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New Paleoclimate Paper: Longest detailed reconstruction plus possible bad news

You’ve probably already heard about his paper because everyone is all a tizzy about it. There is a fundamental complaint being made about one of the paper’s conclusions. I’ve been paying careful attention to what my colleagues are saying about that one aspect of the paper, and I get their point but I’m not sure if they are right. I’ll explain that later.

What everyone so far has almost entirely missed, though, is the actual point of the paper, and that is important and while I’m sure it could be improved with further work, this is good stuff and important.

One of the major contributions people like Michael Mann and Malcolm Hughes and others made some years ago now, to the understanding of climate science, was the extension of the paleoclimate record back far enough to truly contextualize current global temperatures, and to meld that record with more recent instrumental records. There have been other attempts to put together paleo records as well. But this latest attempt is the first time anyone has reconstructed the global average surface temperature (GAST) for about two million years.

This is roughly the same time period as what is known as “The Pleistocene” or, if we want to put this in cave man journalistic terms, “The Ice Age” or slightly more correct “The Ice Ages.” The latter terms are misleadning and muddy, so please lets not us them (by those terms we are in the “ice ages” right now, but not in “an ice age.” See how annoying that can get, and for no good reason?)

The Cenozoic, roughly 65 million years long, is a time of general cooling across the Earth, and the Pleistocene, the most recent sizable period of time, a part of the Cenozoic, is the period when extra cooling seems to have occurred, and during which, there are a couple of dozen or so swings between relatively warm (like we have now) and relatively cool, with some of those cool periods, the most recent half dozen or more, being really really cool, with the big giant glaciers covering Canada, etc. etc. You knew this already.

For this period, we have a pretty good climate reconstruction, or least one that has been slowly building, that uses two sources of data from sea cores. One is the so called “delta-18” curve, and the other is the foram reconstruction.

The delta-18 curve simply measures oxygen isotopes in sea water, indirectly, and uses this to estimate how many cubic gigantometers of the planet’s water is tied up in ice, mainly in glaciers. (Some help on that here.) Examination of this curve starting in the late ’60s, but mainly in the ’80s, confirmed an old and zany theory that the Earth’s climate is controlled by the orbital geometry as our planet goes around the sun. Eventually it would come to be understood that cycles in how exactly the sun hits the Earth, called Milankovitch cycles, are a factor (but not the only factor) in global climate, and that this effect was very weak in the distant past, got stronger about 2 million years ago, and then perhaps got stronger again more recently.

The foram reconstruction is a bit more difficult. Here, fossilized remains of communities of a significant part of what we call “plankton,” which had settled to the bottom of the sea, are interrogated to estimate the sea surface temperature at that location. Certain forams prefer certain temperatures.

The new research, by Carolyn Snynder, published in Nature as “Evolution of global temperature over the past two million years” uses, mostly, this foram data to estimate sea surface temperature, and then, uses this to extrapolate to GAST, for the last two million years.

The result looks like the graphic above.

That, right there, that graph, is cool. It puts the modern world in context, and provides a good look at the Pleistocene.

The graph is not perfectly accurate and it is hard to say how inaccurate it is, given the paucity of data.

I asked the author about the possible limitations of this reconstruction. She told me, “this reconstruction is only as good as the proxy reconstructions and other assumptions it is based on (it is useful to note that three different SST proxy methods were included in the dataset). The more reconstructions available, the better the GAST reconstruction can be. That is why a significant amount of this research was focused on quantifying how large that uncertainty may be so that it was reflected in the final GAST reconstruction.”

Only sea surface temperatures are used, and there are strong seasonal effects in how foram communities form and are deposited. But, any ancient reconstruction is going to have problems, and this appears to be an excellent result. Dr. Snyder told me, “one of the major challenges of creating a global average surface temperature is that the primary reconstructions available over the past 2 million years are of sea-surface temperature. Available terrestrial temperature reconstructions are too infrequent and limited in spatial distribution to be used for a global reconstruction at this time. Therefore, I scale the average sea-surface temperature for 60ºN-60ºS to global average surface temperature using results from climate model experiments from 9 climate models. The scaling factor is necessary to address the fact that land surfaces and the poles tend to have larger temperature changes than the oceans. That assumption also drives a large fraction of the overall estimated uncertainty in the final GAST reconstruction.”

One of the most useful applications of this kind of information is placing modern global average surface temperatures in context. You can do that by looking at the graph, but I went ahead and asked the author how she would characterize modern temperatures vis-a-vis this reconstruction. She told me, “this is what we can say from this reconstruction: The only time periods in the temperature reconstruction when the estimated most likely global temperature change from the past 5,000 years was greater than 1 degree Celsius was during the last interglacial period (around 120,000 years ago) and then not previously until 1.77 million years ago. However, that is a summary of the “most likely” GAST estimate, and the uncertainty ranges are large, especially farther back in time. Also, the GAST reconstruction is relative to average temperature over the past 5,000 years, not directly to preindustrial temperature (due to the resolution of the reconstructions used), and so that is why I am not able to word this as a comparison relative to present temperatures.”

Now, on to what turns out to be a highly controversial result.

Snyder claims, using part of the Abstract of the paper to represent her finding, ” A comparison of the new temperature reconstruction with radiative forcing from greenhouse gases estimates an Earth system sensitivity of 9 degrees Celsius (range 7 to 13 degrees Celsius, 95 per cent credible interval) change in global average surface temperature per doubling of atmospheric carbon dioxide over millennium timescales. This result suggests that stabilization at today’s greenhouse gas levels may already commit Earth to an eventual total warming of 5 degrees Celsius (range 3 to 7 degrees Celsius, 95 per cent credible interval) over the next few millennia as ice sheets, vegetation and atmospheric dust continue to respond to global warming.”

If you have been following the climate science literature, you may see that range as incredibly high. It isn’t actually as high as it looks, because most discussions of “climate sensitivity” refer to the metric “Equilibrium Climate Sensitivity” which is both shorter term and lower (and different in other ways) compared to Earth System Sensitivity. The difference may be as much as 100%. The ECS estimates are all of the map but, nobody believes the number can be below 3 (except a few odd balls), most think 3.5 is a good estimate, but most say it could be as high as 6. So, doubling the ECS to get the ESS (which is probably not appropriate but hell, this blog post is not being submitted to peer review, so complain in the comments if you like) we get 7.0 – 12. In other words, saying that ECS is about 3-6, likley 3.5 and that ESS is 7-13, most likely 9, are not quite as dramatically different as they seem.

But still, the implication is that sensitivity is higher than people have been thinking. And this is where lots of people don’t like the research. Not because of the finding, but because of the effort to calculate this number itself. NASA scientist Gavin Schmidt has been circumspectly tweeting about this for several days, and just wrote a blog post at Real Climate on it. He notes,

Nature published a great new reconstruction of global temperatures over the past 2 million years today. Snyder (2016) uses 61 temperature reconstructions from 59 globally diverse sediment cores and a correlation structure from model simulations of the last glacial maximum to estimate (with uncertainties) the history of global temperature back through the last few dozen ice ages cycles. There are multiple real things to discuss about this – the methodology, the relatively small number of cores being used (compared to what could have been analyzed), the age modeling etc. – and many interesting applications – constraints on polar amplification, the mid-Pleistocene transition, the duration and nature of previous interglacials – but unfortunately, the bulk of the attention will be paid to a specific (erroneous) claim about Earth System Sensitivity (ESS) that made it into the abstract and was the lead conclusion in the press release.

The paper claims that ESS is ~9ºC and that this implies that the long term committed warming from today’s CO2 levels is a further 3-7ºC. This is simply wrong.

That post is here, go read it.

Meanwhile, I’ll be happy to have a go at explaining this complaint as clearly as I can without using math or physics. I’ll use dogs.

When I leave my house, my dog is always looking out the living room window. When I come home, the dog is always by the front door. The distance between the living room window and the front door is ten meters. Therefore, I can estimate that the final net change in dog location, as a result of whatever movements my dog is making all day, is 10 meters.

Now, I’m going to try to model your dog and see how that goes. That’s where I run into problems. This forces me to generlize the problem by getting much more specific about what the actual dog is doing during any given point in time. I don’t know anyting about you, your dog, or your house, so I need a model that takes all the different factors into account, then I predict what your dog will do. Should be easy, right?

When dogs are left alone, they do several things. They sleep in a few locations, they look out various windows, they visit their food bowl to sniff at it a few times. But what exactly they do is different depending on if the time one leaves the home is in the evening or morning, because of light outside, changing the nature of the window visits. Was the toilet bowl left up or not? Is there a treat hiding under the couch? The complexity is enormous, and you really can’t say much about the movements of the dog all day. Then, when you get home, will your dog, or anyone’s dog, automatically go to the door to wait for you? What if your dog hates you? What if your dog has lousy hearing and you walk home quietly, as opposed to a dog with great hearing, and the owner drives a motorcycle?

While correlation between dog’s position at my house over time works well, and allows me to accurately characterize dog position over time as recorded for the past at my location, it does not take into account the fact that some variables may act differently than the correlation implies.

That’s the argument that Snyder can’t say what she says. GAST responds to dust, albedo, which relates to ice distribution and amount, and that is determined by various climatic factors, etc. etc. As long as everything is the same from glacial cycle to glacial cycle, more or less, we can use a set of glacial cycles to emperically estimate what happens for any other glacial cycle. But if they don’t, then forgetaboutit.

The dog actually did move NET 10 meters every day, no matter what happened in between. But, the correlation is either spurious or at least, underdetermined. The ESS estimate is about how things settle down in the end, not about what happens during a unique period of dramatic climate change.

And this is why the criticisms are both correct and incorrect. I thing the criticisms by Gavin Schmidt and others are not especially relevant or interesting when asking this question: “What is the ESS value controlling Pleistocene climate change (with changing CO2 and GAST) over the last 2 million years?” The answer to that question is 9 (but see Schmidt’s commentary, he has other issues). If you don’t like 9, do your own study, change the way you handle the data, get more data, get an arguably better GAST curve, get better CO2 estimates, and recompute.

However, the answer to the question, “What is the ESS or ECS value governing anthropogenic climate change at present, and over the next few decades, based on Snyder’s temperature curve?

Answer: The dog died. Or it ran out the door in the middle of the day. Or some other doggy metaphor indicating a dramatic gap between expectation and reality, because of humans.

Human impacts on the climate over the last two or more centuries, and especially over recent and upcoming decades, via land use changes and greenhouse gas release, are not the same as what happened during previous interglacials. So, really, while this new work places the entire question in historical context, perhaps it doesn’t actually answer the question, because the house we left the dog in is totally different than it ever has been before.

And the author seems to be saying something roughly along these lines. Snyder told me that she followed prior work that had already “… defined the correlation relationship between global temperature and greenhouse gas radiative forcing changes as ESS as a way to summarize patterns in the Earth’s past climate. This is a useful metric that summarizes a combination of interactive feedbacks in the climate system. This does include changes in longer timescale feedbacks, such as ice sheets, vegetation, and dust, within the ESS metric. It is not ECS, as that is defined as explicitly not including those changes as internal feedbacks, but rather as external forcing that need to be explicitly accounted for separately.” She went on to tell me that the ESS is “a useful reference as a way to summarize past relationships from the paleoclimate record. But again, it is a correlation observed in the past, not a test of causation.”

So, in essence, Snyder is only talking about the dog’s past repeated behavior. ESS, she says, “… is likely state dependent, and thus I focused on comparing my new estimate to estimates from previous research on the late Quaternary. I also was able to investigate the state dependence of the metric within the last 800,000 years and found that it was lower in deep glacial states. This is an interesting finding, as some people have assumed that the ESS metric would be higher at the glacial maxima (e.g., the LGM) than during interglacials. That is not what the data shows.”

Which brings me to a couple of other observations, which may be a bit esoteric but if you think about it, are really quite interesting. Remember above when I said that Milankovitch cycles have varied quite a bit in the past as to whether or not they had a big influence on climate? Snyder confirms or proposes that there was an increase in influence about half way through this time period. She also shows that the Pleistocene cooling continued only up to a certain point, then stopped. And, this research appears to elucidate the relationship between the Arctic and Antarctic, and the rest of the world, a phenomenon known as polar amplification, which is the increase in temperature change at the poles compared to the rest of the planet. Cribbed and reworded a bit from the abstract:

<li>Global temperature gradually cooled until roughly 1.2 million years ago and cooling then stalled until the present. </li>

<li>The cooling occurred, then stalled, before the increase in the maximum size of ice sheets around 0.9 million years ago, so global cooling is shown to be a precondition for a shift in Milankofitch effects to the more recent pattern of ~100,000 year cycles.</li>

<li>Over the past 800,000 years, polar amplification has been stable over time.</li>

<li>Global temperature and atmospheric greenhouse gas concentrations have been closely coupled across glacial cycles. </li>

This may be an evolving situation. I asked Carolyn Snyder a few questions about her research after reading Schmidt’s first post, but before his second was posted, and I do not know if she had read either at that time. So don’t take her quotes from above as addressing his questions. They are merely clarifying remarks. Also, frankly, I’ve not heard the opinions of any of my colleagues who are on the higher end of sensitivity estimates. They may show up tomorrow and get in Snyder’s trench.

Yes, it is true that climate change is controversial. But not whether or not climate change is human caused, real, or important. It is all those things. But within the field itself, the scientist are busy fighting it out, as well they should. I’ll keep you posted.

Diatoms Large and Small

ResearchBlogging.orgDiatoms are algae with hard parts. They make up a major part of the plankton found in fresh and salt water environments. Usually, diatoms exist as single celled free floating organisms, but they can also be colonies of several single cells. Their tiny little ‘shells’ are made up of silica (these shells are called “fustules”).
Continue reading Diatoms Large and Small