Last year, I wrote about why the assault on (and some of the defense of) the Mann Bradley and Hughes hockey stick was misplaced. With Stephen McIntyre and Ross McKitrick coming out with a new paper, the subject is worth revisiting. But Stefan Rahmstorf has done a much more capable job than I could, so I’ll just leave you in his capable hands:

So let?s assume for argument?s sake that Mann, Bradley and Hughes made some terrible mistake in their statistical analysis, so we need to discard their results altogether. This wouldn?t change our picture of the last millennium (or anything else) very much: independent groups, with different analysis methods, have arrived at similar results for the last millennium. The details differ (mostly within the uncertainty bounds given by Mann et al, so the difference is not significant), but all published reconstructions share the same basic features: they show relatively warm medieval times, a cooling by a few tenths of a degree Celsius after that, and a rapid warming since the 19th Century. Even without Mann et al, we?d still be stuck with a “hockey stick” type of curve ? quite boring.

Would that it were boring, Stefan.

I spent some more time at work today on the ClimatePrediction.Net paper. It seems as though most of the coverage has missed the point entirely. This is about better understanding how the climate models work, rather than how the climate works. More thoughts here.

There’s been a lot of noise today about a paper in today’s Nature on the range of uncertainties of future climate change. It’s a terrifically interesting and useful paper, but if you just read the press coverage that I’ve been reading, you may have a rather wrong idea about why.

The researchers, using a Seti@home-like distributed computing system, were able to perform a far larger number of climate model simulation runs than is normally done, and they found that, by using a reasonable but far larger range of the adjustable parameters used in the models, they saw a significantly larger range of possible temperature increase.

The 2,017 simulation runs showed a range of possible temperature increase under doubled atmospheric CO2 of from 2 degrees C to more than 11 degrees C. That’s a bigger range, especially at the top end, than the 1.4 to 5.8 degrees cited by the IPCC. Note – and this is important – that the Oxford team that did the calculations did not say that the high end of the range was the most likely. Quite the opposite. The frequency distribution in their paper suggests the lower end, in the 2 to 4 degree range, is the most likely.

Now let’s look at the press coverage.

First, from The Telegraph: Screen saver weather trial predicts 10 degree C rise in British temperatures

Or MSNBC: “Computer models for climate change allow for a global temperature rise of as much as 20 degrees Fahrenheit (11 degrees Celsius), according to the first results from the world?s largest climate-modeling experiment.” (This accompanied by a map color-coded with the extreme case.)

From The Scotsman: “THE biggest computer calculation of its kind has forecast a degree of global warming greater than previously predicted, with Britain becoming an unrecognisable tropical country in a few generations.”

Even Nature itself, in the Web news story accompanying the paper, fell into the trap: “Biggest-ever climate simulation warns temperatures may rise by 11 C.” (To be fair, Michael Hopkin’s second paragraph gets to the meat: “But as well as a predicting a bigger maximum rise, the project has also increased the range of possible temperature changes.”)

I could find no one who wrote a headline saying “Biggest-ever climate simulation finds temperatures may only rise 2 degrees C,” though that would have been equally well supported by the data.

For a more useful take, without the big number alarmism, there is Newsday’s Bryn Nelson, who did a good job of laying out where this fits and why it matters:

In formulating reasonable global warming predictions, researchers say they have long been stymied by the inherent uncertainty in their models. The climateprediction.net experiment, run by a British research consortium, is trying to address this frustration with a deceptively simple solution: unused computer space.

Calling upon thousands of volunteers to run different versions of the same model with their computers’ spare capacity, the team hopes to refine a long list of atmospheric and oceanic variables. Eventually, the researchers hope to produce a 21st-century forecast that neither over-hypes nor underestimates warming scenarios.

This is an important exercise in helping better understand and refine the range of possibilities, and it’s pretty clear from the research that some of them are extreme and worthy of attention. But a lot of the press coverage I read today makes me think that some of the worst fears of the skeptics crowd about biased media coverage on this issue are not entirely unjustified.

We have had March weather for the first three weeks of January here in Albuquerque.

Those are snowdrops, peaking up through the detritus of last year’s iris.

When I say “March weather,” I am speaking empirically, not rhetorically. The average overnight low for the first three weeks of January has been 31.3 F here (a tad less than O C). That’s a normal March 1 temperature. Normal for now is more like 23.3 F (-5 C). Daytime highs have been well above normal too, though the gap is a little less. Overall, though, it’s the warmest first three weeks of January in Albuquerque records going back to 1931.

Snowdrops are usually the garden’s first bloomer. But this is ridiculous.

Since I know there are some climate weenies who read this blog, I will self-consciously point out here that I am not making any assertion about global warming having anything to do with my snowdrop. Chalk it up to a persistent ridge of high pressure over the intermountain west. But I would be remiss in not pointing out that the subtext of the numbers above – overnight low temperatures rising more than the daytime highs – is consistent with the anthropogenic hypothesis. This is the “diurnal temperature range”, the gap between day and night temperatures that is one way of fingerprinting greenhouse warming.