By Stefan Rahmstorf and Martin Vermeer

The scientific sea level discussion has moved a long way since the last IPCC report was published in 2007 (see our post back then). The Copenhagen Synthesis Report recently concluded that “The updated estimates of the future global mean sea level rise are about double the IPCC projections from 2007″. New Scientist last month ran a nice article on the state of the science, very much in the same vein. But now Mark Siddall, Thomas Stocker and Peter Clark have countered this trend in an article in Nature Geoscience, projecting a global rise of only 7 to 82 cm from 2000 to the end of this century.

Coastal erosion: Like the Dominican Republic, many island nations are
particularly vulnerable to sea level rise. (Photo: S.R.)

Semi-empirical sea level models

Siddall et al. use a semi-empirical approach similar to the one Stefan proposed in Science in 2007 (let’s call that R07) and to Grinsted et al. (2009), which we discussed here. What are the similarities and where do the differences come from?

For short time scales and small temperature changes everything becomes linear and the two new approaches are mathematically equivalent to R07 (see footnote 1). They can all be described by the simple equation:

dS/dt = a ΔT(t) + b     (Eq 1)

dS/dt is the rate of change of sea level S, ΔT is the warming above some baseline temperature, and a and b are constants. The baseline temperature can be chosen arbitrarily since any constant temperature offset can be absorbed into b. This becomes clear with an example: Assume you want to compute sea level rise from 1900-2000, using as input a temperature time series like the global GISS data. A clever choice of baseline temperature would then be the temperature around 1900 (averaged over 20 years or so, we’re not interested in weather variability here). Then you can integrate the equation from 1900 to 2000 to get sea level relative to 1900:

S(t) = a ∫ΔT(t’) dt’ + b t     (Eq 2)

There are two contributions to 20th C sea level rise: one from the warming in the 20th Century (let’s call this the “new rise”), and a sea level rise that results from any climate changes prior to 1900, at a rate b that was already present in 1900 (let’s call this the “old rise”). This rate is constant for 1900-2000 since the response time scale of sea level is implicitly assumed to be very long in Eq. 1. A simple matlab/octave code is provided below (2).

If you’re only interested in the total rise for 1900-2000, the temperature integral over the GISS data set is 25 ºC years, which is just another way of saying that the mean temperature of the 20th Century was 0.25 ºC above the 1900 baseline. The sea level rise over the 20th Century is thus:

S(1900-2000) = 25 a + 100 b     (Eq. 3)

Compared to Eq. 1, both new studies introduce an element of non-linearity. In the approach of Grinsted et al, sea level rise may flatten off (as compared to what Eq 1 gives) already on time scales of a century, since they look at a single equilibration time scale τ for sea level with estimates ranging from 200 years to 1200 years. It is a valid idea that part of sea level rise responds on such time scales, but this is unlikely to be the full story given the long response time of big ice sheets.

Siddall et al. in contrast find a time scale of 2900 years, but introduce a non-linearity in the equilibrium response of sea level to temperature (see their curve in Fig. 1 and footnote 3 below): it flattens off strongly for warm temperatures. The reason for both the long time scale and the shape of their equilibrium curve is that this curve is dominated by ice volume changes. The flattening at the warm end is because sea level has little scope to rise much further once the Earth has run out of ice. However, their model is constructed so that this equilibrium curve determines the rate of sea level rise right from the beginning of melting, when the shortage of ice arising later should not play a role yet. Hence, we consider this nonlinearity, which is partly responsible for the lower future projections compared to R07, physically unrealistic. In contrast, there are some good reasons for the assumption of linearity (see below).

Comparison of model parameters

But back to the linear case and Eq. 1: how do the parameter choices compare? a is a (more or less) universal constant linking sea level to temperature changes, one could call it the sea level sensitivity. b is more situation-specific in that it depends both on the chosen temperature baseline and the time history of previous climate changes, so one has to be very careful when comparing b between different models.

For R07, and referenced to a baseline temperature for the year 1900, we get a = 0.34 cm/ºC/year and b = 0.077 cm/year. Corresponding values of Grinsted et al. are shown in the table (thanks to Aslak for giving those to us!).

For Siddall et al, a = s/τ where s is the slope of their sea level curve, which near present temperatures is 4.8 meters per ºC and τ is the response the time scale. Thus a = 0.17 cm/ºC/year and b = 0.04 cm /year (see table). The latter can be concluded from the fact that their 19th Century sea level rise, with flat temperatures (ΔT(t) = 0) is 4 cm. Thus, in the model of Siddall et al, sea level (near the present climate) is only half as sensitive to warming as in R07. This is a second reason why their projection is lower than R07.

Model	a [cm/ºC/year]	b [cm /year]	“new rise” [cm] (25a)	“old rise” [cm] (100b)	25a+100b [cm]	total model rise [cm]
Rahmstorf	0.34	0.077	8.5	7.7	16.2	16.2
Grinsted et al “historical”	0.30	0.141	7.5	14.1	21.6	21.3
Grinsted et al “Moberg”	0.63	0.085	(15.8)	(8.5)	(24.3)	20.6
Siddall et al	0.17	0.04	4.3	4	8.3	8.3 (?) 7.9

Performance for 20th Century sea level rise

For the 20th Century we can compute the “new” sea level rise due to 20th Century warming and the “old” rise due to earlier climate changes from Eq. 3. The results are shown in the table. From Grinsted et al, we show two versions fitted to different data sets, one only to “historical” data using the Jevrejeva et al. (2006) sea level from 1850, and one using the Moberg et al. (2006) temperature reconstruction with the extended Amsterdam sea level record starting in the year 1700.

First note that “old” and “new” rise are of similar magnitude for the 20th Century because of the small average warming of 0.25 ºC. But it is the a-term in Eq. (2) that matters for the future, since with future warming the temperature integral becomes many times larger. It is thus important to realise that the total 20th Century rise is not a useful data constraint on a, because one can get this right for any value of a as long as b is chosen accordingly. To constrain the value of a – which dominates the 21st Century projections — one needs to look at the “new rise”. How much has sea level rise accelerated over the 20th Century, in response to rising temperatures? That determines how much it will accelerate in future when warming continues.

The Rahmstorf model and the Grinsted “historical” case are by definition in excellent agreement with 20th Century data (and get similar values of a) since they have been tuned to those. The main difference arises from the differences between the two sea level data sets used: Church and White (2006) by Rahmstorf, Jevrejeva et al. (2006) by Grinsted et al. Since the “historical” case of Grinsted et al. finds a ~1200-year response time scale, these two models are almost fully equivalent on a century time scale (e^-100/1200=0.92) and give nearly the same results. The total model rise in the last column is just 1.5 percent less than that based on the linear Eq. 3 because of that finite response time scale.

For the Grinsted “Moberg” case the response time scale is only ~210 years, hence our linear approximation becomes bad already on a century time scale (e^-100/210=0.62, the total rise is 15% less than the linear estimate), which is why we give the linear estimates only in brackets for comparison here.

The rise predicted by Siddall et al is much lower. That is not surprising, since their parameters were fitted to the slow changes of the big ice sheets (time scale τ=2900 years) and don’t “see” the early response caused by thermal expansion and mountain glaciers, which makes up most of the 20th Century sea level rise. What is surprising, though, is that Siddall et al. in their paper claim that their parameter values reproduce 20th Century sea level rise. This appears to be a calculation error (4); this will be resolved in the peer-reviewed literature. Our values in the above table are computed correctly (in our understanding) using the same parameters as used by the authors in generating their Fig.3. Their model with the parameters fitted to glacial-interglacial data thus underestimates 20th Century sea level rise by a factor of two.

Future projections

It thus looks like R07 and Grinsted et al. both reproduce 20th Century sea level rise and both get similar projections for the 21st Century. Siddall et al. get much lower projections but also strongly under-estimate 20th Century sea level rise. We suspect this will hold more generally: it would seem hard to reproduce the 20th Century evolution (including acceleration) but then get very different results for the 21st Century, with the basic semi-empirical approach common to these three papers.

In fact, the lower part of their 7-82 cm range appears to be rather implausible. At the current rate, 7 cm of sea level rise since 2000 will be reached already in 2020 (see graph). And Eq. 1 guarantees one thing for any positive value of a: if the 21st Century is warmer than the 20th, then sea level must rise faster. In fact the ratio of new sea level rise in the 21st Century to new sea level rise in the 20th Century according to Eq. 2 is not dependent on a or b and is simply equal to the ratio of the century-mean temperatures, T₂₁/T₂₀ (both measured again relative to the 1900 baseline). For the “coldest” IPCC-scenario (1.1 ºC warming for 2000-2100) this ratio is 1.3 ºC / 0.25 ºC = 5.2. Thus even in the most optimistic IPCC case, the linear semi-empirical approach predicts about five times the “new” sea level rise found for the 20th Century, regardless of parameter uncertainty. In our view, when presenting numbers to the public scientists need to be equally cautious about erring on the low as they are on the high side. For society, after all, under-estimating global warming is likely the greater danger.

Does the world have to be linear?

How do we know that the relationship between temperature rise and sea level rate is linear, also for the several degrees to be expected, when the 20th century has only given us a foretaste of 0.7 degrees? The short answer is: we don’t.

A slightly longer answer is this. First we need to distinguish two things: linearity in temperature (at a given point in time, and all else being equal), and linearity as the system evolves over time. The two are conflated in the real world, because temperature is increasing over time.

Linearity in temperature is a very reasonable assumption often used by glaciologists. It is based on a heat flow argument: the global temperature anomaly represents a heat flow imbalance. Some of the excess heat will go into slowly warming the deep ocean, some will be used to melt land ice, a tiny little bit will hang around in the atmosphere to be picked up by the surface station network. If the anomaly is 2 ºC, the heat flow imbalance should be double that caused by a 1 ºC anomaly. That idea is supported by the fact that the warming pattern basically stays the same: a 4 ºC global warming scenario basically has the same spatial pattern as a 2 ºC global warming scenario, only the numbers are twice as big (cf. Figure SMP6 of the IPCC report). It’s the same for the heating requirement of your house: if the temperature difference to the outside is twice as big, it will lose twice the amount of heat and you need twice the heating power to keep it warm. It’s this “linearity in temperature” assumption that the Siddall et al. approach rejects.

Linearity over time is quite a different matter. There are many reasons why this cannot hold indefinitely, even though it seems to work well for the past 120 years at least. R07 already discusses this and mentions that glaciers will simply run out of ice after some time. Grinsted et al. took this into account by a finite time scale. We agree with this approach – we merely have some reservations about whether it can be done with a single time scale, and whether the data they used really allow to constrain this time scale. And there are arguments (e.g. by Jim Hansen) that over time the ice loss may be faster than the linear approach suggests, once the ice gets wet and soft and starts sliding. So ultimately we do not know how much longer the system will behave in an approximately linear fashion, and we do not know yet whether the real sea level rise will then be slower or faster than suggested by the linear approach of Eq. 1.

Getting soft? Meltwater lake and streams on the Greenland Ice Sheet near 68ºN at 1000 meters altitude. Photo by Ian Joughin.

Can paleoclimatic data help us?

Is there hope that, with a modified method, we may successfully constrain sea level rise in the 21st Century from paleoclimatic data? Let us spell out what the question is: How will sea level in the present climate state respond on a century time scale to a rapid global warming? We highlight three aspects here.

Present climate state. It is likely that a different climate state (e.g. the glacial with its huge northern ice sheets) has a very different sea level sensitivity than the present. Siddall et al. tried to account for that with their equilibrium sea level curve – but we think the final equilibrium state does not contain the required information about the initial transient sensitivity.

Century time scale. Sea level responds on various time scales – years for the ocean mixed layer thermal expansion, decades for mountain glaciers, centuries for deep ocean expansion, and millennia for big ice sheets. Tuning a model to data dominated by a particular time scale – e.g. the multi-century time scale of Grinsted et al. or the multi-millennia time scale of Siddall et al. – does not mean the results carry over to a shorter time scale of interest.

Global warming. We need to know how sea level – oceans, mountain glaciers, big ice sheets all taken together – responds to a globally near-uniform forcing (like greenhouse gas or solar activity changes). Glacial-interglacial climate changes are forced by big and highly regional and seasonal orbital insolation changes and do not provide this information. Siddall et al use a local temperature curve from Greenland and assume there is a constant conversion factor to global-mean temperature that applies across the ages and across different mechanisms of climate change. This problem is not discussed much in the paper; it is implicit in their non-dimensional temperature, which is normalised by the glacial-holocene temperature difference. Their best guess for this is 4.2 ºC (as an aside, our published best guess is 5.8 ºC, well outside the uncertainty range considered by Siddall et al). But is a 20-degree change in Greenland temperature simply equivalent to a 4.2-degree global change? And how does local temperature translate into a global temperature for Dansgaard-Oeschger events, which are generally assumed to be caused by ocean circulation changes and lead to a temperature seesaw effect between northern and southern hemisphere? What if we used their amplitude to normalise temperature – given their imprint on global mean temperature is approximately zero?

Overall, we find these problems extremely daunting. For a good constraint for the 21st Century, one would need sufficiently accurate paleoclimatic data that reflect a sea level rise (a drop would not do – ice melts much faster than it grows) on a century time scale in response to a global forcing, preferably from a climate state similar to ours – notably with a similar distribution of ice on the planet. If anyone is aware of suitable data, we’d be most interested to hear about them!

Update (8 Sept): We have now received the computer code of Siddall et al (thanks to Mark for sending it). It confirms our analysis above. The code effectively assumes that the warming over each century applies for the whole century. I.e., the time step for the 20^th Century assumes the whole century was 0.74 ºC warmer than 1900, rather than just an average of 0.25 ºC warmer as discussed above. When this is corrected, the 20^th Century rise reduces from 15 cm to 8 cm in the model (consistent with our linear estimate given above). The 21st Century projections ranging from 32-48 cm in their Table 1 (best estimates) reduce to 24-32 cm.

Martin Vermeer is a geodesist at the Helsinki University of Technology in Finland.

Footnotes

(1) Siddall et al. use two steps. First they determine an equilibrium sea level for each temperature (their Eq 1, and shown in their Fig. 1). Second, they assume an exponential approach of sea level to this equilibrium value in their Eq. 2, which (slightly simplified, for the case of rising sea level) reads:

dS/dt = (S_e(T) – S(t)) / τ.

Here S is the current sea level (a function of time t), S_e the equilibrium sea level (a function of temperature T), and τ the time scale over which this equilibrium is approached (which they find to be 2900 years).
Now imagine the temperature rises. Then S_e(T) increases, causing a rise in sea level dS/dt. If you only look at short time scales like 100 years (a tiny fraction of those 2900 years response time), S(t) can be considered constant, so the equation simplifies to

dS/dt = S_e(T)/ τ + constant.

Now S_e(T) is a non-linear function, but for small temperature changes (like 1 ºC) this can be approximated well by a linear dependence S_e(T) = s * T + constant. Which gives us

dS/dt = s/τ * T + constant, i.e. Eq (1) in the main post above.

R07 on the other hand used:
dS/dt = a * (T – T0), which is also Eq. (1) above.
Note that a = s/τ and b = -a*T0 in our notation.

(2) Here is a very basic matlab/octave script that computes a sea level curve from a given temperature curve according to Eq. 2 above. The full matlab script used in R07, including the data files, is available as supporting online material from Science

% Semi-empirical sea level model - very basic version
T1900=mean(tempg(11:30)); T=tempg-T1900;

a=0.34; % sea level sensitivity parameter [cm/degree/year]
b=0.077; % note this value depends on a and on the temperature
% baseline, here the mean 1890-1909

% rate of rise - here you need to put in an annual temperature time series T
% with same baseline as chosen for fitting b!
dSdt = a*T + b;

% integrate this to get sea level over the period covered by the temperature series
S = cumsum(dSdt); plot(S);

(3) Here is a matlab/octave script to compute the equilibrium sea level curve of Siddall et al. Note the parameters differ in some cases from those given in the paper – we obtained the correct ones from Mark Siddall.

% Siddall et al equilibrium sea level curve, their Fig. 1, NGRIP scenario
A = 15.436083479092469;
b = 0.012630000000000;
c = 0.760400212014386;
d = -73.952809369848552;

Tdash=[-1.5:.05:2];
% Equilibrium sea level curve
Se=A*asinh((Tdash+c)/b) + d;
% Tangent at current temperature
dSe=A/sqrt(1+((0+c)/b)^2)/b;
Se0= A*asinh((0+c)/b) + d;
Te=dSe*Tdash + Se0;
plot(Tdash, Se, 'b', Tdash, Te, 'c', Tdash, 0.0*Se, 'k', [0 0], [-150 40], 'k')
xlabel('Dimensionless temperature')
ylabel('Equilibrium sea level (m)')
fprintf(1, 'Slope: %f m/K, Sensitivity: %f cm/K/year, zero offset: %f m\n\n', dSe/4.2, 100*dSe/4.2/2900, Se0);

(4) We did not yet receive the code at the time of writing, but based on correspondence with the authors conclude that for their values in Fig. 3 and table 1, Siddall et al. integrated sea level with 100-year time steps with a highly inaccurate numerical method, thus greatly overestimating the a-term. In their supporting online information they show a different calculation for the 20th Century with annual time steps (their Fig. 5SI). This is numerically correct, giving an a-term of about 4 cm, but uses a different value of b close to 0.12 cm/year to obtain the correct total 20th Century rise.

References

Church, J. A. & White, N. J. A 20th century acceleration in global sea-level rise. Geophysical Research Letters 33, L01602 (2006).

Grinsted, A., Moore, J. C. & Jevrejeva, S. Reconstructing sea level from paleo and projected temperatures 200 to 2100 ad. Climate Dynamics (2009).

Jevrejeva, S., Grinsted, A., Moore, J. C. & Holgate, S. Nonlinear trends and multiyear cycles in sea level records. Journal of Geophysical Research 111 (2006).

Moberg, A., Sonechkin, D. M., Holmgren, K., Datsenko, N. M. & Karlen, W. Highly variably Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data. Nature 433, 613-617 (2005).

Rahmstorf, S. A semi-empirical approach to projecting future sea-level rise. Science 315, 368-370 (2007).

Rahmstorf, S. Response to comments on “A semi-empirical approach to projecting future sea-level rise”. Science 317 (2007).

Siddall, M., Stocker, T. F. & Clark, P. U. Constraints on future sea-level rise from past sea-level change. Nature Geoscience (advance online publication, 26 July 2009).

Some of you may be aware of George Monbiot’s so-far-unsuccessful attempt to pin down Ian Plimer on his ridiculous compendium of non-science. In response to Monbiot’s request for explanation and sources for some of Plimer’s more bizarre claims, Plimer has responded with a homework assignment that is clearly beyond even his (claimed) prowess. This is quite transparently a device to avoid dealing with Monbiot’s questions and is designed to lead to an argument along the lines of “Monbiot can’t answer these questions and so knows nothing about the science (and by the way, please don’t notice that I can’t cite any sources for my nonsense or even acknowledge that I can’t answer these questions either)”. (Chris Colose and Greenfyre have made similar points). It’s also worth pointing out as Andrew Dodds has done that each question is actually referencing a very well known contrarian and oft-debunked argument, but dressed up in pseudo-scientific complexity.

However, as a service both to Plimer and Monbiot (as well as anyone else interested), we give a quick scorecard on the relevance, actual scientific content (whether the questions can actually be answered) and sources for discussion for each of the, to be charitable, ‘odd’ questions. For relevance, we grade each question on a scale from 0 to 5, 0 being irrelevant to the issue of detection and attribution of 20th Century climate change, 5 being extremely relevant. For scientific content, we rate the reasonableness of the question posed (i.e. does it make any sense at all), from A to F (A being a very well posed question, F making no sense). For sources, we generally point to a paper or discussion that addresses the real issue.

1. From the distribution of the vines, olives, citrus and grain crops in Europe, UK and Greenland, calculate the temperature in the Roman and Medieval Warmings and the required atmospheric CO2 content at sea level to drive such warmings. What are the errors in your calculation? Reconcile your calculations with at least five atmospheric CO2 proxies. Show all calculations and justify all assumptions.
• Relevance: 0 – poor. Basic logical fallacy. The existence of prior warm periods that may have been caused by different effects (such as solar changes, orbital variation, continental configuration etc.) does not imply that the human-caused increase in CO2 is not causing warming now.
• Scientific Content: D – phenology (the distribution and timing of species) can potentially be useful for tracking climate changes, but it is just one of many different types of proxy information available, and has its own regional, temporal, and seasonal limitations. Even more problematic, it is well known that the patterns of surface temperature variability during the “MWP” – more accurately, the Medieval Climate Anomaly (MCA) – and LIA periods were spatially quite heterogeneous, and a record at one or two locations generally tells us very little if anything about global patterns. Even a cursory examination of the relevant recent literature (for instance, Osborn and Briffa, 2006) reveals that the pattern of warmth during the Medieval era was far regional in nature, and does not approach the truly global scale of warmth evident in recent decades.
• Sources: Greater extent of vineyards today in England than in medieval times. Ice core records. Incoherence of the Medieval warm period.
2. Tabulate the CO2 exhalation rates over the last 15,000 years from (i) terrestrial and submarine volcanism (including maars, gas vents, geysers and springs) and calc-silicate mineral formation, and (ii) CH4 oxidation to CO2 derived from CH4 exhalation by terrestrial and submarine volcanism, natural hydrocarbon leakage from sediments and sedimentary rocks, methane hydrates, soils, microbiological decay of plant material, arthropods, ruminants and terrestrial methanogenic bacteria to a depth of 4 km. From these data, what is the C12, C13 and C14 content of atmospheric CO2 each thousand years over the last 15,000 years and what are the resultant atmospheric CO2 residence times? All assumptions need to be documented and justified.
• Relevance: 0 – pure misdirection.
• Scientific Content: F – We know what CO2 and CH4 levels have been over the last 15,000 years and they oscillated within about 10 ppmv (CO2) and 100 ppbv (CH4) of their Holocene values since the start of the current era – until the industrial period (around 1750) since when CO2 has increased by 35%, and methane concentrations have more than doubled. In each case the values being measured today are way higher than anything measured in 800,000 years of ice core records, and likely higher than anything since the Pliocene (~3 million years ago). The idea that bacterial methane production at 4km in the Earth’s crust has anything to with this is laughable.
• Sources: IPCC FAQ is all that is required. Do volcanoes produce more CO2 than human activity? Not even close.
3. From first principles, calculate the effects on atmospheric temperature at sea level by changes in cloudiness of 0.5%, 1% and 2% at 0%, 20%, 40%, 60% and 80% humidity. What changes in cloudiness would have been necessary to drive the Roman Warming, Dark Ages, Medieval Warming and Little Ice Age? Show all calculations and justify all assumptions.
• Relevance: 3 – clouds certainly have an effect on climate and understanding their variability is the subject of much research.
• Scientific Content: F – The question makes no sense. Clouds at 0% humidity? Is humidity supposed to be globally uniform? And where should these cloud changes occur? The change for low-level clouds will be of the opposite sign to changes in high level clouds, and changes in the Arctic will give different answers than changes in the tropics. It should go without saying that Plimer is mistakenly assuming that he has accurate information for global temperatures over 2000 years.
• Sources: Cloud Feedbacks in the Climate System.
4. Calculate the changes in atmospheric C12 and C13 content of CO2 and CH4 from crack-seal deformation. What is the influence of this source of gases on atmospheric CO2 residence time since 1850? Validate assumptions and show all calculations.
• Relevance: 0 – completely irrelevant.
• Scientific Content: F – for those that don’t know ‘crack-seal deformation’ is a geologic process that causes the veins of crystals/minerals etc. in many rock types. (see here). Its relevance to atmospheric concentrations and isotopic composition is absolutely zero. It has no influence on atmospheric residence time – whether since 1850 or at any time in the past.
• Sources Discussions of the actual carbon cycle and the real influences upon it.
5. From CO2 proxies, carbonate rock and mineral volumes and stable isotopes, calculate the CO2 forcing of temperature in the Huronian, Neoproterozoic, Ordovician, Permo-Carboniferous and Jurassic ice ages. Why is the “faint Sun paradox” inapplicable to the Phanerozoic ice ages in the light of your calculations? All assumptions must be validated and calculations and sources of information must be shown.
• Relevance: 0 – (again). The acknowledged climate changes in the past caused by natural events in no way implies that human effects are negligible today. Does the existence of forest fires caused by lightning imply that arson can never happen?
• Scientific Content: C – There is a lot of interesting science related to deep time, but any discussion of such changes must be prefaced with the acknowledgment that our knowledge of greenhouse gases, temperatures or any other potential forcing or response is very limited compared to what we know about climate today or even in the last ice age. Given that we don’t know precisely what CO2 levels were (let alone CH4, N2O, ozone, aerosols, ice sheet configurations, vegetation distribution etc.), the attributions of climate change at this distance is speculative at best.
• Sources: The faint young sun paradox.
6. From ocean current velocity, palaeotemperature and atmosphere measurements of ice cores and stable and radiogenic isotopes of seawater, atmospheric CO2 and fluid inclusions in ice and using atmospheric CO2 residence times of 4, 12, 50 and 400 years, numerically demonstrate that the modern increase in atmospheric CO2 could not derive from the Medieval Warming.
• Relevance:1 – There are amplifying feedbacks between climate and CO2 – which are most evident in the long ice cores from Antarctica, but this argument is trivial to dismiss without any recourse to ocean current velocities etc.
• Scientific Content:D – You can calculate the change in CO2 per deg C global warming over long (multi-centennial) timescales from the ice age data – it’s roughly 100ppmv/5ºC = 20 ppmv/ºC. The increase in atmospheric CO2 in the last 200 years is now about 110ppmv, implying that any natural driver would have need to have been more than 5ºC natural warming in recent centuries. This would have been noticed by someone.
• Sources: None required.
7. Calculate the changes in the atmospheric transmissivity of radiant energy over the last 2,000 years derived from a variable ingress of stellar, meteoritic and cometary dust, terrestrial dust, terrestrial volcanic aerosols and industrial aerosols. How can your calculations show whether atmospheric temperature changes are related to aerosols? All assumptions must be justified and calculations and sources of information must be shown.
• Relevance: 4 – aerosols are an important climate forcing, and their history through time (even in the 20th Century) are quite uncertain.
• Scientific Content: C – Calculating the impacts of aerosols is quite hard, first because we don’t have great records for their distribution through time and space, and secondly there are uncertainties in how the mix with each other and how they interact with clouds. Forcing estimates for the human-caused changes in aerosols over the 20th Century therefore have quite large uncertainties associated with them and are a principle reason why attempts to constrain climate sensitivity from the recent record along have not been very successful. Volcanic effects are however quite well characterised, and actually provide one of the many lines of evidence for why GCM simulations are reasonable since they get the right magnitude and character of the volcanic effects on climate. However, there is no evidence whatsoever for large changes in interstellar dust changes in recent millennia and trying to pin recent warming on that is really grasping at straws.
• Sources: Climate sensitivity and aerosol forcings.
8. Calculate 10 Ma time flitches using W/R ratios of 10, 100 and 500 for the heat addition to the oceans, oceanic pH changes and CO2 additions to bottom waters by alteration of sea floor rocks to greenschist and amphibolite facies assemblages, the cooling of new submarine volcanic rocks (including MORBs) and the heat, CO2 and CH4 additions from springs and gas vents since the opening of the Atlantic Ocean. From your calculations, relate the heat balance to global climate over these 10 Ma flitches. What are the errors in your calculations? Show all calculations and discuss the validity of any assumptions made.
• Relevance: 0 – again more misdirection. The throwing around of irrelevant geologic terms and undefined jargon is simply done in order to appear more knowledgeable than your interlocutor. The argument appears to that climate is changing due to tectonically slow changes the direct heat input from ocean sea floor spreading. This is absurd.
• Scientific Content: F.
• Sources: Definition of ‘flitch’.
9. Calculate the rate of isostatic sinking of the Pacific Ocean floor resulting from post LGM loading by water, the rate of compensatory land level rise, the rate of gravitationally-induced sea level rise and sea level changes from morphological changes to the ocean floor. Numerically reconcile your answer with the post LGM sea level rise, oceanic thermal expansion and coral atoll drilling in the South Pacific Ocean. What are the relative proportions of sea level change derived from your calculations?
• Relevance: 2 – pretty much irrelevant.
• Scientific Content: C – isostatic issues in sea level are important on long time scales, and there is still an effect today from the deglaciation 15000 years ago. It contributes a decrease of about 0.3 mm/yr to the global sea level rise, compared to 3 mm/yr total (i.e. about 10%). If the idea was to imply that current sea level rise is simply the response to the deglaciation, then it was completely misleading.
• Sources: Reconciliation of the sea level rise, thermal expansion and ice melt.
10. From atmospheric CO2 measurements, stable isotopes, radiogenic Kr and hemispheric transport of volcanic aerosols, calculate the rate of mixing of CO2 between the hemispheres of planet Earth and reconcile this mixing with CO2 solubility, CO2 chemical kinetic data, CO2 stable and cosmogenic isotopes, the natural sequestration rates of CO2 from the atmosphere into plankton, oceans, carbonate sediments and cements, hydrothermal alteration, soils, bacteria and plants for each continent and ocean. All assumptions must be justified and calculations and sources of information must be shown. Calculations may need to be corrected for differences in 12CO2, 13CO2 and 14CO2 kinetic adsorption and/or molecular variations in oceanic dissolution rates.
• Relevance: 5 – the carbon cycle is actually a key issue.
• Scientific Content: A – understanding the carbon cycle given multiple constraints on the carbon fluxes (including some of the issues raised in the question) is important in showing that the ~35% rise in CO2 since ~1750 is in fact anthropogenic. This has been shown numerous times to be consistent with the known human emissions, increases in oceans and terrestrial carbon, the decrease in 14C content of the atmosphere, the decrease in 13C content in the atmosphere, the decrease in O2 in the atmosphere.
• Sources: Read the FAQ.
11. Calculate from first principles the variability of climate, the warming and cooling rates and global sea level changes from the Bölling to the present and compare and contrast the variability, maximum warming and maximum sea level change rates over this time period to that from 1850 to the present. Using your calculations, how can natural and human-induced changes be differentiated? All assumptions must be justified and calculations and sources of information must be shown.
• Relevance: 4 – detection and attribution of climate change is an important issue.
• Scientific Content: B – First principles calculations of climate variability are most closely approximated by GCMs and multiple modelling groups have done various Holocene simulations. Attribution of any climate changes requires model simulations with and without each particular forcing and for the Holocene, this involves changes in the orbit, greenhouse gases, solar, meltwater regimes, ice sheet change, aerosols etc. and a comparison of the signature of the responses with patterns observed in the real world. However, comparable data to 20th Century sea levels or temperature changes are not available going back to the beginning of the Holocene.
• Sources: Attribution of mid-Holocene hydrologic changes to orbital forcing. Attribution of patterns of cooling at 8.2 kya to drainage of Lake Agassiz. Attribution of pre-industrial variability over the last millennia to solar and volcanic forcing (IPCC Ch8, p680+).
12. Calculate the volume of particulate and sulphurous aerosols and CO2 and CH4 coeval with the last three major mass extinctions of life. Use the figures derived from these calculations to numerically demonstrate the effects of terrestrial, deep submarine, hot spot and mid ocean ridge volcanism on planktonic and terrestrial life on Earth. What are the errors in your calculations?
• Relevance: 1 – irrelevant. Has nothing to do with current causes of species extinction nor sources of CO2.
• Scientific Content: D – insufficient data exist to infer atmospheric composition, nor the sources of any hypothesised fluxes. We think that it is likely that mass extinctions are probably bad for “planktonic and terrestrial life on Earth” with very little error.
• Sources: This is a good intro to the P/T extinction event which is fascinating even if mostly irrelevant to today.
13. From the annual average burning of hydrocarbons, lignite, bituminous coal and natural and coal gas, smelting, production of cement, cropping, irrigation and deforestation, use the 25µm, 7µm and 2.5µm wavelengths to calculate the effect that gaseous, liquid and solid H2O have on atmospheric temperature at sea level and at 5 km altitude at latitudes of 20º, 40º, 60º and 80ºS. How does the effect of H2O compare with the effect of CO2 derived from the same sources? All assumptions must be justified and calculations and sources of information must be shown.
• Relevance: 3 – radiative transfer is a key issue.
• Scientific Content: F – the question as it stands makes no sense. How can using fossil fuel emissions of CO2 allow you to calculate the impact of total H2O? And why only three wavelengths? You would need the whole atmosphere distribution of water (in all three phases and which doesn’t exist outside a model) in order to calculate the radiative fluxes, and a full GCM to calculate all the other fluxes that influence the temperature. If Plimer is actually alluding to the impact of the direct injection of water vapour into the atmosphere from the combustion of hydrocarbons, then this makes even less sense since the perturbation time for water vapour is measured in days (rather than decades to centuries for CO2) and the relative importance of anthropogenic fluxes is much much less.
• Sources: Importance of water vapour and clouds compared to CO2 for the total greenhouse effect (roughly, 50%, 25% and 20% once overlaps are apportioned). Complete irrelevance of anthropogenic addition of H2O. Calculation of radiative forcing for anthropogenic CO2.

In summary, the relevance of these questions is extremely low, and even when the basic question deals with an issue that is relevant, the question itself is usually nonsensical and presupposes many assumptions that are certainly not a given (at least in the real world). In fact, for the couple of cases where the scientific content is high, the answer is in contradiction to Plimer’s unstated assumptions. The most obvious use of these questions to support a ‘we don’t know everything, so we must know nothing’ type of argument, which is a classic contrarian trope, and one that is easily dealt with.

These questions have as much to do with a debate on human caused climate change as tribbles have to do with astrobiology. Both are troubling, but for very different reasons.

The three new projects involve UEA's School of Environmental Sciences; School of Medicine, Health and Policy Practice; and School of Development Studies. The projects all begin in 2010

Tyndall Sussex's research in China mentioned in the Financial Times

One of the strengths of science is its capacity to resolve controversies by generally accepted procedures and standards. Many scientific questions (especially more technical ones) are not matters of opinion but have a correct answer.

Scientists document their procedures and findings in the peer-reviewed literature in such a way that they can be double-checked and challenged by others. The proper way to challenge results is, of course, also through the peer-reviewed literature, so that the challenge follows the same standards of documentation as did the original finding.

Such a challenge can either be in form of a new, independent paper, or in the form of a comment to a published paper. The latter is the appropriate avenue if the challenge is not based on new data (and is thus a piece of research in its own right), but is a criticism of the methods used in a paper.

Such technical comments are routinely published in journals, and RealClimate authors have of course also been involved in writing or receiving such comments. One prominent example was a comment in Science showing that a challenge by Von Storch et al. (2004) to the “hockey stick” climate reconstruction of Mann et al. (1998) “was based on incorrect implementation of the reconstruction procedure”. We discussed the implications on Realclimate after the comment appeared. Another recent example was a comment by Schmith et al. on a Science paper on sea level rise by Stefan, noting that he failed to account for the effect of smoothing on the autocorrelation in the data he used. In his response, Stefan acknowledged this mistake but showed that it does not affect his main conclusions.

That the original authors are allowed to respond to a comment in the same journal issue, and the comment’s authors get to consider this response before deciding to go ahead with their comment, are key hallmarks of a fair procedure, in addition to a neutral journal editor and independent reviewers overseeing the process. Even if the authors of comment and reply continue to disagree to some extent, this comment process in most cases resolves the issue to the satisfaction of the scientific community. It lays out the facts in a fair and transparent way and gives outsiders a good basis for judging whom is right. In this way it advances science.

There is however a different way of criticizing scientific papers that is prevalent in blogs like ClimateAudit. This involves challenging, ‘by all means necessary’, any paper whose conclusions are not liked. This can be based on simple typos, basic misunderstandings of the issues and ‘guilt by association’ though there is sometimes the occasional interesting point. Since these claims are rarely assessed to see if there is any actual impact on the main result, the outcome is a series of misleading critiques, regardless of whether any of these criticisms are in fact even valid or salient, that give the impression that every one of these papers is worthless and that all their authors incompetent at best and dishonest at worst. It is the equivalent of claiming to have found spelling errors in a newspaper article. Fun for a while, but basically irrelevant for understanding any issue or judging the worth of the journalist.

While commentary — even quite negative commentary — of papers on blogs is entirely reasonable (after all, we do it here occasionally), claims that a particular paper has been ‘discredited’ or ‘falsified’ that have not withstood (at minimum) the process of peer-review should be viewed with extreme skepticism. So should accusations of dishonesty or misconduct that have not already been conclusively and unequivocally substantiated.

This brings us to the recent claim by Hu McCulloch that a post on ClimateAudit.org, detailing an error in Steig et al’s paper in Nature on Antarctic temperature change, was not given due credit by Steig et al. when they published a Corrigendum earlier this month. In this case, McCulloch’s comment on the paper were perfectly valid, but he chose to avoid the context of normal scientific exchange — instead posting his comments on ClimateAudit.org — and then playing a game of ‘gotcha’ by claiming plagiarism when he wasn’t cited.

McCulloch accuses Steig et al. of appropriating his ‘finding’ that Steig et al. did not account for autocorrelation when calculating the significance of trends. While the published version of the paper didn’t include such a correction, it is obvious that the authors were aware of the need to do so, since in the text of the paper it is stated that this correction was made. The corrected calculations were done using well-known methods, the details of which are available in myriad statistics textbooks and journal articles. There can therefore be no claim on Dr. McCulloch’s part of any originality either for the idea of making such a correction, nor for the methods for doing so, all of which were discussed in the original paper. Had Dr. McCulloch been the first person to make Steig et al. aware of the error in the paper, or had he written directly to Nature at any time prior to the submission of the Corrigendum, it would have been appropriate to acknowledge him and the authors would have been happy to do so. Lest there be any confusion about this, we note that, as discussed in the Corrigendum, the error has no impact on the main conclusions in the paper.

There is nothing wrong with constructive criticism, and pointing out errors — even fairly minor ones — is important and useful. The difference, though, between people who want to find out something about the real world and people who just want to score political points, is what is made of those errors. That is the test of constructive scientific dialog. Specious accusations of fraud, plagiarism and the like don’t pass such a test; instead they simply poison the atmosphere to everyone’s loss.

Cambridge Atmospheric Carbon Action Group meets generally on the second Thursday of every month from 8pm at CB1 Cafe, Mill Road.  It is the counterpart of the Zero Carbon (University) Society in the City of Cambridge.

The Climate Change Action Review is published regularly and provides a summary of the talks and actions accomplished by the group. Recent editions are shown below:

<a href=”http://www.zerocarbonnow.org/wordpress//uploads/actionreview2.doc” title=”Climate Change Action Review 2 (Oct-Nov 07)”>Climate Change Action Review 2 (Oct-Nov 07)</a>

<a href=”http://www.zerocarbonnow.org/wordpress//uploads/actionreview2.doc” title=”Climate Change Action Review 2 (Oct-Nov 07)”></a><a href=”http://www.zerocarbonnow.org/wordpress//uploads/actionreview3.doc” title=”Climate Change Action Review 3 (Dec-Jan 08)”></a><a href=”http://www.zerocarbonnow.org/wordpress//uploads/actionreview3.doc” title=”Climate Change Action Review 3 (Dec-Jan 08)”>Climate Change Action Review 3 (Dec-Jan 08)</a>
<p align=”justify”><a href=”http://www.zerocarbonnow.org/?p=720″><u>MORE FEEDBACK,  PLEASE</u></a></p>
One feature of future Issue of the CamACAG Climate Change Action Review will be re-writes  and updates on several of the position statements. All feedback and  suggestions for improvements or additions to the list of CamACAG Position  Statements are greatly appreciated.  Please email <a href=”mailto:cambridge.slater%5Ba%5Dyahoo.co.uk” target=”_blank”>
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Guest commentary by Alan Robock – Rutgers University

Bjorn Lomborg’s Climate Consensus Center just released an un-refereed report on geoengineering, An Analysis of Climate Engineering as a Response to Global Warming, by J Eric Bickel and Lee Lane. The “consensus” in the title of Lomborg’s center is based on a meeting of 50 economists last year. The problem with allowing economists to decide the proper response of society to global warming is that they base their analysis only on their own quantifications of the costs and benefits of different strategies. In this report, discussed below, they simply omit the costs of many of the potential negative aspects of producing a stratospheric cloud to block out sunlight or cloud brightening, and come to the conclusion that these strategies have a 25-5000 to 1 benefit/cost ratio. That the second author works for the American Enterprise Institute, a lobbying group that has been a leading global warming denier, is not surprising, except that now they are in favor of a solution to a problem they have claimed for years does not exist.

Geoengineering has come a long way since first discussed here three years ago. [Here I use the term “geoengineering” to refer to “solar radiation management” (SRM) and not to carbon capture and sequestration (called “air capture” in the report), a related topic with quite different issues.] In a New Scientist interview, John Holdren, President Obama’s science adviser, says geoengineering has to be examined as a possible response to global warming, but that we can make no such determination now. A two-day conference on geoengineering organized by the U.S. National Academy of Sciences was held in June, 2009, with an opening talk by the President, Ralph Cicerone. The American Meteorological Society (AMS) has just issued a policy statement on geoengineering, which urges cautious consideration, more research, and appropriate restrictions. But all this attention comes with the message that we know little about the efficacy, costs, and problems associated with geoengineering suggestions, and that much more study is needed.

Bickel and Lane, however, do not hesitate to write a report that is rather biased in favor of geoengineering using SRM, by emphasizing the low cost and dismissing the many possible negative aspects. They use calculations with the Dynamic Integrated model of Climate and the Economy (DICE) economic model to make the paper seem scientific, but there are many inherent assumptions, and they up-front refuse to present their results in terms of ranges or error bars. Specific numbers in their conclusions make the results seem much more certain than they are. While they give lip service to possible negative consequences of geoengineering, they refuse to quantify them. Indeed, the purpose of new research is to do just that, but the tone of this report is to claim that cooling the planet will have overall benefits, which CAN be quantified. The conclusions and summary of the report imply much more certainty as to the net benefits of SRM than is really the case.

My main areas of agreement with this report are that global warming is an important, serious problem, that SRM with stratospheric aerosols or cloud brightening would not be expensive, and that we indeed need more research into geoengineering. The authors provide a balanced introduction to the issues of global warming and the possible types of geoengineering.

But Bickel and Lane ignore the effects of ocean acidification from continued CO2 emissions, dismissing this as a lost cause. Even without global warming, reducing CO2 emissions is needed to do the best we can to save the ocean. The costs of this continuing damage to the planet, which geoengineering will do nothing to address, are ignored in the analysis in this report. And without mitigation, SRM would need to be continued for hundreds of years. If it were stopped, by the loss of interest or means by society, the resulting rapid warming would be much more dangerous than the gradual warming we are now experiencing.

Bickel and Lane do not even mention several potential negative effects of SRM, including getting rid of blue skies, huge reductions in solar power from systems using direct solar radiation, or ruining terrestrial optical astronomy. They imply that SRM technologies will work perfectly, and ignore unknown unknowns. Not one cloud has ever been artificially brightened by injection of sea salt aerosols, yet this report claims to be able to quantify the benefits and the costs to society of cloud brightening.

They also imply that stratospheric geoengineering can be tested at a small scale, but this is not true. Small injections of SO2 into the stratosphere would actually produce small radiative forcing, and we would not be able to separate the effects from weather noise. The small volcanic eruptions of the past year (1.5 Tg SO2 from Kasatochi in 2008 and 1 Tg SO2 from Sarychev in 2009, as compared to 7 Tg SO2 from El Chichón in 1982 and 20 Tg SO2 from Pinatubo in 1991) have produced stratospheric clouds that can be well-observed, but we cannot detect any climate impacts. Only a large-scale stratospheric injection could produce measurable impacts. This means that the path they propose would lead directly to geoengineering, even just to test it, and then it would be much harder to stop, what with commercial interests in continuing (e.g., Star Wars, which has not even ever worked).

Bickel and Lane also ignore several seminal papers on geoengineering that present much more advanced scientific results than the older papers they cite. In particular, they ignore Tilmes et al. (2008), Robock et al. (2008), Rasch et al. (2008), and Jones et al. (2009).

With respect to ozone, they dismiss concerns about ozone depletion and enhanced UV by citing Wigley (2006) and Crutzen (2006), but ignore the results of Tilmes et al. (2008), who showed that the effects would prolong the ozone hole for decades and that deployment of stratospheric aerosols in a couple decades would not be safe as claimed here. Bickel and Lane assert, completely incorrectly, “On its face, though, it does not appear that the ozone issue would be likely to invalidate the concept of stratospheric aerosols.”

With respect to an Arctic-only scheme, they suggest in several places that it would be possible to control Arctic climate based on the results of Caldeira and Wood (2008) who artificially reduce sunlight in a polar cap in their model (the “yarmulke method”), whereas Robock et al. (2008) showed with a more realistic model that explicitly treats the distribution and transport of stratospheric aerosols, that the aerosols could not be confined to just the Arctic, and such a deployment strategy would affect the summer Asian monsoon, reducing precipitation over China and India. And Robock et al. (2008) give examples from past volcanic eruptions that illustrate this effect, such as the pattern of precipitation reduction after the 1991 Pinatubo eruption (Trenberth and Dai, 2007):

With respect to cloud brightening, Bickel and Lane ignore the Jones et al. (2009) results that cloud brightening would mainly cool the oceans and not affect land temperature much, so that it is an imperfect method at best to counter global warming. Furthermore Jones et al. (2009) found that cloud brightening over the South Atlantic would produce severe drought over the Amazon, destroying the tropical forest.

They also ignore a huge class of ethical and world governance issues. Whose hand would be on the global thermostat? Who would trust military aircraft or a multi-national geoengineering company to have the interests of the people of the planet foremost?

They do not seem to realize that volcanic eruptions affect climate change because of sulfate aerosols produced from sulfur dioxide gas injections into the stratosphere, the same that is proposed for SRM, and not by larger ash particles that fall out quickly after and eruption and do not cause climate change.

They dismiss air capture (“air capture technologies do not appear as promising as solar radiation management from a technical or a cost perspective”) but ignore the important point that it would have few of the potential side effects of SRM. Air capture would just remove the cause of global warming in the first place, and the only side effects would be in the locations where the CO2 would be sequestered.

For some reason, they insist on using the wrong units for energy flux (W) instead of the correct units of W/m^2, and then mix them in the paper. I cannot understand why they choose to make it so confusing.

The potential negative consequences of stratospheric SRM were clearly laid out by Robock (2008) and updated by Robock et al. (2009), which still lists 17 reasons why geoengineering may be a bad idea. One of those important possible consequences, the threat to the water supply for agriculture and other human uses, has been emphasized in a recent Science article by Gabi Hegerl and Susan Solomon.

Robock et al. (2009) also lists some benefits from SRM, including increased plant productivity and an enhanced CO2 sink from vegetation that grows more when subject to diffuse radiation, as has been observed after every recent large volcanic eruption. But the quantification of these and other geoengineering benefits, as well as the negative aspects, awaits more research.

It may be that the benefits of geoengineering will outweigh the negative aspects, and that most of the problems can be dealt with, but the paper from Lomborg’s center ignores the real consensus among all responsible geoengineering researchers. The real consensus, as expressed at the National Academy conference and in the AMS statement, is that mitigation needs to be our first and overwhelming response to global warming, and that whether geoengineering can even be considered as an emergency measure in the future should climate change become too dangerous is not now known. Policymakers will only be able to make such decisions after they see results from an intensive research program. Lomborg’s report should have stopped at the need for a research program, and not issued its flawed and premature conclusions.

References:

Jones, A., J. Haywood, and O. Boucher 2009: Climate impacts of geoengineering marine stratocumulus clouds, J. Geophys. Res., 114, D10106, doi:10.1029/2008JD011450.

Rasch, Philip J., Simone Tilmes, Richard P. Turco, Alan Robock, Luke Oman, Chih-Chieh (Jack) Chen, Georgiy L. Stenchikov, and Rolando R. Garcia, 2008: An overview of geoengineering of climate using stratospheric sulphate aerosols. Phil. Trans. Royal Soc. A., 366, 4007-4037, doi:10.1098/rsta.2008.0131.

Robock, Alan, 2008: 20 reasons why geoengineering may be a bad idea. Bull. Atomic Scientists, 64, No. 2, 14-18, 59, doi:10.2968/064002006. PDF file Roundtable discussion of paper

Robock, Alan, Luke Oman, and Georgiy Stenchikov, 2008: Regional climate responses to geoengineering with tropical and Arctic SO2 injections. J. Geophys. Res., 113, D16101, doi:10.1029/2008JD010050. PDF file

Robock, Alan, Allison B. Marquardt, Ben Kravitz, and Georgiy Stenchikov, 2009: The benefits, risks, and costs of stratospheric geoengineering. Submitted to Geophys. Res. Lett., doi:10.1029/2009GL039209. PDF file

Tilmes, S., R. Müller, and R. Salawitch, 2008: The sensitivity of polar ozone depletion to proposed geoengineering schemes, Science, 320(5880), 1201-1204, doi:10.1126/science.1153966.

Trenberth, K. E., and A. Dai (2007), Effects of Mount Pinatubo volcanic eruption on the hydrological cycle as an analog of geoengineering, Geophys. Res. Lett., 34, L15702, doi:10.1029/2007GL030524.

The Paleocene-Eocene Thermal Maximum (PETM) was a very weird period around 55 million years ago. However, the press coverage and discussion of a recent paper on the subject was weirder still.

For those of you not familiar with this period in Earth’s history, the PETM is a very singular event in the Cenozoic (last 65 million years). It was the largest and most abrupt perturbation to the carbon cycle over that whole period, defined by an absolutely huge negative isotope spike (> 3 permil in ¹³C). Although there are smaller analogs later in the Eocene, the size of the carbon flux that must have been brought into the ocean/atmosphere carbon cycle in that one event, is on a par with the entire reserve of conventional fossil fuels at present. A really big number – but exactly how big?

The story starts off innocently enough with a new paper by Richard Zeebe and colleagues in Nature Geoscience to tackle exactly this question. They use a carbon cycle model, tuned to conditions in the Paleocene, to constrain the amount of carbon that must have come into the system to cause both the sharp isotopic spike and a very clear change in the “carbonate compensation depth” (CCD) – this is the depth at which carbonates dissolve in sea water (a function of the pH, pressure, total carbon amount etc.). There is strong evidence that the the CCD rose hundreds of meters over the PETM – causing clear dissolution events in shallower ocean sediment cores. What Zeebe et al. come up with is that around 3000 Gt carbon must have been added to the system – a significant increase on the original estimates of about half that much made a decade or so ago, though less than some high end speculations.

Temperature changes at the same time as this huge carbon spike were large too. Note that this is happening on a Paleocene background climate that we don’t fully understand either – the polar amplification in very warm paleo-climates is much larger than we’ve been able to explain using standard models. Estimates range from 5 to 9 deg C warming (with some additional uncertainty due to potential problems with the proxy data) – smaller in the tropics than at higher latitudes.

Putting these two bits of evidence together is where it starts to get tricky.

First of all, how much does atmospheric CO2 rise if you add 3000 GtC to the system in a (geologically) short period of time? Zeebe et al. did this calculation and the answer is about 700 ppmv – quite a lot eh? However, that is a perturbation to the Paleocene carbon cycle – which they assume has a base CO2 level of 1000 ppm, and so you only get a 70% increase – i.e. not even a doubling of CO2. And since the forcing that goes along with an increase in CO2 is logarithmic, it is the percent change in CO2 that matters rather than the absolute increase. The radiative forcing associated with that is about 2.6 W/m2. Unfortunately, we don’t (yet) have very good estimates of background CO2 levels in Paleocene. The proxies we do have suggest significantly higher values than today, but they aren’t precise. Levels could have been less than 1000 ppm, or even significantly more.

If (and this is a key assumption that we’ll get to later) this was the only forcing associated with the PETM event, how much warmer would we expect the planet to get? One might be tempted to use the standard ‘Charney’ climate sensitivity (2-4.5ºC per doubling of CO2) that is discussed so much in the IPCC reports. That would give you a mere 1.5-3ºC warming which appears inadequate. However, this is inappropriate for at least two reasons. First, the Charney sensitivity is a quite carefully defined metric that is used to compare a certain class of atmospheric models. It assumes that there are no other changes in atmospheric composition (aerosols, methane, ozone) and no changes in vegetation, ice sheets or ocean circulation. It is not the warming we expect if we just increase CO2 and let everything else adjust.

In fact, the concept we should be looking at is the Earth System Sensitivity (a usage I am trying to get more widely adopted) as we mentioned last year in our discussion of ‘Target CO2‘. The point is that all of those factors left out of the Charney sensitivity are going to change, and we are interested in the response of the whole Earth System – not just an idealised little piece of it that happens to fit with what was included in GCMs in 1979.

Now for the Paleocene, it is unlikely that changes in ice sheets were very relevant (there weren’t any to speak of). But changes in vegetation, ozone, methane and aerosols (of various sorts) would certainly be expected. Estimates of the ESS taken from the Pliocene, or from the changes over the whole Cenozoic imply that the ESS is likely to be larger than the Charney sensitivity since vegetation, ozone and methane feedbacks are all amplifying. I’m on an upcoming paper that suggests a value about 50% bigger, while Jim Hansen has suggested a value about twice as big as Charney. That would give you an expected range of temperature increases of 2-5ºC (our estimate) or 3-6ºC (Hansen) (note that uncertainty bands are increasing here but the ranges are starting to overlap with the observations). ALl of this assumes that there are no huge non-linearities in climate sensitivity in radically different climates – something we aren’t at all sure about either.

But let’s go back to the first key assumption – that CO2 forcing is the only direct impact of the PETM event. The source of all this carbon has to satisfy two key constraints – it must be from a very depleted biogenic source and it needs to be relatively accessible. The leading candidate for this is methane hydrate – a kind of methane ice that is found in cold conditions and under pressure on continental margins – often capping large deposits of methane gas itself. Our information about such deposits in the Paleocene is sketchy to say the least, but there are plenty of ideas as to why a large outgassing of these deposits might have occurred (tectonic uplift in the proto-Indian ocean, volcanic activity in the North Atlantic, switches in deep ocean temperature due to the closure of key gateways into the Arctic etc.).

Putting aside the issue of the trigger though, we have the fascinating question of what happens to the methane that would be released in such a scenario. The standard assumption (used in the Zeebe et al paper) is that the methane would oxidise (to CO2) relatively quickly and so you don’t need to worry about the details. But work that Drew Shindell and I did a few years ago suggested that this might not quite be true. We found that atmospheric chemistry feedbacks in such a circumstance could increase the impact of methane releases by a factor of 4 or so. While this isn’t enough to sustain a high methane concentration for tens of thousands of years following an initial pulse, it might be enough to enhance the peak radiative forcing if the methane was being released continuously over a few thousand years. The increase in the case of a 3000 GtC pulse would be on the order of a couple of W/m2 – for as long as the methane was being released. That would be a significant boost to the CO2-only forcing given above – and enough (at least for relatively short parts of the PETM) to bring the temperature and forcing estimates into line.

Of course, much of this is speculative given the difficulty in working out what actually happened 55 million years ago. The press response to the Zeebe et al paper was, however, very predictable.

The problems probably started with the title of the paper “Carbon dioxide forcing alone insufficient to explain Palaeocene–Eocene Thermal Maximum warming” which on it’s own might have been unproblematic. However, it was paired with a press release from Rice University that was titled “Global warming: Our best guess is likely wrong”, containing the statement from Jerry Dickens that “There appears to be something fundamentally wrong with the way temperature and carbon are linked in climate models”.

Since the know-nothings agree one hundred per cent with these two last statements, it took no time at all for the press release to get passed along by Marc Morano, posted on Drudge, and declared the final nail in the coffin for ‘alarmist’ global warming science on WUWT (Andrew Freedman at WaPo has a good discussion of this). The fact that what was really being said was that climate sensitivity is probably larger than produced in standard climate models seemed to pass almost all of these people by (though a few of their more astute commenters did pick up on it). Regardless, the message went out that ‘climate models are wrong’ with the implicit sub-text that current global warming is nothing to worry about. Almost the exact opposite point that the authors wanted to make (another press release from U. Hawaii was much better in that respect).

What might have been done differently?

First off, headlines and titles that simply confirm someone’s prior belief (even if that belief is completely at odds with the substance of the paper) are a really bad idea. Many people do not go beyond the headline – they read it, they agree with it, they move on. Also one should avoid truisms. All ‘models’ are indeed wrong – they are models, not perfect representations of the real world. The real question is whether they are useful – what do they underestimate? overestimate? and are they sufficiently complete? Thus a much better title for the press release would have been more specific “”Global warming: Our best guess is likely too small” – and much less misinterpretable!

Secondly, a lot of the confusion is related to the use of the word ‘model’ itself. When people hear ‘climate model’, they generally think of the big ocean-atmosphere models run by GISS, NCAR or Hadley Centre etc. for the 20th Century climate and for future scenarios. The model used in Zeebe et al was not one of these, instead it was a relatively sophisticated carbon cycle model that tracks the different elements of the carbon cycle, but not the changes in climate. The conclusions of the study related to the sensitivity of the climate used the standard range of sensitivities from IPCC TAR (1.5 to 4.5ºC for a doubling of CO2), which have been constrained – not by climate models – but by observed climate changes. Thus nothing in the paper related to the commonly accepted ‘climate models’ at all, yet most of the commentary made the incorrect association.

To summarise, there is still a great deal of mystery about the PETM – the trigger, where the carbon came from and what happened to it – and the latest research hasn’t tied up all the many loose ends. Whether the solution lies in something ‘fundamental’ as Dickens surmises (possibly related to our basic inability to explain the latitudinal gradients in any of the very warm climates) , or whether it’s a combination of a different forcing function combined with more inclusive ideas about climate sensitivity, is yet to be determined. However, we can all agree that it remains a tantalisingly relevant episode of Earth history.

DEPARTMENT OF ENERGY AND CLIMATE CHANGE (DECC) POLICY FELLOWSHIPS
The Research Councils Energy Programme and DECC are offering two
placement opportunities for Policy Fellowships to provide input into policy
development at DECC. One of the placements is for an applicant with a Social Science
background the other for an applicant with an Engineering background
(with understanding of energy supply and demand). The placements are for 6-12
months and are open to applicants with from 1-5 years postdoctoral
experience.

The call is being administered through the ESRC policy placement
scheme. Closing Date 1st September 2009.
http://www.esrc.ac.uk/ESRCInfoCentre/index_academic.aspx

I've been looking for resources on assertiveness. Assertiveness is about communicating positive and negative ideas and feelings "openly, honestly and directly". What I particularly liked about this article was the emphasis of choice that we have between four modes of communication which were outlined:

• direct aggression: bossy, arrogant, bulldozing, intolerant, opinionated, and overbearing

• indirect aggression: sarcastic, deceiving, ambiguous, insinuating, manipulative, and guilt-inducing

• submissive: wailing, moaning, helpless, passive, indecisive, and apologetic

• assertive: direct, honest, accepting, responsible, and spontaneous

Among these four identifiable modes of communication, the assertive is clearly the most effective.

The article also gives a few tips to improve our assertiveness. Quite a lot of it is about body language: having good body posture, even tone. Interestingly, it seems it is necessary to talk about oneself; to start statements with 'I'. I clearly have ownership over statements I make about myself. Factual statements are also secure.

This University of Iowa information sheet lays out three parts of an assertive communication:

empathy/validation: Try to say something that shows your understanding of the other person's feelings. This shows them that you're not trying to pick a fight, and it takes the wind out of their sails. From the above example, "I know that you get anxious when you're all ready to go and I'm not … ."

statement of problem: This piece describes your difficulty/dissatisfaction, tells why you need something to change. For example, "… but when you do that, I get all flustered and take even more time. By the time we get in the car, we're mad at each other and not much in the mood to have a good time."



statement of what you want: This is a specific request for a specific change in the other person's behavior. For example, "From now on, let's be sure we know what time we want to leave, and if you're ready before I am, will you please just go to another room and read the paper or watch TV?

Summarization is a key part of being assertive. We will often need to repeat what we say as well. Assertiveness appears also to be fundamentally about being specific. Rather than asking for general thing; we pick a time and date and place for an important meeting, for example.
Interestingly, compromise appears to be an important part of assertiveness, although not over things that are a matter of one's self worth or self respect.

Further Reading

1. Essortment: Ten tips for being a more assertive person
2. Ezine: Assertive Communication - Twenty helpful tips
3. University of Iowa: Assertive Communication

CommonFuture: While we're working on our Journal -get active: "Don’t nuke the climate" : needs your support ! http://www.dont-nuke-the-climate.org

CommonFuture: beeing ashamed of making so few updates -I'm Sorry and working on this. #JM

OK, so I have to decide on what I am called. "But surely your parents decide that?" I hear you say?
But the thing is; they only give you a suggestion. It's one's own choice what to tell people, and how to sign off. The decision arises because of the collision of two worlds: the 'friend' world of "Steve" and the 'family and work' world of "Stephen"... The two worlds move closer together with an "activist" world having elements of both.

The decision becomes necessary for consistency purposes and consistency is of course a large part of professionalism. The specific decision needed is what to sign off at the end of emails.
There are two options:

• Steve; or
• Stephen

I need to be consistent. A person with ideas about global problems should at least be able to decide on what he is called.

The problem is, that 'Steve' is not really a shortening of 'Stephen'. The correct shortening would be 'Stephe', pronounced 'Steve', as one or two of my friends have noted... Except that Steph is not pronounced 'Steve' at all but 'Stef'. So I can't really consistently be both Stephen and Steve; I can only be one or the other for official purposes.

Now, it's easier to go for the more informal of the two. There are more friends around than family and easy informality is a part of business as well as friendliness. For a while, my housemate was called 'Stephen' and so 'Steve' was easier.

But there are considerations for 'Stephen' too. I generally prefer it; it seems a more beautiful and generally higher class name than 'Steve', and 'Stephen' is actually slightly easier to say that 'Steve'. When combined with my surname, 'Stephen' has a better ring to it than 'Steve'.

Of course people can call me what they like. If people know me as 'Steve' then the definition of my name 'Stephen' is not going to change anything between us. It will just be how I sign emails and introduce myself.

So that is where I am. If people have any comments, please say so in the next few days. I will then post my final decision.

In a new GRL paper, Svensmark et al., claim that liquid water content in low clouds is reduced after Forbush decreases (FD), and for the most influential FD events, the liquid water content in the oceanic atmosphere can diminish by as much as 7%. In particular, they argue that there is a substantial decline in liquid water clouds, apparently tracking a declining flux of galactic cosmic rays (GCR), reaching a minimum days after the drop in GCR levels. The implication would be that GCR can affect climate through modulating the low-level cloudiness. The analysis is based on various remote sensing products.

The hypothesis is this: a rapid reduction in GCR, due to FD, results in reduced ionization of the atmosphere, and hence less cloud drops and liquid water in low clouds. Their analysis of various remote sensing products suggest that the opacitiy (measured in terms of the Angstrom exponent) due to aerosols reaches a minimum ~5 days after FD, and that there is a minimum in the cloud liquid water content (CWC) minimum occurring ~7 days later than the FD. They also observe that the CWC minimum takes place ~4 days after the fine aerosol minimum (the numbers here don’t seem to add up).

The paper is based on a small selection of events and specific choice of events and bandwidths. The paper doesn’t provide any proof that GCR affect the low clouds– at best -, but can at most only give support to this hypothesis. There are still a lot of hurdles that remain before one can call it a proof.

One requirement for successful scientific progress in general, is that new explanations or proposed mechanisms must fit within the big picture, as well as being consistent with other observations. They must also be able to explain other relevant aspects. A thorough understanding of the broader subject is therefore often necessary to put the new pieces in the larger context. It’s typical of non-experts not to place their ideas in the context of the bigger picture.

If we look at the big picture, one immediate question is why it should take days for the alleged minimum in CWC to be visible? The lifetime of clouds is usually thought to be on the order of hours, and it is likely that most of the CWC has precipitated out or re-evaporated within a day after the cloud has formed.

In this context, the FD is supposed to suppress the formation of new cloud condensation nuclei (CCN), and the time lag of the response must reflect the life time of the clouds and the time it takes for new ultra-fine molecule clusters (tiny aerosols) to grow to CCN.

Next question is then, why the process, through which ultra-fine molecule clusters grow by an order of ~1000 to become CCN, takes place over several days while the clouds themselves have a shorter life time?

There is also a recent study in GRL (also a comment on May 1st, 2009 in Science) by Pierce and Adams on modeling CCN, which is directly relevant to Svensmark et al.’s hypothesis, but not cited in their paper.

Pierce and Adams argue that the theory is not able to explain the growth from tiny molecule clusters to CCN. Thus, the work by Svensmark et al. is not very convincing if they do not discuss these issues, on which their hypothesis hinges, even if the paper by Pierce and Adams was too recent for being included in this paper.

But Svensmark et al. also fail to make reference to another relevant paper by Erlykin et al. (published January 2009), which argues that any effect on climate is more likely to be directly from solar activity rather than GCR, because the variations in GCR lag variations in temperature.

Furthermore, there are two recent papers in the Philosophical Transactions A of the Royal Society, ‘Enhancement of cloud formation by droplet charging‘ and ‘Discrimination between cosmic ray and solar irradiance effects on clouds, and evidence for geophysical modulation of cloud thickness‘, that are relevant for this study. Both support the notion that GCR may affect the cloudiness, but in different aspects to the way Svensmark et al. propose. The first of these studies focuses on time scales on the order of minutes and hours, rather than days. It is difficult to explain how the changes in the current densities taking place minutes to hours after solar storms may have a lasting effect of 4-9 days.

There are many micro-physical processes known to be involved in the low clouds, each affecting the cloud droplet spectra, CWC and the cloud life times. Such processes include collision & coalescence, mixing processes, winds, phase changes, heat transfer (e.g., diffusive and radiative), chemical reactions, precipitation, and effects from temperature. The ambient temperature determines the balance between the amount of liquid water and that of water vapour.

On a more technical side, the paper did not communicate well why 340 nm and 440 nm should the magic numbers for the remote sensing data and the Angstrom exponents, calculated from the Aerosol Robotic Network (AERONET). There are also measurements for other wavelengths, and Svensmark et al. do not explain why these particular choices are best for the type of aerosols they want to study.

For a real effect, one would expect to see a response in the whole chain of the CCN-formation, from the smallest to the largest aerosols. So, what about the particles of other sizes (or different Angstrom exponents) than those Svensmark et al. have examined? Are they affected in the same way, or is there a reason to believe that the particles grow in jumps and spurts?

If one looks long enough at a large set of data, it is often possible to discern patterns just by chance. For instance, ancient scholars thought they found meaningful patterns in the constellations of the stars on the sky. Svensmark et al. selected a smaller number of FDs than Kristjansson et al. (published in 2008) who found no clear effect of GCR on cloudiness.

Also, statistics based on only 26 data points or only 5 events as presented in the paper is bound to involve a great deal of uncertainty, especially in a noisy environment such as the atmosphere. It is important to ask: Could the similarities arise from pure coincidence?

Applying filtering to the data can sometimes bias the results. Svensmark et al. applied a Gaussian smooth with a width of 2 days and max 10 days to reduce fluctuations. But did it reduce the ‘right’ fluctuations? If the aerosols need days to form CCNs and hence clouds, wouldn’t there be an inherent time scale of several days? And is this accounted for in the Monte-Carlo simulations they carried out to investigate the confidence limits? By limiting the minimum to take place in the interval 0-20 days after FD, and defining the base reference to 15 to 5 days before FD, a lot is already given. How sensitive are the results to these choices? The paper does not explore this.

For a claimed ‘FD strength of 100 %’ (whatever that means) the change in cloud fraction was found to be on the order 4% +-2% which, they argue, is ’slightly larger than the changes observed during a solar cycle’ of ~2%. This is not a very precise statement. And when the FD only is given in percentage, it’s difficult to check the consistency of the numbers. E.g. is there any consistency between the changes in the level of GCR between solar min and max and cloud fraction and during FD? And how does cloud fraction relate with CWC?

Svensmark et al. used the south pole neutron monitor to define the FD, with a cut-off rigidity at 0.06GV that also is sensitive to the low-energy particles from space. Higher energies are necessary for GCR to reach the lower latitudes on Earth, and the flux tends to diminish with higher energy. Hence, the south pole monitor is not necessarily a good indicator for higher-energy GCR that potentially may influence stratiform clouds in the low latitudes.

In their first figure, they show a composite of the 5 strongest FD events. But how robust are these results? Does an inclusion of the 13 strongest FD events or only the 3 leading events alter the picture?

Svensmark et al. claim that the results are statistically significant at the 5%-level, but for the quantitative comparison (their 2nd figure) of effect of the FD magnitude in each of the four data sets studied, it is clear that there is a strong scatter and that the data points do not lie neatly on a line. Thus, it looks as if the statistical test was biased, because the fit is not very impressive.

The GRL paper claims to focus on maritime clouds, but it is reasonable to question if this is true as the air moves some distance in 4-9 days (the time between the FD and the minimum in CWC) due to the winds. This may suggest that the initial ionization probably takes place over other regions than where the CWC minima are located 4—9 days afterward. It would be more convincing if the study accounted for the geographical patterns and the advection by the winds.

Does the width of the minimum peak reveal time scales associated with the clouds? The shape of the minimum suggests that some reduction starts shortly after the FD, which then reaches a minimum after several days. For some data, however, the reduction phase is slower, for others the recovery phase is slower. The width of the minimum is 7-12 days. Do these variations exhibit part of the uncertainty of the analysis, or is there some real information there?

The paper does not discuss the lack of trend in the GCR of moderate energy levels or which role GCR plays for climate change. They have done that before (see previous posts here, here, and here), and it’s wise to leave out statements which do not have scientific support. But it seems they look for ways to back up their older claim, and news report and the press release on their paper make the outrageous claim that GCR have been demonstrated to play an important role in recent global warming.

A recent analysis carried out by myself and Gavin, and published in JGR, compares the response to solar forcing between the GISS GCM (ER) and the observations. Our analysis suggests that the GCM provides a realistic response in terms of the global mean temperature – well within the bounds of uncertainty, as uncertainties are large when applying linear methods to analyse chaotic systems. The model does not include the GCR mechanism, and the general agreement between model and observations therefore is consistent with the effect of GCR on clouds being minor in terms of global warming.

As an aside to this issue, there has been some new developements regarding GCR, galaxy dynamics and our climate (see the commentary environmentalresearchweb.org) – discussed previously here.