Open Mind

Preliminary CO₂ data for March of this year are available from the Muana Loa Atmospheric Observatory. The data indicate that CO₂ concentration rose slightly from February to March, but not by as much as it usually does, so the seasonally adjusted value actually dropped from February to March:

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I’ve already shown one of the reasons Anthony Watts’ and Basil Copeland’s analysis of the solar-cycle/temperature connection is not just wrong, it’s an example of grotesque incompetence as data analysts. Let’s have a look at another reason.

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Many have sought, but few have found, a connection between the solar cycle and global temperature. Such a connection only makes sense; solar irradiance varies with the solar cycle, being greater when the sunspot cycle is at maximum and less when it’s at minimum. And solar irradiance means energy coming into the climate system; more energy input should cause a temperature increase. Yet the change in solar irradiance throughout the solar cycle is small, and the resultant change in climate forcing is smaller still, so the impact is likely to be hard to find. In addition, the response to changes in forcing is likely to lag behind the forcing itself, and when that forcing is periodic the lag can strongly dampen the response. So, the temperature response to solar-cycle variations is likely to be very small indeed, which may explain why it’s so hard to pin down.

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If earth were nothing but a big ball of rock, then computing the effect of changes in energy balance on our planet’s temperature would be easy. That’s because the only relevant factors would be the shortwave (SW) solar energy coming in, and the longwave (LW) radiation escaping to space, and we’ve got a good handle on that. The Stefan-Boltzmann radiation law enables us to compute that for near earth conditions, an additional 1 watt per square meter (W/m^2) of energy coming in to the planet would increase temperature by about 0.3 deg.C. This is the climate sensitivity to radiative forcing, which is the temperature change due to an additional 1 W/m^2 of climate forcing. It’s not the same as the climate sensitivity to doubling CO₂; doing that would increase radiative forcing by around 4 W/m^2, so climate sensitivity to doubling CO₂ would be around 4 times greater, about 1.2 deg.C. (Note: this is based on a global average temperature of about 14 deg.C, which is a real-world value, but if earth had no atmosphere it would be considerably cooler and climate sensitivity would be a bit less.)

But: earth has an atmosphere, and oceans, and ice caps, and glaciers, and plants and animals and people, oh my! As a result, the response of the climate system to additional climate forcing is quite a bit more complicated. Temperature change can alter other factors which themselves affect climate forcing, which in turn affects temperature, in a feedback loop. Because of these feedbacks, it becomes difficult to estimate with precision exactly how climate responds to climate forcing because it can be difficult to estimate the feedback factors with precision. Let’s consider some of the known factors, and estimates of their impact on climate sensitivity.

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Just so it’s easy for eveyone to find an open thread, where discussion of topics not covered in other threads is appropriate, here’s a new one.

Anthony Watts and Basil Copeland have collaborated on another post claiming to establish a connection between solar activity (as proxied by the sunspot cycle) and global temperature (as indicated by the HadCRUT3v data set). Let’s take a close look.

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Recently a reader commented that Anthony Watts had been deleting comments from his blog, after the fact of having not only approved them, but responded to them. So I went to see for myself, and found out that the entire post in question was gone. Then a comment arrived here saying that not only was that post gone, so was part 2 of that series. I went to find out, but I hadn’t saved a link to part 2 of that series, so I waded through all the posts on Watts’ blog subsequent to part 1. Indeed I failed to find part 2 of the series. But what I did find, astounded me.

Not long after, the absent posts reappeared. I don’t know whether there was a technical glitch, or Watts was removing then restoring entire posts, but that’s neither here nor there. This post is about what I found.

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The last post witnessed the utterly ridiculous (by which I mean, worthy of ridicule) attempt to justify the garbage analysis by Jim Goodridge. Much of the vain attempt focused on trying to say that the accumulated departure from average of sunspot counts, as a proxy for accumulated departure from average of solar irradiance, was somehow a meaningful indicator of heat content of the climate system — as though heat loss from the climate system were somehow constant. Of course, under this model if solar irradiance remains above average, even by a little, heat content will increase without bound, as will temperature. If you actually believe that under those conditions, temperature will continue to rise at a roughly constant rate forever, then you’re in need of remedial critical-thinking classes. Sit in the front so you can pay better attention, and try to help Anthony Watts — he needs it. And by the way, Goodridge doesn’t suggest that model; he doesn’t suggest any model, instead he suggests that his analysis is a valid way to characterize trends in solar output. That’s even more ridiculous.

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Anthony Watts has had a number of posts suggesting that solar activity is the primary driver of climate change. It appears that most of the real work has been done by others, including Jim Goodridge, who contributed this one. It provides an almost unbelievable example of how not to analyze data.

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There’s been some hoopla in the blogosphere lately about comparing projections of temperature from the IPCC TAR (third assessment report), published in 2001, to observed temperature. The comparisons have been made to temperature data since 2001, on the basis of the claim that that’s when the projections start so that’s when the comparison should start. It appears such claims are in error.

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