04 November 2008
Election Day
US readers, please do get out and vote. If you have to endure some rain, well, you're not water soluble.
01 November 2008
Happy 30th to sea ice
A belated happy 30th birthday to our continuous* record of sea ice coverage from satellite! 26 October 1978 is the first data from the SMMR instrument, so last weekend the record finally hit 30 years.
* Ok, not exactly continuous, there's a gap between SMMR and the first SSMI to follow. But it's only a matter of (quite a few) weeks, rather than years as happened between ESMR and SMMR.
* Ok, not exactly continuous, there's a gap between SMMR and the first SSMI to follow. But it's only a matter of (quite a few) weeks, rather than years as happened between ESMR and SMMR.
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.:
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.
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.
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:
The blog commentator responds:
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.
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.
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