RealClimate
North Pole notes (continued)
This is a continuation of the previous (and now unwieldy) post on the current Arctic situation. We'll have a proper round up in a few weeks.
Climate change methadone?
Geoengineering is increasingly being discussed (not so sotto voce any more) in many forums. The current wave of interest has been piqued by Paul Crutzen's 2005 editorial and a number of workshops (commentary) and high profile advocacy. But most of the discussion has occurred in almost total ignorance of the consequences of embarking on such a course.
A wider range of people have now started to publish relevant studies - showing clearly the value of continued research on the topic - and a key one came out this week in JGR-Atmospheres. Robock et al used a coupled GCM with interactive aerosols to see what would happen if they injected huge amounts of SO2 (the precursor of sulphate aerosols) into the tropical or Arctic stratosphere. This is the most talked about (and most feasible) geoengineering idea, based on the cooling impacts of large tropical volcanic eruptions (like Mt. Pinatubo in 1991). Bottom line? This is no panacea.
Figure 1: Results from Robock et al showing the imapct on temperature of their scenarios.
So what are the problems? Robock's study looks at a subset of the potential ones - in particular, the impacts on precipitation. These arise because evaporation is more sensitive to changes in solar radiation than it is to long-wave radiation - so increasing LW and decreasing SW (as you would have in a geo-engineered future) gives a net reduction in evaporation even if the temperatures stay pretty constant. In the experiments they report on, there is a substantial reduction in rainfall in the northern tropics (especially the Sahel and the monsoonal belts). This is actually quite a robust result: reductions in tropical precipitation were reported in simpler tests of this idea in papers by Matthews and Caldiera and Bala et al.
Figure 2: The impact on precipitation in the geoengineered case compared to the control (no GHGs or geoengineering).
Other problems relate to the speed of any recovery if geo-engineering efforts should falter (let's really talk about rapid climate change!), and impacts on stratospheric ozone, increases in acid rain in polar regions, possible indirect aerosol effects on high cirrus clouds (hopefully other studies in future will better quantify these). But the results so far give a flavour of the kind of issues any geoengineering implementation will involve. Notably, how does anyone balance temperature changes that effect ice sheets versus the failure of the Indian Monsoon? The Amazon drying up versus the North Atlantic overturning circulation? It would make the current international climate negotiators seem rather like medieval theologians.
Recently I heard geo-engineering likened to climate change methadone - an emergency treatment to substitute one addiction (carbon emissions) with another. This seems rather apt, and like the analogous situation with heroin, methadone isn't going to be a cure.
Are geologists different?
The International Geological Congress (IGC) is sometimes referred to as the geologists' equivalent of the Olympic Games and is an extremely large gathering of geologists from all over the world, taking place at 4-year intervals. This time, the IGC took place in Lillestrøm, a small place just outside Oslo, Norway (August 6-14). The congress was opened by the Norwegian King (before he continued to the real games in Beijing), and was attended by some 6,000 scientists from 113 countries. Even the Danish Minister of Energy & Climate participated in a panel discussion on climate change. In other words, this was a serious meeting.
I didn't attend the meeting myself, but the scientific programme for the session on climate, shows that the 'climate contrarians' were quite well represented. The organizers probably wanted to give room to “other views”. Together with web cast of the panel discussion on climate change (by the way, you may need Windows to view this because of the video format…), the proportion of attendees with a skeptical attitude to the notion of anthropogenic global warming appeared to be notably higher than in other conferences, such as the European Geosciences Union or European Meteorological Society, or indeed the scientific literature. So be it.
Svensmark was there, even though he's not a geologist, and said that he didn't understand what he was doing on the panel. He didn't say much during the panel debate, apart from that clouds are not well described by GCMs (which is true and discussed in the latest IPCC report), and that the 90% confidence in the human influence on recent trends is derived only from models (not true). There is an irony in that, whereas detailed microphysics in clouds are not well understood (hence the uncertainties in the GCMs), Svensmark's own hypothesis hinges entirely on the cloud response to cosmic rays (which is even less well understood).
Robert Carter said a great deal more than Svensmark on the panel. He made a point of the last couple of years being cold. But he did not appear to understand Jansen's explanation of the difference between trends and natural variability (see here). What really struck me was not who was saying what, but the intellectual level of discussion: the debate often got stuck at misunderstood trivialities which for a long time have been regarded as solved or explained in the climate research community. When you keep starting at square one, you'll never make much progress.
Other statements did not have a scientific basis (e.g. Morner popped out from the crowd and said that the sea levels are not rising - not true - and then saluted the panel). Thus the debate seemed to be a step backwards towards confusion rather than a progress towards resolution.
What is going on? Is there a higher proportion of geologists that have a completely different view on climate change, or was this a biased representation of the community? The thought of stifling a scientific debate by insisting on outrageous or ignorant claims also has struck me.
Update: Marc Roberts sent along this mildly relevant cartoon:
Hypothesis testing and long range memory
What is the actual hypothesis you are testing when you compare a model to an observation? It is not a simple as 'is the model any good' - though many casual readers might assume so. Instead, it is a test of a whole set of assumptions that went into building the model, the forces driving it, and the assumptions that went in to what is presented as the observations. A mismatch between them can arise from a mis-specification of any of these components and climate science is full of examples where reported mismatches ended up being due to problems in the observations or forcing functions rather than the models (ice age tropical ocean temperatures, the MSU records etc.). Conversely of course, there are clear cases where the models are wrong (the double ITCZ problem) and where the search for which assumptions in the model are responsible is ongoing.
As we have discussed, there is a skill required in comparing models to observations in ways that are most productive, and that requires a certain familiarity with the history of climate and weather models. For instance, it is well known that the individual trajectory of the weather is chaotic (in models this is provable; in the real world, just very likely) and unpredictable after a couple of weeks. So comparing the real weather at a point with a model simulation outside of a weather forecast context is not going to be useful. You can see this by specifying exactly what the hypothesis is you are testing in performing such a comparison in a climate model - i.e. "is a model's individual weather correlated to the weather in the real world (given the assumptions of the model and no input of actual weather data)". There will be a mismatch between model and observation, but nothing of interest will have been learnt because we already know that the weather in the model is chaotic.
Hypotheses are much more useful if you expect that there will be a match; a mismatch is then much more surprising. Your expectations are driven by past experience and are informed by a basic understanding of the physics. For instance, given the physics of sulphate aerosols in the stratosphere (short wave reflectors, long wave absorbers), it would be surprising if putting in the aerosols seen during the Pinatubo eruption did not reduce the planetary temperature while warming the stratosphere in the model. Which it does. Doing such an experiments is much more a test of the quantitative impacts then, rather than the qualitative response.
With that in mind, I now turn to the latest paper that is getting the inactivists excited by Demetris Koutsoyiannis and colleagues. There are very clearly two parts to this paper - the first is a poor summary of the practice of climate modelling - touching all the recent contrarian talking points (global cooling, Douglass et al, Karl Popper etc.) but is not worth dealing with in detail (the reviewers of the paper include Willie Soon, Pat Frank and Larry Gould (of Monckton/APS fame) - so no guessing needed for where they get their misconceptions). This is however just a distraction (though I'd recommend to the authors to leave out this kind of nonsense in future if they want to be taken seriously in the wider field). The second part is their actual analysis, the results of which lead them to conclude that "models perform poorly", and is more interesting in conception, if not in execution.
Koutsoyiannis and his colleagues are hydrologists by background and have an interest in what is called long term persistence (LTP or long term memory) in time series (discussed previously here). This is often quantified by the Hurst parameter (nicely explained by tamino recently). A Hurst value of greater than 0.5 is indicative of 'long range persistence' and complicates issues of calculating trend uncertainties and the like. Many natural time series do show more persistent 'memory' than a simple auto-regression (AR) process - in particularly (and classically) river outflows. This makes physical sense because a watershed is much more complicated than just a damper of higher frequency inputs. Soil moisture can have an impact from year to year, as can various groundwater reservoirs and their interactions.
It's important to realise that there is nothing magic about processes with long term persistence. This is simply a property that complex systems - like the climate - will exhibit in certain circumstances. However, like all statistical models that do not reflect the real underlying physics of a situation, assuming a form of LTP - a constant Hurst parameter for instance, is simply an assumption that may or may not be useful. Much more interesting is whether there is a match between the kinds of statistical properties seen in the real world and what is seen in the models (see below).
So what did Koutsoyiannis et al do? They took a small number of long station records and compared them to co-located grid points in single realisations of a few models and correlate their annual and longer term means. Returning to the question we asked at the top, what hypothesis is being tested here? They are using single realisations of model runs, and so they are not testing the forced component of the response (which can only be determined using ensembles or very long simulations). By correlating at the annual and other short term periods they are effectively comparing the weather in the real world with that in a model. Even without looking at their results, it is obvious that this is not going to match (since weather is uncorrelated in one realisation to another, let alone in the real world). Furthermore, by using only one to four grid boxes for their comparisons, even the longer term (30 year) forced trends are not going to come out of the noise.
Remember that the magnitude of annual, interannual and decadal variability increases substantially as spatial scales go from global, hemispheric, continental, regional to local. The IPCC report for instance is very clear in stating that the detection and attribution of climate changes is only clearly possible at continental scales and above. Note also that K et al compare absolute temperatures rather than anomalies. This isn't a terrible idea, but single grid points have offsets to a co-located station for any number of reasons - mean altitude, un-resolved micro-climate effects, systematic but stable biases in planetary wave patterns etc. - and anomaly comparison are generally preferred since they can correct for these oft-times irrelevant effects. Finally (and surprisingly given the attention being paid to it in various circles), K et al do not consider whether any of their selected stations might have any artifacts within them that might effect their statistical properties.
Therefore, it comes as no surprise at all that K and colleagues find poor matches in their comparisons. The answer to their effective question - are very local single realisations of weather coherent across observations and models? - is no, as anyone would have concluded from reading the IPCC report or the existing literature. This is why no one uses (or should be using) single grid points from single models in any kind of future impact study. Indeed, it is the reason why regional downscaling approaches exist at all. The most effective downscaling approaches use the statistical correlations of local weather to larger scale patterns and use model projections for those patterns to estimate changes in local weather regimes. Alternatively, one can use a regional model embedded within a global model. Either way, no-one uses single grid boxes.
What might K et al have done that would have been more interesting and still relevant to their stated concerns? Well, as we stated above, comparing statistical properties in the models to the real world is very relevant. Do the models exhibit LTP? Is there spatial structure to the derived Hurst coefficients? What is the predictability of Hurst at single grid boxes even within models? Of course, some work has already been done on this.
For instance, Kiraly et al (2006, Tellus) calculated Hurst exponents for the entire database of weather stations and show that there is indeed significant structure (and some uncertainty in the estimates) in different climate regimes. In the US, there is a clear difference between the West Coast, Mountain States, and Eastern half. Areas downstream of the North Atlantic appear to have particular high Hurst values.
Other analyses show similar patterns (in this case, from Fraedrich and Blender (2003) who used the gridded datasets from 1900 onwards), though there is enough differences with the first picture that it's probably worth investigating methodological issues in these calculations. What do you get in models? Well in very long simulations that provide enough data to estimate Hurst exponents quite accurately, the answer is mostly something similar.
The precise patterns do vary as a function of frequency ranges (i.e. the exponents in the interannual to multi-decadal band are different to those over longer periods), and there are differences between models. This is one example from Blender et al (2006, GRL) which shows the basic pattern though. Very high Hurst exponents over the parts of the ocean with known multi-decadal variability (North Atlantic for instance), and smaller values over land.
However, I'm not aware of any analyses of these issues for models in the AR4 database, and so that would certainly be an interesting study. Given the short period of the records are the observational estimates of the Hurst exponents stable enough to be used as a test for the models? Do the models suggest that 100-year estimates of these parameters are robust? (this is testable using different realisations in an ensemble). Are there sufficient differences between the models to allow us to say something about the realism of their multi-decadal variability?
Answering any of these questions would have moved the science forward - it's a shame Koutsoyiannis et al addressed a question whose answer was obvious and well known ahead of time instead.
Comprehensive climate glossary
Recently we received a request for setting up a glossary-only search mechanism, or perhaps one web page with a long list of glossary entries with hot links to full explanations. The glossary that we already have is a good start, but we are all busy and it's hard to find the time for extending this.
But there are also a number of external web pages which provide climate-related glossaries, such as the NOAA (they also have a seperate page for paleo-stuff), the Bureau of Meteorology (Australia, and there is even one by the Australian EPA), the Environmental Protection Agency (EPA, the U.S.), and the Western Regional Climate Center (WRCC, the U.S.). Wikipedia also has a glossary for climatological terms.
For those who seek the explanation for more bureaucratic terms, both the EU and the UNFCCC provide glossaries that may be useful.
Furthermore, there are some nice resources available, such as the Encyclopedia of Earth.
Bridging the divides
We often discuss the issues that arise in doing interdisciplinary work in climate science, and Liz Moyer and I have a commentary on that just out in Nature Reports Climate Change. Normally I don't mention these kinds of pieces on the blog, but in this case the editors commissioned a nice cartoon (from Mark Roberts) illustrating our point. I liked the cartoon a lot, and so it deserves as wide an audience as possible.
A bit of context is probably useful. The three main protagonists are representative of the somewhat different foci of paleo-climatologists, climate modellers and economists. Very broadly speaking, paleo-climate science is built around the analysis of single location time series (often from holes that are drilled). Climate modellers spend a lot of time trying to see what is coming up in all its complexity, while economists tend to eschew complexity and look for insight in highly idealised situations. But in order to increase the credibility of models, they have to do well at simulating past climates and what might happen in the future is certainly informed by what has happened in the past. And in order to better understand the impacts of climate change and various proposed policies, economists will need to embrace the complexity of human-climate interactions while modellers need to better understand what aspects of climate really do make a difference. None of these things will happen if we continue to all look in different directions, and more problematically, fail to support and reward those scientists who want to bridge the divides. Sea monsters notwithstanding.
Journalistic whiplash
Andy Revkin has a good article in the Science Times today on the problem of journalistic whiplash in climate change (also discussed here). This phenomena occurs with the more uncertain parts of a science that are being actively researched and where the full story is only slowly coming together. In such cases, new papers often appear in high profile journals (because they meet the 'of general interest' test), and are often parsed rather simplistically to see what side of the fence they fall - are they pro or anti? This leads to wide press interest, but rather shallow coverage, and leaves casual readers with 'whiplash' from the 'yes it is', 'no it isn't' messages every other week.
This is a familiar pattern in health reporting (is coffee good for you/bad for you etc.), but in more recent times has started happening in climate science too. Examples picked out in the article include the hurricanes/global warming connection and the state of Greenland's ice sheet. In both cases, many new pieces of evidence, new theories and new models are being thrown into the pot, but full syntheses of the problems remain elusive. Scientists are of course interested in knowing how it all fits together (and it usually does), but the public - unaware of what is agreed on and what is uncertain - see only the ping-pong across the media. Unlike more mature parts of the science (such as the radiative effect of greenhouse gases), there is much less context available to relate to these new pieces of science.
This spectacle of duelling and apparently contradictory science fuels the notion that scientists can't agree on anything. Ironically, just as climate change has made it on to the front page because the weight of evidence supporting a human role in recent warming, increased coverage may actually be leading people to think that scientists are more divided on the basic questions.
Is this inevitable? Or can scientists, press officers and journal editors and journalists actually do anything about it? Your thoughts are most welcome!
Once more unto the bray
We are a little late to the party, but it is worth adding a few words now that our favourite amateur contrarian is at it again. As many already know, the Forum on Physics and Society (an un-peer-reviewed newsletter published by the otherwise quite sensible American Physical Society), rather surprisingly published a new paper by Monckton that tries again to show using rigorous arithmetic that IPCC is all wrong and that climate sensitivity is negligible. His latest sally, like his previous attempt, is full of the usual obfuscating sleight of hand, but to save people the time in working it out themselves, here are a few highlights.
As Deltoid quickly noticed the most egregious error is a completely arbitrary reduction (by 66%) of the radiative forcing due to CO2. He amusingly justifies this with reference to tropical troposphere temperatures - neglecting of course that temperatures change in response to forcing and are not the forcing itself. And of course, he ignores the evidence that the temperature changes are in fact rather uncertain, and may well be much more in accord with the models than he thinks.
But back to his main error: Forcing due to CO2 can be calculated very accurately using line-by-line radiative transfer codes (see Myhre et al 2001; Collins et al 2006). It is normally done for a few standard atmospheric profiles and those results weighted to produce a global mean estimate of 3.7 W/m2 - given the variations in atmospheric composition (clouds, water vapour etc.) uncertainties are about 10% (or 0.4 W/m2) (the spatial pattern can be seen here). There is no way that it is appropriate to arbitrarily divide it by three.
There is a good analogy to gas mileage. The gallon of gasoline is equivalent to the forcing, the miles you can go on a gallon is the response (i.e. temperature), and thus the miles per gallon is analogous to the climate sensitivity. Thinking that forcing should be changed because of your perception of the temperature change is equivalent to deciding after the fact that you only put in third of a gallon because you ran out of gas earlier than you expected. The appropriate response would be to think about the miles per gallon - but you'd need to be sure that you measured the miles travelled accurately (a very big issue for the tropical troposphere).
But Monckton is not satisfied with just a factor of three reduction in sensitivity. So he makes another dodgy claim. Note that Monckton starts off using the IPCC definition of climate sensitivity as the forcing associated with a concentration of 2xCO2 - this is the classical "Charney Sensitivity" and does not include feedbacks associated with carbon cycle, vegetation or ice-sheet change. Think of it this way - if humans raise CO2 levels to 560 ppm from 280 ppm through our emissions, and then as the climate warms the carbon cycle starts adding even more CO2 to the atmosphere, then the final CO2 will be higher and the temperature will end up higher than standard sensitivity would predict, but you are no longer dealing with the sensitivity to 2xCO2. Thus the classical climate sensitivity does not include any carbon cycle feedback term. But Monckton puts one in anyway.
You might ask why he would do this. Why add another positive feedback to the mix when he is aiming to minimise the climate sensitivity? The answer lies in the backwards calculations he makes to derive the feedbacks. At this point, I was going to do a full analysis of that particular calculation - but I was scooped. So instead of repeating the work, I'll refer you there. The short answer is that by increasing the feedbacks incorrectly, he makes the 'no-feedback' temperature smaller (since he is deriving it from the reported climate sensitivities divided by the feedbacks). This reverses the causality since the 'no-feedback' value is actually independent of the feedbacks, and is much better constrained.
There are many more errors in his piece - for instance he accuses the IPCC of not defining radiative forcing in the Summary for Policy Makers and not fixing this despite requests. Umm… except that the definition is on the bottom of page 2. He bizarrely compares the net anthropogenic forcing to date with the value due to CO2 alone and then extrapolates that difference to come up with a meaningless 'total anthropogenic forcings Del F_2xCO2′. His derivations and discussions of the no-feedback sensitivity and feedbacks is extremely opaque (a much better description is given on the first couple of pages of Hansen et al, 1984)). His discussion of the forcings in that paper are wrong (it's 4.0 W/m2 for 2xCO2 (p135), not 4.8 W/m2), and the no-feedback temperature change is 1.2 (Hansen et al, 1988, p9360), giving k=0.30 C/(W/m2) (not his incorrect 0.260 C/(W/m2) value). Etc… Needless to say, the multiple errors completely undermine the conclusions regarding climate sensitivity.
Generally speaking, these are the kinds of issues that get spotted by peer-reviewers: are the citations correctly interpreted? is the mathematics correct? is the reasoning sound? do the conclusions follow? etc. In this case, there really wouldn't have been much left, and so it is fair to conclude that Monckton's piece only saw the light of day because it wasn't peer-reviewed, not because it was. Claims that the suggested edits from the editor of the newsletter constitute 'peer-review' are belied by the editor's obvious unfamiliarity with the key concepts of forcing and feedback - and the multitude of basic errors still remaining. The even more egregious claims that this paper provides "Mathematical proof that there is no 'climate crisis' " or is "a major, peer-reviewed paper in Physics and Society, a learned journal of the 10,000-strong American Physical Society" are just bunk (though amusing in their chutzpah).
The rational for the FPS publication of this note was to 'open up the debate' on climate change. The obvious ineptitude of this contribution underlines quite effectively how little debate there is on the fundamentals if this is the best counter-argument that can be offered.
Aerosols, Chemistry and Climate
Everyone can probably agree that the climate system is complex. Not only do the vagaries of weather patterns and ocean currents make it hard to see climate changes, but the variability in what are often termed the Earth System components complicates the picture enormously. These components - specifically aerosols (particulates in the air - dust, soot, sulphates, nitrates, pollen etc.) and atmospheric chemistry (ozone, methane) - are both affected by climate and affect climate, since aerosols and ozone can interact, absorb, reflect or scatter solar and thermal radiation. This makes for a rich research environment, but can befuddle the unwary.
I occasionally marvel at the amount of nonsense that is written about climate change in the more excitable parts of the web, and most of the time, I don't bother to comment. But in relation to the issue of aerosols, chemistry and climate, I read yesterday (h/t Atmoz) probably the most boneheaded article that I have seen in ages (and that's saying a lot).
The hook for this piece of foolishness were two interesting articles published this week by Ruckstuhl and colleagues and a draft EPA report on the impacts of climate on air quality. First, Ruckstuhl et al found that as aerosols have decreased in Europe over the last few decades (as a result of environmental standards legislation), the amount of solar radiation at the ground has increased while the amount reflected to space has decreased. They hypothesize that this may have helped Europe warm faster in the last few decades than it would have otherwise done. Or equivalently, since the aerosols are anthropogenic, that European temperatures had been subdued due to the cooling effects of the aerosols - and since they are now decreasing, the full effects of the greenhouse gases are starting to be felt. This is just an update to the 'global brightening' story we have touched on before. The EPA report is concerned with the impacts that climate change can have on atmospheric chemistry, and in particular the summertime peaks in urban ground-level ozone which are a well-known and serious health hazard. These are affected by local temperatures, cloudiness, temperature sensitive biogenic emissions and patterns of weather variability. Again, it is a story we have discussed before.
But the NewsBusters article succeeded in getting almost every aspect of these stories wrong. How do I correct thee? Let me count the ways.
- Aerosols are not smog:
First they confuse aerosols with photochemical smog. Both are pollutants, but the first is dominated by sulphate emissions from coal burning power plants, the second from ozone precursors such as NOx, volatile organic compounds, and carbon monoxide mainly emitted from vehicles. (Note that ozone is not directly emitted, but is created by chemical reactions from the precursors with the addition of a bit of photolysis - i.e. sunlight-driven chemistry). The effects on climate are very different: ozone is a greenhouse gas, so increases cause a warming, while sulphate aerosols are reflective, and so increases cause a cooling. The air quality issues in the EPA are almost all focused on ozone.
- Europe is not the Globe:
The next error is to equate changes in temperatures in Europe to the globe. While it would be true that if global aerosol levels declined it would lead to increased global warming, aerosol trends in Asia are increasing strongly, even while those in the US and Europe are dropping. The net effect is possibly a slight drop, but the impact on global temperature is as yet unclear. This regionality matters in both the sulphates case and for ozone. The relevant chemistry is sensitive to water vapour and temperature in varying ways as a function of the pollution level. In remote ocean areas, surface ozone will likely decrease as the globe warms for instance (due to increasing water vapour). In polluted environments increased temperatures and larger temperature-sensitive emissions of isoprene cause enhanced ozone levels.
- Surface ozone is not in the stratosphere:
Next, NewsBusters asserts that the ozone story is confusing because of the
.. treaty called the Montreal Protocol. This was designed to reduce and eventually eliminate the production and release of a number of substances thought at the time to be depleting ozone.
Ummm…. those substances (chiefly chlorofluorocarbons - CFCs) are still thought to be depleting the ozone layer - which is in the stratosphere, some 30km above the ground-level ozone that people shouldn't be breathing. CFCs have no impact on ground-level ozone at all (since their reactive chlorine is only released in the stratosphere).
- The final inanity:
Wouldn't it be fascinating if such efforts [such as the Montreal Protocol] lead to cleaner air around the world which ended up warming the planet, and that additional warmth is now breaking down the very ozone we thought we could save?
Every part of this sentence is wrong. The Montreal Protocol had no impact on cleaning the air, it stopped the growth of CFCs which are powerful greenhouse gases (in addition to their role in depleting stratospheric ozone), therefore it slowed global warming, rather than increasing it, and we aren't trying to save ground-level ozone. Had any of this been true it would indeed have been fascinating.
What should we make of this? Unfortunately one must conclude that no mistake is too dumb for someone, somewhere to make if they think they can spin it into supporting their anti-science agenda. For them complexity is something to be abused rather than a challenge to be understood, underlining quite clearly (again) the difference between science and propaganda.
Weekend round-up
A few interesting pieces from around the web relevant to some previous postings:
- The latest satellite imagery from the Wilkins Ice Sheet (discussed recently) is not looking good. And most curiously the collapse is happening in winter.
- The Weather Channel "Forecast Earth" team make a valiant attempt to explain the problems and promise for regional climate change projections by 2050. See our post on the general subject from last year).
- And for those of you following the various sagas of political interference in the communication of climate science, a nice interactive graphic summary, courtesy of UCS.
Next week will be a little quiet - it is mid-summer after all - so apologies in advance if the moderation is a somewhat slow. You may also note that we have instituted a "captcha" step to the commenting process. This uses reCAPTCHA which as well as providing protection against spam, helps with the digitization of old books.
All-paper salutes to the environment
The Onion last week had a great (recycled) spoof on the various 'green' special issues being published but, not to be outdone, the contributors to RealClimate have also been busy producing paper products about the environment.
Surprisingly perhaps, as well as having day jobs and writing for this blog, collectively we have written a number of popular science books about climate change. Some of these have already been published, but there are a few more "in the pipeline". We try not to overdo self-promotion on this website (for instance, we don't blog about most of our own technical publications) but since these projects are synergistic with our aims here, it makes sense to let people know what we've been up to. We have therefore set up a page listing "Our Books" that we will keep up-to-date as more titles become available. It's also linked from the new animated gif image on the side bar.
CO2 is not the only greenhouse gas, and greenhouse effects are not the only CO2 problem
The title here should strike a familiar theme for most readers. Climate forcings do not just include CO2 (other greenhouse gases, aerosols, land use, the sun, the orbit and volcanoes all contribute), and the impact of human emissions often has non-climatic effects on biology and ecosystems.
First up last week was a call from Michael Prather and colleagues that the production of a previously neglected greenhouse gas (NF3) was increasing and could become a significant radiative forcing. This paper was basically an update of calculations done for the IPCC combined with new information about the production of this non-Kyoto gas.
Most of the media stories that picked this up focused on the use of this gas in a particular manufacturing process - flat screen plasma TVs. Thus the headlines almost all read something like "Flat-screen TVs cause global warming"! (see here, here, here etc.). Unfortunately, very few of the headline writers read the small print.
NF3 is indeed a more powerful greenhouse gas than CO2 (as are methane, CFCs and SF6 etc.), but because it is much less prevalent, the net radiative forcing (as with other Kyoto gases) is much smaller. Unfortunately, no-one has any measures of the concentration of NF3 in the atmosphere. This is likely to be increasing, since production has stepped up rapidly in recent years, but the amount of gas that escapes to the air is unknown. Manufacturers claim that it is only a very small percentage - but historically such claims have not always been very reliable. However, it is almost certain that NF3 has not caused a significant amount of global warming (yet).
The one issue that many stories did get wrong was in the comparison with coal. Prather's paper compared the effect of the entire global production of NF3 being released into the atmosphere with the CO2 impact of one coal-fired power station. Since that is the maximum estimate of the current effect, and only matches a single power-station, the subtlety of the comparison got a little lost on the way to "Flat screen TVs 'worse than coal'" story….
Needless to say, no-one should be throwing away their flat screen TVs because of this (it's not in the use of the TV that causes a problem), but manufacturers will likely need to step up monitoring of NF3 leakage or switch to an alternative process which some have already done.
The second story getting some attention, is the ocean acidification issue. As we've discussed previously, the increased take up in the oceans of human-released CO2 is rapidly increasing the acidity (lowering the pH) of the oceans, making it more difficult for many carbonate-producing organisms to produce calcite or aragonite. These organisms include corals, coccolithophores, foraminfera, shell fish etc.
Both of these issues are relevant to the ongoing climate change discussion and it's good to see the media picking up (albeit imperfectly) on these ancillary discussions. But as with the "North Pole" lightning rod discussed last week, there always needs to be a hook before something gets wide press (the 'tyranny of the news peg' as ably described by Andy Revkin). In the first case, there was a link to a popular consumer item and in the second, there has been a concerted effort to get the ocean acidification issue higher up the agenda.
The fact of the matter is that most of what goes on in the sciences is completely (and usually correctly) well below the radar of the public at large. But when there are discoveries and issues that do have public policy ramifications, getting the public to pay attention often requires finding just these kinds of resonances. Now if there was only a way to make sure the story underneath was accurate….
CO2 is not the only greenhouse gas, and greenhouse effects are not the only CO2 problem
The title here should strike a familiar theme for most readers. Climate forcings do not just include CO2 (other greenhouse gases, aerosols, land use, the sun, the orbit and volcanoes all contribute), and the impact of human emissions often has non-climatic effects on biology and ecosystems.
First up last week was a call from Michael Prather and colleagues that the production of a previously neglected greenhouse gas (NF3) was increasing and could become a significant radiative forcing. This paper was basically an update of calculations done for the IPCC combined with new information about the production of this non-Kyoto gas.
Most of the media stories that picked this up focused on the use of this gas in a particular manufacturing process - flat screen TVs. Thus the headlines almost all read something like "Flat-screen TVs cause global warming"! (see here, here, here etc.). Unfortunately, very few of the headline writers read the small print.
NF3 is indeed a more powerful greenhouse gas than CO2 (as are methane, CFCs and SF6 etc.), but because it is much less prevalent, the net radiative forcing (as with other Kyoto gases) is much smaller. Unfortunately, no-one has any measures of the concentration of NF3 in the atmosphere. This is likely to be increasing, since production has stepped up rapidly in recent years, but the amount of gas that escapes to the air is unknown. Manufacturers claim that it is only a very small percentage - but historically such claims have not always been very reliable. However, it is almost certain that NF3 has not caused a significant amount of global warming (yet).
The one issue that many stories did get wrong was in the comparison with coal. Prather's paper compared the effect of the entire global production of NF3 being released into the atmosphere with the CO2 impact of one coal-fired power station. Since that is the maximum estimate of the current effect, and only matches a single power-station, the subtlety of the comparison got a little lost on the way to "Flat screen TVs 'worse than coal'" story….
Needless to say, no-one should be throwing away their flat screen TVs because of this (it's not in the use of the TV that causes a problem), but manufacturers will likely need to step up monitoring of NF3 leakage or switch to an alternative process which some have already done.
The second story getting some attention, is the ocean acidification issue. As we've discussed previously, the increased take up in the oceans of human-released CO2 is rapidly increasing the acidity (lowering the pH) of the oceans, making it more difficult for many carbonate-producing organisms to produce calcite or aragonite. These organisms include corals, coccolithophores, foraminfera, shell fish etc.
Both of these issues are relevant to the ongoing climate change discussion and it's good to see the media picking up (albeit imperfectly) on these ancillary discussions. But as with the "North Pole" lightning rod discussed last week, there always needs to be a hook before something gets wide press (the 'tyranny of the news peg' as ably described by Andy Revkin). In the first case, there was a link to a popular consumer item and in the second, there has been a concerted effort to get the ocean acidification issue higher up the agenda.
The fact of the matter is that most of what goes on in the sciences is completely (and usually correctly) well below the radar of the public at large. But when there are discoveries and issues that do have public policy ramifications, getting the public to pay attention often requires finding just these kinds of resonances. Now if there was only a way to make sure the story underneath was accurate….
Global trends and ENSO
It's long been known that El Niño variability affects the global mean temperature anomalies. 1998 was so warm in part because of the big El Niño event over the winter of 1997-1998 which directly warmed a large part of the Pacific, and indirectly warmed (via the large increase in water vapour) an even larger region. The opposite effect was seen with the La Niña event this last winter. Since the variability associated with these events is large compared to expected global warming trends over a short number of years, the underlying trends might be more clearly seen if the El Niño events (more generally, the El Niño - Southern Oscillation (ENSO)) were taken out of the way. There is no perfect way to do this - but there are a couple of reasonable approaches.
In particular, the Thompson et al (2008) paper (discussed here), used a neat way to extract the ENSO signal from the SST data, by building a simple physical model for how the tropical Pacific anomalies affect the mean. He kindly used the same approach for the HadCRUT3v data (pictured below) and I adapted it for the GISTEMP data as well. This might not be ideal, but it's not too bad:
(Each line has been re-adjusted so that it has a mean of zero over the period 1961-1990).
The basic picture over the long term doesn't change. The trends over the last 30 years remain though the interannual variability is slightly reduced (as you'd expect). The magnitude of the adjustment varies between +/-0.25ºC. You can more clearly see the impacts of the volcanoes (Agung: 1963, El Chichon: 1982, Pinatubo: 1991). Over the short term though, it does make a difference. Notably, the extreme warmth in 1998 is somewhat subdued, as is last winter's coolness. The warmest year designation (now in the absence of a strong El Niño) is more clearly seen to be 2005 (in GISTEMP) or either 2005 or 2001 (in HadCRUT3v). This last decade is still the warmest decade in the record, and the top 8 or 10 years (depending on the data source) are all in the last 10 years!
Despite our advice, people are still insisting that short term trends are meaningful, and so to keep them happy, standard linear regression trends in the ENSO-corrected annual means are all positive since 1998 (though not significantly so). These are slightly more meaningful than for the non-ENSO corrected versions, but not by much - as usual, corrections for auto-correlation would expand the error bars further.
The differences in the two products (HadCRUT3v and GISTEMP) are mostly a function of coverage and extrapolation procedures where there is an absence of data. Since one of those areas with no station coverage is the Arctic Ocean, (which as you know has been warming up somewhat), that puts in a growing difference between the products. HadCRUT3v does not extrapolate past the coast, while GISTEMP extrapolates from the circum-Arctic stations - the former implies that the Arctic is warming at the same rate as the rest of the globe, while the latter assumes that the Arctic is warming as fast as the highest measured latitudes. Both assumptions might be wrong of course, but a good test will be from the Arctic Buoy data once they have been processed up to the present and a specific Arctic Ocean product is made. There are some seasonal issues as well (spring Arctic trends are much stronger the summer trends since it is very hard to go significantly above 0ºC while there is any ice left).
Update: A similar analysis (with similar conclusions was published by Fawcett (2008) (p141).
The ENSO-corrected data can be downloaded here. Note that because the correction is not necessarily zero for the respective baselines, each each time series needs to be independently normalised to get a common baseline.
North Pole notes
I always find it interesting as to why some stories get traction in the mainstream media and why some don't. In online science discussions, the fate of this years summer sea ice has been the focus of a significant betting pool, a test of expert prediction skills, and a week-by-week (almost) running commentary. However, none of these efforts made it on to the Today program. Instead, a rather casual article in the Independent showed the latest thickness data and that quoted Mark Serreze as saying that the area around the North Pole had 50/50 odds of being completely ice free this summer, has taken off across the media.
The headline on the piece "Exclusive: no ice at the North Pole" got the implied tense wrong, and I'm not sure that you can talk about a forecast as evidence (second heading), but still, the basis of the story is sound (Update: the headline was subsequently changed to the more accurate "Scientists warn that there may be no ice at North Pole this summer"). The key issue is that since last year's dramatic summer ice anomaly, the winter ice that formed in that newly opened water is relatively thin (around 1 meter), compared to multi-year ice (3 meters or so). This new ice formed quite close to the Pole, and with the prevailing winds and currents (which push ice from Siberia towards Greenland) is now over the Pole itself. Given that only 30% of first year ice survives the summer, the chances that there will be significant open water at the pole itself is high.
The actuality will depend on the winds and the vagaries of Arctic weather - but it certainly bears watching. Ironically, you will be able to see what happens only if it doesn't happen (from these web cams near the North Pole station).
This is very different from the notoriously over-excited story in the New York Times back in August 2000. In that case, the report was of the presence of some open water at the pole - which as the correction stated, is not that uncommon as ice floes and leads interact. What is being discussed here is large expanses of almost completely ice-free water. That would indeed be unprecedented since we've been tracking it.
So why do stories about an geographically special, but climatically unimportant, single point traditionally associated with a christianized pagan gift-giving festival garner more attention than long term statistics concerning ill-defined regions of the planet where very few people live?
I don't really need to answer that, do I?
More PR related confusion
It's a familiar story: An interesting paper gets published, there is a careless throwaway line in the press release, and a whole series of misleading headlines ensues.
This week, it's a paper on bromine- and iodine-mediated ozone loss in marine boundary layer environments (see a good commentary here). This is important for the light that it shines on tropospheric ozone chemistry ("bad ozone") which is a contributing factor to global warming (albeit one which is about only about 20% as important as CO2). So far so good. The paper contains some calculations indicating that chemical transport models without these halogen effects overestimate ozone near the Cape Verde region by about 15% - a difference that certainly could be of some importance if it can be extrapolated across the oceans.
However, the press release contains the line
Large amounts of ozone – around 50% more than predicted by the world’s state-of-the-art climate models – are being destroyed in the lower atmosphere over the tropical Atlantic Ocean.
(my highlights). Which led directly to the headlines like Study highlights need to adjust climate models.
Why is this confusing? Because the term 'climate models' is interpreted very differently in the public sphere than it is in the field. For most of the public, it is 'climate models' that are used to project global warming into the future, or to estimate the planet's sensitivity to CO2. Thus a statement like the one above, and the headline that came from it are interpreted to mean that the estimates of sensitivity or of future warming are now in question. Yet this is completely misleading since neither climate sensitivity nor CO2 driven future warming will be at all affected by any revisions in ozone chemistry - mainly for the reason that most climate models don't consider ozone chemistry at all. Precisely zero of the IPCC AR4 model simulations (discussed here for instance) used an interactive ozone module in doing the projections into the future.
What the paper is discussing, and what was glossed over in the release, is that it is the next generation of models, often called "Earth System Models" (ESMs), that are starting to include atmospheric chemistry, aerosols, ozone and the like. These models may well be significantly affected by increases in marine boundary layer ozone loss, but since they have only just started to be used to simulate 20th and early 21st Century changes, it is very unclear what difference it will make at the large scale. These models are significantly more complicated than standard climate models (having dozens of extra tracers to move around, and a lot of extra coding to work through), are slower to run, and have been used much less extensively.
Climate models today are extremely flexible and configurable tools that can include all these Earth System modules (including those mentioned above, but also full carbon cycles and dynamic vegetation), but depending on the application, often don't need to. Thus while in theory, a revision in ozone chemistry, or soil respiration or aerosol properties might impact the full ESM, it won't affect the more basic stuff (like the sensitivity to CO2). But it seems that the "climate models will have to be adjusted" meme is just too good not to use - regardless of the context.
Ocean heat content revisions
Hot on the heels of last months reporting of a discrepancy in the ocean surface temperatures, a new paper in Nature (by Domingues et al, 2008) reports on the revisions of the ocean heat content (OHC) data - a correction required because of other discrepancies in measuring systems found last year.
Before we get to the punchline though, it's worth going over the saga of the OHC trends in the literature over the last 8 years. In 2001, Syd Levitus and colleagues first published their collation of ocean heat content trends since 1950 based on archives of millions of profiles taken by oceanographic researchers over the last 50 years. This showed a long term upward trend up, but with some very significant decadal variability - particularly in the 1970s and 1980s. This long term trend was in reasonable agreement with model predictions, but the decadal variability was much larger in the observations.
As in all cases where there is a data-model mismatch, people go back to both in order to see what might be wrong. One of the first suggestions was that since the spatial sampling became much coarser in the early part of the record, there might be more noise earlier on that didn't actually reflect a real ocean-wide signal. Sub-sampling the ocean models at the same sampling density as the real observations did increase the decadal variability in the diagnostic but it didn't provide a significantly better match (AchutaRao et al, 2006).
Other problems came up when trying to tally the reasons for sea level rise (SLR) over that 50 year period. Global SLR is a product of (in rough order of importance) ocean warming, land ice melting, groundwater extraction/dam building, and remnant glacial isostatic adjustment (the ocean basins are still slowly adjusting to the end of the last ice age). The numbers from tide gauges (and later, satellites) were higher than what you got by estimating each of those terms separately. (Note that the difference is mainly due to the early part of the record - more recent trends do fit pretty well). There were enough uncertainties in the various components so that it wasn't obvious where the problems were though.
Since 2003, the Argo program has seeded the oceans with autonomous floats which move up and down the water column and periodically send their data back for analysis. This has at last dealt with the spatial sampling issue (at least for the upper 700 meters in the ocean - greater depths remain relatively obscure). Initial results from the Argo data seemed to indicate that the ocean cooled quite dramatically from 2003 to 2005 (in strong contradiction to the sea level rise which had continued) (Lyman et al, 2006). But comparisons with other sources of data suggested that this was only seen with the Argo floats themselves. Thus when an error in the instruments was reported in 2007, things seemed to fit again.
In the meantime however, calibrations of the other sources of data against each other were showing some serious discrepancies as well. Ocean temperatures at depth are traditionally made with CTDs (a probe that you lower on line that provides a continuous temperature and salinity profile), Nansen bottles (water samples that are collected from specified depths) or XBTs (eXpendable bathy-thermographs) which are basically just thrown overboard. CTDs are used over and again and can be calibrated continuously to make sure their pressure and temperature measurements are accurate, but XBTs are free falling and the depths from which they are reporting temperatures needs to be estimated from the manufacturers fall rate calculations. As the mix of CTDs, bottles, XBTs and floats has changed over time, minor differences in the bias of each methodology can end up influencing the trends.
(If this is all starting to sound very familiar to those who looked into the surface stations or sea surface temperature record issues, it is because it is the same problem. Almost all long historical climate records were not collected with the goal of climate in mind.)
In particular, analysis (or here) of the XBT data showed that it was biased warm compared to the CTDs, and that this bias changed over time, and was dependent on the kind of XBT used (deep versus shallow). Issues with the fall rate calculation were well known, but corrections were not necessarily being applied appropriately or uniformly and in some cases were not correct themselves. The importance of doing the corrections properly has been subject to some ongoing debate (for instance, contrast the presentations of Levitus and Gourteski at this meeting earlier this year).
So where are we now? The Domingues et al paper that came out yesterday, along with a companion paper from essentially the same group (in press at Journal of Climate) have updated the XBT corrections and dealt with the Argo issues, and….
… show a significant difference from earlier analyses (the new analysis is the black line). In particular, the difficult-to-explain 'hump' in the 1970s has gone (being due to the increase in warm-biased XBTs at that time). The long term trend is slightly higher, while the more recent trends are slightly lower. Interestingly, while there still decadal variability, it is much more obviously tied to volcanic eruptions than was previously the case. Note that this is a 3-year smooth, so the data actually goes to the end of 2004.
So what does this all mean? The first issue is tied to sea level rise. The larger long term trend in ocean warming reported here makes it much easier to reconcile the sea level estimates from thermal expansion with the actual rises. Those estimates do now match. But remember that the second big issue with ocean heat content trends is that they largely reflect the planetary radiative imbalance. This imbalance is also diagnosed in climate models and therefore the comparison serves as an independent check on their overall consistency. Domingues et al show some comparisons with the IPCC AR4 models in their paper. Firstly, they note that OHC trends in the models that didn't use volcanic forcings are consistently higher than the observations. This makes sense of course because each big eruption cools the ocean significantly. For the models that did include volcanic forcings (including the model we used in Hansen et al, 2005, GISS-ER), the match is much better:
(Note that the 3-year smoothed observations are being compared to annual data from the models, the lines have been cut off at 1999, and everything is an anomaly relative to 1961). In particular, the long term (post 1970) observational trends are now a better match to the models, and the response to volcanoes is seen clearly in both. The recent trends are a little lower than reported previously, but are still within the envelope of the model ensemble. One interesting discrepancy is noted however - the models have a slight tendency to mix down the heat more evenly than in the observations.
This isn't going to be the last word on OHC trends, and different groups are going to be publishing their own versions of this analyses relatively soon and updates to the most recent years are still forthcoming. But the big picture is that ocean heat content has indeed been increasing in recent decades, just like the models said it should.
Ocean heat content revisions
Hot on the heels of last months reporting of a discrepancy in the ocean surface temperatures, a new paper in Nature (by Domingues et al, 2008) reports on the revisions of the ocean heat content (OHC) data - a correction required because of other discrepancies in measuring systems found last year.
Before we get to the punchline though, it's worth going over the saga of the OHC trends in the literature over the last 8 years. In 2001, Syd Levitus and colleagues first published their collation of ocean heat content trends since 1950 based on archives of millions of profiles taken by oceanographic researchers over the last 50 years. This showed a long term upward trend up, but with some very significant decadal variability - particularly in the 1970s and 1980s. This long term trend was in reasonable agreement with model predictions, but the decadal variability was much larger in the observations.
As in all cases where there is a data-model mismatch, people go back to both in order to see what might be wrong. One of the first suggestions was that since the spatial sampling became much coarser in the early part of the record, there might be more noise earlier on that didn't actually reflect a real ocean-wide signal. Sub-sampling the ocean models at the same sampling density as the real observations did increase the decadal variability in the diagnostic but it didn't provide a significantly better match (AchutaRao et al, 2006).
Other problems came up when trying to tally the reasons for sea level rise (SLR) over that 50 year period. Global SLR is a product of (in rough order of importance) ocean warming, land ice melting, groundwater extraction/dam building, and remnant glacial isostatic adjustment (the ocean basins are still slowly adjusting to the end of the last ice age). The numbers from tide gauges (and later, satellites) were higher than what you got by estimating each of those terms separately. (Note that the difference is mainly due to the early part of the record - more recent trends do fit pretty well). There were enough uncertainties in the various components so that it wasn't obvious where the problems were though.
Since 2003, the Argo program has seeded the oceans with autonomous floats which move up and down the water column and periodically send their data back for analysis. This has at last dealt with the spatial sampling issue (at least for the upper 700 meters in the ocean - greater depths remain relatively obscure). Initial results from the Argo data seemed to indicate that the ocean cooled quite dramatically from 2003 to 2005 (in strong contradiction to the sea level rise which had continued) (Lyman et al, 2006). But comparisons with other sources of data suggested that this was only seen with the Argo floats themselves. Thus when an error in the instruments was reported in 2007, things seemed to fit again.
In the meantime however, calibrations of the other sources of data against each other were showing some serious discrepancies as well. Ocean temperatures at depth are traditionally made with CTDs (a probe that you lower on line that provides a continuous temperature and salinity profile), Nansen bottles (water samples that are collected from specified depths) or XBTs (eXpendable bathy-thermographs) which are basically just thrown overboard. CTDs are used over and again and can be calibrated continuously to make sure their pressure and temperature measurements are accurate, but XBTs are free falling and the depths from which they are reporting temperatures needs to be estimated from the manufacturers fall rate calculations. As the mix of CTDs, bottles, XBTs and floats has changed over time, minor differences in the bias of each methodology can end up influencing the trends.
(If this is all starting to sound very familiar to those who looked into the surface stations or sea surface temperature record issues, it is because it is the same problem. Almost all long historical climate records were not collected with the goal of climate in mind.)
In particular, analysis (or here) of the XBT data showed that it was biased warm compared to the CTDs, and that this bias changed over time, and was dependent on the kind of XBT used (deep versus shallow). Issues with the fall rate calculation were well known, but corrections were not necessarily being applied appropriately or uniformly and in some cases were not correct themselves. The importance of doing the corrections properly has been subject to some ongoing debate (for instance, contrast the presentations of Levitus and Gourteski at this meeting earlier this year).
So where are we now? The Domingues et al paper that came out yesterday, along with a companion paper from essentially the same group (in press at Journal of Climate) have updated the XBT corrections and dealt with the Argo issues, and….
… show a significant difference from earlier analyses (the new analysis is the black line). In particular, the difficult-to-explain 'hump' in the 1970s has gone (being due to the increase in warm-biased XBTs at that time). The long term trend is slightly higher, while the more recent trends are slightly lower. Interestingly, while there still decadal variability, it is much more obviously tied to volcanic eruptions than was previously the case. Note that this is a 3-year smooth, so the data actually goes to the end of 2004.
So what does this all mean? The first issue is tied to sea level rise. The larger long term trend in ocean warming reported here makes it much easier to reconcile the sea level estimates from thermal expansion with the actual rises. Those estimates do now match. But remember that the second big issue with ocean heat content trends is that they largely reflect the planetary radiative imbalance. This imbalance is also diagnosed in climate models and therefore the comparison serves as an independent check on their overall consistency. Domingues et al show some comparisons with the IPCC AR4 models in their paper. Firstly, they note that OHC trends in the models that didn't use volcanic forcings are consistently higher than the observations. This makes sense of course because each big eruption cools the ocean significantly. For the models that did include volcanic forcings (including the model we used in Hansen et al, 2005, GISS-ER), the match is much better:
(Note that the 3-year smoothed observations are being compared to annual data from the models, the lines have been cut off at 1999, and everything is an anomaly relative to 1961). In particular, the long term (post 1970) observational trends are now a better match to the models, and the response to volcanoes is seen clearly in both. The recent trends are a little lower than reported previously, but are still within the envelope of the model ensemble. One interesting discrepancy is noted however - the models have a slight tendency to mix down the heat more evenly than in the observations.
This isn't going to be the last word on OHC trends, and different groups are going to be publishing their own versions of this analyses relatively soon and updates to the most recent years are still forthcoming. But the big picture is that ocean heat content has indeed been increasing in recent decades, just like the models said it should.
Wired Magazine’s Incoherent Truths
Many of our tech-savvy friends — the kind of folks who nurse along the beowulf clusters our climate models run on — are scratching their heads over some cheeky shrieking that recently appeared in a WIRED magazine article on Rethinking What it Means to be Green . Crank up the A/C! Kill the Spotted Owl! Keep the SUV! What's all that supposed to be about?
Let's take air conditioning for starters. Basically WIRED took a look at the carbon footprint of New England heating vs. Arizona cooling and jumped to the conclusion that air conditioning was intrinsically more efficient than heating. To see where they were led astray let's consider a house sitting where you need to cool it by 20 degrees to be comfortable. The heat leaks into the house at a rate that is approximately proportional to this temperature difference, and the heat leaking in needs to be removed. Now, in order to move that heat from inside to outside, energy has to be expended. Given a fixed electric power usage (in watts), a better air conditioner can remove more heat per day than a worse one, but every air conditioner needs to expend some energy to move the heat. That's just thermodynamics.
Efficiency of air conditioners is measured by a SEER rating, which is the ratio of heat moved to the outside (in BTU/hr) to the electric power consumption (in Watts). A typical modern air conditioner has a SEER rating of 10, We can convert this into nicer units by converting BTU/hr into Watts, which means dividing the SEER rating by 3.413, which then gives us a Coefficient of Performance, in units of Watts of heat moved per Watt of electricity used. For the aforementioned efficiency, we move heat at a rate of 2.92 Watts if we expend 1 Watt of electric energy. An air conditioner is just a heat engine run in reverse: instead of making use of a temperature differential to use heat flow from hot to cold to do work, we expend mechanical work in order to move heat from a colder place to a hotter place. Thus, an efficient heat engine is an inefficient air conditioner. That's basically why the Coefficient of Performance gets smaller when the temperature difference between indoors and outdoors is greater — with bigger temperature difference heat engine cycles tend to get more efficient, which means that air conditioner cycles tend to get less efficient. That's also where the "S" in SEER comes from. It stands for "Seasonal," and reflects the fact that efficiency must be averaged over the range of actual temperature differentials experienced in a "typical" climate. Your mileage may vary.
This situation can be contrasted with heating. If that same house were in an environment that were too cold instead of too warm, so that it had to be kept 20 degrees warmer than the environment, then the amount of heat leaking out of the house each day would be about the same as the amount leaking into the house in the previous case. That heat loss needs to be replaced by burning fuel. Now, generating heat is the only thing that can be done with 100% efficiency. Old furnaces lose a lot of heat up the chimney, but modern sealed-combustion burners– the kind that can use PVC pipes instead of a chimney — lose virtually nothing. With a heat exchanger between the air intake and the exhaust, they could closely approach the ideal. But still, in this case we are generating heat rather than just moving it, so it takes 1 watt of heat power from fuel burning to make up 1 watt of heat loss. That would seem to make heating a factor of 2.92 less efficient than air conditioning.
But wait, the story doesn't stop there. First, there's the fact that air conditioning almost invariably runs off of electricity, and the increased electricity demand is a big source of the pressure to build more coal-fired power plants. A house can be heated by burning natural gas, and right there air conditioning becomes 1.8 times worse than heating, because natural gas emits only 55% of the carbon of coal, per unit of heat energy produced. And it gets even worse: Coal fired power plants are only 30% efficient at converting heat into electricity, on average, so there you get another factor of 3.3 in carbon emissions per unit of energy transferred between the house and its environment. Finally, figure in a typical electric line transmission loss of 7% and you get another factor 1.075. Put it all together with the energy efficiency of the air conditioner itself and air conditioning comes in at a whopping 2.19 times less efficient than heating. for a given amount of temperature difference between house and environment. That means that so far as carbon emissions go, heating a house to 70 degrees when the outside temperature is 40 degrees is like cooling the same house to 70 degrees when the outside temperature is 83.7 degrees.
And that's still not the end of the story. A house in need of air conditioning has other heat inputs besides the heat leaking in from outside, and all that extra heat needs to be gotten rid of as well. For example, heat is a waste-product of all energy use going on in the house. Four people produce 400W that needs to be gotten rid of, and then there's the heat from hot water, lighting, the TV, cooking and what have you — all the energy usage within the house, plus 100W of biological heat per person needs to be gotten rid of. On top of that, you've got direct radiative heating from the sun, both from the sunllight getting through windows and solar heating of the exterior surfaces of the house, some of which will leak in through the insulation. Energy must be expended to remove all this heat. In contrast, in the heating season waste heat is subtracted from the energy needed for home heating.
So, WIRED got the story egregiously wrong, and not just because they did the arithmetic wrong. In their rush to be cute, they didn't even make a half-baked attempt to do the arithmetic. But what if they had been right and air conditioning really were intrinsically more efficient than heating. Would that justify their conclusion that you can just "crank up the A/C?" without worry? No, of course not, because cranking up the A/C would still use additional energy and still lead to the emission of additional carbon. For the conclusion to be justified, it wouldn't be enough for A/C to be more efficient than heating; it would have to be so much more efficient that the incremental energy usage from cranking it up were trivial. WIRED didn't even try to make that case. If they had, they might have spotted their errors.
Is there any real conclusion that could have been drawn from more clear thinking about the heating vs. air conditioning issues danced around in the article? Yes, in fact. The conclusion is that it makes a lot of sense to build houses in places where the environment requires neither much heating nor much cooling. This is in fact why Los Angeles scores pretty well in carbon footprint per capita, despite all the driving (as noted recently in The Economist.). Another conclusion to be drawn from the carbon footprint of New England heating is that there are probably a lot of leaky homes up there heated by inefficient oil-fired furnaces. Fixing that situation represents a huge untapped virtual energy source.
What's more, for a magazine that purports to be written by and for tech geeks, WIRED missed the biggest and most interesting part of the story: the same intrinsic efficiences of heat pumps can be run in reverse to give you the same economies for home heating as you get for air conditioning. To do this effectively, you'd have to run the heat pump off of natural gas rather than electricity (or perhaps run it off of locally generated solar power or wind). You'd also have to deal with the fact that heat pumps become less efficient when working across large temperature gradients, but that's where geothermal heat storage systems come in, making use of the fact that the deep subsurface temperature remains near a nice 55F all year around. Now that would have been a nice story for a tech magazine to cover. And by the way, the decrease in efficiency of heat pumps as the temperature differential increases has another implication that WIRED missed: not only does global warming increase the basic demand for air conditioning, with all the attendant pressures on electricity demand, but it exacerbates the situation by decreasing the efficiency of the entire installed base of air conditioners.
Now about that spotted owl. This refers to a claim that industrial tree plantations take up carbon faster than old growth forests; Since spotted owls require the large trees found only in old-growth, the supposed implication is that if we want to soak up carbon we ought to damn the spotted owl and cut down all the old growth. WIRED really committed serial stupidities on this one. First of all, the article they cited in support of their claim was about carbon emissions from Canada's managed forests, not from old growth. Now, it's true that a rapidly growing young tree takes carbon out of the atmosphere more rapidly than a mature forest which more slowly transfers carbon to long term storage in soil. However, to figure out how much net carbon sequestration you get out of that young tree once it's chopped down, you need to figure what happens to it. Lots of trees wind up in paper, carboard boxes, shipping palettes and other things that rapidly sit around decomposing or get burned off (or worse, turn into methane in landfills). Even the part that turns into houses has a relatively short residence time before being oxidized. Anybody who has maintained an old Victorian house knows about the constant battle against rot, and the amount of wood that needs to be replaced even if (knock wood) the thing doesn't burn down or turn into a tear-down. So, WIRED is totally off the mark there, unless, to use the colorful language of my colleague Dave Archer, they can get trees to "drop diamonds instead of leaves."
Worse, they ignore the abundant literature indicating that old growth forests can be a net sink of carbon even in equilibrium, whereas the soil disturbance of clear cutting and industrial forestry can lead to large soil carbon releases. A classic article in the genre is "Effects on carbon storage of conversion of old-growth forests to young forests" (Harmon et al. Science 1990) . They state "Simulations of carbon storage suggest that conversion of old-growth forests to young fast-growing forests will not decrease atmospheric carbon dioxide (CO2) in general, as has been suggested recently.". For more recent work, take a look at what Leighty et al. (ECOSYSTEMS Volume: 9 Issue: 7 Pages: 1051-1065. 2006 ) have to say about the Tongass:.
- "The Tongass National Forest (Tongass) is the largest national forest and largest area of old-growth forest in the United States. Spatial geographic information system data for the Tongass were combined with forest inventory data to estimate and map total carbon stock in the Tongass; the result was 2.8 +/- 0.5 Pg C, or 8% of the total carbon in the forests of the conterminous USA and 0.25% of the carbon in global forest vegetation and soils. Cumulative net carbon loss from the Tongass due to management of the forest for the period 1900-95 was estimated at 6.4-17.2 Tg C. Using our spatially explicit data for carbon stock and net flux, we modeled the potential effect of five management regimes on future net carbon flux. Estimates of net carbon flux were sensitive to projections of the rate of carbon accumulation in second-growth forests and to the amount of carbon left in standing biomass after harvest. Projections of net carbon flux in the Tongass range from 0.33 Tg C annual sequestration to 2.3 Tg C annual emission for the period 1995-2095. For the period 1995-2195, net flux estimates range from 0.19 Tg C annual sequestration to 1.6 Tg C annual emission. If all timber harvesting in the Tongass were halted from 1995 to 2095, the economic value of the net carbon sequestered during the 100-year hiatus, assuming $20/Mg C, would be $4 to $7 million/y (1995 US dollars). If a prohibition on logging were extended to 2195, the annual economic value of the carbon sequestered would be largely unaffected ($3 to $6 million/y). The potential annual economic value of carbon sequestration with management maximizing carbon storage in the Tongass is comparable to revenue from annual timber sales historically authorized for the forest."
So, it looks like that old Spotted Owl and its kindred old-growth denizens are in fact sitting not just on a nest, but on a treasure trove of carbon credits worth potentially more than the timber harvest.
And should you keep that SUV? This blurb in fact contains some useful advice, buried amidst some fuzzy reasoning and published over a witless tag line stating that "pound for pound" a Prius takes more energy to manufacture than a Hummer. The apparent implication of that tag line is rebutted in the article itself, but why give the reader that as a 32-point type take-home point when the WIRED editors don't even themselves believe it's an important statistic? This factoid refers to the energy used in the nickel component of Prius batteries, but it's irrelevant because "pound for pound" doesn't count if your point is moving 4 people from point A to point B. What transport value do you get from transporting four people plus the weight of the Hummer? Now, the rest of the fuzziness in the logic is a bit more subtle. The author notes quite rightly that there is a very significant carbon emission from manufacturing a car, which is indeed more for a Prius (at least for the moment) than it is for comparable sized non-hybrids.. Thus, if you are faced with ditching your existing car (whatever it may be) and buying a Prius, you need to consider how much you drive per year and see how long it takes to "pay back" the carbon emission from manufacturing the Prius. So far so good. But this is more a statement about the transition to more efficient cars, and how to deal with mistakes of the past, rather than a statement about what is intrinsically desirable in the fleet. As far as carbon emissions go, we'd still be better off if everybody who needed a car were in a Prius, except maybe for people who drive very little per year — who should then be into shared hybrids via iGO or ZipCars, Maybe if you drive very little and live out in a rural area where there are not going to be any shared cars, getting a compact non-Hybrid might make sense. There must be at least a dozen or two people out there in that category, I guess.
The rest of the advice WIRED gives makes even less sense. They say that if you want to be green, you ought to buy a used Civic or something like that, not a Prius. That's because the used car already has the manufacturing carbon emissions "written down" (or, I guess at least the carbon guilt accrues to the original owner, not that the atmospheric radiative forcing is going to care much about that). However, this advice, sensible-sounding though it is — ignores the fact that to make that used car available to you, the original owner almost certainly had to buy something else, and probably that was a new car, or at least a newer one. So, for the scheme to work, you'd have to buy your used Civic from somebody who was giving up driving altogether. I no longer own a car myself, but I'm sorry I wasn't able to participate in a scheme like this; by the time I gave up our remaining car ten years ago, it was suitable only for the crusher, and in fact had to be towed there.
The real implication is that manufacturing costs count, so most people should buy a small, efficient hybrid and keep it until it runs into the ground. The implication is also that durability of cars counts for nearly as much as gas mileage, since an efficient car that needs to be replaced every five years isn't really all that efficient.
Along with all the nonsense is a certain amount of true (if by now commonplace) advice. Among this is the basic truth that urban living is inherently green, and if more people lived in cities (and if more cities were kept livable so people would want to move there). then per capita carbon emissions would go down. Even there, the Economist managed to be both more informative and more iconoclastic with its surprising analysis of the pattern of urbanism in Los Angeles. The other truism in WIRED is that nuclear power deserves a second look, and probably has an important role to play in a decarbonized energy future. Still, if you compare the cost of making all those chilly New England homes efficient with the total true cost of building more nuclear plants, well, let's just say I'm buying stock in argon-filled low-e window manufacturers rather than Areva, much as I like their track record on nuclear electricity.
Ice Shelf Instability
Guest contribution from Mauri S. Pelto
Ice shelves are floating platforms of ice fed by mountain glaciers and ice sheets flowing from the land onto the ocean. The ice flows from the grounding line where it becomes floating to the seaward front, where icebergs calve. For a typical glacier when the climate warms the glacier merely retreats, reducing its low elevation, high melting area by increasing its mean elevation. An ice shelf is nearly flat and cannot retreat in this fashion. Ice shelves cannot persist unless the entire ice shelf is an accumulation zone, where snowpack does not completely melt even in the summer.
Ice shelves have long been recognized as keys in buttressing Antarctic Ice Sheets. In turn ice shelves rely on pinning points for buttressing. The pinning point are where the floating ice shelf meets solid ground, either at lateral margins or a subglacial rise meets the bottom of the ice shelf causing an ice rise on the shelf surface.
The recent collapse of Wordie Ice Shelf, Mueller Ice Shelf, Jones Ice Shelf, Larsen-A and Larsen-B Ice Shelf on the Antarctic Peninsula has made us aware of how dynamic ice shelve systems are. After their loss the reduced buttressing of feeder glaciers has allowed the expected speed-up of inland ice masses after shelf ice break-up. (Rignot and others, 2004).
Several recent papers examine the causes of breakup of both Larsen B and Wilkins Ice Shelf, which prompts a closer look at the role of surface melting, structural weakness development and ice shelf thinning in this process.
In 1995 a substantial section of the northern Larsen Ice Shelf broke up in a few days. This was the first glimpse at a rapid ice shelf collapse. The breakup followed a period of warming and ice shelf front retreat, prompting (Rott and others, 1996) to observe that “after an ice shelf retreats beyond a critical limit, it may collapse rapidly as a result of perturbated mass balance”.
During the austral summer of 2001/02, melting at the surface of Larsen Ice Shelf in the Antarctic Peninsula was three times in excess of the mean. This exceptional melt event was followed by the collapse of Larsen B Ice Shelf, during which 3,200 km2 of ice shelf surface was lost. That meltwater was playing a key role in collapse was underscored by the unusual number of melt ponds that existed that summer and that the new ice front after collapse close to the limit of surface meltponds seen in images leading up to the March event (Scambos and others, 2003).
The ice shelves actually collapse via rapid calving, and the physics connecting meltwater to calving is its ability to enhance crevasse propagation. When filled 90% or more with meltwater a sufficiently deep crevasse can overcome the overburden pressure that tends to close the crevasse at depth (Scambos and others, 2000). Days before the final Larsen break-up, it is evident that the crevasses cut through the entire ice shelf. It also appeared that large meltponds contracted indicating that they were beginning to drain though the crevasses to the sea (Scambos and others, 2003).
As scientists it would have been easy to close the book on the issue after identifying the meltwater process. However, detailed examinations have continued identifying other key elements in the tale of collapse. The decade prior to collapse the Larsen-B Ice Shelf had thinned primarily by melting of the ice shelf bottom by 18 m (Shepard and others, 2003). This preconditions the ice shelf to failure by weakening its connection to pinning points as the shelf becomes more buoyant. This goes back to the critical limit mentioned by Rott (1996).
Glasser and Scambos (2008) reexamined the Larsen Ice Shelf breakup for structural weaknesses and observed the following. They noted that the rifting and crevasses parallel to the ice front crosscut the meltwater channels and ponds, hence, post dating them. The number and length of the rifts increased markedly in the year before collapse. Substantial rifts also existed between tributary glaciers feeding the ice shelf as far as 40 km behind the ice front. Enlargement of and development of new rifts in these regions occurred in the year prior to collapse. Downstream of the tributary glacier junction there are no evidence of relict rifts, illustrating that these rifts are a feature of the last 20 years. After ice shelf collapse the ice front receded to the pre-existing rifts, and the pre-existing rifts defined the area of collapse. In this case the structural weaknesses preconditioned the ice to rapid breakup. Rift formation occurred in areas of velocity differences and natural weaknesses Velocity differences are largest between tributaries and near the ice front.
The latest example of a collapsing ice shelf is Wilkins Ice Shelf (WIS), which lost 425 km2 in late February and early March 2008. The dynamic nature of the WIS is examined by Braun, Humbert and Moll (2008), their findings are summarized below. WIS is buttressed by Alexander, Latady, Charcot and Rothschild Island and by numerous small ice rises, indicating subglacial contact. Recent history indicates that WIS experiences no continuous ordinary calving, but single break-up events of various magnitudes. They further show that drainage of melt ponds into crevasses were of no relevance for the break-up at WIS. On WIS the evolution of failure zones is associated with ice rises. Analysis of rifting indicated that in 1990 the central area of WIS did not have any substantial rifts. In 1993/94, rift formation started to expand at the northern ice front. Today, the central part of WIS is intersected by long rifts that formed in and around ice rises. The rifts can cover tens of kilometers. The evolution and coalescing of the rifts are followed by break-up events at the ice front. Hence, the connection of rift systems seems to be the trigger for collapse. The recent break-up has left a narrow 6 km wide; already fractured connection to Charcot Island in a sensitive area that is stabilizing the northern part of the ice shelf. A new rift connection formed between already existing fractures, crosses almost the entire northern shelf, which makes WIS even more fragile and vulnerable. This area of interconnected rifts is 2100 km2. An additional 3000 km2 of the 13 000km2 of WIS, is at risk if this connection to Charcot Island is lost as rifts around the Petrie Ice Rise indicate an area of weakness. The conclusion for WIS is pre-conditioning of the ice shelf by failure zones occurring at ice rises and triggered by break-up events are leading to a sequence cascade of failure.
Below you can see the evident rifts near Charcot Island in this March MODIS image and the narrow connection of the ice shelf to this pinning point. The lack of sea ice on the north facing ice front is also noteworthy.
It appears that ice shelf thinning is the key pre-conditioning factor for collapse. The mechanisms for ice shelf thinning include basal melting, meltwater production and rift development. These are interrelated mechanisms that pre-condition the ice shelves to collapse. This will be a key area of continued investigation to understand this critical process for the Antarctic Ice Sheet. At the moment it seems that the key process to rapid calving events is the rift development. Rift development is observed to begin at points of natural weakness. For both ice shelves prior to collapse an expansion of the area where rifts exists has been observed. In both cases this seems to result from pre-conditioning via thinning due to basal melt and surface melt. Rifts development is accentuated by water filling crevasses. A new study will be looking at the impact of reduced sea ice at the front as well (Scambos and Massom, 2008). It is obvious that the glaciologic community will be watching the Wilkins Ice Shelf next Austral summer.
References:
Rignot, E., Casassa, G., Gogineni, P., Krabill, W., Rivera, A., and Thomas, R. (2004). Accelerated ice discharge from the Antarctic Peninsula following the collapse of Larsen B Ice Shelf. Geophysical Research Letters 31: L18401, doi:10.1029/2004GL020697.
Scambos, T., Hulbe, C., Fahnestock, M. and Bohlander, J. (2000). The link between climate warming and break-up of ice shelves in the Antarctic Peninsula. Journal of Glaciology 46: 516–530.
Scambos, T., C. Hulbe, and M. Fahnestock (2003). Climate-induced ice shelf disintegration in the Antarctic Peninsula. In: Domack, E., Leventer, A. Burnett, A., R. Bindschadler, R., P.
Vaughan, D. G., Marshall, G. J., Connolley, W.M., Parkinson, C., Mulvaney, R., D., Hodgson, D.A., King, J.C., Pudsey, C.J. and Turner, J. (2003). Recent rapid regional climate warming on the Antarctic Peninsula. Climate Change 60: 243-274, 2003.
