From this BBC article:
Of course a lot of climate change skeptics are going to ignore what mainstream scientists say, but a lot of the recent research seems pretty decisive that the significant component of climate change is cause by humans.
It was pretty poor reporting. One example:
This is the reverse of the solar hypothesis, which says that cosmicrays are getting pushed aside by the solar wind. Also, not all these solar outbursts actually hit the Earth. Further, these happen over a very short period of time whereas the theory is concerned with the longer-term more general effect.
The next bit is far more sensible:
Also
Aren’t the pro-AGWers always saying that there’s a lag? And, for the past few years, there has indeed been no increase.
Anyway, the full paper isn’t up, so it’s really far too early to say more.
The paper has now been published as a letter here. I gave it a quick scan - I’ve an exam tomorrow - and it looks fairly impenetrable.
I do hope that they’ll follow this up with a study of upper cloud cover.
Publishing a direct quote from the researcher is not poor reporting.
This in bold at the top. But after reading the article and the abstract of the report itself, all they’re saying is there is reason to doubt that solar activity changes certain levels of cloud cover. That seems a far way from saying “modern-day climate change is not caused…”
I’m repeatedly baffled by the known uncertainly of cloud cover being marginalized in long-term climate discussions. Is the possible effects of cloud cover so minimal? Or do they average out over time?
-Eben
From What They Studied to What Was Announced is a very long distance. The study as given did not conclusively prove that there is no link between the Sun and Climate Change. It only proved that they didn’t find the limited linkage that they were looking for over a historically short period of time.
Of course, no one study is going to definitely determine a question such as that. You should think of it as another piece in the puzzle. Unfortunately, the media do tend to want to simplify things as complicated as science (as it is kind of boring to say, “Another piece in the 5000 piece jigsaw puzzle that is the earth’s climate system was filled in today…”), which is why it is ultimately best to rely on respected reviews of the peer-reviewed literature rather than the results of one or even a few specific papers.
Well, the point is that, while there may be considerable uncertainty regarding some aspects of clouds, this uncertainty will basically cancel out as long as there is not some dramatic change in clouds that occurs with warming of the climate that is not captured in the current models. (A very rough analogy might be that to predict the speed of a pool ball in response to a collision with another ball, I don’t need to know the speed our solar system is travelling through the galaxy even though this speed is presumably much much larger than the speeds of the balls relative to the pool table.)
Richard Lindzen has tried to put forth a hypothesis that there is something in cloud system of the tropics that does cause such a negative feedback with increasing temperature…but so far the body of evidence in the scientific community does not support this. Furthermore, if Lindzen were correct, it would mean not only revising our understanding of current climate change but also considerably revising our understand of past climate change (such as the ice age - interglacial cycles) in order to understand how such dramatic changes in climate could have occurred in the past given our current estimates of the forcings involved.
[QUOTE=jshore]
(A very rough analogy might be that to predict the speed of a pool ball in response to a collision with another ball, I don’t need to know the speed our solar system is travelling through the galaxy even though this speed is presumably much much larger than the speeds of the balls relative to the pool table.)QUOTE]
That makes a lot of sense jshore. To further your pool ball analogy, the initial speed and impact point of the cue ball gives us both direction and curve for the cue ball therefore allowing us to model the interactions with other balls. Unless the felt on the table changes (felt = clouds in this case) it doesn’t really change things if we hit the cue the same way every time. I like this analogy because the experimental studies I’ve done on pool ball interactions indicate that with a good deal of background experience, I can rapidly adjust my mental model of pool ball interaction when the felt changes (I switch tables) and therefor continue to get useful predictibility out of my model.
Strangely, that analogy gets me closer to understanding, and therefore believing, that AGW models might have something going for them. I think part of the problem with me understanding AGW is that in the end I don’t see it as a problem for the Earth, just humans and critters/plants we like. I don’t consider ourselves to be a unique, one-time phenomenom and in need of special protection. And if we are, then we should be doing everything in our power to colonize the rest of space. So given very little initial reason to buy into AGW, but no real reason to disagree either, I find myself confused by the lack of long-term modeling for it (not anyone’s fault there, we only started modelling recently).
-Eben
ps I’ve noticed that I ramble, does that mean I’m getting old or over-educated? 
jshore, another day, another thread, good to see you again. You say:
A few comments on that:
- There is no certainty, and indeed likely no way of knowing, whether the “uncertainty will basically cancel out”. This is merely an assumption of the modelmakers, and is not a fact. Having had a reasonable amount of experience with models and modeling, I would say that the odds of the uncertainties basically canceling out is quite small.
For example, consider the GISS model. They modeled the whole climate as best they could, but neither the albedo nor the top-of-atmosphere radiation balance was anywhere near correct. They had to fix it by adjusting the model so that there were much less clouds than we find in the world (modeled coverage = 58%, actual coverage = 69%). So in that case, despite the modelers best efforts, the uncertainty absolutely did not “cancel out”, it led to huge errors that could only be fixed by playing with the parameters.
- A 1% change in albedo (which is ruled mostly by clouds, particularly in the vital tropical regions) is enough to totally cancel out a doubling of CO2. I would call that pretty dramatic, wouldn’t you, wiping out the effect of doubling CO2?
So jshore’s statement means the “uncertainty will basically cancel out as long as there is not a 1% error in how the clouds respond” … and an error of that size is virtually guaranteed.
If you want analogies, an analogy would be to modeling the speed of a car given the variables of engine temperature, compression ration, position of the throttle (gas pedal), and the like. The clouds, of course, represent the position of the throttle.
Now while the engine temperature and such affect the speed, it is mostly determined by the position of the throttle. The same is true of the climate. If all the CO2 stopped absorbing radiation tomorrow, the climate wouldn’t change much. But if all the clouds disappeared tomorrow, the planet would roast.
In the models, though, the clouds are not calculated, they are not modeled from basic principles, they are parameterized. The tiniest, 1% error in the parameters will make the results greatly wrong.
So, Eben, from my perspective you have asked a most important question: how can we trust the models when the cloud cover is so uncertain? For me, the answer is simple: I don’t trust them, in no small part for that very reason.
w.
PS - The problem with jshore’s analogy is that the speed of the planet through the universe is constant. He is right that we can safely ignore constants in a model if we are looking to analyse changes in the resulting output (increase in temperature, say).
But the analogy fails immediately when we apply it to the climate. Nothing in the climate is constant. There is no basis for assuming that other factors, both known and unknown, will make no difference in the result. In addition, nothing in the climate exists by itself, everything affects everything else. The wind affects the clouds, but the clouds in turn affect the wind. The rate of cloud formation affects the temperature, and in turn the temperature affects the rate of cloud formation.
So we cannot, as jshore advises, simply take the Pollyanna position that “everything will balance out”. That’s the modelmaker’s mantra, but it simply is not true.
And even if all these effects were somehow to balance out, to average out to zero over time, that still doesn’t mean that the result will be correct. To understand why, let me extend jshore’s analogy. It’s like playing pool on a pool table on board a ship.
Yes, the rolling of the ship will definitely average out over time. For every ball that swerves right, there will be a ball that swerves left, the net effect of the rolling averaged over enough time will be very, very close to zero.
But the fact that the rolling cancels out entirely does not mean that the final score of the game will be unaffected by the rolling …