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Some of you might have read about the lawsuit by a number of municipalities (including San Francisco and Oakland) against the major oil companies for damages (related primarily to sea level rise) caused by anthropogenic climate change. The legal details on standing, jurisdiction, etc. are all very interesting (follow @ColumbiaClimate for those details), but somewhat uniquely, the judge (William Alsup) has asked for a tutorial on climate science (2 hours of evidence from the plaintiffs and the defendents). Furthermore, he has posted a list of eight questions that he’d like the teams to answer.
It’s an interesting list. They are quite straightforward (with one or two oddities), but really, pretty much textbook stuff. Andrew Dessler made a quick stab at answering them on Twitter:
Here are answers to questions posed by the Judge Alsup re: climate science (https://t.co/DLFDT70PdL). Turns out answers to those questions are actually pretty well known. 1/
But I think we can do better. So what I propose is that we crowd-source the responses. They should be pithy, to the point, with references (not Wikipedia) and, preferentially, accompanied by a good graphic or two. If we can give a credible uncertainty to any numbers in the answer that’s a bonus. I’ve made a start on each, but further voices are needed. Put your response in the comments and I’ll elevate the best ones (giving credit of course) to the main post. If you have any other comments or edits to suggest, feel free to do so. The best of those will also be incorporated.
What caused the various ice ages (including the “little ice age” and prolonged cool periods) and what caused the ice to melt? When they melted, by how much did sea level rise?
What is the molecular difference by which CO2 absorbs infrared radiation but oxygen and nitrogen do not?
What is the mechanism by which infrared radiation trapped by CO2 in the atmosphere is turned into heat and finds its way back to sea level?
Does CO2 in the atmosphere reflect any sunlight back into space such that the reflected sunlight never penetrates the atmosphere in the first place?
Apart from CO2, what happens to the collective heat from tail pipe exhausts, engine radiators, and all other heat from combustion of fossil fuels? How, if at all, does this collective heat contribute to warming of the atmosphere?
In grade school, many of us were taught that humans exhale CO2 but plants absorb CO2 and return oxygen to the air (keeping the carbon for fiber). Is this still valid? If so, why hasn’t plant life turned the higher levels of CO2 back into oxygen? Given the increase in human population on Earth (four billion), is human respiration a contributing factor to the buildup of CO2?
What are the main sources of CO2 that account for the incremental buildup of CO2 in the atmosphere?
What are the main sources of heat that account for the incremental rise in temperature on Earth?
Note this is an updating text. Last edit: March 11, 2018
The “ice ages” are the dominant cycles of change over the last 2.5 million years (Snyder, 2016):
They vary in amplitude and phasing (becoming larger in the last 800,000 years), and moving from a dominant 40,000 yr periodicity in the first half to a 100,000 yr periodicity in the later period. It was discovered in the 1970’s that the pacing of the cycles seen in benthic foraminiferal oxygen isotopes was highly correlated to the Milankovitch cycles of orbital variability (Hays, Imbrie and Shackleton, 1976). More recent work has shown that the growth and collapse of the ice sheets is strongly tied to the insolation (Roe, 2006):
The magnitude of the cycles is strongly modified by various feedbacks, including ice-albedo, dust, vegetation and, of course, the carbon cycle. Estimates of the drivers of global temperature change in the ice ages show that the changes in greenhouse gases (CO2, methane and nitrous oxide) made up about a third of the effect, amplifying the ice sheet changes by about 50% (Köhler et al, 2010).
Greenhouse gases are those that are able to absorb and emit radiation in the infrared, but this is highly dependent on the gases molecular structure. Diatomic molecules (like N2 or O2) have stretching modes (with the distance between the two molecules expanding and contracting), but these require a lot of energy (so they absorb only at higher energies. Vibrational modes in triatomic molecules (H2O, CO2, O3, N2O) or in more complex modecules (CH4, CFCs, HFCs…) are easier to excite and so will absorb and emit lower energy photons (corresponding to the infrared bands, that just happen to be how the Earth loses heat to space).
The Earth’s surface emits infrared radiation. This is absorbed by greenhouse gases, which through collisions with other molecules cause the atmosphere to heat up. Emission from greenhouse gases (in all directions) adds to the warming at the surface.
Not enough to matter. The latest update to the estimates of radiative forcing of CO2 (Etminan et al., 2016) shows a shortwave effect (i.e. a change in the absorption of downward solar radiation) is about -0.14 W/m2 for CO2 going from 389 to 700 ppm (compared to 3.43W/m2 in longwave forcing) – contributing to about a 4% decrease in the net forcing.
Direct heat generated by the total use of fossil fuels and other forms of energy adds up to about 18TW [IEA,2017]. Spread over the planet that is 0.04W/m2. Compared to anthropogenic forcings since 1750 of about 2.29±1.1W/m2 [IPCC AR5, Figure SPM 5], it’s about 1/100th the size. Locally however (say in cities or urban environments), this can be more concentrated and have a bigger impact.
All animals (including humans) breathe in oxygen and exhale CO2. The carbon in the exhaled CO2 comes from the food that the animals have eaten, which comes (ultimately) from carbon that plants have taken from the atmosphere during photosynthesis. So respiration is basically carbon neutral (it releases CO2 to the atmosphere that came from the atmosphere very recently). Note that any net change in biomass (whether trees, or cows or even humans) does affect atmospheric CO2, but the direct impact of human population growth is tiny even though the indirect effects are huge. For scale, the increase of 3 billion people over the last 40 years, is equivalent to:
0.185 (fraction of carbon by mass) * 80 kg (average mass of a human) * 3 billion (additional humans) * 10-3 (conversion to GtC) / 40 years = 0.001 GtC/yr
compared to current fossil fuel and deforestation emissions of ~10 GtC/yr (4 orders of magnitude bigger).
Main sources of human CO2 emissions are fossil fuel burning and (net) deforestation. This figure is from the Global Carbon Project in 2017.
This is the biggie. What is the attribution for the temperature trends in recent decades? The question doesn’t specify a time-scale, so let’s assume either the last 60 years or so (which corresponds to the period specifically addressed by the IPCC, or the whole difference between now and the ‘pre-industrial’ (say the decades around 1850) (differences as a function of baseline are minimal). For the period since 1950, all credible studies are in accord with the IPCC AR5 statement:
It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimate of the human-induced contribution to warming is similar to the observed warming over this period.
Basically, all of the warming trend in the last ~60yrs is anthropogenic (a combination of greenhouse gases, aerosols, land use change, ozone etc.). To get a sense of the breakdown of that per contribution for the global mean temperature, and over a longer time-period, the Bloomberg data visualization, using data from GISS simulations is very useful.
What's Really Warming the World? - YouTube
The difference in the bottom line for attribution for the last ~160 years is that while there is more uncertainty (since aerosol and solar forcings are increasingly shaky that far back), the big picture isn’t any different. The best estimate of the anthropogenic contribution is close to the entire warming. The potential for a solar contribution is slightly higher (perhaps up to 10% assuming maximum estimates for the forcing and impacts). In all cases, the forcing from anthropogenic greenhouse gases alone is greater than the observed warming.
The role of internal climate variability gets smaller as the time-scale increases, but needs to be accounted for in these assessments. Note too that this can go both ways, internal variability might have wanted to cool overall in one period, and warm in another.
P. Köhler, R. Bintanja, H. Fischer, F. Joos, R. Knutti, G. Lohmann, and V. Masson-Delmotte, "What caused Earth's temperature variations during the last 800,000 years? Data-based evidence on radiative forcing and constraints on climate sensitivity", Quaternary Science Reviews, vol. 29, pp. 129-145, 2010. http://dx.doi.org/10.1016/j.quascirev.2009.09.026
M. Etminan, G. Myhre, E.J. Highwood, and K.P. Shine, "Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing", Geophysical Research Letters, vol. 43, pp. 12,614-12,623, 2016. http://dx.doi.org/10.1002/2016GL071930
This month’s open thread on responses to climate change (politics, adaptation, mitigation etc.). Please stay focused on the overall topic. Digressions into the nature and history of communism/feudal societies/anarchistic utopias are off topic and won’t be posted. Thanks. The open thread for climate science topics is here.
The responses to the last post on the Rideau Canal Skateway season changes were interesting, and led to a few pointers to additional data sets that show similar trends and some rather odd counter-points from the usual suspects.
The most comprehensive (and up-to-date) set of “ice out” data for lakes is, unsurprisingly perhaps, from the Dept. of Natural Resources in Minnesota. Data (sometimes patchy) goes back in places to the 19th Century. The earliest data is for Lake Pepin starting in 1843. By 1900, there are a further 6 lakes with data: Clear, Christmas, Minnetonka, Osakis, Sagatagan, and Shields.
Figure 1: The seven longest data sets of Minnesotan lake “ice out” dates (with data back to at least 1900). Ice out date is shown relative to the vernal equinox (see below for details). Red lines are loess ~30yr smooths.
One commentator on twitter made a point of picking out Lake Minnetonka, and noting that the earliest ice out date on record was in 1878, as if that negated any of the long term trends there or elsewhere. It is however quite interesting to look into data from that year. Pepin, Osakis and Clear had huge anomalies that year, and estimates of regional temperature show a very warm winter that has only recently been matched. Given the standard deviation in the residuals (about 10 days), the 30+ day earlier ice out was a massive anomaly (more than 3) and was noticed and commented on at the time. Contemporary reports from Minneapolis described it the “Year without a Winter”. But one warm winter does not a trend make, and the trends in almost all the lakes are clearly towards an earlier ice out over the last 40 years. Given the interannual variability though, you still need a multiple decades to significantly detect a trend of 10 days or so per century.
Other North American lakes
There are good data sets for dozens of other lakes in North America, notably ice duration from Lakes Mendota and Monona in Wisconsin. Note that ice duration is slightly less noisy dataset than ice out.
One reader pointed me to a graph of declining “schaatsdagen” (skate days) at De Bilt in the Netherlands made by Bart Vreeken. There is a partial dataset online, but I’m not really clear on the provenance of the data or how it was calculated.
Note on accounting for calendrical anomalies
Because of the fact that the orbital period of the Earth around the sun is not an integer number of days, the astronomical “seasons” move around a little in the calendar. Thankfully, it doesn’t move around quite as much since the adoption of the Gregorian Calendar, but on short timescales (< 500 years) the impacts of leap years and the variation of the vernal equinox can alias climatic trends. The VE is normally either the 20th or 21st of March, though this century will have a few years with the VE on March 19th as well (calculations are here). Records which are based on calendrical dates (such as ice on, or ice out) therefore have a little noise in them just because of this. So for ease of comparison, in my plots I generally show the number of days from the vernal equinox to account for it. This is a small correction and in general doesn’t make any noticeable difference, though it can affect the rankings of individual years.
Since 1971, the National Capitol Commission (NCC) in Ottawa has (once the ice is thick enough for safe skating) methodically tried to keep the frozen canal available for ice skaters (by clearing snow, smoothing surfaces, filling cracks etc.). This is possible only if the weather permits – first by being cold enough to sufficiently freeze the ice, and second by not being warm enough to melt the ice surface as the season progresses. Apart from the first season, which was not planned ahead of time, each year since has been anticipated to start in the second half of December (or early January) and ideally extends to March.
However, DJF temperatures in Ottawa have been rising, and so one might anticipate some trends in opening/closing dates and the length of the skating season. This year’s season (Jan 5th to Feb 21st) was shorter than the average season, but is that part of a trend?
The weather factors underlying the year-to-year variability in the season length were explored in Brammer et al (2015), and they used that to predict a slow decline in viability over time. For instance, the correlation of season length to the (negative) mean DJF temperature anomaly is over 0.4.
Oddly enough the full data set of season dates, length (since 1971) and skating days (collected since 1995) does not appear to be publically available from NCC. However, some of it is around (here and here), and so one can put together a full dataset of season lengths, skating days (since 1995), and opening/closing dates (since 2002).
Updating the Brammer et al graph to 2018 (including the record shortest season in 2016) is straightforward:
As expected, there are clear trends in season length (a reduction of ~23±11 days (95% CI) since 1972), and while there are decreases in skating days, they aren’t significant due to the too short period (similarly with the available opening/closing dates). There is of course the possibility on non-climatic artifacts. Increasing skill/experience of the Skateway managers might prolong the season, while decreasing tolerances for risk(?) might shorten it. These are issues that are hard to quantify without much greater amounts of the meta-data associated with the opening and closing.
Nevertheless, we have another independent dataset which conforms to our expectations that outdoor ice in North America is suffering.
The basic facts about the global increase of CO2 in our atmosphere are clear and established beyond reasonable doubt. Nevertheless, I’ve recently seen some of the old myths peddled by “climate skeptics” pop up again.Are the forests responsible for the CO2 increase? Or volcanoes? Or perhaps the oceans?
Let’s start with a brief overview of the most important data and facts about the increase in the carbon dioxide concentration in the atmosphere:
Since the beginning of industrialization, the CO2 concentration has risen from 280 ppm (the value of the previous millennia of the Holocene) to now 405 ppm.
This increase by 45 percent (or 125 ppm) is completely caused by humans.
The additional 125 ppm CO2 have a heating effect of 2 watts per square meter of earth surface, due to the well-known greenhouse effect – enough to raise the global temperature by around 1 °C until the present.
Fig. 1 Perhaps the most important scientific measurement series of the 20th century: the CO2 concentration of the atmosphere, measured on Mauna Loa in Hawaii. Other stations of the global CO2 measurement network show almost exactly the same; the most important regional variation is the greatly subdued seasonal cycle at stations in the southern hemisphere. This seasonal variation is mainly due to the “inhaling and exhaling” of the forests over the year on the land masses of the northern hemisphere. Source (updated daily): Scripps Institution of Oceanography.
Fig. 2 The CO2 concentration of the atmosphere during the Holocene, measured in the ice cores from Antarctica until 1958, afterwards Mauna Loa. Source: Scripps Institution of Oceanography.
These facts are well known and easy to understand. Nevertheless, I am frequently confronted with attempts to play down the dangerous CO2-increase, e.g. recently in the right-leaning German newspaper Die Welt.
Are the forests to blame?
Die Welt presented a common number-trick by climate deniers (readers can probably point to some english-language examples):
In fact, carbon dioxide, which is blamed for climate warming, has only a volume share of 0.04 percent in the atmosphere. And of these 0.04 percent CO2, 95 percent come from natural sources, such as volcanoes or decomposition processes in nature. The human CO2 content in the air is thus only 0.0016 percent.
The claim “95 percent from natural sources” and the “0.0016 percent” are simply wrong (neither does the arithmetic add up – how would 5% of 0.04 be 0.0016?). These (and similar – sometimes you read 97% from natural sources) numbers have been making the rounds in climate denier circles for many years (and have repeatedly been rebutted by scientists). They present a simple mix-up of turnover and profit, in economic terms. The land ecosystems have, of course, a high turnover of carbon, but (unlike humans) do not add any net CO2 to the atmosphere. Any biomass which decomposes must first have grown – the CO2 released during rotting was first taken from the atmosphere by photosynthesis. This is a cycle. Hey, perhaps that’s why it’s called the carbon cycle!
That is why one way to reduce emissions is the use of bioenergy, such as heating with wood (at least when it’s done in a sustainable manner – many mistakes can be made with bioenergy). Forests only increase the amount of CO2 in the air when they are felled, burnt or die. This is immediately understood by looking at a schematic of the carbon cycle, Fig. 3.
Fig. 3 Scheme of the global carbon cycle. Values for the carbon stocks are given in Gt C (ie, billions of tonnes of carbon) (bold numbers). Values for average carbon fluxes are given in Gt C per year (normal numbers). Source: WBGU 2006 . (A similar graph can also be found at Wikipedia.) Since this graph was prepared, anthropogenic emissions and the atmospheric CO2 content have increased further, see Figs 4 and 5, but I like the simplicity of this graph.
If one takes as the total emissions a “natural” part (60 GtC from soils + 60 GtC from land plants) and the 7 GtC fossil emissions as anthropogenic part, the anthropogenic portion is about 5% (7 of 127 billion tons of carbon) as cited in the Welt article. This percentage is highly misleading, however, since it ignores that the land biosphere does not only release 120 GtC but also absorbs 122 GtC by photosynthesis, which means that net 2 GtC is removed from the atmosphere. Likewise, the ocean removes around 2 GtC. To make any sense, the net emissions by humans have to be compared with the net uptake by oceans and forests and atmosphere, not with the turnover rate of a cycle, which is an irrelevant comparison. And not just irrelevant – it becomes plain wrong when that 5% number is then misunderstood as the human contribution to the atmospheric CO2 concentration.
The natural earth system thus is by no means a source of CO2 for the atmosphere, but it is a sink! Of the 7 GtC, which we blow into the atmosphere every year, only 3 remain there. 2 are absorbed by the ocean and 2 by the forests. This means that in the atmosphere and in the land biosphere and in the ocean the amount of stored carbon is increasing. And the source of all this additional carbon is the fact that we extract loads of fossil carbon from the earth’s crust and add it to the system. That’s already clear from the fact that we add twice as much to the atmosphere as is needed to explain the full increase there – that makes it obvious that the natural Earth system cannot possibly be adding more CO2 but rather is continually removing about half of our CO2 emissions from the atmosphere.
The system was almost exactly in equilibrium before humans intervened. That is why the CO2 concentration in the air was almost constant for several thousand years (Figure 2). This means that the land ecosystems took up 120 GtC and returned 120 GtC (the exact numbers don’t matter here, what matters is that they are the same). The increased uptake of CO2 by forests and oceans of about 2 GtC per year each is already a result of the human emissions, which has added enormous amounts of CO2 to the system. The ocean has started to take up net CO2 from the atmosphere through gas exchange at the sea surface: because the CO2 concentration in the atmosphere is now higher than in the surface ocean, there is net flux of CO2 into the sea. And because trees take up CO2 by photosynthesis and can do this more easily if you offer them more CO2 in the air, they have started to photosynthesize more and thus take up a bit more CO2 than is released by decomposing old biomass. (To what extent and for how long the land biosphere will remain a carbon sink is open to debate, however: this will depend on the extent to which the global ecosystems come under stress by global warming, e.g. by increasing drought and wildfires.)
The next diagram shows (with more up-to-date and accurate numbers) the net fluxes of CO2 (this time in CO2 units, not carbon units!).
Fig. 4 CO2 budget for 2007-2016, showing the various net sources and sinks. The figures here are expressed in gigatons of CO2 and not in gigatons of carbon as in Fig. 3. The conversion factor is 44/12 (molecular weight of CO2 divided by atomic weight of carbon). Source: Global Carbon Project.
Fig. 5 shows where the CO2 comes from (in the upper half you see the sources – fossil carbon and deforestation) and where it ends up (in the lower half you sees the sinks), in the course of time. It ends up in comparably large parts in air, oceans and forests. The share absorbed by the land ecosystems varies greatly from year to year, depending on whether there were widespread droughts, for example, or whether it was a good growth year for the forests. That is why the annual CO2 increase in the atmosphere also varies greatly each year, and this short-term variation is not mainly caused by variations in our emissions (so a record CO2 increase in the atmosphere in an El Niño year does not mean that human emissions have surged in that year).
Fig. 5 Annual emissions of carbon from fossil sources and deforestation, and annual emissions from the biosphere, atmosphere and ocean (the latter are negative, meaning net uptake). This is again in carbon (not CO2) units; the 12 gigatons of carbon emitted in 2016 are a lot more than the 7 gigatons in the older Fig. 3. Source: Global Carbon Project.
The “climate skeptics” blaming the forests for most of the increase in atmospheric CO2, because of decaying foliage and deadwood, is not merely wrong, it is pretty bonkers. Have leaves started to decompose only since industrialization? Media with a minimum aspiration to credibility should clearly reject such nonsense, instead of spreading it further. In case of Die Welt, one of my PIK colleagues had explicitly pointed out to the author, in response to a query by him, that the 5% human share of CO2 is misleading and that humans have caused a 45% increase. That the complete CO2 increase is anthropogenic has been known for decades. The first IPCC report, published in 1990, put it thus:
Since the industrial revolution the combustion of fossil fuels and deforestation have led to an increase of 26% in carbon dioxide concentration in the atmosphere.
In the 27 years since then, the CO2 increase caused by our emissions has gone up from 26% to 45%.
How Exxon misled the public against better knowledge
One fascinating question is where this false idea of humans just contributing a tiny bit to the relentless rise in atmospheric CO2 has come from? Have a look at this advertorial (a paid-for editorial) by ExxonMobil in the New York Times from 1997:
Fig. 6 Excerpt from the New York Times of 6 November 1997
The text to go with it read:
While most of the CO2 emitted by far is the result of natural phenomena – namely respiration and decomposition, most attention has centered on the three to four percent related to human activities – burning of fossil fuels, deforestation.
That is pretty clever and could hardly be an accident. The impression is given that human emissions are not a big deal and only responsible for a small percentage of the CO2 increase in the atmosphere – but without explicitly saying that. In my view the authors of this piece knew that this idea is plain wrong, so they did not say it but preferred to insinuate it. A recent publication by Geoffrey Supran und Naomi Oreskes in Environmental Research Letters has systematically assessed ExxonMobil’s climate change communications during 1977–2014 and found:
We conclude that ExxonMobil contributed to advancing climate science—by way of its scientists’ academic publications—but promoted doubt about it in advertorials. Given this discrepancy, we conclude that ExxonMobil misled the public.
Another age-old climatic skeptic myth, is that the CO2 is coming from volcanoes – first time I had to rebut this was as a young postdoc in the 1990s. The total volcanic emissions are between 0.04 and 0.07 gigatonnes of CO2 per year, compared to the anthropogenic emissions of 12 gigatons in 2016. Anthropogenic emissions are now well over a hundred times greater than volcanic ones. The volcanic emissions are important for the long-term CO2 changes over millions of years, but not over a few centuries.
Does the CO2 come from the ocean?
As already mentioned and shown in Figs. 4 and 5, the oceans absorb net CO2 and do not release any. The resulting increase in CO2 in the upper ocean is documented and mapped in detail by countless ship surveys and known up to a residual uncertainty of + – 20% . This is, in itself, a very serious problem because it leads to the acidification of the oceans, since CO2 forms carbonic acid in water. The observed CO2 increase in the world ocean disproves another popular #fakenews piece of the “climate skeptics”: namely that the CO2 increase in the atmosphere might have been caused by the outgassing of CO2 from the ocean as a result of the warming. No serious scientist believes this.
Remember also from Figs. 4 and 5 that we emit about twice as much CO2 as is needed to explain the complete rise in the atmosphere. In case you have not connected the dots: the denier myth of the oceans as cause of the atmospheric CO2 rise most often comes in the form of “the CO2 rise lagged behind temperature rise in glacial cycles”. It is true that during ice ages the oceans took up more CO2 and that is why there was less in the atmosphere, and during the warming at the end of glacial cycles that CO2 came back out of the ocean, and this was an important amplifying feedback. But it is a fallacy to conclude that the same natural phenomenon is happening again now. As I explained above: measurements clearly prove that the modern CO2 rise has a different cause, namely our fossil fuel use. What is the same now and over past glacial cycles is not the CO2 source, but the greenhouse effect of the atmospheric CO2 changes: without that we could not understand (or correctly simulate in our climate models) the full extent of glacial cycles.
The cyanide cocktail
A man offers you a cocktail with a little bit of cyanide at a party. You reject that indignantly, but the man assures you it is completely safe: after all, the amount of cyanide in your body after this drink would be only 0.001 percent! This could hardly be harmful! Those scientists who claim that 3 mg cyanide per kg of body weight (ie 0.0003 percent) are fatal are obviously not to be trusted. Are you falling for that argument?
We hope not, and we hope you will neither fall for the claim that 0.0125 percent of CO2 (that’s the 125 ppm increase caused by humans) can’t be bad because that number is small. Of course, the amount of CO2 in the air could also be expressed in kilograms: it is 3200 billion tons or 3,200,000,000,000,000 kilograms. Of this humans are responsible for almost 1000 billion tons. (Does that sound more harmful than 0.0125 percent?) Since the year 1870, we have even emitted a total of about 2,000 billion tons. As already explained, forests and oceans have removed about half of that from the atmosphere.
Scientists specify the concentration of individual gases in the atmosphere as volume fractions (rather than, e.g., grams per cubic meter of air) because then the numbers do not depend on temperature and pressure, which vary greatly in the atmosphere. As far as climatic impact is concerned, however, the fraction of the total mass of the atmosphere is irrelevant since the atmosphere consists of 99.9% nitrogen, oxygen and argon, i.e. gases which cannot absorb infrared radiation. Only molecules made of at least three atoms absorb heat radiation and thus only such trace gases makes the greenhouse effect, and among these CO2 is the second most important after water vapor. All this has been known since John Tyndall’s measurements of the greenhouse effect of various gases in 1859. Tyndall back then wrote:
[T]he atmosphere admits of the entrance of the solar heat, but checks its exit; and the result is a tendency to accumulate heat at the surface of the planet.
That is still a great concise description of the greenhouse effect! Without CO2 in the air our planet would be completely frozen, no life would be possible. With CO2, we are turning one of the major control knobs of global climate.
The climate effect
So let’s finally come to the climatic effect of the CO2 increase. As for cyanide, the effect is what counts, and not whether compared to some large mass the fraction is 10 percent or 0.01 percent. The dose effect of toxins on humans can be determined from experience with victims. The climatic impact of greenhouse gases can either be calculated on the basis of an understanding of the physical processes, or it can be determined from the experience of climate history (see my previous post). Both come to the same conclusion. The climate sensitivity (global warming in equilibrium after CO2 doubling) is around 3 °C, and the expected warming to date, due to the current CO2 increase, is around 1 °C. This corresponds quite exactly to the observed global warming (Fig. 7). For which, by the way, there is no natural explanation, and the best estimate for the anthropogenic share of global warming since 1950 is 110 percent – more on this in my previous post.
Fig. 7 Time evolution of global temperature, CO2 concentration and solar activity. Temperature and CO2 are scaled relative to each other as the physically expected CO2 effect on the climate predicts (i.e. best estimate of the climate sensitivity). The amplitude of the solar curve is scaled as derived from the observed correlation of solar and temperature data. (Details are explained here ). This graph can be created here and you can copy a code that can be used as a widget in any website (as in my home page), where it is automatically updated every year with the latest data. Thanks to Bernd Herd who programmed this.
Finally, here is a slick new video clip illustrating the history of CO2 emissions on the map:
A revised calculation of how greenhouse gases drive up the planet’s temperature reduces the range of possible end-of-century outcomes by more than half, …
It was based on a study recently published in Nature (Cox et al. 2018), however, I think its conclusions are premature.
The calculations in question involved both an over-simplification and a set of assumptions which limit their precision, if applied to Earth’s real climate system.
They provide a nice idealised and theoretical description, but they should not be interpreted as an accurate reflection of the real world.
There are nevertheless some interesting concepts presented in the analysis, such as the connection between climate sensitivity and the magnitude of natural variations.
Both are related to feedback mechanisms which can amplify or dampen initial changes, such as the connection between temperature and the albedo associated with sea-ice and snow. Temperature changes are also expected to affect atmospheric vapour concentrations, which in turn affect the temperature through an increased greenhouse effect.
However, the magnitude of natural variations is usually associated with the transient climate sensitivity, and it is not entirely clear from the calculations presented in Cox et al. (2018) how the natural variability can provide a good estimate of the equilibrium climate sensitivity, other than using the “Hasselmann model” as a framework:
Cox et al. assumed that the same feedback mechanisms are involved in both natural variations and a climate change due to increased CO2. This means that we should expect a high climate sensitivity if there are pronounced natural variations.
But it is not that simple, as different feedback mechanisms are associated with different time scales. Some are expected to react rapidly, but others associated with the oceans and the carbon cycle may be more sluggish. There could also be tipping points, which would imply a high climate sensitivity.
The Hasselmann model is of course a gross simplification of the real climate system, and such a crude analytical framework implies low precision for when the results are transferred to the real world.
To demonstrate such lack of precision, we can make a “quick and dirty” evaluation of how well the Hasselmann model fits real data based on forcing from e.g. Crowley (2000) through an ordinary linear regression model.
The regression model can be rewritten as , where , , and . In addition, and are the regression coefficients to be estimated, and is a constant noise term (more details in the R-script used to do this demonstration).
Figure 1. Test of the Hasselmann model through a regression analysis, where the coloured curves are the best-fit modelled values for Q based on the Hasselmann model and global mean temperatures (PDF).
It is clear that the model fails for the dips in the forcing connected volcanic eruptions (Figure 1). We also see a substantial scatter in both (some values are even negative and hence unphysical) and (Figure 2).
Figure 2. The regression coefficients. Negative values for C are unphysical and suggest that the Hasselmann model is far from perfect. The estimated error margins for C are substantial, however, and also include positive values. Blue point shows the estimates for NCEP/NCAR reanalysis. The shaded areas cover the best estimates plus/minus two standard errors (PDF).
The climate sensitivity is closest associated with , for which the mean estimate was 1.11, with a 5-95-percentile interval of 0.74-1.62.
We can use these estimates in a naive attempt to calculate the temperature response for a stable climate with and a doubled forcing associated with increased CO2.
It’s plain mathematics. I took a doubling of 1998 CO2-forcing of 2.43 from Crowley (2000), and used the non-zero terms in the Hasselmann model, .
The mean temperature response to a doubled CO2-forcing for GCMs was 2.36, with a 90% confidence interval: 1.5 – 3.3. The estimate from reanalysis was 1.71
The true equilibrium climate sensitivity for the climate models used in this demonstration is in the range 2.1 – 4.4 , and the transient climate sensitivity is 1.2 – 2.6 (IPCC AR5, Table 8.2).
This demonstration suggests that the Hasselmann model underestimates the climate sensitivity and the over-simplified framework on which it is based precludes high precision.
Another assumption made in the calculations was that the climate forcing Q looks like a white noise after the removal of the long-term trends.
This too is questionable, as there are reasons to think the ocean uptake of heat varies at different time scales and may be influenced by ENSO, the Pacific Decadal Oscillation (PDO), and the Atlantic Multi-decadal Oscillation (AMO). The solar irradiance also has an 11-year cycle component and volcanic eruptions introduce spikes in the forcing (see Figure 1).
Cox et al.’s calculations were also based on another assumption somewhat related to different time scales for different feedback mechanisms: a constant “heat capacity” represented by C in the equation above.
The real-world “heat capacity” is probably not constant, but I would expect it to change with temperature.
Since it reflects the capacity of the climate system to absorb heat, it may be influenced by the planetary albedo (sea-ice and snow) and ice-caps, which respond to temperature changes.
It’s more likely that C is a non-linear function of temperature, and in this case, the equation describing the Hasselmann model would look like:
Cox et al.’s calculations of the equilibrium climate sensitivity used a key metric which was derived from the Hasselmann model and assumed a constant C: . This key metric would be different if the heat capacity varied with temperature, which subsequently would affect the end-results.
I also have an issue with the confidence interval presented for the calculations, which was based on one standard deviation . The interval of represents a 66% probability, and can be illustrated with three numbers: and two of them are “correct” and one “wrong”, which means there is a 1/3 chance that I pick the “wrong” number if I were to randomly pick one of the three.
To be fair, the study also stated the 90% confidence interval, but it was not emphasised in the abstract nor in the press-coverage.
One thing that was not clear, was whether the analysis, that involved both observed temperatures from the HadCRUT4 dataset and global climate models, took into account the fact that the observations do not cover 100% of Earth’s surface (see RC post ‘Mind the Gap!’).
A spatial mask would be appropriate to ensure that the climate model simulations provide data for only those regions where observations exists. Moreover, it would have to change over time because the thermometer observations have covered a larger fraction of Earth’s area with time (see Figure 3).
An increase in data coverage will affect the estimated variance and one-year autocorrelation associated with the global mean temperature, which also should influence the the metric .
Figure 3. The area of Earth’s surface with valid temperature data (PDF).
My last issue with the calculations is that the traditional definition of climate sensitivity only takes into account changes in the temperature. However, there is also a possibility that a climate change involves a change in the hydrological cycle. I have explained this possibility in a review of the greenhouse effect (Benestad, 2017), and this possibility would add another term the equation describing the Hasselmann model.
I nevertheless think the study is interesting and it is impressive that the results are so similar to previously published results. However, I do not think the results are associated with the stated precision because of the assumptions and the simplifications involved. Hence, I disagree with the following statement presented in the Guardian:
These scientists have produced a more accurate estimate of how the planet will respond to increasing CO2 levels
P.M. Cox, C. Huntingford, and M.S. Williamson, "Emergent constraint on equilibrium climate sensitivity from global temperature variability", Nature, vol. 553, pp. 319-322, 2018. http://dx.doi.org/10.1038/nature25450
This is a thread to discuss the surface temperature records that were all released yesterday (Jan 18). There is far too much data-vizualization on this to link to, but feel free to do so in the comments. Bottom line? It’s still getting warmer.
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