There’s so much gold on them thar climate blogs, whether climate science or denialist/skeptic, that a poor policy lass can hardly keep up! However, there were a few choice tidbits that I wanted to note.
I read a lot of blogs, daily and some less often, and here is a round up of my response to some of the climate blogs I follow:
CP reports that CNN meteorologist Chad Meyers finally admits that global warming is real and not only that, it’s man made!
Is it caused by man? Yes. Is it 100% caused by man? No. There are other things involved. We are now in the sun spot cycle. We are now in a very hot sun cycle. there are many other things going on. But, yes, a significant portion of this is caused by greenhouse gases keeping heat on the shore, on the land, in the atmosphere that could have escaped without those greenhouse gases, so, yes, it’s warmer. . ..
There is absolutely something going on here for this summer being the hottest and some of the water that we have in the Atlantic and the Gulf of Mexico the hottest ever on record which could cause a pretty significant hurricane season still to come. [emphasis CP’s]
Of course, you should be wanting to knock Meyers on the noggin for claiming we’re in a really hot sunspot period. No. We. Are. Not. We just came out of one of the deepest minimums in quite a while. So. No.
NASA reports that January to July is set to be the hottest on record and that “July is what global warming looks like”.
Of course, we know from our climate skeptic friends that it’s all just a big hoax, invalid adjustments to the temp record by socialists hoping to bring about world communism — and Satan!
CP also reports that the Daily Mail now agrees with Chad Meyers on the reality of global warming and its threat. Science Editor Michael Hanlon sez:
“I have long been something of a climate-change sceptic, but my views in recent years have shifted. For me, the most convincing evidence that something worrying is going on lies right here in the Arctic.”
As CP notes, it wasn’t too long ago that Hanlon, influenced by of all people, Michael Crichton, wrote:
“Will the activities of a few pesky homo sapiens with their cars and power stations really cause the earth that much bother in the long term?”
Duh! Ya think maybe 6 billion of those pesky technologically savvy H. sapiens with their cars and coal burning plants and energy hog ways might have an effect? Talk about understatements…
Here’s a tidbit from the Washington Post:
IN A DEPRESSING case of irony by juxtaposition, the death of climate change legislation in the Senate has been followed by the appearance of two government reports in the past week that underscore the overwhelming scientific case for global warming — and go out of the way to repudiate skeptics…
Many climate-change skeptics will simply dismiss these reports as more evidence of a sprawling conspiracy instead of what they really are: yet more affirmation of the risks humanity runs if it continues to pump carbon into the atmosphere.
Of course, the climate change “skeptics” will simply dismiss the reports. It’s not about the science — it’s about politics and economics — you need no evidence for that.
In the “Lies, Damned Lies and Cherry Picking Statistics” category, I go to Tamino when I want to understand how statistics can be manipulated to mislead and obfuscate for he debunks many a skeptical myth and when is a cherry-pick and cherry-pick.
In a few recent posts, Tamino does a few “tricks” to reveal the decline in cognitive capacity of some climate skeptics…
In a discussion about CO2 concentrations on Real Climate, guest hosted by Barry Bickmore, Moncton complains his treatment and rejects the dataset Tamino used to analyze CO2:
It is suggested that we did the test incorrectly, because a climate-extremist performed a similar test on the Mauna Loa CO2 concentration dataset and came up with a different result. However, as our detractors ought to have realized, the Mauna Loa dataset, taken from a single location intermittently perturbed by regional volcanic activity, is not the same dataset as the NOAA global dataset that we used. Accordingly, we are unimpressed by their reliance upon an entirely different dataset.
Thankfully, Tamino knows better:
Yes, those two data sets are sure different…
Tamino also takes on Steve Goddard’s cherry picking of start dates to analyse summer temperatures, in order to show that hey, global warming is just the result of some climate scientists dishonestly adjusting the temp record…
Let’s compare Goddard and Tamino:
Goddard’s graph of Mass. summer temps:
Look Ma! No trend!
Look Ma! Look at the trend!
Gee. Using all the data available and calculating the 30 year trend properly seems to show a slightly different result than using 1930 as a starting point…
In this week’s most interesting post, Mr. Eli Rabett focused on ice and its crumbling, posting a scary graphic of the arctic sea ice volume anomaly. Ya see, the “skeptics” tend to focus on sea ice extent, claiming that whenever it increases, global warming is OVER! Of course, this is another example of cherry picking based on personal choice rather than science.
What matters is sea ice volume and how much of the really old ice remains after the summer melt.
Here’s the graph showing the sea ice volume anomaly:
Yikes! In addition, the amount of old multi-year ice hanging around is declining, meaning that the whole place is crumbling. Not good.
Here’s the sea ice extent graphic from the NSIDC:
Speaking of hilarity, much fun ensued with Eli hosted the first annual Moncton Limerick contest. Here are my favorites:
An obstreperous journo inclined
To distort all the facts he could find
Enhanced his credentials
To be influential
And lie to the willfully blind
Lord Monckton has sure got it rough;
His audience has turned very tough.
They’re no longer beguiled,
But instead he’s reviled
For continually making up stuff.
He claims to have cured most disease,
And disproved global warming with ease.
So wild are his pitches
They have us in stitches.
What color’s the sky that he sees?
A fellow named John Abraham
Put the potty peer in a jam
When he calmly debunked
All of Lord Monckton’s junk
In one thorough and well-reasoned slam.
In it for the Gold:
I mean, it’s 2010…, the past decade has been the hottest on record, all around the world ice is melting, there are droughts, and fires and floods and crops have failed and record temps are killing people and McIntyre is still honking on about MBH98 and the fraking Bristlecones!
Adaptation is crucial. It is necessary, but it is not sufficient.
As Eli says, “no adaptation without mitigation”. Without mitigation, the size of the disruption we are adapting to grows without any meaningful bound. If we are determined to get to the worst case, it will be pretty much the worst.
Adaptation is relatively local and relatively short-term. Mitigation is global and long-term. So we don’t need to talk about century time scales for adaptation, nor do we need to talk about global policy alignment and international governance…Mitigation, however, presents new and urgent difficulties which require changes in how the whole world operates.
In short, adaptation and mitigation are not a tradeoff. They are two faces of the same coin. The longer mitigation is delayed, the more mitigation will cost and the more adaptation will cost. But most adaptation discussion needs to focus on particular regions and particular vulnerabilities.
There is a cliche metaphor about adaptation without mitigation: deck chairs.
Adaptation without mitigation — deck chairs on the Titanic.
Here’s the FAO’s take on that:
The image that comes to mind when contemplating today’s energy quagmire is that of deckhands re-arranging the chairs on the Titanic in the minutes after it hit the iceberg.
Instead of focusing on how best to save the passengers, the captain and his crew – by analogy, those in the energy business as well as myopic policymakers – are busy rearranging the deck chairs to obtain a better view of the iceberg that caused the gash in the hull.
Skeptics/Contrarians/Denialist (take your pick):
Over at my favorite climate skeptic blog, CA, Steve McIntyre has several posts about his recent co-authored paper responding to Santer 08’s analysis of the climate model’s performance vis a vis the troposphere. Aside from some whinging about previous comments to the journal being rejected, McIntyre tries to explain to readers why his approach to analyzing the climate models is a vast improvement over that of climate scientists like Santer.
This is above my paygrade in terms of knowledge and expertise, but it is an interesting debate nonetheless, which I have tried to follow.
There is an interesting back and forth between the two sides of the climate divide on the MMH10 paper, including James Annan, Steve McIntyre, Gavin Schmidt, Steve Bloom, TCO, Ron Cram and others on James Annan on his blog James’ Empty Blog:
A commenter pointed me towards this which has apparently been accepted for publication in ASL. It’s the same sorry old tale of someone comparing an ensemble of models to data, but doing so by checking whether the observations match the ensemble mean.
Well, duh. Of course the obs don’t match the ensemble mean. Even the models don’t match the ensemble mean – and this difference will frequently be statistically significant (depending on how much data you use). Is anyone seriously going to argue on the basis of this that the models don’t predict their own behaviour? If not, why on Earth should it be considered a meaningful test of how well the models simulate reality?
It really goes over the whole Santer v. Douglass and now McIntyre v. Santer matchups pretty well.
In another post continuing on the discussion of the new paper and methods, McIntyre tries to “pin the concept of ensemble mean” down in statistical terms”. He then presented a boxplot and discussion about the global climate models. Very enlightening commentary ensues and commenters raise questions about the boxplot.
The thread is now closed, with this as the final post:
There was a mistake in the collation of trends that I used in the post – which was (confusingly) supposed to help clarify things rather than confuse things. I used trends calculated up to 2099 instead of 2009, which ended up making the within-group standard deviations too narrow. I’ll rework this and re-post. However, I’m going to Italy next Tuesday and am working on a presentation and so the re-post will have to wait. This has also been a distraction from the MMH issues so let’s focus on them. So let’s stick to MMH10. Sorry about that.
I wait with bated breath…
What’s interesting to me is that once again, M&M try to introduce new methods of analysis from other disciplines, claiming that first year students in stats wouldn’t make the mistakes that Santer and others such as Gavin Schmidt make in their work. I can’t find the quote for that, as I think it has been deleted or edited.
To sum it up, the usual pedantic technical point about the proper use of statistics, Steve’s schtick, some whining about unfairness of the mean popular boys on the playground not picking him for the sports team, and a lot of “bravos” and “good job” from the peanut gallery.
Is that too harsh?
Actually, over at James’ Empty Blog, TCO sums it up best:
The whole thing is silly. The Denialists (and since I am one, I can use the term) are using the wrong method for showing variability in “model space”. When challenged, they say, “but the models differ a lot from each other, in some cases more than within model run to run”. Duh. then they have this whole, “we’ll admit X, but then you need to admit Y” thing going on. It’s the same crap that was going on wrt Douglas in the blogs.
First, they needed to put their logic for their too tight whiskers into their paper (just so others could discount or debate it). This is the Feynmanian ideal of showing where you “might be wrong”. But instead they hid it, larded on a bunch of matrices and algebra to confuse people. And shopped around for 2 years to try to slide their paper through.
Second, they’re wrong. We don’t even USE models in the way that the MMH method would assume. When we think about the century-long temp rise, we don’t report a super-tight point estimate. We recognize the structural uncertainty.
And yes, granted, a wide spread of models or adding nonsense models can make it easier to pass a more open or range-based view of the ensemble…but…see the paragraph preceding!
Add onto that, the paper is just poorly done. Look at table one: they list the average trend and standard deviation of the models. But they call it standard deviation in one spot, standard error in another. They list a standard deviation for single run models! (must be some time series thing, not a classic sampling statistic, but is NOT EXPLAINED in the table).
Now they are flailing around trying to do damage control in the blogs. And messing those up as well. What a mess.
2 years spent on this crap.
It’s also funny how close they kept this thing to the vest, before putting it out. McI often justifies his blog as a “lab notebook” when challenged on either it’s usefulness or its accuracy. But it really seems like a PR organ. They didn’t share the in review copies for instance of MMH.