The absorption of atmospheric CO₂ by the oceans results in a decline in ocean pH, hence ‘ocean acidification’, and reduces carbonate ion availability. This presents a problem to calcifying organisms (those that deposit calcium as either calcite or aragonite as hard parts) because they cannot produce their shells, valves (in the case of bivalves), or tests (in the case of diatoms) as readily.

To explain this, we need a little chemistry. When CO₂ dissolves, it combines with water to form carbonic acid (H₂CO₃). This then breaks down to form bicarbonate (HCO₃^-) when one hydrogen ion is lost, and then carbonate (CO₃^2-) as the other hydrogen ion is lost. This carbonate is the important stuff, as it combines with calcium to form the calcium carbonate (CaCO₃) used by bivalves to produce shells. If something (such as the ocean) is more acidic, there must be more hydrogen ions available. These hydrogen ions interfere with the calcification process as they bond with carbonate, meaning there is less available for shell formation.

Calcification: carbonate chemistry in action!

This process is relatively well established for a number of calcifying organisms, although there are exceptions to (the coccolith, Emiliania huxleyi, for example) and the response to elevated CO₂ levels is not uniform across species.

Much of current research has focussed on the effect of constant CO₂ levels on calcification, but what about animals that live in environments where the CO₂ concentration is constantly changing? The availability of carbonate in estuaries is particularly variable as CO₂ concentrations vary seasonally (there’s a greater carbon load in the winter as storms wash nutrients into rivers), diurnally and with the tide. The impact of elevated CO₂ levels on an organism is also dependant on its life stage; something that is particularly true of bivalves.

Bivalve larvae. Photo credit: Minami Himemiya (source).

Bivalves spend the first part of their life in the plankton, first as a veliger (a relatively amorphous looking ciliated blob) and then as a pediveliger (that same blob, but this time with an identifiable foot) before metamorphosing into a miniature adult. During these larval stages, they are particularly vulnerable to ocean acidification and, until recently, both the reasons behind this, and the longer-term implications of this vulnerability, were unclear.

This is where doctors Christopher Gobler and Stephanie Talmage come in. They took to the lab to tackle why larvae are especially vulnerable to acidification and what this means for them in both the short and long term. It’s impossible to take a look at how all bivalves respond to acidification, though, so to tackle these questions, two bivalve species, the hard-shelled clam (Mercenaria mercenaria) and the Atlantic bay scallop (Argopecten irradians) joined the team.

The Atlantic bay scallop, Argopecten irradians. Photo credit: Rachael Norris and Marina Freudzon (source).

Using their RNA:DNA ratio as a proxy for growth and the uptake of a radioactive calcium isotope, ⁴⁵Ca, to estimate calcification, Gobler and Talmage found that growth in the presence of elevated CO₂ results in individuals of a smaller size. This is because there is less calcium available for uptake. Their findings, revealed that high CO₂ concentrations, not only affected size, but also negatively impacted bivalve physiology, as individuals reared in these conditions were found to have thinner shells. Shells are an important defence against predators and the reduction in shell thickness (and hence strength) may put them at greater risk from predation.

The higher the CO2, the slower the calcium uptake: calcium uptake rates of larval Atlantic bay scallop, Argopecten irradians, under different CO2 concentrations over a 12-hour period (Gobler and Talmage, 2013).

When transferred from a high CO₂ environment to an environment with an ambient CO₂ concentration, larvae grew faster than those in ambient conditions throughout the whole of their development. However, this higher growth rate doesn’t compensate for the low calcification rate during larval stages, as their final is still smaller than individuals reared in ambient conditions at all life stages. This “legacy effect” presents a significant problem for adult bivalves, due to the detrimental impact of reduced calcification on their defences.

By Sara Mynott, EGU Communications Officer

Reference:

Gobler, C. J. and Talmage, S. C.: Short- and long-term consequences of larval stage exposure to constantly and ephemerally elevated carbon dioxide for marine bivalve populations, Biogeosciences, 10, 2241-2253, doi:10.5194/bg-10-2241-2013, 2013.

We model the changes in the geographic location of continents via paleogeographic reconstructions. However, the current methodology for generating these reconstructions is not without problems! Publication of palaeogeographic reconstructions is scarce, probably resulting from the difficulties associated with generating them. Conventional reconstructions are presented as static maps which have poor spatial and temporal resolution. In addition, they are often difficult to replicate as the ‘input data’ used to produced the reconstructions is usually not included in publication. Reconstructions quickly become outdated as the models they are superimposed onto are improved and become more refined.

In Biogeosciences, Wright et al. (2013) present a new method which hopes to overcome some of the issues associated with conventional palaeogrographic reconstructions. Combing the open-source plate motion reconstruction tool, GPlates, with paleobiological data the aim is to uncover spatial and temporal correlations and test the reliability of existing reconstructions. GPlates allows for easy modification and updating of reconstructions and is easily linked to already established models. The new method is tested against the already existing publicly accessible Palaegeographic Atlas of Australia (Totterdell, 2002). It contains 70 palaeogeographic time slices for the Phanerozoic derived from palaeoenvironmental reconstructions, tectonic histories and other geological evidence. In addition, the model is supplemented with fossil indicators from the open-access Palaeobiology database.

Fossil collections (a), palaeogeographical reconstructions taken from the Palaeogeographic Atlas for Australia (b), are reconstructed in GPlates (c) using the Phanerozoic plate motion model (d) and data associations, as per the Emsian example (e) to test and refine the palaeogeographic and plate motion models (click for larger). Source: Wright et al., 2013.

In order to generate their own plate reconstruction in 1Myr intervals in GPlates, for the Australian Phanerozoic, the authors based their relative plate motions on work by Dr. Jan Golonka. The plate motions are derived from palaeomagentic data and Apparent Polar Wander Paths (APW) and are further supported by geological observations, such as location of orogenies and sedimentary basins. A number of taxonomical data were acquired from the Palaeobiology database and assigned GPlates mark-up language so that the data could be included in the new reconstructions. The time scales between the Palaoegeographic Atlas of Australia and the Paleobiology database differed, so they were standardised. The spatial and temporal associations between the palaeogeography and fossil collections were tested for inconsistencies. Where these arose; the fossil collections were taken as the true representation of the palaeoenvironment. For example, if the fossils indicated a truly marine environment, whilst the palaeogeography suggested a terrestrial setting, this was flagged as an inconsistency in the model that needed refining.

The new model has allowed the authors to gain a detailed understanding of the plate tectonic movements of Australia during the Phanerozoic. The article goes into much greater detail than I intend to do so here, I refer you to the article itself if you want more information! During the Cambrian, the new model suggests that Australia spanned equatorial latitudes and formed part of Gondwana. By the Palaeozoic, the Northern margin of Gondwana (North and South China, Tibet and Indochina, amongst others) had detached and this marked the onset of opening and closing of a number of palaeo-Asiatic and Tethys basis. The remaining Pangaea further breaks-up during the Cretaceous, with India and Australia moving northwards, away from Antarctica.

Temporal coverage of eastern Australia basins (EA) and the Eromanga Basin (EB). The data gaps may be related to sampling gaps, orogenic episodes and the influence of glaciations during the late Palaeozoic. Source: Wright et al., 2013.

Palaeogeographic and biofacies data can be embedded into the plate tectonic models in order to uncover inconsistencies and refine the reconstructions. The clear benefits of including palaeobiological data are highlighted during the Emsian time period (402Ma). The paleogeographic reconstruction from the Atlas for Australia proposed a land environment for deposition at this time, whilst the fossil and lithological evidence, suggest a marine environment. Temporal ranges of fossils in relation to the deposition of their associated Formations were problematic and no formations which displayed age disagreements were included in the new model.

Whilst the inclusion of paleobiological data is clearly beneficial to the construction of the models, geographical and temporal gaps in the fossil record, compromise the accuracy of the plate reconstructions. In some cases the gaps in the fossil record are simply due to a sampling bias, but in others it is not clear if the issue is fossil preservation or the environment at the time of deposition.  As a result, other data are required as a proxy for biological data. Improvements to the models could be made by including other paleoenvironment indicators such as data from well logs could be included in future models. To further improve the methodology, it is important to remember that sediments and fossils deposition is often confined to basins. In future, it would be valuable to included elevation data or proxies for these into the models. GPlates will also soon allow the incorporation of chronostratigraphic data (Sikora et al., 2006) as well as paleobiological data.

By Laura Roberts Artal, PhD Student, University of Liverpool

References:

Golonka, J.: Late Triassic and Early Jurassic palaeogeography of the world, Palaeogeogr. Palaeocl., 244, 297–307, 2007.

Totterdell, J. M.: Palaeogeographic Atlas of Australia, Geoscience, Australia, 2002.

Sikora, P. J., Ogg, J. G., Gary, A., Cervato, C., Gradstein, F., Huber,B. T., Marshall, C., Stein, J. A., and Wardlaw, B.: An integrated chronostratigraphic data system for the twenty-first century, Geoinformatics: data to knowledge, 397, 53–59, 2006.

Wright, N., Zahirovic, S., Müller, R. D., and Seton, M.: Towards community-driven paleogeographic reconstructions: integrating open-access paleogeographic and paleobiology data with plate tectonics, Biogeosciences, 10, 1529-1541,  2013.

The UK House of Commons Science and Technology Select Committee has recently launched an inquiry entitled “Climate Change: public understanding and its policy implications”, which is due to address the issue of communicating climate change research. This inquiry was raised following a recent surge in climate change scepticism and a diminishing public concern regarding its effects, with a survey suggesting that 76% of people were concerned by climate change in 2009 against 81% in 2008.

Climate change is certainly a topical issue. It lies at the junction between a panel of physical scientific disciplines (atmospheric physics, oceanography, ecology, chemistry and computing) and social sciences, being a prominent topic in politics and policy-making. There seems to be a constant flow of climate-related articles in the media. They may describe the negative effects of climate change on our environment or the place of climate and environmental change within education, with recent talks to include climate change on the school curriculum in the US being but one recent example. But to what extent do people really take notice? What does the public actually think of climate change and do they really consider our environment to be at risk? As a climate scientist, this got me thinking: How can we better communicate scientific results and the overwhelming consensus within the research community that action needs to be taken?

The inquiry: What, who and how?

In their call for evidence, the Commons Select Committee has outlined a series of questions to be discussed at the inquiry:

• What is the state of public understanding and opinion on climate change issues? What is the role of publicly funded scientists, Government Departments, scientific advisers and the media in communicating climate change?
• Who does the public trust?
• How can public understanding be improved? How important is this understanding in developing appropriate policy?

So what does the public think about climate change?

In September 2012, scientists from the British Antarctic Survey, the Universities of Cambridge and Cardiff and the Global Sustainable Institute at Anglia Ruskin University published a report on public attitudes to climate science and how this science is represented in the media. The purpose of the report was to examine how climate change research is being communicated, the public’s attitude towards it and the means by which this communication could be improved. To go about answering these questions, the investigators carried out a series of focus groups across the UK population. In each case, participants were presented with a range of UK newspaper, radio and television articles on climate science and invited to pick one article for discussion. They were then asked to judge the chosen piece based on the level of interest in the subject, how easy it was to understand and where the news piece could be improved.

Tongue of a glacier on Baffin Island, Canada. Credit: Angsar Walk.

The study revealed that 80% of the survey participants did believe that the world’s climate is changing through a combination of both human activity and natural variability. However, many people felt that they were not properly informed about new findings in climate science and therefore felt relatively uninterested in the field. More importantly, nearly half of the surveyed people believed that scientists exaggerate the seriousness of climate change and trust in “authority groups” such as government, industry, environmental groups, scientists and the media has decreased in recent years.

Climate change and public opinion – who matters?

Despite this growing skepticism, a recent poll published by climate and environmental policy news fact-checker Carbon Brief revealed that the UK population trusts scientists more than any other source to inform them about climate change. In second position, the poll placed Green charities, closely followed by BBC journalists. Far behind and in last place came both politicians and social media, with only 7% of voters trusting these sources to provide accurate, up-to-date information. In addition, the poll showed that as many as 64% of participants did not trust politicians’ information and 53% would not trust the information they read in social media.

Despite trusting scientists most, the number of concerned citizens is still dwindling. So how can we as scientists better convey our results and our concern? The last issue of the journal Nature Climate Change dedicated an editorial to the “climate consensus” and the factors affecting public opinion. The article revealed that the public would be more likely to believe that human causes are affecting long-term climate change if there was a clear scientific consensus that anthropogenic global warming is indeed happening. Luckily, this consensus does exist among the vast majority of climate scientists, so where is this information lost in translation?

Could, may, possibly, maybe… The uncertainty paradox

While the vast majority of people trust scientists, the 2012 report’s working groups also revealed that uncertainty is a big issue for public trust, with readers getting frustrated at fuzzy and seemingly contradictory statements. What is the point of saying that something could possibly happen without developing on this statement? On what basis should people then make decisions? The difficulty is of course that natural variability of the climate system and the complexity of the physical mechanisms involved mean that climate predictions intrinsically have a degree of uncertainty associated with them. There is no real debate among the climate scientific community that we humans are influencing our climate and that this will have consequences on a number of different parameters and sub-systems.

Global warming predictions for the end of the 21st century from the Hadley Centre HadCM3 climate model. Source: Wikimedia Commons.

The question is what impact do these changes have in different parts of the world and to what degree can climate models assign a particular outcome to a specific human source? It is perhaps the definition of this uncertainty that scientists need to spend time explaining. Yes, a cluster of climate models may produce a range of results for a particular experiment. But ultimately they may all show the same trend or allow us to draw hard conclusions that can be translated to the public. When talking about climate forecasting at a recent Royal Meteorological Society meeting, Swedish Meteorologist Anders Persson stated that uncertainty is inevitable but must be acknowledged. He suggested that we stop blaming the models and start taking responsibility for uncertain forecasts. Uncertainty exists, full stop. Let’s start acknowledging it and, more importantly, explaining it.

So how can we scientists improve the communication of climate change research?

Given that scientists are in fact trusted and have a good understanding of the state of the art of climate research and the areas that still need exploring, it seems to me it is up to us to reach out to the public and talk about our research and its results. If, for each paper published in top scientific journals, the authors associated a short, simple piece of outreach to explain the steps taken to come to their conclusion and explain why they trust their results, perhaps more people would find an interest in climate research and would be willing to take personal action. But without this incentive and hard evidence clearly agreed upon by scientists, it is perhaps understandable that climate change is not the priority on everybody’s personal agenda. To put it in the words of financier Jeremy Grantham: “Be persuasive. Be brave. Be arrested (if necessary)”. In other words, let’s take risks and show our involvement and concern to make sure that it is heard by the public and policy-makers. This is possibly more easily achieved by established professors (and financiers such as Jeremy Grantham himself) than by young scientists trying to fight their way through to the next fellowship and piece of funding. But I believe the bottom line is true. Scientists must make a stand and show their agreement. Most of us are concerned and have the data to back this up, so let’s make it clear and give people a way to understand our work and ask their questions.

By Marion Ferrat, postdoctoral researcher at Imperial College London

Carbon capture and storage (CCS) has been on the research and political agenda for some time now, but there has been a surge in media coverage recently in the European Union (EU). This is in part due to the announcement of the results of the CCS funding commercialisation competition run by the Department of Energy and Climate Change (DECC) in the UK and also the second call for European Commission (EC) NER300 proposals which was announced on 3^rd April. This, together with a peak in discussion in the EU on shale gas and climate change targets, has put CCS in the headlines again. General discussion on the development of CCS has been building for some time in conjunction with  the controversial advent of shale gas in Europe. Carbon capture and storage is often touted as something of a catch-all solution to runaway carbon emissions – so why is CCS development moving so slowly?

What is CCS and what current research is taking place?

Firstly – how does CCS work? In terms of capture at a coal power station, there are three approaches: you can either remove the CO₂ before the coal is combusted, scrub it from the exhaust gases after combustion or burn the fuel with extra oxygen so that the exhaust produced is almost CO₂ free. But it is in the CO₂ storage process that geoscience expertise is of particular significance, since geologic storage has huge potential for CO₂ sequestration.

Schematic showing both terrestrial and geological sequestration of carbon dioxide emissions from a coal-fired plant (click for larger), (Source: Wikimedia Commons).

The majority of large-scale CO₂ storage research in Europe has been carried out in the Sleipner oil and gas field off the coast of Norway (see map below), where, since 1996, a Norwegian oil company has been burying CO₂ in the depleted reservoir. Here the CO₂ is separated and then pumped into a saline aquifer in the Utsira formation – a 200-250 m thick massive sandstone. Sleipner was the world’s first commercial CO₂ storage project and to date 8-9 million tons of CO₂ has been successfully stored in the former oil and gas field, with a further capacity of up to 600 billion tons of CO₂. Ongoing monitoring has shown that there has so far been no evidence of CO₂ leakage which is promising for further development.

Location of Sleipner oil and gas field in the North Sea (modified from Wikimedia Commons)

What’s happened so far?

While sequestration research is promising, political developments have been lagging. The most recent progress was that of the shortlisting of the DECC CCS competition to 2 projects. The Shell–Peterhead gas power station project based on North Sea storage and the White Rose project in Yorkshire, involving a coal-fired power station with subsequent storage in the North Sea. This decision, made last month, has been part of a slow, convoluted process in CCS funding. The competition first began in 2011 when, in the absence of other bidders, the Longannet CCS proposal was chosen for the first CCS commercialisation project. This was subsequently scrapped in late 2011 and a call for new proposals was not announced until May 2012, the shortlisting of which was finally announced in March 2013.

In the EU, the NER300 funding programme aims to create a renewable energy and CCS demonstration project comprising the best possible projects involving all member states. The NER300 programme, so-called because it contains a provision to set aside 300 million allowances (rights to emit one tonne of carbon dioxide) , was split into the NER200 and NER100 allowances (for more on the background to NER300 see www.ner300.com). However, following the submission of 13 CCS proposals for consideration for NER200, there were no CCS projects awarded funding in the first round and instead funding was allocated to 23 renewable projects. The second round, NER100, was called on 3^rd April 2013.

Many have championed Northern Europe’s unique opportunity to push CCS development due to its home grown experience and knowledge of the North Sea oil fields, which represent a very viable location for UK- and Norway-based carbon storage, and there has been significant criticism of what is deemed to be the UK government’s slow commitment to the CCS and low carbon projects

So what’s the big hold up?

The delay in CCS development in the UK and Europe – coupled with the often disappointing and slow progress of climate change mitigation, most recently evidenced by the faltering discussions in Doha – has increased media, public and political pressure on governments to push ahead with the 2030 climate change targets, of which the advancement of CCS is a significant part.

But the delay has come about because of myriad concerns and unforeseen timing issues. From a policy perspective there has been historic concern over both the cost and environmental integrity of the capture and storage process. There is some debate as to whether the price of energy with attached CCS could become economical within a reasonable timescale, particularly as the start-up projects require a lot of capital investment. However, the cost should fall as the technology matures and economies of scale facilitate growth in this sector. Many of the issues over environmental integrity are being addressed through ongoing research, but a funded commercial-scale CCS project is an important part of the commercialisation process.

There are also some concerns that the development of CCS will act as a green light to the so-called ‘shale gas bonanza’ and will result in fossil fuel exploitation with impunity. While CCS will ease the decision to build shale gas into the energy profile, there should be some caution as to its role in the energy mix. Without a balanced combination of energy sources in the future energy profile, carbon emission targets will become impossible to meet. Additionally, the recent trend in discussing energy and water security together – from both a research and a policy perspective – has highlighted the high water consumption of CCS, which increases by 30-100% when added to a coal-fired power plant.

Slow progress on CCS has often been down to political issues such as the election of the coalition government in the UK – the two main parties of which have a frequently clashing energy agenda –  and the widespread affects of the financial crisis, which have undermined the move towards green energy in the UK and EU. DECC, which runs the CCS competition in the UK, is headed up by minsters of opposing political parties with very differing views on this issue. This political tension, together with the long term instability of ministers in the department, has led to hampered progress in energy and environment policy.

A further issue, often omitted from the debate, is the potential for an independent Scotland – which is now a very real possibility following the announcement of the Scottish independence referendum in September 2014. This raises several issues with regard to the sovereignty of the North Sea and the potential storage locations contained therein.

The expeditious development of CCS is of significant importance if climate change targets are to be met with the continued use of fossil fuels.  Both the science community and policymakers will be required to act together to improve the sustainability of CCS technologies but to also push the agenda in-line with climate change targets.

Flo Bullough

Policy Assistant at The Geological Society

I’ve been ruminating over the idea for this post for some time now; since last October in fact, when the EGU Twitter Journal Club discussed a paper about tagging (You can find the Storify for the discussion here). Not tagging as in the playground favourite, but the idea of keeping track of certain molecules in your chemical transport model, so you can follow them as they move through the atmosphere and undergo chemical transformations.

I’ve decided to offer my opinion on tagging, which I’ve come to through after much deliberation; reading, listening and discussing the topic with colleagues. I thought this might be of general interest, as the concept of tagging frequently sparks debates (in my experience) and seems to arouse stronger and more varied views than I would usually expect from a modelling technique. So with this post, I want to answer the question “what is tagging and what is it used for?” and at least attempt to answer “why does it generate such mixed feelings?”.

I think that the answer to the second may lie in the answer to the first, so let’s start with that. One way of describing tagging is as an accounting method. Doesn’t sound very geophysical? Well, we’re talking the model world here, and we can keep track of – or account for – every little thing we do in our model world. To try and understand the composition of the Earth’s atmosphere, people have constructed computer models to describe both the physical and chemical processes in the atmosphere. I’m particularly interested in trace gases like ozone, which is found in parts-per-billion quantities in the troposphere (roughly the lowest 10-15 km of the atmosphere). Tropospheric ozone is a popular species to study, as it is a greenhouse gas, it’s bad for human and plant health, and it’s one of the key oxidants in the atmosphere.

The Troposphere, the lowest and most dense part of the atmosphere (source: Wikimedia Commons, photo by Nick Juhasz).

Another interesting thing about ozone is that it’s not emitted directly. Many other pollutants and greenhouse gases, like methane or nitrogen oxides, are emitted by both natural and anthropogenic sources, but ozone is formed through photochemical reactions, which occur in the presence of both sunlight and nitrogen dioxide. So, to study the ozone in the atmosphere using a model, it needs to include emissions of relevant gases, motions in the atmosphere that move these gases around, chemical reactions that transform one gas into another, as well as other processes like deposition of certain gases to surfaces or removal in rain.

With all this going on, it can be hard to disentangle one process from another, particularly since all the different processes are interlinked. This is where tagging can come in handy as an accounting tool. Say we are interested in how much ozone is added to the atmosphere as a result of activity in a particular city – let’s call it Mega-City One. How could you find this out? Well, one quite common way is to run the model as normal, and then to repeat the simulation but with Mega-City One removed. So you take out any emissions coming from Mega-City One and see what difference it makes. This tells you what would happen if you simply removed that city.

However, you may not want to know about this unrealistic “annihilation” situation, as a city won’t simply disappear overnight. You may be more interested in your normal run (which you think best represents the real world) and what is contributing to the ozone in that run. The non-linearly minded amongst you will see the subtle difference between the two questions. If we were talking about an inert tracer, there would be no difference, as what was emitted by Mega-City One would just stay in the atmosphere unchanged, and would be directly attributable to Mega-City One. The difference with ozone is that it’s not emitted, and the chemistry that creates and destroys it can and does behave nonlinearly.

So to answer the attribution question (in my model simulation, how much ozone is a result of Mega-City One emissions?), tagging is one method that is used. The idea is that you ‘tag’ tracers that you are interested in, and follow them through the model. So you can ‘tag’ all the emissions from Mega-City One, and when one of the nitrogen dioxide molecules from this city undergoes photolysis to make an oxygen atom, which then reacts with molecular oxygen (O₂) to form ozone (O₃), you know that this ozone molecule can be attributed to Mega-City One. This is done by solving a set of equations for the tags alongside the usual chemistry scheme. This does not disturb the normal running of the model, and you will find that the total amount of ozone attributed to Mega-City One will be different from calculating the difference in ozone between your normal and your annihilation runs.

Why would you want to do either of these things anyway? Well, you might want to know what effect different cities or other sources are actually having, or would have on the atmosphere if they were built. So you’d use the annihilation method. Or, you might want to know what the biggest culprit was for particularly bad air quality in a particular place. So you’d use tagging to find out if it was Mega-City One or Mega-City Two, or if it was the road transport or the power stations that was the biggest source.

I hope I’ve achieved my first aim of answering my first question, about what tagging is and what it’s used for. The second question is not quite so straightforward, but I’ll give my thoughts on the matter: I think the key to why – to put in bluntly – some people aren’t so keen on tagging, and some people aren’t so keen on the annihilation method, stems from different notions of what tagging is really being used for. Ultimately, I think this boils down to finding ways of communicating complex ideas and their applications, without being misconstrued. Existing pre-conceptions probably also play a part, as these will (rightly or wrongly) fill the gaps when someone else’s explanation is incomplete.

Successful communication of complex ideas isn’t easy! It takes time and effort, but it really pays off in the end. Just think, how often have you heard (or taken part in) a heated discussion in which you find everyone was actually in agreement all along, they just didn’t know it yet?

By Michelle Cain, post-doc at the University of Cambridge & NERC policy placement fellow at Defra

Reference:

Grewe, V, Dahlmann, K, Matthes, S and Steinbrecht, W. (2012) Attributing ozone to NO_x emissions: Implications for climate mitigation measures. Atmospheric Environment. Vol. 59, pp 102-107.

Ocean thermal expansion, that is, the increase in water volume due to temperature alone, is relatively well understood – as is the retreat of both mountain glaciers and ice caps. While most models simulate these effectively, there is little understanding of how both the Greenland and Antarctic ice sheets will respond to climate change. This is because the full extent of ice-ocean interactions is not included in climate models – it’s no wonder when there are so many factors to consider: melting of mountain glaciers, ice caps and polar ice sheets, glacial isostatic adjustment and ocean thermal expansion to name just a few!

Mahé Perrette and his colleagues have developed a novel approach for sussing out sea level rise (SLR); combining simple models with general circulation models (GCMs) to use the benefits of both in predicting future change. To get an idea of the uncertainties associated with SLR, take a look at this graph, in which red is a highly uncertain prediction (up to 70 cm variation) and dark blue is an estimate we can be quite confident of (only 5 cm variation):

The first of the three panels combines the uncertainty for all components of SLR considered by Dr Perrette and his team – there’s really not much blue there is there?! [Source: Perrette et al., 2013].

Both the magnitude of SLR and the timescales over which it occurs varies wildly between models, but it remains clear that the effects of SLR will be felt most in the low-lying coastal regions of the world: from small island nations such as Tuvalu, which at only marginally above sea level, is a country only too aware of this threat; to the densely populated, and agriculturally important, coastal plains of Bangladesh.

Each of the contributions to SLR (meltwater from the Antarctic and Greenland Ice Sheets, and melting of mountain glaciers and icecaps) vary locally, which means that SLR will also vary from region to region. This interactive map by Perrette and his team is a great demonstration of how SLR varies throughout the world under different emissions scenarios.

Predicted sea level rise for coastal regions. The key indicates the different components contributing to SLR: MGIC = Mountain Glaciers and Ice Caps, AIS = Antarctic Ice Sheet, GIS = Greenland Ice Sheet and GIA = Glacial Isostatic Adjustment [Source: Perrette et al., 2013].

Rates of relative sea-level change [Souce: Riva et al., 2010].

Gravitational forces influence global, as well as local, water distribution. The declining mass of ice caps at the poles means there will be weaker gravitational forces acting on Arctic and Antarctic waters. The weakening of these poleward-pulling forces will cause water to be redistributed throughout the globe, resulting in greater SLR at the equator than at the poles. So, despite the large local variations in SLR, its effects will be felt most in the tropics and at the equator.

By Sara Mynott

References:

Perrette, M., Landerer, F., Riva, R., Frieler, K., and Meinshausen, M. (2013), A scaling approach to project regional sea level rise and its uncertainties, Earth Syst. Dynam., 4, 11-29, doi:10.5194/esd-4-11-2013.

Riva, R. E. M., J. L. Bamber, D. A. Lavallée, and B. Wouters (2010), Sea-level fingerprint of continental water and ice mass change from GRACE, Geophys. Res. Lett., 37, L19605, doi:10.1029/2010GL044770.

Effective responses to natural disasters require the rapid acquisition of information about where has been affected, how many people are in the affected areas and what the magnitude of the damage is. This information is critical in both disaster and emergency rescue management. Indeed, the first three days after the onset of a disaster has been dubbed the “72-hour golden rescue period”, after which the survival rate of victims sharply declines. With this in mind, the need for rapid data collection could not be more evident.

Aerial photography is a useful tool in determining which areas have been affected by an earthquake, but resolution may not always be adequate to determine the damage to buildings and infrastructure within them. For this, satellite technology provides a helping hand. For example, the spectral characteristics of a building can be used to determine whether or not it has been structurally damaged. There is, however, a time delay associated with gathering and analysing satellite data and it is ineffective for more minor quakes. More importantly though, these tools provide no indication of the number of people affected within these areas beyond the assumed population density (affected rural land is likely to have fewer people immediately at risk than in an affected urban area).

Building collapse as a result of the 1995 Hanshin-Awaji earthquake [Source: Wikimedia Commons].

This is where Dr Jing Hai Xu and his team come in, as they have developed a method of using text messages to report and disseminate disaster information and Geographic Information Systems (GIS) to analyse and extract details relevant to search and rescue teams.

The network is separated into country level, provincial level, and city level, with the smallest components being streets within a town or city. One reporter is enough to include the impact on a particular location in the disaster information network. One downside of the model, though, is that the reporters need to be formal local government employees. Whilst this measure is proposed to increase the reliability of reports, it vastly reduces the number of people that can feed into the network. Perhaps an alternative way of addressing the problem of reliability would be to only include information in the network after multiple reports of a similar incident are received from the same area. Here we are faced with new problems: what constitutes one area? Will reports of the same event from different observers be sufficiently similar to be picked up in the network? This also requires the contact details of the disaster network to be disseminated to a greater proportion of the population… perhaps Xu et al.’s approach is an effective one after all!

Now that that’s decided – how does it work? Principally, there are two kinds of nodes that help the network function: 1) edge nodes, these are the people responsible for reporting disaster information, and 2) central nodes, which correspond to the central earthquake office within each city and are responsible for collecting and disseminating information. After an earthquake, the city earthquake office (central node) contacts the reporters (edge nodes), asking for information about the impact of the disaster where they are. This information is fed back to the office and these central nodes pass the information on to the provincial offices and then on to the country’s government office so that appropriate action can be taken.

Having a simple code for different impacts helps collate useful information. In this model, the first number indicates the type of damage (e.g. 4 for damage to buildings) and the second indicates the severity (with 1 being low severity and 5 being high). So the code for a few damaged buildings would be 42, or 44 for a large quantity of damaged buildings, with some partially collapsed, etc. Here are the other codes:

Earthquake disaster information codes (click to enlarge), [modified from Xu et al., 2013].

Disaster information distribution (level of shaking) from the 2012 Yangzhou earthquake, [modified from Xu et al., 2013].

So there you have it – the key to disaster management success: send an SMS.

By Sara Mynott

Reference:

Xu, J. H., Nie, G. Z., and Xu, X.: A digital social network for rapid collection of earthquake disaster information, Nat. Hazards Earth Syst. Sci., 13, 385-394, doi:10.5194/nhess-13-385-2013, 2013

In this month’s Geoscience’s column, Alex Stubbings discusses the water scarcity problems in the Middle East and North Africa region and  the recent developments in modelling water resources here. 

The Middle East and North Africa (MENA) region is considered the most water-scarce region in the world. As such, the region faces a multitude of challenges in the 21^st century including population growth, economic development, food production and climate change. With these challenges in mind, a team of researchers led by hydrologist Dr. Peter Droogers explored how “Water resources trends in the Middle East and North Africa towards 2050” will change over the first half of the 21^st century. The study is published in EGU’s Open Access journal Hydrology and Earth System Sciences.

Presently, there exist huge spatial variations in water allocation, and the region as a whole is the driest and most water scarce region in the world. This is increasingly affecting the social and economic development of the region.  For example, the average water resource availability per capita is only marginally above the physical water availability of 1076 m³yr^-1, compared to the world average of 8500 m³yr^-1.

The prevailing arid conditions found within the area mean that over 85% of the MENA region can be considered desert. It follows that the region can be further subdivided into three distinct climate spaces: the Maghreb region, which constitutes North African countries with a Mediterranean climate, and is climatically heterogeneous; the Gulf Cooperation Countries located within the Middle East, and have a typical desert climate; and lastly, the Mashreq region, which includes countries that have a milder and wetter climate, such as Iraq and Syria.

The Middle East and North Africa (MENA) region (blue), (Source: Wikimedia Commons).

Therefore the lead question Droogers et al. focused on filling vital knowledge gaps. Indeed, they highlight that “a complete analysis on water demand and water shortage over the coming 50 year period based on a combined use of hydrological and water resource models, remote sensing and socio-economic changes has never been undertaken for the MENA region”. Moreover, they intend to achieve this by assessing water demand in the 22 MENA countries by taking into account the dynamics and uncertainties of climate change, demographic changes and economic development.

The team used two distinct models that covered a 50 year time period (2000–2050). Firstly, the PCR-GLOBWB (PC Raster Global Water Balance) hydrological model was run to determine the internal and external renewable water resources for present and future climate. And the second model employed was a water allocation model, referred to as the MENA Water Outlook Framework (MENA-WOF). This was chosen to analyse the linkage between renewable water resources and sectoral water demands, and utilises the Water Evaluation and Planning (WEAP) framework.

This approach allowed the research team to simulate the average hydrological conditions with great accuracy – best demonstrated by its ability to accurately model and replicate actual flows on the Blue Nile, White Nile and Atbora tributaries. The team singled this out as a key indicator of its robustness. They noted that other similar studies, to date, have yet to model these flow regimes accurately.

Long-term average annual observed and simulated flow (Source: Droogers et al., 2012).

Nevertheless, as with other empirical modelling studies the authors issue a caveat: that the results regarding water resources, derived through GCM output, should be interpreted with great care. The model predicts total water shortage will increase by 157 km³yr^-1, while water supply and demand are only projected to increase by 132 km³yr^-1.  In short, the overall trend is that all MENA region countries will see an increase in water shortages, as the increase in supply will not meet the growth in demand, except for Djibouti.

Droogers et al. naturally consider the contribution of climate change to water scarcity. Their results indicate that only 10% of the change in water demand will be attributed to climate change and the rest entirely due to socio-economic changes (under their average climate change scenario). Furthermore in the other two scenarios, wet and dry, socio-economic factors, again, are more important than the effects of climate change. However, they emphasise that despite the small contribution made by climate change its effects should still be taken into consideration when planning adaptation interventions.

The contribution of socio-economic changes and climate changes on total water demand in 2050 (Source: Droogers et al., 2012).

The findings presented here by Droogers et al. are unique. They have combined different data, models and tools in order to forecast changes in water demand and supply over a geographically diverse area. Despite this novel approach, a clear drawback of the study, recognised by the team, is that the spatial resolution is lower than the output for smaller geographical areas and utilising a single methodological approach would have allowed more in depth comparisons to be made between countries.

When looking at the wider landscape of climate change impacts and adaptation strategies the team refer to a World Bank study from 2010, which estimated the cost of adaptation for developing counties at 0.12% of GDP, with costs associated with adaptation increasing linearly with time. The authors offer a number of pragmatic solutions, which fall under the umbrella of ecological modernisation, highlighting the potential of desalination plants.

As a work in progress, Droogers and his team offer direction for future work. Firstly, they suggest that further research should be carried out at a higher spatial resolution, for instance, employing the same methodology but focusing on individual countries rather than on an entire region. And secondly, of the need to analyse potential adaptation strategies and the associated costs of implementing them within the region. Both directions have their merits, but with the uncertain nature of climate change makes it difficult to distinguish which step we should take next.

By Alex Stubbings

In this month’s Geoscience’s column, Sara Mynott discusses the geological hazards associated with climate warming and how recent research sheds new light on our understanding of rockfall frequency.

Rockfalls are the free-falling movement of bedrock material from a rock face, a phenomenon also encompassed by the terms ‘landslide’, ‘rockslide’ and ‘rock avalanche’. They range from small debris falls of only a few cubic-metres to large ‘bergsturz’ events of over 1 million metres-cubed. The number of rockfalls reported has increased in recent years and is often attributed to global warming, despite the lack of research in this area. The debate among scientists regarding the effect of climate change on geomorphic hazards has led to a lot of confusion among the media and hence, the public.

Climate change is expected to have numerous consequences for natural hazards and the IPCC has predicted that geomorphic hazards will increase in alpine regions as a result. However, recent research published in Natural Hazards and Earth Systems Science suggests that this may not be the case. In a recent assessment of Austrian rockfalls over the period 1990-2010, Oliver Sass and Manfred Oberlechner investigated how temperature influences their frequency. Their dataset was compiled from events that were large enough to be recorded in the media, restricting it to events that have the capacity to affect people and/or infrastructure. The Huben rockslide that occurred in 1999, which resulted in both the loss of alpine road access and the destruction of a local sawmill, presents one such example.

Rockfall in Huben, Austria, that occurred on 11 March 1999, far below the permafrost limit. This rockfall resulted in both the destruction of a sawmill and loss of road access (Source: Sass and Oberlechner, 2012).

Historical records of rockfalls are scarce, making predictions for the future a challenge and, until recently, little research on the temporal frequency of rockfall events had been carried out. This is partly due to the research focus on areas of permafrost, which cover less than 4 % of the Austrian Alps. Consequently, the relationship between surface temperature and rockslide frequency in permafrost regions is well-known. Permafrost, which exists at sub-zero temperatures, cements sediment together and gives it stability. Unsurprisingly, warming causes permafrost to degrade, leading to a loss of sediment stability and an increased risk of geomorphic hazards. The likelihood of these hazards occurring is a function of substrate type. However, areas of public interest (those with infrastructure) tend to be permafrost-free. In fact, 91% of the events studied were below the permafrost limit (less than 2100 m elevation).

Contrary to the IPCC’s predictions, the study found that there was no relationship between temperature and the number of rockfall events below the permafrost limit, nor was there any correlation between precipitation and rockfall frequency. The increasing settlements and infrastructure within the Alps means there is a greater risk of a geomorphic hazard occurring and the increase in availability of information means there appears to be more events than 20 years ago. Thus, the apparent increase in rockfall occurrence in recent years is likely to be due to a reporting bias.

Whilst there is no evidence for warming increasing the annual number of rockfalls, changes in seasonal weather patterns have resulted in a shift in their occurrence throughout the year. Rockfalls are generally more common in spring than at any other time of year as both the increase in water supply (through snowmelt and high precipitation rates) and high degree of freeze-thaw activity (also known as cryoturbation) destabilises the sediment. However, in recent decades, a greater proportion of rockfalls have occurred during the summer months, leading to a more even distribution of these hazards throughout the year.

Below the permafrost limit there is insufficient evidence to support the notion that increasing rockfall events are associated with climate warming. In fact, the study reveals that milder winters may even reduce the number of rockfalls outside areas of permafrost. Whilst Sass emphasises that these results are preliminary, they highlight the complexity of predicting the impacts of climate change and expose an alternative way in which it can affect hazardous earth processes.

By Sara Mynott, EGU Communications Officer

A French and Algerian study team seeks markers of underwater earthquakes off the Algerian coast. The team also matched the site’s paleoseismic history to land-based historical reports. Wayne Deeker reports.

The Mediterranean Sea represents the boundary between the African and Eurasian plates. Yet the fault segment off the Algerian coast is one of the most active in the western Mediterranean. It is associated with a series of moderate to large earthquakes: about 22 magnitude 6+ events since 856 CE. According to historical records, very large events in Algeria have been rare, though approximately one third of documented earthquakes would have been Mw 7+.

One of the most destructive was also the most recent. In May 2003, the Algerian coast experienced a Mw 6.8 earthquake, centred on the town of Boumerdès. It killed more than 2,300 people, injured some 10,000, and did all the usual structural damage earthquakes do in such countries. It also caused a tsunami which affected the western Mediterranean.

Building damage in the city of Boumerdes, Algeria (Credit: Ali Nour CGS; National Center of Applied Research in Earthquake Engineering)

The authors of a 2012 study published in EGU’s Open Access journal Natural Hazards and Earth System Sciences wanted to understand more about this event and earthquake recurrence intervals in the area. They found interesting clues deep underwater, where the quake likely caused landslides that resulted in almost 30 breaks of submarine telecommunications cables.

The researchers say it is especially worthwhile to investigate earthquake threats in areas that, like those surrounding the Algerian fault, have irregular, long-recurrence patterns because people there will be less prepared than where earthquakes are frequent. Another good reason motivates this research. While 2003 was a very well documented earthquake, most studies of its impact were conducted on land, with little attention paid to the effects and signatures offshore. This is unsurprising, as submarine earthquakes are difficult to monitor in real time, especially during catastrophic events. Therefore, the seafloor signatures of such events have remained elusive because they are occasional, erosive, and are a complex combination of many processes.

The damage to Algerian submarine telecommunications cables provides a clue to what happened underwater in 2003. While cable breaks often denote a definite time and place, pinpointing an event which can be interpreted in context with the landscape, the 2003 breaks were vague in all but one case. The location of the recovered cables also did not correspond to the point of damage, which suggests erosive action of turbidity currents (streams of rapidly moving sediment-rich water that deposit to form so-called turdibite sedimentary beds). Satellite images confirmed this, yet the flow pattern must have been quite complex, apparently following different paths along the underwater scarp system.

Resolving this complexity is challenging and, to do it, the researchers focused partly on seafloor morphology, in particular on the signs of seafloor rupture and instability, such as submarine landslides. Once the researchers started looking, they found the scarps had been affected by numerous landslides. The research team also found evidence of significant sediment transport, confined between salt domes and scarp walls. Sonar images showed signatures of high-energy events: ditches formed by erosion, indicating flow direction, plus perpendicular structures interpreted as pebble or gravel waves. These features probably constitute the sought-after signs of undersea earthquake activity, which can now be matched to other sites.

Direct sediment sampling compliments the scans. At the foot of the scarp slopes, the sediments are too mixed up to reveal any bedding that might be dated. Further out, this is not the case, and the presence of  turbidite beds alternating with another type of sedimentary deposit allows for some cautious dating of those layers. Preliminary results, from layers within the upper 1.5m of the core, show at least eleven turbidites accumulated during the Holocene, giving an average recurrence interval of about 800 years in this area. This matches the main seismic cycle on land, supporting the view that large earthquakes in Algeria are the main responsible for the large turbidity flows.

The authors concluded that the 2003 cable breaks were, for the most part, caused by the passage of a turbidity current triggered by the earthquake. The likely path of currents depends on the roughness and the irregularities of the sea floor: seafloor scarps in some cases deflect turbidity flow paths, while perched basins may trap them. The scarps seem prone to sediment failure, and are potential additional sources of cable breaks.

By Wayne Deeker, freelance science writer