30 October 2008

Pielke's poor summary of sea ice

I was amazed to see the following quote from Roger Pielke Sr. in an interview published yesterday in Mother Jones

Roger A. Pielke, Sr.:
In terms of sea ice, if you look at Antarctic sea ice, it actually has been well above average, although in the last couple days it's close to average, but for about a year or longer, it's been well above average, and the Arctic sea ice is not as low as it was last year. So in the global context, the sea ice has been fairly close to average. It doesn't mean it can't happen because we are altering the climate system. But whenever I look at the data, I see a much more complicated picture than what you typically hear about.

It's usually the case that if you look at the data yourself, the picture is more complicated than 'what you typically hear about'. (It also making some difference where you usually listen.) So that's a noncomment.

It's shocking, however, to hear someone who says he is looking at the data arrive at the conclusion that 'sea ice has been fairly close to average'. A brief visit to Cryosphere Today, a site well worth a long visit and run by a fellow (William Chapman) who is a scientist who studies sea ice (which isn't Pielke's area), quickly takes you to the anomaly graphs for the northern hemisphere and the southern hemisphere. The northern hemisphere is far (about a million square km) below the climatology, and has been below that average continually since early 2003. The trend in this curve became apparent years ago (compare the scatter in the first 21 years to the difference between 0 anomaly and where the northern hemisphere has been the last 5 years). The southern hemisphere trend, which is there and positive (towards more ice) only recently emerged from background noise. Compare the current value (eyeball of about +0.3 million km^2 as I write on the 30th of October) to the scatter (eyeball value of about 0.5 million km^2) for the Antarctic and you see why it's taken so long for a trend to emerge from noise).

So on one hand, we have the Arctic ice, which is well (a couple of standard deviations, by eye) below normal, and has been below normal continually for over 5 years. On the other hand, we have the Antarctic, which shows a statistically weak trend and has been bouncing back and forth across normal every year of the record.

However one may describe this for the global net effect, 'fairly close to average' isn't an option.

I'm emailing this to Dr. Pielke once I find an address for him. I'm hoping that he simply was quoted exceedingly badly.

19 October 2008

Discussion: A role for atmospheric CO2 in preindustrial climate forcing

Some climate spinners are no doubt having a field day with the van Hoof et al. paper Steve Bloom pointed us to. It does, after all, say something critical of the IPCC. But if you read the paper itself, you will see that spinners shouldn't be happy; a conclusion I get in reading the paper is that climate is less sensitive to solar and volcanic variations, and CO2 is more variable than previously thought.

Let us take a look at the content. I hope you already have, as I encouraged when Steve first mentioned it. In doing it myself, I'm largely reading it as a nonspecialist. While I have studied more things outside physical oceanography than typical for a physical oceanographer (on the scale a things, by the way, a fairly broadly educated bunch), the biology of plant stomata is not on that list. On the other hand, a good knowledge of how science works gets you pretty far, and you don't need to be a scientist for that.

The central experimental idea is that the density of stomata in plant leaves goes up when there is less CO2 in the atmosphere, and down when there is more. (Stoma being 'mouth' and stomata being a bunch of mouths -- the leaves breathe air in through these mouths.) The Oak (genus Quercus) has been used to infer older CO2 levels before, and these authors do so again. It's more to the novel side that they're trying to infer much shorter term variations than has typically been done before. But even that (their citations 20-24) is not entirely new by now. If you can find Oak leaves (say in swamps) and date when they're from, you then have a way of reconstructing past CO2 levels in the atmosphere that is entirely independent of ice cores. You might also have a method which doesn't have the averaging and delay problems that ice cores have. On the other hand, you have a method which probably has other problems. (All data have problems. That isn't the question; whether the problems affect your conclusions is the question.) The prime novelty in this paper is now to apply the method to the last 1000 years and consider what it may tell us about the climate system.

A quick question is how reliable the method might be. In results and discussion, and figure 1, we get an idea. On the counting stomata side, we're looking at something whose standard deviation ranges up to almost 18 ppmv (parts per million by volume -- the usual unit for CO2 concentrations; the v is often left off), with an average over the whole set of about 6 ppmv. Since the authors are looking at their largest signal being 34 ppmv, the 18 ppmv standard deviation is not small, though the 6 ppmv should be good enough. So we'll set a reminder to ourselves to see if the conclusion depends sensitively on this '34'. Turns out that a conclusion relies on 34 being different from 12; so the 6 ppmv standard deviation is definitely good enough.

In figure 1b, we're shown the regression scatter plot between stomatal index and CO2 values. Though it isn't mentioned this way, eyeball suggests that the CO2 levels inferred have less scatter at low CO2 levels (higher stomatal index levels). My being a nonprofessional, though, means that there might be some obvious, to a professional, bit of biology which says that I'm over-reading the graph. Taking the figure as given shows why there's typically a substantial standard deviation in the inferred CO2 levels -- the stomatal index doesn't have a tight correspondence to CO2.

So we have a bit of a concern about how faithful a record the oak leaves give. The authors address this by looking at how the oak leaf record they construct compares to the ice core record from Antarctica, after processing it through a filter which has a similar averaging and delay behavior. The result (figure 1d, red vs. blue curves) shows pretty good agreement. Though there's some wide error bars to use (the gray band), the two curves from wildly different sources agree pretty well in the few decades and up time scale. In saying 'few decades and up', what it means is that every single bump on the curves don't line up exactly. But if you look at averages over 30-50 years, they do compare pretty closely. Obviously an area for research is to attack exactly why there are any differences at all.

Now let's turn to the significance of the work if we take the reconstruction as given. As nonprofessionals, we can't go much farther now with whether we should do so, but we've got some pointers to ourselves about what to look at further if we were of a mind to pursue it. The ice cores, partly due to their time-averaging, only show a variation in the period discussed (1000-1500) of at most 12 ppmv. That, versus the 34 ppmv difference the authors find from their different recorder -- one we might expect to have much finer time resolution. If free variations of CO2 are much larger than previously thought, then more of the climate would be CO2-driven than previously thought. This continues an idea (as far as I know) William Ruddiman started (see citation 13). Tripling the CO2 contribution in the pre-industrial period also means that prior estimates of climate sensitivity to volcanoes and solar variations would have been overestimates.

This is why folks who are going to leap on 'IPCC was wrong' parts of the paper really shouldn't be happy. The conclusion is that climate is less sensitive to solar and volcanic, and that the natural carbon cycle is more prone to variation. Independently of any of this, however, we know that the recent 100 ppm rise was due to human activity. (See Jan Schloerer's CO2 rise FAQ if you wonder about this.) Whatever caused the 34 ppmv variation observed in this study hasn't yet been going on.

Now let's see if we know anything outside the paper that is relevant. The parts inside look reasonable. The prime thing which struck me is the 34 ppmv variation, occurring in only 120 or so years (1200 to 1320 or so by eye). That's a lot of CO2 to be released in a short period by natural means. The authors mention that it's contemporary with a warming of the North Atlantic, which is the right sign of change -- warmer water holds less CO2. But they don't present a quantitative argument about the water being enough warmer over a large enough part of the world to have released that much CO2. Time and space are limited in a PNAS paper so this isn't the issue it would be in a different source. But it's something to pursue. Prompted by this, though, I arrive at a different biological question. Or geological; or both. That is, the places where Oak leaves get buried in such a way that you can dig them up 1000 years later to analyze stomata have to be pretty special. Could such a special locale exert a local effect, say that when it's warmer stuff decomposes faster -- releasing more CO2 but only mattering to local trees? If so, then some portion of the 34 vs. 12 ppmv signal is a local effect, and the discrepancy between leaves and ice cores is reduced. Then again, this may not be a factor. Not knowing the biology leaves me in that position of needing to find more informed sources.

To that end, I'm sending this blog note and address to the corresponding author and inviting him to respond either on the blog or by email. Hank Roberts (you've seen him here a few times) brought up the idea elsewhere, that it might be a good thing for people to let authors know when their science is being discussed in a blog. Thanks for the idea Hank.

You should also see a new icon next to this note. It's from Research Blogging, and the idea is to tag blog notes about scientific papers. Then readers who'd like to see research-oriented blogging can go to the main site and have a summary feed of such postings.

17 October 2008

Science is collaborative

I wouldn't have thought it so, but apparently it is a surprise to some (many, actually I've seen quite a few such comments before) that science is a collaborative activity.

Quoting the scientist:

I am speaking for myself… Thanks to Stephanie Renfrow, Ted Scambos, Mark Serreze, and Oliver Frauenfeld of NSIDC for their input.

The blog commentator responds:

The result of this “groupspeak” is unconvincing to this reader. It would have been nice to hear the real thoughts of one real man.

Real scientists know that they are not omniscient. Even within your professional area, you know that you don't know everything. So, if you're contacted by some group with 'a few questions' and have a chance to do so, you run the questions and your answers past some other knowledgeable people. This is lower level stuff than hard core 'peer review', but some basic check that you weren't too focused on your own sub-sub-sub-niche at the expense of other relevant parts of the situation, and that you didn't have a thinko/typo in your answer.

There's nothing terribly special about scientists in this. Science or not, most people know they're not omniscient. I'm pretty sure that the Cubs first time in the post season since 1945 was 1984. And the next time after that was 1989. But if I were to be answering in a situation (as the above scientist was) loaded with people who think that I'm a liar before I answer, and that people in my profession are participating in some grand conspiracy, or that international decisions would depend on my answer, I'm going to do some checking with references and other Cubs fans about whether it was 1984 and 1989 or some other years. Those are probably the right years, and in a casual chat between you and me, I'd go with them. But if it mattered, time for research and checking with other knowledgeable people.

Yet, come to climate -- a big hairy mess of a system that no one person can hope to understand all of in detail -- and responses like the above are common. Somehow an individual scientist is supposed to become omniscient and not rely on checking out his answers with others. Yet any honest person as a matter of routine does so even in far less public and far less socially important situations.

16 October 2008

Computers in climate

Earlier I talked a bit about the math and science classes you would probably take if you went to study climate. Somehow, perhaps because they're so ubiquitous, I forgot to mention anything about the computer end of things. On the other hand, they are ubiquitous, so I should catch up a bit and mention the computer hardware, operating systems, software packages, and programming languages you might run in to, or that I have, in working on climate modelling and data analysis. A different part: the computers are just tools. Being good with computers (knowing many languages, whatever) is like being good with a hammer. Being good with hammers doesn't make you a carpenter, nor does being good with computers make you a scientist.

The hardware is pretty much anything you can find. For small models or data sets, a single processor desktop is still used. Small being defined as 'what you can do on a single processor desktop system'. Given that they're about a million times more powerful than the desktops of 30 years ago, this is actually not a minor set. In intermediate ranges are multiprocessor desktops or workstations (or at least what we used to call workstations; the distinction seems far less common now), up to a few dozen home-style processors. I see that you can now get at home, if not cheaply, 8 processor systems with 8 Gb memory. The first computer I worked on had 8 Kb of memory. These mid-range systems can do substantial work, particularly if used well. At the high end, you're looking at hundreds to thousands of processors, or vector processors. The latter were the domain of Cray in the mid 70s-90s; NEC started producing them as well. They had (from the later 80s) multiple processors, but the number was fairly small. The power of such systems was that each processor could do the same thing many time (16-32 in the early 90s). Since our models tend to do just that, this can be an effective design.

Operating systems have often been a matter of whatever the vendor shipped. In the 70s and 80s, this was often home-grown at the vendor's. These days for larger systems it's almost always some flavor of Unix or related. For smaller systems, it's hardware-based (Mac, which these days is also Unix-based), Unix-related (Linux, BSD), Windows, or other, what seem to be more regional systems (Acorn?).

Programming languages are often a matter that people get ... let's stay 'testy' ... about. I don't really understand it myself. For the models themselves, the main language is Fortran in whatever flavor is widespread. These days 90/95. But others get used as well or instead, including C, C++, Java, and Python. For the data processing, it is usually one of these others which is most-used (mostly C, with the others increasing; at least from where I sit). The reason I don't see the problem is that I am polylingual myself (more below) and learning a new programming language just isn't a big deal and doesn't seem like it ought to be. The one significant hurdle is going between procedural languages like Fortran/C/... and object oriented languages like C++/Java/... But if you're staying on one side of that hurdle, going from one language to another is a fairly minor matter if you learned to be rigorous in the first place.

You'll also likely wind up using one or another graphics or toolbox sort of package. Some are: Matlab, IDL, R, GraDS, MacSYMA, MAPL. I'm sure there are a raft more; these are just ones I've heard of recently. As they're (mostly) commercial packages, which one gets used varies widely by what center you're at.

So a fairly typical set to know is something like:
  • Fortran and at least one other language (C/C++/Java/Python/...)
  • A Unix-related operating system plus a home system (Mac, Windows, ...)
  • A graphics package
And, for all of them, be ready and able to learn a new one with fair speed. As you'll see from my list of systems, languages, and packages (all of which are incomplete), knowing any one of them will only suffice for a while and often not a long while.

My own hardware list (as I recall it over the decades):

Home-type computers:
Wang 8k, Apple II, Commadore 64, Mac Plus (wrote my PhD on one), Mac (IIx, IIfx, SE30, Powermac 120, PowerMac G5, Mac Pro), IBM-PC (when it really was IBM), PC-AT, 386-type, 486-type, pentium I, II, III, IV.

DEC PDP-8, PDP-11, VAX 11/750, VAX 11/780
HP (... never seemed to name theirs, but a 68030/68881, running HP-UX 5, and then, later, an HP-UX 10 system)
SGI Iris, Indigo, Origin,
Sun Sparc 1, 10, and a couple of Solaris systems

Big systems:
CDC 180, 195
IBM (old big-iron systems)
Cray 1, 2, X-MP, Y-MP, C-90, J-916
IBM RS/6000 (PowerPC based parallel systems PowerPC 2-6 if I remember correctly)

Operating systems:
NUCC (Northwestern University CDC system, SNOBOL-based)
NOS-Ve (CDC system of early 1980s)
COS (Cray operating system)
IBM systems: MVS, VM/CMS, ... (?)
*nix flavors: HP-UX, PDP unix, Solaris, Linux (slackware, redhat), UNICOS (Cray unix), AIX (IBM Unix), ... no doubt several more
CP/M (not really an operating system, but, for lack of a better word ...)
DOS 1.0, 3.0, 5.0, 6.0; Windows 3.1, 95, XP; Desqview X
MacOS 1-9, X

Programming Languages:
Fortran (4, 66, 5, 77, 90/95; Ratfor, Watfor, Watfiv)
Pascal, Basic, Java
Logo, Algol, APL
Forth, Lisp
Not languages, but:
VAX/VMS assembler, 68030 assembler

And, again I wouldn't call them languages, but I use them: Perl, Javascript

... and yes, I did use punched cards. Wrestled a pterodactyl so I could use it's beak to punch out the holes!

13 October 2008

Ad hominem

One of the more heavily abused terms around blogs and such is ad hominem, which is unfortunate because it is actually a useful method for weeding sources -- if you understand what it really means. The bare translation of the Latin, against the man, doesn't help us much unfortunately. But it's a start. You know something is up when someone starts talking about a person instead of the science in what is supposed to be a scientific discussion.

The classic form of an ad hominem is:
"X is a bad person, therefore they're wrong about Y".

'bad person' is usually substituted with something else ('travels', 'has a big house', ...), and the 'therefore' is often omitted. One I commonly see is, for example "AGW is a scam. Al Gore has a big house and uses a lot of electricity. "

The logical fallacy being that comments about Al Gore say exactly nothing about the science on anthropogenic global warming. But if someone says it loud enough, often enough, and maybe shouts it at you, you might get swept up into their emotional argument. They're hoping so.

My wife occasionally reminds me that there's more to the world than science. So I'll step outside that and look at the policy implications the ad hominem people want us to draw. One is obviously that they want us to think that doing anything about AGW requires us to give up having large houses and using 'a lot' of electricity. Except this is false. See my comments about keeping your vehicle how you choose for more. Part of how Gore is dealing with the carbon produced in his energy use is to buy carbon credits (the idea being that if you cause 10 units of carbon to be released, and you also cause 10 units to be drawn back out of the atmosphere, then your net effect is zero -- and you can do what you like as long as your net is zero). If that's brought up, the ad hominem folks then say something about Gore owning (part of? I don't know) the company he buys the carbon credits from. As long as the carbon is buried, though, it doesn't matter -- to the science, or honest policy -- who gets the corporate profit. Their complaint, then, is that Gore is able to make money while living large and not contributing to climate change. Huh? Shouldn't he be getting a medal for that? There are jobs to be had in carbon credit sorts of activities -- planting trees, building windmills, whatever. But that means a common whine from them -- that doing anything about climate change would bankrupt the world (talk about folks who want to scare us!) -- would also be false.

If you've got examples of people whose opinions are quite different from Gore's on climate and are regularly attacked in similarly ad hominem ways, do submit names and examples. It was a Gore ad hominem article I just saw that prompted this note. He, Jim Hansen, and Michael Mann, in that order, are the three I see the most ad hominem attacks against. No doubt a function of where I read.

Back to the science. When you see a note that talks about the person who holds an idea, rather than the idea, you can be fairly confident that the source isn't concerned about the idea. If there is no such thing as a greenhouse effect, present evidence against that; don't tell me about Al Gore's house. And so on. A google search on "al gore" agw scam brings up the following examples of folks doing the ad hominem game against Gore instead of saying anything substantive about the science), so can be added to the list of unreliable sources

(This site showd up earlier as an unreliable source -- as I mentioned early on, there's a lot of consistency in being unreliable. Once you've found one such example, you're likely to find multiple if you spend more time. That's the value of discovering at some point that a site is unreliable.)

John Coleman is the person quoted above.


And you'll see quite a lot of examples in blog comments, but I excluded sites where such things only appeared in the comments.

There's a converse mistake about ad hominem that's often made (usually by the same people) -- that to say anything about a person is ad hominem. Of course they don't apply that rule consistently. For instance, it is certainly important to consider the qualifications (a personal attribute) of a speaker. So a comment that Al Gore is a (retired) politician, rather than a climate scientist, is perfectly reasonable. I don't get my science from him for that reason. If you are, then please read some science books as well, say Spencer Weart's Discovery of Global Warming. Equally, though, it's not ad hominem to observe that John Coleman is a TV weather forecaster, not a climate scientist. So it probably isn't a good idea to rely on him for your climate science either.

12 October 2008

Question Place 3

Have questions about science, especially if some relating to oceanography, meteorology, glaciology, climate? Here's a place to put them. For that matter, about running as well. Maybe I'll answer them here, and maybe (as happened back when with Dave's note back in May, or Bart's in September) they'll prompt a post or three in their own right.

11 October 2008

We're all related

On Greg Laden's Blog, I've been joining the discussion a bit about race and its meaninglessness as a biological thing for humans. If you want to take that up, please join that thread. Here, I'm taking up the more genealogical side of relationship.

I've mentioned before that I've been doing some genealogy. This has included running mitochondrial and Y chromosome DNA samples. (Well, having someone else do so :-) The mitochondria pass solely from mother to child, so it gives a pointer on where my strictly matrilineal line comes from. The Y chromosomes pass strictly from father to son, so points to where the strictly patrilineal side comes from. In both cases 'points' is a generous description for something that really means 'within a few thousand miles, give or take a lot'. For the strictly patrilineal, I already 'know' the location outside the US (colonies as it turned out) -- Leonhart Krumbein of Strasbourg, who came in 1754 on the ship Brothers.

For the strictly matrilineal side, I had some hope of an interesting result. That side runs back to the early history of Maryland, and then is lost. Could have been that one of the women was a Native American. I'd have liked that. Unfortunately, both sides point to the most common haplogroups in Europe (H for the maternal side, R for the paternal). So no great surprises or novelty there. Oh well. It also established (not that this was a question) that I'm a mutant. (So are you, don't worry.) My mitochondria differ in 7 places (out of about 1500 checked) from the reference sequence. A little looking around shows one of the mutations to be fairly uncommon, even though the rest are very common.

By the time we're looking at 10 generations back (which is where I've tracked, loosely, the matrilineal side to), we've got 1024 ancestors. These tests only speak to 2 of those 1024. Quite a lot of variety could exist in the remaining 1022, but it won't show up in these two parts of our genome. At 20 generations back (about 1350), we've got about a million ancestors. That starts to get interesting, as it gets to be comparable to the population of significant areas (all of England at the time, for instance). Go to 30 generations (about 1050) and there are a billion ancestors -- greater than the population of the world at the time. Make it 40 generations, about 750, back to grandpa Chuck, and we've got a trillion ancestors -- more than 2000 times the world population of the time.

Grandpa Chuck is Charlemagne, who shows up in my tree. Given world population at the time, he probably shows up at least 2000 times in my tree if the whole thing were to be discovered. Back in college a friend (hi Derek) mentioned his descent from Charlemagne. This was before I knew about pedigree collapse so I was skeptical. Now that I do, it's more the converse -- it'd take evidence to show that you (for any of you, anywhere in the world) do not share him as an ancestor. Pedigree collapse is this business that as you go back in time, world population drops, but your number of ancestors keeps increasing. You hit a point where the same person must show up multiple times in your ancestry.

Related is that with a trillion slots to fill in your ancestry, even some connections that may seem intuitively unlikely are certain to happen. Intuition isn't a very good guide when numbers get large (among other times).

So I already know my real list of relatives -- everybody, everywhere. The only question would be how closely related we are. Even before starting the genealogy, I'd realized this. Even after greatly extending my knowledge of who came from where, 60% of the 'where' is still unknown. I take the rest of the world in that 60%.

07 October 2008

Radiative Heating

Short example of radiative heating from today's lunch. We were at a Japanese restaurant and they did the usual bit of cleaning the surface and then spraying it down with something flammable and igniting it. We noticed that we felt the heat even from the burners 20-30 feet away as the big whoosh of flame went up.

I've mentioned before that there are three methods of moving heat around -- conduction (molecules bouncing in to each other; very slow), convection (carrying the hot air from one place to another, and radiation. Now hot air rises, and we were not sitting above the burners! So what is left is radiation. The short-lived, but hot, sheet of flame radiated some heat over to us 20-30 feet away.

Some fireplaces take advantage of the principle by using a 'firebrick' which absorbs heat and then efficiently radiates it back in to the room, rather than letting it go with the air up the chimney..

Anyone else have a daily experience with (non-solar) heat transfer by radiation?