtful. Clearly, the way to not select products that don't grab a market niche... is to not be an early adopter. Lots of products fail; if you're an early adoptor, you're likely to be adopting failed products. If you instead wait to see where a product is going before buying-- you never buy products that fail a month after launch.
FWIW, the original article is here:
http://papers.ssrn.com/sol3/pa...

OK, I did a search of other threads, and see that in fact in a post responding to somebody else, in a different fork, you did make an attempt to back up your assertions.

First take-away point: you can't expect people to be familiar with something you posted in response to a different person, in a different fork.

Most of your comments were addressed by riverat1, who points out that you misinterpreted what was pretty clearly stated by the IPCC report.

What I deduce from your comments is that no, you didn't read any of the IPCC reports, but you did skim them to quote mine, without bothering to actually try to understand what you were reading.

OK, that's a start. I suggest next you actually read some of these reports. Then you will be able to comment from a position of knowledge, instead of ignorance, and the discussion may at least be somewhat higher level.

riverat1 doesn't address one comment. You wrote:
what's important [about climate sensitivity estimates] "is they keep shrinking as we learn more."

Refining estimates is, of course, how science works-- but, in fact, they haven't been shrinking. The reference you give is a blog that seems to have cherry picked a dozen estimates over a very short time period-- out of perhaps thousands of climate models run over fifty years by dozens of groups on five contents. The first real estimate-- by "real", I mean "using experimentally measured values of IR absorption, and numerically integrating, instead of approximating"-- is of course Manabe and Weatherald 1967. Their estimate, with no feedback other than the assumption of constant humidity, was 2.25C per doubling. The 1979 National Academy of Sciences estimate was 3 C, plus or minus 1.5 C. Since then, the IPCC has been compiling the results of many models to come up with "best guess" estimates of climate sensitivity. These have been:
1990 IPCC: 1.5 - 4.5 C ( "best guess" of 2.5)
2nd IPCC: "No strong reasons have emerged to change" these estimates
3rd IPCC: 1.5 - 4.5 C.
4th IPCC: 2 - 4.5 C
5th IPCC: 1.5C - 4.5C

(These actual IPCC WG-1 reports give detailed explanation of what they mean by "likely," and citations and figures showing where the estimates come from, as well as discussion of the high and low outliers.)

What is astonishing about climate sensitivity is how little they have changed since the National Academy of Sciences assessment in 1979. Basically, the models have been getting progressively finer scale, with more nodes and more and more of the second and third-order effects incorporated, but the overall result has not changed.

In fact, the original 1967 estimate, 2.25C, is still within the error bars-- it's quite remarkable how Manabe's very simply model (simple by today's standards: a top-of-the-line supercomputer model by 1967 standards) still holds up.

I would... except you didn't.

Possibly in some other thread somewhere, but in multiple replies to me in this thread you made no "specific mention" of where you claim to have gotten your data. Not only did you not "specifically mention where," you didn't even say which IPCC report you think you got your information from (in fact, this is the first post you've made that suggests that you know that there even is more than one IPCC report.)