Table of contents

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC; Christensen et al 2007) has, with greater confidence than previous reports, warned the international community that the increase in anthropogenic greenhouse gases emissions will result in global climate change. One of the most direct and threatening impacts it may have on human societies is the potential consequences on global crop production. Indeed agriculture is considered as the most weather-dependent of all human activities (Hansen 2002) since climate is a primary determinant for agricultural productivity. The potential impact of climate change on crop productivity is an additional strain on the global food system which is already facing the difficult challenge of increasing food production to feed a projected 9 billion people by 2050 with changing consumption patterns and growing scarcity of water and land (Beddington 2010). In some regions such as Sub-Saharan Africa or South Asia that are already food insecure and where most of the population increase and economic development will take place, climate change could be the additional stress that pushes systems over the edge. A striking example, if needed, is the work from Collomb (1999) which estimates that by 2050 food needs will more than quintuple in Africa and more than double in Asia. Better knowledge of climate change impacts on crop productivity in those vulnerable regions is crucial to inform policies and to support adaptation strategies that may counteract the adverse effects.

Although there is a growing literature on the impact of climate change on crop productivity in tropical regions, it is difficult to provide a consistent assessment of future yield changes because of large uncertainties in regional climate change projections, in the response of crops to environmental change (rainfall, temperature, CO₂ concentration), in the coupling between climate models and crop productivity functions, and in the adaptation of agricultural systems to progressive climate change (Roudier et al 2011, Challinor et al 2007). These uncertainties result in a large spread of crop yield projections indicating a low confidence in future yield projections.

A recent study by Knox et al (2012) is among the first to provide robust evidence of how climate change will impact productivity of major crops in Africa and South Asia. Using a meta-analysis, which is widely used in epidemiology and medicine and consists in comparing and combining results from different independent published studies, Knox et al (2012) show a consistent yield loss by the 2050s of major crops (wheat, maize, sorghum and millet) in both regions. This systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies nicely extend previous works by Müller et al (2011) and Roudier et al (2011), confirming the threat of negative climate change impacts in Africa but also in South Asia. Knox et al (2012) estimate that mean yield change for all crops is -8% by the 2050s with strong variations among crops and regions. For instance evidence of yield reduction up to -40% are detected for some regions of Africa while no mean yield change is detected for rice in India. Variations in crop yield projections decrease when considering a large number of climate models confirming the relevance of the expanded use of multi-model ensembles of projections of future climate change adopted in the IPCC Fourth Assessment Report. Conversely, variations in crop yield projections increase with the crop model complexity especially when using process-based crop models over statistical models. Such differences in crop yield variations may be attributed either to the structural differences between crop model approaches or to the spatial scale differences; biophysical crop models operating at finer spatial scales and thus reproducing the higher variability of impacts at these scales.

Such robust evidence of future yield change in Africa and South Asia can be surprising in regards to the diverging projections in a warmer climate of summer monsoon rainfall, the primary driver for rainfed crop productivity in the region, especially in West Africa where some studies make projections of wetter conditions and some predict more frequent droughts (Druyan 2011). This is because of the adverse role of higher temperatures in shortening the crop cycle duration and increasing evapotranspiration demand and thus reducing crop yields, irrespective of rainfall changes (Berg et al 2012, Roudier et al 2011, Schlenker and Lobell 2010). Potential wetter conditions or elevated CO₂ concentrations hardly counteract the adverse effect of higher temperatures.

Although such systematic reviews and meta-analyses conducted by Knox et al (2012), Müller et al (2011) or Roudier et al (2011) can provide important insights about sign, magnitude and uncertainty of climate change impacts, direct comparison among studies suffers from inevitable limitations. In particular the diversity of the studies selected for the meta-analysis, encompassing a range of different countries, scales, crops and methods (climate models and scenarios, crop models, downscaling technique), makes it difficult to aggregate crop yield projections to provide a consistent and precise impact assessment. A rigorous multi-ensembles approach, with varying climate models, emissions scenarios, crop models, and downscaling techniques, as recommended by Challinor et al (2007), would enable a move towards a more complete sampling of uncertainty in crop yield projections. In that sense, coordinated modeling experiments such as the ones conducted throughout the Agricultural Model Intercomparison and Improvement Project (AgMIP; www.agmip.org/) are likely to improve substantially the characterization of the threat of crop yield losses and food insecurity due to climate change.

In spite of the threat of crop yield losses in a warmer climate, it is important to keep in mind, as discussed by Berg et al (2012), that developing countries in the tropics have the potential to more than offset such adverse impacts by implementing more intensive agricultural practices and adapting agriculture to climate and environmental change. Indeed Africa and in a lesser extend South Asia are among the only regions of the world where there is an untapped potential for raising agricultural productivity since poor soil fertility and low input levels, combined with extensive agricultural practices, contribute to a large gap between actual and potential yields (Licker et al 2010).

References

Beddington J 2010 Food security: contributions from science to a new and greener revolution Phil. Trans. R. Soc. B365 61–71

Berg A, de Noblet-Ducoudré N, Sultan B, Lengaigne N and Guimberteau M 2012 Projections of climate change impacts on potential crop productivity over tropical regions Agric. For. Meteorol. at press (doi:10.1016/j.agrformet.2011.12.003)

Challinor A, Wheeler T, Garforth C, Craufurd P and Kassam A 2007 Assessing the vulnerability of food crop systems in Africa to climate change Clim. Change83 381–99

Christensen J H et al 2007 Regional climate projections Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon, D Qin, M Manning, Z Chen, M Marquis, K B Averyt, M Tignor and H L Miller (Cambridge: Cambridge University Press)

Collomb P 1999 A narrow road to food security from now to 2050 FAO Economica (Paris: FAO)

Druyan L M 2011 Studies of 21st-century precipitation trends over West Africa Int. J. Climatol.31 1415–572

Hansen J W 2002 Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges Agric. Syst.74 309–30

Knox J, Hess T, Daccache A and Wheeler T 2012 Climate change impacts on crop productivity in Africa and South Asia Environ. Res. Lett.7 034032

Licker R, Johnston M, Foley J A, Barford C, Kucharik C J, Monfreda C and Ramankutty N 2010 Mind the gap: how do climate and agricultural management explain the 'yield gap' of croplands around the world? Glob. Ecol. Biogeogr.19 769–82

Müller C, Cramer W, Hare W L and Lotze-Campen H 2011 Climate change risks for African agriculture Proc. Natl Acad. Sci. USA108 4313–5

Roudier P, Sultan S, Quirion P and Berg A 2011 The impact of future climate change on West African crop yields: what does the recent literature say? Glob. Environ. Change21 1073–83

Schlenker W and Lobell D 2010 Robust negative impacts of climate change on African agriculture Environ. Res. Lett.5 014010

Goelzer et al (2012) paint a portentous picture of what is likely to happen to the global sea-level over the next 1000 years. This worrying assessment is based on our current best understanding of how the world's giant ice sheets of Greenland and Antarctica, as well as a quarter of a million smaller glacial ice masses, and the ocean collectively respond to ongoing climate change. Theirs is a state of the science study that integrates these key contributors of sea-level change based on the latest models and current understanding, and an integrated Earth systems modelling approach termed LOVECLIM. As they point out in their study, only a handful of global climate models to date—i.e. models that are used to make predictions of future climate change—incorporate dynamically (fully) coupled ice-sheet models.

According to the scenarios presented by Goelzer et al (2012), we could see between 2.1 and 6.8 m of global sea-level rise by 3000 AD, compared with 'just' 1.1 m if the atmosphere is stabilised at 2000 CO₂ levels. Much, up to some 4 m, of this contribution comes from increased melting and mass loss of the Greenland ice sheet, which is several times more sensitive than the Antarctic ice sheet to warming temperatures in these simulations. Interestingly, dynamical ice mass losses through iceberg calving become increasingly less significant for Greenland as the ice sheet retreats further inland during the 1000 yr runs (Sole et al 2008). The latest modelling studies show that around a half, perhaps more, of the recent Greenland mass losses (Barletta et al 2012, Rignot et al 2011) are already through increased melt and runoff (Hanna et al 2008, 2012, van den Broeke et al 2009); note also the recent (summer 2012) record surface melting of the Greenland ice sheet (Nghiem et al 2012) caused by atmospheric forcing (Overland et al 2012) and the potential of such events to impact on ice flow (Bartholomew et al 2011). By contrast, the greatest sea-level rise reported for Antarctica by 3000 AD is no more than 94 cm; Antarctica remains relatively insensitive for future sea-level rise given a temperature increase of no more than 5–6 °C (quite a lot) above present levels. Oceanic thermal expansion and, especially, glacier melt seem very much second-order effects, compared with the Greenland sea-level contribution, for the next millennium.

As expected, there are considerable differences between the outcomes of the model experiments depending on the time and level at which greenhouse gas emissions are stabilised. I am not quite sure why they 'prefer' the model version which reaches stabilisation at 2000 greenhouse gas levels since those levels have since been significantly exceeded and show no signs of tailing off yet—quite the reverse. According to the famous Keeling et al dataset from Mauna Loa in Hawaii, atmospheric CO₂ levels at about 369 parts per million by volume of the global atmosphere in 2000 have since risen to about 392 ppmv in 2012, and this increase shows no signs of abating. Realistically, it's going to be at least another decade or two (or longer) before we can effectively even begin to stabilise atmospheric greenhouse gas levels, assuming the political will is there: which at the moment it is not. Of course this does not commit us to the other three more extreme experimental results (from greenhouse gas stabilization at 2100) reported in the study but we are heading dangerously in that direction. In effect the simulations are sensitivity studies, which may be largely unrealistic but are still useful as a kind of guide to what might happen under future climate change.

Naturally, many uncertainties remain, especially concerning how ice-sheet motion ('dynamics') is represented in the models (e.g. the absence of so-called 'higher order physics' including longitudinal (push–pull) stresses which can rapidly transfer peripheral ice velocity perturbations inland (Price et al 2011)). Furthermore, the atmospheric model used in LOVECLIM is very coarse at 5.625° latitude/longitude resolution. There appears to be a cancelling out of errors in LOVECLIM, where its climate sensitivity seems quite low (in comparison with other models) but the simulated enhanced high-latitude warming—often termed Arctic amplification and evident in observed climate data for the last 30 years—is quite high. It would be good to include precipitation as well as temperature changes when modelling the future response of glaciers, even though the former is likely to be less important. I do not agree that uncertainties in climate sensitivity can be adequately accounted for by varying boundary and initial conditions in ensembles of models, as all of the model simulations may be systematically biased due to some physical effect that is improperly considered—or unrepresented—by all of the models, but this is a widely used technique and probably the best that can be done here.

Despite these caveats, Goelzer et al 's (2012) results will undoubtedly prove useful for the Intergovernmental Panel on Climate Change (IPCC)'s upcoming Fifth Assessment Report due to be released in 2014. The key challenge remains to further improve the individual components of the Earth system model, especially those concerning ice-sheet dynamics.

Acknowledgments

EH thanks Ben Brock, Amy Jowett and Andrew Sole for useful editorial suggestions to the text.

References

Barletta V R, Sørensen L S and Forsberg R 2012 Variability of mass changes at basin scale for Greenland and Antarctica Cryosp. Discuss.6 3397–446

Bartholomew I, Nienow P, Sole A, Mair D, Cowton T and King M A 2011 Seasonal variations in Greenland ice sheet motion: inland extent and behaviour at higher elevations Earth Planet. Sci. Lett.307 271–8

Goelzer H, Huybrechts P, Raper S C B, Loutre M -F, Goosse H and Fichefet T 2012 Millennial total sea-level commitments projected with the Earth system model of intermediate complexity LOVECLIM Environ. Res. Lett.7 045401

Hanna E, Huybrechts P, Steffen K, Cappelen J, Huff R, Shuman C, Irvine-Fynn T, Wise S and Griffiths M 2008 Increased runoff from melt from the Greenland ice sheet: a response to global warming J. Clim.21 331–41

Hanna E, Jones J M, Cappelen J, Mernild S H, Wood L, Steffen K and Huybrechts P 2012 The influence of North Atlantic atmospheric and oceanic forcing effects on 1900–2010 Greenland summer climate and ice melt/runoff Int. J. Climatol. at press (doi:10.1002/joc.3475)

Nghiem S V, Hall D K, Mote T L, Tedesco M, Albert M R, Keegan K, Shuman C A A, DiGirolamo N E and Neumann G 2012 The extreme melt across the Greenland ice sheet in 2012 Geophys. Res. Lett. at press (doi:10.1029/2012GL053611)

Overland J E, Francis J, Hanna E and Wang M 2012 The recent shift in early summer Arctic atmospheric circulation Geophys. Res. Lett.39 L19804

Price S F, Payne A J, Howat I M and Smith B E 2011 Committed sea-level rise for the next century from Greenland ice sheet dynamics during the past decade Proc. Natl Acad. Sci.108 8978–83

Rignot E, Velicogna I, van den Broeke M R, Monaghan A and Lenaerts J 2011 Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise Geophys. Res. Lett.38 L05503

Sole A, Payne T, Bamber J, Nienow P and Krabill W 2008 Testing hypotheses of the cause of peripheral thinning of the Greenland ice sheet: is land-terminating ice thinning at anomalously high rates? Cryosphere2 205–18

van den Broeke M, Bamber J, Ettema J, Rignot E, Schrama E, van de Berg W, van Meijgaard E, Velicogna I and Wouters B 2009 Partitioning recent Greenland mass loss Science326 984–6

How can we build a reliable and affordable energy supply based on renewables? How rapidly do we need to cut greenhouse gas emissions to keep climate change within manageable bounds? What does it take to maintain a stable common currency of different nations?

These are just a few examples of questions that are critical for our future and that require an understanding of complex systems—the energy system, the climate system, the financial system. Finding sound answers to these questions requires sophisticated scientific analysis and expert knowledge; a lay person's intuition will clearly not suffice. Yet, decisions in a democracy are (and should be!) taken by politicians and the voting public who are not usually scientific experts. Hence the well-being of our societies—and even more so the living conditions of future generations, which are defined by the decisions we take today—depends on the wider public being well informed about the state of scientific knowledge and discourse.

The media are the most important means by which lay people obtain their information about science. Good science journalism is therefore a decisive factor for the long-term success of modern society. Good science journalism clearly must be critical journalism, and it requires journalists who know what is what, who can put things into a perspective, and who are able to make well-informed judgements. After all, the role of science journalism is not simply to act as a 'translator' who conveys the findings of scientists in a language understandable to lay people. Rather, good science journalism will provide the public with a realistic impression of what is well established in science and what are current 'hot topics', uncertainties and controversies. It will also discuss the methods and social context of the scientific endeavour.

There is ample evidence that in the area of climate science, journalism too often is failing to deliver this realistic picture to its audience, despite many good science journalists. Perhaps this can be most clearly seen from the end result: does the public have a realistic understanding of climate science? Data from the world's prime science nation, the US, suggest not.

To give just one striking example, a representative poll conducted by Yale and George Mason Universities (Leiserowitz et al 2011) in 2011 asked the US public what percentage of climate scientists think that global warming is happening. The true answer is a number well above 95%, as surveys of climate scientists or the scientific literature show (Anderegg et al 2010, Doran and Kendall Zimmerman 2009, Oreskes 2004), fully consistent with my own direct experience of working in the climate science community over the past twenty years. But only a small minority (13%) of the survey respondents picked the correct category (81–100%). The largest group of respondents (24%) chose the category 41–60%, i.e. they erroneously thought there are two roughly equal camps in climate science—and this despite the question not even being about the anthropogenic contribution to global warming, but only about the measured fact that global climate is warming! That shows that the general public, at least in the US, has no idea of the very broad consensus that exists in the scientific community about fundamental aspects of climate change.

How can such a vast misconception of what is controversial and what is well-established in climate science come about? Important evidence is provided by the analyses of media articles on climate change in six countries just published by James Painter, a BBC journalist for many years, and Teresa Ashe from the University of London (Painter and Ashe 2012).

Painter and Ashe analysed climate articles in quality newspapers in the USA, Brazil, China, France, India and the UK over two periods in 2007 and 2009/2010. They find that the voices of 'climate sceptics' are particularly present in the US and the UK, namely in one third and one fifth of the examined articles (respectively) during the latter time period. The US and the UK also were the only of the six countries where 'type 1' sceptics (Rahmstorf 2004)—those that deny even the existence of global warming—got a significant media airing. The 'sceptical voices' are particularly prevalent in right-leaning papers.

What could be wrong about airing sceptical voices? In principle that is one of the strengths of free societies, of course, but in my view two problems can arise. Problem one occurs if the overall balance is so skewed that the public is given a seriously false impression of the scientific discourse: a phenomenon known as 'balance as bias' (Boykoff and Boykoff 2004). Media tend to balance statements with opposing views, which is fine with matters of opinion. But this tendency to 'quote the other side' then gives the public the erroneous concept of there being 'two equal camps' in science, as the poll cited above shows. The late Steven Schneider, one of the great communicators of climate science, used to say that this is as if with each report of a satellite launch, someone from the Flat Earth Society was quoted for balance.

Problem number two arises if the facts are outright wrong. To give one example, the British TV documentary 'The Great Global Warming Swindle' claimed that volcanoes emit more carbon dioxide than human activities, in a bizarre brew with many other falsehoods, deceptive graphs and fabricated data. A representative of Channel 4, where the documentary was first broadcast, justified this by stating: 'this is a controversial film but we feel that it is important that all sides of the debate are aired' (Wikipedia 2012). Again the false impression of a 'debate' was promoted about issues where none exists, instead of shedding light on the real controversies which of course can be found in climate science just like in any other field of research. But how is the viewer to know, e.g., that in reality anthropogenic CO₂ emissions are a hundred times greater than volcanic ones (Gerlach 2011)? How ethical is it to present false claims as 'other side of the debate'? I suspect that in a TV documentary about history, a similarly cavalier attitude about well-documented facts would be unthinkable.

Even some high-quality media are affected by the atmosphere created by the aggressive lobbying activity of 'climate sceptics' interest groups. Some time ago, an otherwise excellent article on sea level rise in a US newspaper cited a 'climate sceptic' falsely claiming that the current sea level rise had been on-going since the end of the last Ice Age. I asked the author, a good environment reporter, why she included this false claim by a scientist who is not noted for any research on sea level. She responded that in the US, she cannot publish articles on climate change without citing a 'sceptic', even though she knew well the statement was wrong.

You would not find newspapers that routinely seek commentary on soccer tactics from a golfer or tennis player who claims that everything that the successful soccer practitioners say is wrong. Or newspapers that would print the views on the latest heart transplantation techniques by a dentist who muddles even simple verifiable facts on the matter. In climate reporting, though, such things are commonplace. Yet it has never been easier to find out who the successful practitioners of science, i.e. the genuine experts, in a given research field are, thanks to the online scientific publication and citation databases.

Of course, as in every science, many issues are legitimately debated amongst climate scientists. But these real controversies are quite different from the fake controversies about global warming pushed into the media by various ill-informed lay people, pseudo-experts and hardboiled interest groups. Far too few journalists have bothered to investigate and describe the activities of such interest groups, like the Heartland Institute in the US, which in a bill-board campaign earlier this year likened those who accept the facts of global warming to mass murderers (Hickman 2012). Yet the public also needs to understand the background story about where the 'climate sceptics' claims originate and who finances their dissemination.

Let us hope that the study by Painter and Ashe will help to initiate a critical discussion on climate science coverage in the media, particularly in 'Anglo-Saxon' countries, and help to improve it in future. There are so many science journalists out there who work hard every day, striving for quality under most difficult working conditions. Their efforts should not be in vain.

References

Anderegg W R L et al 2010 Expert credibility in climate change Proc. Natl Acad. Sci. USA107 12107–9

Boykoff M T and Boykoff J M 2004 Balance as bias: global warming and the US prestige press Glob. Environ. Change—Human Policy Dimen.14 125–36

Doran P and Kendall Zimmerman M 2009 Examining the scientific consensus on climate change EOS Trans. Am. Geophys. Union90 22

Gerlach T 2011 Volcanic versus anthropogenic carbon dioxide EOS Trans. Am. Geophys. Union92 201–8

Hickman L 2012 Heartland Institute compares belief in global warming to mass murder Guardian (www.guardian.co.uk/environment/blog/2012/may/04/heartland-institute-global-warming-murder)

Leiserowitz A et al 2011 Global Warming's Six Americas, May 2011 (New Haven, CT: Yale University and George Mason University) p 57(http:/environment.yale.edu/climate/files/SixAmericasMay2011.pdf)

Oreskes N 2004 Beyond the ivory tower—the scientific consensus on climate change Science306 1686

Painter J and Ashe T 2012 Cross-national comparison of the presence of climate scepticism in the print media in six countries, 2007–10 Environ. Res. Lett.7 044005

Rahmstorf S 2004 The climate skeptics Weather Catastrophes and Climate Change—Is There Still Hope for Us? ed Re Munich (Munich: Munich Re) pp 76–83

Wikipedia 2012 The Great Global Warming Swindle  (http://en.wikipedia.org/wiki/The_Great_Global_Warming_Swindle, accessed 17 October 2012)

The scenarios of the IPCC Special Report on Emissions Scenarios (SRES) (Nakicenovic and Swart 2000) are both widely cited and widely criticized. This combination of censure and regard reflects their importance, as they provide both a point of reference and a point of departure for those wishing to understand the long-term implications of policies and human activities for the climate and adaptive capacity. The paper by Schweizer and Kriegler in this issue (Schweizer and Kriegler 2012) reports a unique and interesting critique of the SRES scenarios. The authors find several results, including that the path the world may now be on (labeled by them 'coal-powered growth') is under-represented in the SRES scenarios. While such post-hoc critiques are easy to dismiss, Schweizer and Kriegler were careful to use only the information available to the SRES authors, and they applied a technique that (if it had been available) could have been carried out at that time. In this way they demonstrate that not only was coal-powered growth a clearly discernible possible future at the time of the SRES, but variants on the theme dominate the handful of highly consistent and robust scenarios as identified by their method. Their paper is well-timed because a new round of climate scenarios is now under development (Kriegler et al 2012, van Vuuren et al 2012), and it could learn from evaluations of the SRES process and scenarios.

Schweizer and Kriegler (2012) construct a consistent scenario logic using a relatively new foresight technique, cross-impact balances (CIB) (Weimer-Jehle 2006). As explained above, to sharpen their critique and properly evaluate the method, they apply CIB to the information that the authors of the SRES had at their disposal at the time they constructed their scenarios. Their study is therefore anachronistic, in that the CIB method was not published when the SRES was released, but historically faithful in that Schweizer and Kriegler limit themselves to the information available at that time, based on statements that appear in the SRES itself. The CIB method is a technique for constructing internally consistent qualitative scenarios. Global-scale scenario exercises, in particular climate scenarios, typically include both qualitative (narrative) and quantitative (model) elements. As noted by Schweizer and Kriegler, the dominant method for such studies, which Alcamo (2001, 2008) formalized and named the 'story and simulation' (SAS) approach, relies at least in part on quantitative modeling to ensure consistency. Schweizer and Kriegler rightly criticize the idea that models alone can ensure consistency of a scenario narrative. By itself, this critique is not new. Indeed, if asked, both Alcamo and Raskin et al  (Raskin et al 2005), whom Schweizer and Kriegler (2012) cite, would probably agree with them; both sources emphasize the need for qualitative storylines that go beyond what models can provide. However, Schweizer and Kriegler correctly point out that these sources provide little or no guidance to those responsible for the narratives beyond a dialog with the model outputs. The CIB method addresses this problem, and Schweizer and Kriegler's application of the method shows that even the best narrative-writing teams can benefit from this guidance.

While the paper of Schweizer and Kriegler makes a compelling argument for using CIB in global scenarios, it should be used in combination with other methods. A scenario exercise has several aims, of which consistency is one. Another important goal is diversity: given a set of internally consistent scenarios, a diverse set covers the space of possibilities, and thereby helps users of the scenarios avoid underestimating or overestimating the potential for change in one or another key factor (e.g., see (Carlsen 2009)). From this point of view, the SRES authors could legitimately respond to Schweizer and Kriegler's finding that the SRES scenarios excluded interesting variants on coal-fueled growth by arguing that they did include some variants, and to include more would have conflicted with a legitimate goal of breadth. In this imagined dialog, Schweizer and Kriegler could concede the point, but then point out that several of the SRES scenarios were revealed to be either marginally or very inconsistent by their exercise. Thus, CIB and a technique that helps ensure breadth can usefully complement one another.

The CIB method is also liable to a form of specification error, in that the worldviews of the people filling in the cross-impact table influence the results. This is a problem with many foresight techniques, but it is masked by the formalism of CIB, and there is a danger it will go unnoticed. For example, Schweizer and Kriegler's paper suggests that the A1T2 scenario is (marginally) internally consistent. It has relatively low carbon emissions, low rates of population growth, very high GDP per capita growth rates, low primary energy intensity, very low carbon intensity, high fossil-fuel availability, global economic policy focus, and mixed global and regional energy policy focus. It has been argued by Jackson (2009) and Victor (2008), among others, that the evidence is slim that we ever will decouple carbon emissions from GDP to any meaningful extent. Thus, they would presumably argue that this is an inconsistent scenario, and might very well have done so at the time the SRES was written. That is not by itself a reason to reject the scenario, but it suggests that a CIB exercise could be run assuming the qualitative models implied by different worldviews, and the results contrasted. Such an exercise would go beyond the sensitivity analysis that Schweizer and Kriegler report in their paper.

The cross-impact balance method should be a useful tool for constructing the next round of climate scenarios. It will be even more useful if combined with techniques that ensure a diversity of scenarios. This could include formal techniques such as 'scenario diversity analysis', which maximizes a quantitative measure of the spread of a set of qualitative scenarios defined by states of driving forces (Carlsen 2009). It could also include a survey of different worldviews, and the qualitative models that they imply, such as that carried out by Sunderlin (Sunderlin 2003). Futures studies has moved forward from the time the SRES was published, and new techniques are now available that can help us to tell better stories of the future.

References

Alcamo J 2001 Scenarios as Tools for International Environmental Assessments (Cophenhagen: European Environment Agency)

Alcamo J 2008 The SAS approach: combining qualitative and quantitative knowledge in environmental scenarios Environmental Futures—The Practice of Environmental Scenario Analysis vol 2, ed J Alcamo (Amsterdam: Elsevier) pp 123–50

Carlsen H 2009 Climate change and the construction of scenario sets that span the range of societal uncertainties Paper for International Studies Association Annual Convention 2009 (New York City, February)

Jackson T 2009 Prosperity Without Growth: Economics for a Finite Planet (London: Earthscan)

Kriegler E, O'Neill B C, Hallegatte S, Kram T, Lempert R J, Moss R H and Wilbanks T 2012 The need for and use of socio-economic scenarios for climate change analysis: a new approach based on shared socio-economic pathways Glob. Environ. Change22 807–22

Nakicenovic N and Swart R (eds) 2000 Special Report on Emissions Scenarios (Cambridge: Cambridge University Press)

Raskin P, Monks F, Ribeiro T, van Vuuren D and Zurek M 2005 Global scenarios in historical perspective Ecosystems and Human Well-Being: Scenarios: Findings of the Scenarios Working Group vol 2, ed S R Carpenter et al (Washington, DC: Island) pp 35–44

Schweizer V J and Kriegler E 2012 Improving environmental change research with systematic techniques for qualitative scenarios Environ. Res. Lett.7 044011

Sunderlin W D 2003 Ideology, Social Theory, and the Environment (Lanham, MD: Rowman & Littlefield)

van Vuuren D P et al 2012 A proposal for a new scenario framework to support research and assessment in different climate research communities Glob. Environ. Change22 21–35

Victor P A 2008 Managing Without Growth: Slower by Design, Not Disaster(Advances in Ecological Economics Series) (Cheltenham: Edward Elgar)

Weimer-Jehle W 2006 Cross-impact balances: a system—theoretical approach to cross-impact analysis Technol. Forecast. Social Change73 334–61

While there is general consensus that observed global mean air temperature has increased during the past few decades and will very likely continue to rise in the coming decades, the assessment of the effective impacts of increased global mean air temperature on a specific regional-scale system remains highly challenging. This study takes up the widely discussed concept of limiting global mean temperature to a certain target value, like the so-called 2 °C target, to assess the related impacts on the Swiss Alpine glaciers. A model setup is introduced that uses and combines homogenized long-term meteorological observations and three ensembles of transient gridded Regional Climate Model simulations to drive a distributed glacier mass balance model under a (regionalized) global 2 °C target scenario. 101 glaciers are analyzed representing about 50% of the glacierized area and 75% of the ice volume in Switzerland. In our study, the warming over Switzerland, which corresponds to the global 2 °C target is met around 2030, 2045 and 2055 (depending on the ensemble) for Switzerland, and all glaciers have fully adjusted to the new climate conditions at around 2150. By this time and relative to the year 2000, the glacierized area and volume are both decreased to about 35% and 20%, respectively, and glacier-based runoff is reduced by about 70%.

Black carbon (BC) particles in snow can significantly reduce the snow albedo and enhance the absorption of solar radiation, with important impacts on climate and the hydrological cycle. A field campaign was carried out to measure the BC content in seasonal snow in Qinghai and Xinjiang provinces of western China, in January and February 2012. 284 snow samples were collected at 38 sites, 6 in Qinghai and 32 in Xinjiang. The observational results at the sites in Xinjiang, where the absorbing impurities in snow are dominated by BC particles, are reported in this work. The BC mass fractions in seasonal snow across northern Xinjiang have a median value of ∼70 ng g⁻¹, much lower than those in northeast China. The estimated concentration of BC at the cleanest site in Xinjiang is 20 ng g⁻¹, which is similar to that found along the coast of the Arctic Ocean. It is found that the BC content of snow decreases with altitude. Taking into account this altitude dependence, our measured BC contents in snow are consistent with a recent measurement of BC in winter snow on Tianshan glacier. The data from this field campaign should be useful for testing transport models and climate models for the simulated BC in snow.

Human-made transformations to the environment, and in particular the land surface, are having a large impact on the distribution (in both time and space) of rainfall, upon which all life is reliant. Focusing on precipitation, soil moisture and near-surface temperature, we compare data from Phase 5 of the Climate Modelling Intercomparison Project (CMIP5), as well as blended observational–satellite data, to see how the interaction between rainfall and the land surface differs (or agrees) between the models and reality, at daily timescales.

As expected, the results suggest a strong positive relationship between precipitation and soil moisture when precipitation leads and is concurrent with soil moisture estimates, for the tropics as a whole. Conversely a negative relationship is shown when soil moisture leads rainfall by a day or more. A weak positive relationship between precipitation and temperature is shown when either leads by one day, whereas a weak negative relationship is shown over the same time period between soil moisture and temperature. Temporally, in terms of lag and lead relationships, the models appear to be in agreement on the overall patterns of correlation between rainfall and soil moisture. However, in terms of spatial patterns, a comparison of these relationships across all available models reveals considerable variability in the ability of the models to reproduce the correlations between precipitation and soil moisture. There is also a difference in the timings of the correlations, with some models showing the highest positive correlations when precipitation leads soil moisture by one day. Finally, the results suggest that there are 'hotspots' of high linear gradients between precipitation and soil moisture, corresponding to regions experiencing heavy rainfall. These results point to an inability of the CMIP5 models to simulate a positive feedback between soil moisture and precipitation at daily timescales. Longer timescale comparisons and experiments at higher spatial resolutions, where the impact of the spatial heterogeneity of rainfall on the initiation of convection and supply of moisture is included, would be expected to improve process understanding further.

A consensus regarding the impact of solar variability on cloud cover is far from being reached. Moreover, the impact of cloud cover on climate is among the least understood of all climate components. This motivated us to analyze the persistence of solar signals in cloud cover for the time interval 1984–2009, covering two full solar cycles. A spatial and temporal investigation of the response of low, middle and high cloud data to cosmic ray induced ionization (CRII) and UV irradiance (UVI) is performed in terms of coherence analysis of the two signals. For some key geographical regions the response of clouds to UVI and CRII is persistent over the entire time interval indicating a real link. In other regions, however, the relation is not consistent, being intermittent or out of phase, suggesting that some correlations are spurious. The constant in phase or anti-phase relationship between clouds and solar proxies over some regions, especially for low clouds with UVI and CRII, middle clouds with UVI and high clouds with CRII, definitely requires more study. Our results show that solar signatures in cloud cover persist in some key climate-defining regions for the entire time period and supports the idea that, if existing, solar effects are not visible at the global level and any analysis of solar effects on cloud cover (and, consequently, on climate) should be done at the regional level.

Previous academic research on climate scepticism has tended to focus more on the way it has been organized, its tactics and its impact on policy outputs than on its prevalence in the media. Most of the literature has centred on the USA, where scepticism first appeared in an organized and politically effective form. This letter contrasts the way climate scepticism in its different forms is manifested in the print media in the USA and five other countries (Brazil, China, France, India and the UK), in order to gain insight into how far the US experience of scepticism is replicated in other countries. It finds that news coverage of scepticism is mostly limited to the USA and the UK; that there is a strong correspondence between the political leaning of a newspaper and its willingness to quote or use uncontested sceptical voices in opinion pieces; and that the type of sceptics who question whether global temperatures are warming are almost exclusively found in the US and UK newspapers. Sceptics who challenge the need for robust action to combat climate change also have a much stronger presence in the media of the same two countries.

Multi-gas approaches to climate change policies require a metric establishing 'equivalences' among emissions of various species. Climate scientists and economists have proposed four kinds of such metrics and debated their relative merits. We present a unifying framework that clarifies the relationships among them. We show, as have previous authors, that the global warming potential (GWP), used in international law to compare emissions of greenhouse gases, is a special case of the global damage potential (GDP), assuming (1) a finite time horizon, (2) a zero discount rate, (3) constant atmospheric concentrations, and (4) impacts that are proportional to radiative forcing. Both the GWP and GDP follow naturally from a cost–benefit framing of the climate change issue. We show that the global temperature change potential (GTP) is a special case of the global cost potential (GCP), assuming a (slight) fall in the global temperature after the target is reached. We show how the four metrics should be generalized if there are intertemporal spillovers in abatement costs, distinguishing between private (e.g., capital stock turnover) and public (e.g., induced technological change) spillovers. Both the GTP and GCP follow naturally from a cost-effectiveness framing of the climate change issue. We also argue that if (1) damages are zero below a threshold and (2) infinitely large above a threshold, then cost-effectiveness analysis and cost–benefit analysis lead to identical results. Therefore, the GCP is a special case of the GDP. The UN Framework Convention on Climate Change uses the GWP, a simplified cost–benefit concept. The UNFCCC is framed around the ultimate goal of stabilizing greenhouse gas concentrations. Once a stabilization target has been agreed under the convention, implementation is clearly a cost-effectiveness problem. It would therefore be more consistent to use the GCP or its simplification, the GTP.

We evaluate differences in clear-sky upwelling shortwave radiation reaching the top of the atmosphere in response to increasing the albedo of roof surfaces in an area of India with moderately high aerosol loading. Treated (painted white) and untreated (unpainted) roofs on two buildings in northeast India were analyzed on five cloudless days using radiometric imagery from the IKONOS satellite. Comparison of a radiative transfer model (RRTMG) and radiometric satellite observations shows good agreement (R² = 0.927). Results show a mean increase of ∼50 W m⁻² outgoing at the top of the atmosphere for each 0.1 increase of the albedo at the time of the observations and a strong dependence on atmospheric transmissivity.

We have investigated the spatio-temporal carbon balance patterns resulting from forcing a dynamic global vegetation model with output from 18 climate models of the CMIP5 (Coupled Model Intercomparison Project Phase 5) ensemble. We found robust patterns in terms of an extra-tropical loss of carbon, except for a temperature induced shift in phenology, leading to an increased spring uptake of carbon. There are less robust patterns in the tropics, a result of disagreement in projections of precipitation and temperature. Although the simulations generally agree well in terms of the sign of the carbon balance change in the middle to high latitudes, there are large differences in the magnitude of the loss between simulations. Together with tropical uncertainties these discrepancies accumulate over time, resulting in large differences in total carbon uptake over the coming century (−0.97–2.27 Pg C yr⁻¹ during 2006–2100). The terrestrial biosphere becomes a net source of carbon in ten of the 18 simulations adding to the atmospheric CO₂ concentrations, while the remaining eight simulations indicate an increased sink of carbon.

Countries are encouraged to identify drivers of deforestation and forest degradation in the development of national strategies and action plans for REDD+. In this letter we provide an assessment of proximate drivers of deforestation and forest degradation by synthesizing empirical data reported by countries as part of their REDD+ readiness activities, CIFOR country profiles, UNFCCC national communications and scientific literature. Based on deforestation rate and remaining forest cover 100 (sub)tropical non-Annex I countries were grouped into four forest transition phases. Driver data of 46 countries were summarized for each phase and by continent, and were used as a proxy to estimate drivers for the countries with missing data. The deforestation drivers are similar in Africa and Asia, while degradation drivers are more similar in Latin America and Asia. Commercial agriculture is the most important driver of deforestation, followed by subsistence agriculture. Timber extraction and logging drives most of the degradation, followed by fuelwood collection and charcoal production, uncontrolled fire and livestock grazing. The results reflect the most up to date and comprehensive overview of current national-level data availability on drivers, which is expected to improve over time within the frame of the UNFCCC REDD+ process.

The Amazon river basin has been recently affected by extreme climatic events, such as the exceptional drought of 2005, with significant impacts on human activities and ecosystems. In spite of the importance of monitoring freshwater stored and moving in such large river basins, only scarce measurements of river stages and discharges are available and the signatures of extreme drought conditions on surface freshwater dynamics at the basin scale are still poorly known. Here we use continuous multisatellite observations of inundation extent and water levels between 2003 and 2007 to monitor monthly variations of surface water storage at the basin scale. During the 2005 drought, the amount of water stored in the river and floodplains of the Amazon basin was ∼130 km³ (∼70%) below its 2003–7 average. This represents almost a half of the anomaly of minimum terrestrial water stored in the basin as estimated using the Gravity Recovery and Climate Experiment (GRACE) data.

Scenarios are key tools in analyses of global environmental change. Often they consist of quantitative and qualitative components, where the qualitative aspects are expressed in narrative, or storyline, form. Fundamental challenges in scenario development and use include identifying a small set of compelling storylines that span a broad range of policy-relevant futures, documenting that the assumptions embodied in the storylines are internally consistent, and ensuring that the selected storylines are sufficiently comprehensive, that is, that descriptions of important kinds of future developments are not left out. The dominant approach to scenario design for environmental change research has been criticized for lacking sufficient means of ensuring that storylines are internally consistent. A consequence of this shortcoming could be an artificial constraint on the range of plausible futures considered. We demonstrate the application of a more systematic technique for the development of storylines called the cross-impact balance (CIB) method. We perform a case study on the scenarios published in the IPCC Special Report on Emissions Scenarios (SRES), which are widely used. CIB analysis scores scenarios in terms of internal consistency. It can also construct a very large number of scenarios consisting of combinations of assumptions about individual scenario elements and rank these combinations in terms of internal consistency. Using this method, we find that the four principal storylines employed in the SRES scenarios vary widely in internal consistency. One type of storyline involving highly carbon-intensive development is underrepresented in the SRES scenario set. We conclude that systematic techniques like CIB analysis hold promise for improving scenario development in global change research.

Decadal climate prediction is a branch of climate modelling with the theoretical potential to anticipate climate impacts years in advance. Here we present analysis of the ENSEMBLES decadal simulations, the first multi-model decadal hindcasts, focusing on the skill in prediction of temperature and precipitation—important for impact prediction. Whilst previous work on this dataset has focused on the skill in multi-year averages, we focus here on the skill in prediction at smaller timescales. Considering annual and seasonal averages, we look at correlations, potential predictability and multi-year trend correlations.

The results suggest that the prediction skill for temperature comes from the long-term trend, and that precipitation predictions are not skilful. The potential predictability of the models is higher for annual than for seasonal means and is largest over the tropics, though it is low everywhere else and is much lower for precipitation than for temperature. The globally averaged temperature trend correlation is significant at the 99% level for all models and is higher for annual than for seasonal averages; however, for smaller spatial regions the skill is lower. For precipitation trends, the correlations are not skilful on either annual or seasonal scales.

Whilst climate models run in decadal prediction mode may be useful by other means, the hindcasts studied here have limited predictive power on the scales at which climate impacts and the results presented suggest that they do not yet have sufficient skill to drive impact models on decadal timescales.

k-means statistical-cluster analysis of submicron aerosol size distributions is combined with coincident humidity tandem differential mobility analyser data, leading to five unique aerosol categories for hygroscopic growth factors (HGFs): low sea-salt background marine, high sea-salt background marine, coastal nucleation, open ocean nucleation and anthropogenically influenced scenarios. When considering only marine conditions, and generic aerosol species associated with this environment (e.g. non-sea-salt sulfate, sea-salt, partly soluble organic matter and water insoluble organic matter), the two-year annual average contribution to aerosol number concentration from the different generic species was made up as follows: 46% (30–54%) of partially modified ammonium sulfate particles; 23% (11–40%) of partially modified sea-salt; and the remaining 31% (25–35%) contribution attributed to two distinct organic species as evidenced by different, but low, HGFs. The analysis reveals that on annual timescales, ∼30% of the submicron marine aerosol number concentration is sourced from predominantly organic aerosol while 60% of the anthropogenic aerosol number is predominantly organic. Coastal nucleation events show the highest contribution of the lowest HGF mode (1.19), although this contribution is more likely to be influenced by inorganic iodine oxides. While organic mass internally mixed with inorganic salts will lower the activation potential of these mixed aerosol types, thereby potentially reducing the concentration of cloud condensation nuclei (CCN), pure organic water soluble particles are still likely to be activated into cloud droplets, thereby increasing the concentration of CCN. A combination of dynamics and aerosol concentrations will determine which effect will prevail under given conditions.

There is increasing evidence of crop yield response to recent global warming, yet there is poor understanding of the relative contributions of different climatic variables to changes in crop production. Using a spatially calibrated crop model with cultivars and crop inputs held constant for the year 2000, we simulate idealized national cereal production during the period 1961–2010 under different combinations of observed climate and CO₂ forcings. With increasing CO₂ and all climate forcings, production shows a slight and insignificant change (−0.9% between 1961 and 2010); however, without CO₂ the combined climate forcings decrease production (−8.6%). Changing one climate variable at a time, whilst holding the other variables constant at 1961 values, observed warming has virtually no overall effect on production (0.01%), precipitation decreases it by 1.2% and radiation decreases it by 7.0%. The effects are management and crop dependent, with decreasing radiation responsible for reduced irrigated crop production, and precipitation for variability in rain-fed crop production. Rice is the most sensitive crop, with the largest decline (−12.4%) in simulated production. Wheat shows reduced yield (−9.7%) owing to climate factors, whilst offset by CO₂ fertilization (overall change 0.9%). Maize shows insignificant change (−1.2%) and moderate increase in production (2.6%), respectively. These model results suggest that decreasing radiation due to increasing aerosol concentration and other atmospheric pollutants has had a greater effect on crop production than warming trends in China. This underscores the need for crop–climate studies to resolve better the effects of radiation on crop yield and examine climate model projections of radiation in greater detail.

Cool and wet weather conditions hit northern Central Asia, East Asia and central North America during the 2009 summer in concert with a strong jet stream and a prominent meandering upper-level circulation in the Northern Hemisphere mid-latitudes despite the fact that the year 2009 is the fifth warmest year globally in the modern record. It is found that the conspicuous atmospheric variability in the entire Northern Hemisphere mid-latitudes during the summer of 2009 was caused by a combination of teleconnections associated with significant tropical thermal forcings, strong polar forcing, and interaction between high-frequency weather events and climate anomalies. The strong negative circumglobal teleconnection pattern associated with the deficient Indian summer monsoon rainfall and developing El Niño condition was the major contributor to the cool and wet summer in June. On the other hand, the July weather conditions were attributable to the high-latitude impact of the unprecedented negative Arctic Oscillation, together with the Rossby wave response to the subtropical heating generated by convective activities over the Western North Pacific summer monsoon region. It is also noted that enhanced storm track activity and frequent cold surges from high-latitudes may have played a role in the cool and wet summer over the regions of interest.

We report on life cycle assessment (LCA) of the economics, global warming potential and water (both for desalination and water use in operation) for a distributed concentrating solar combined heat and power (DCS-CHP) system. Detailed simulation of system performance across 1020 sites in the US combined with a sensible cost allocation scheme informs this LCA. We forecast a levelized cost of $0.25 kWh⁻¹ electricity and $0.03 kWh⁻¹ thermal, for a system with a life cycle global warming potential of ∼80 gCO₂eq kWh⁻¹ of electricity and ∼10 gCO₂eq kWh⁻¹ thermal, sited in Oakland, California. On the basis of the economics shown for air cooling, and the fact that any combined heat and power system reduces the need for cooling while at the same time boosting the overall solar efficiency of the system, DCS-CHP compares favorably to other electric power generation systems in terms of minimization of water use in the maintenance and operation of the plant.

The outlook for water desalination coupled with distributed concentrating solar combined heat and power is less favorable. At a projected cost of $1.40 m⁻³, water desalination with DCS-CHP would be economical and practical only in areas where water is very scarce or moderately expensive, primarily available through the informal sector, and where contaminated or salt water is easily available as feed-water. It is also interesting to note that $0.40–$1.90 m⁻³ is the range of water prices in the developed world, so DCS-CHP desalination systems could also be an economical solution there under some conditions.

Relatively little is known about the effects of regional warming on the carbon cycle of subtropical evergreen forest ecosystems, which are characterized by year-round growing season and cold winters. We investigated the carbon balance in three typical East Asia subtropical evergreen forests, using eddy flux, soil respiration and leaf-level measurements. Subtropical evergreen forests maintain continuous, high rates of photosynthetic activity, even during winter cold periods. Warm summers enhance photosynthetic rates in a limited way, because overall ecosystem productivity is primarily restrained by radiation levels during the warm period. Conversely, warm climates significantly enhance the respiratory carbon efflux. The finding of lower sensitivity of photosynthesis relative to that of respiration suggests that increased temperature will weaken the carbon-sink strength of East Asia subtropical evergreen forests.

Recent studies have examined tropical upper tropospheric warming by comparing coupled atmosphere–ocean global circulation model (GCM) simulations from Phase 3 of the Coupled Model Intercomparison Project (CMIP3) with satellite and radiosonde observations of warming in the tropical upper troposphere relative to the lower-middle troposphere. These studies showed that models tended to overestimate increases in static stability between the upper and lower-middle troposphere. We revisit this issue using atmospheric GCMs with prescribed historical sea surface temperatures (SSTs) and coupled atmosphere–ocean GCMs that participated in the latest model intercomparison project, CMIP5. It is demonstrated that even with historical SSTs as a boundary condition, most atmospheric models exhibit excessive tropical upper tropospheric warming relative to the lower-middle troposphere as compared with satellite-borne microwave sounding unit measurements. It is also shown that the results from CMIP5 coupled atmosphere–ocean GCMs are similar to findings from CMIP3 coupled GCMs. The apparent model-observational difference for tropical upper tropospheric warming represents an important problem, but it is not clear whether the difference is a result of common biases in GCMs, biases in observational datasets, or both.

The potential natural vegetation (PNV) distribution is required for several studies in environmental sciences. Most of the available databases are quite subjective or depend on vegetation models. We have built a new high-resolution world-wide PNV map using a objective statistical methodology based on multinomial logistic models. Our method appears as a fast and robust alternative in vegetation modelling, independent of any vegetation model. In comparison with other databases, our method provides a realistic PNV distribution in agreement with respect to BIOME 6000 data. Among several advantages, the use of probabilities allows us to estimate the uncertainty, bringing some confidence in the modelled PNV, or to highlight the regions needing some data to improve the PNV modelling. Despite our PNV map being highly dependent on the distribution of data points, it is easily updatable as soon as additional data are available and provides very useful additional information for further applications.

Chemical nitrogen (N) fertilizer has long been used to help meet the increasing food demands in China, the top N fertilizer consumer in the world. Growing concerns have been raised on the impacts of N fertilizer uses on food security and climate change, which is lack of quantification. Here we use a carbon–nitrogen (C–N) coupled ecosystem model, to quantify the food benefit and climate consequence of agronomic N addition in China over the six decades from 1949 to 2008. Results show that N fertilizer-induced crop yield and soil C sequestration had reached their peaks, while nitrous oxide (N₂O) emission continued rising as N was added. Since the early 2000s, stimulation of excessive N fertilizer uses to global climate warming through N₂O emission was estimated to outweigh their climate benefit in increasing CO₂ uptake. The net warming effect of N fertilizer uses, mainly centered in the North China Plain and the middle and lower reaches of Yangtze River Basin, with N₂O emission completely counteracting or even exceeding, by more than a factor of 2, the CO₂ sink. If we reduced the current N fertilizer level by 60% in 'over-fertilized' areas, N₂O emission would substantially decrease without significantly influencing crop yield and soil C sequestration.

Wildfires are a natural and important element in the functioning of boreal forests. However, in some years, fires with extreme spread and severity occur. Such severe fires can degrade the forest, affect human values, emit huge amounts of carbon and aerosols and alter the land surface albedo. Usually, wind, slope and dry air conditions have been recognized as factors determining fire spread. Here we identify surface moisture as an additional important driving factor for the evolution of extreme fire events in the Baikal region. An area of 127 000 km² burned in this region in 2003, a large part of it in regions underlain by permafrost. Analyses of satellite data for 2002–2009 indicate that previous-summer surface moisture is a better predictor for burned area than precipitation anomalies or fire weather indices for larch forests with continuous permafrost. Our analysis advances the understanding of complex interactions between the atmosphere, vegetation and soil, and how coupled mechanisms can lead to extreme events. These findings emphasize the importance of a mechanistic coupling of soil thermodynamics, hydrology, vegetation functioning, and fire activity in Earth system models for projecting climate change impacts over the next century.

Global climate change is altering terrestrial water and energy budgets, with subsequent impacts on surface and groundwater resources; recent studies have shown that local water management practices such as groundwater pumping and irrigation similarly alter terrestrial water and energy budgets over many agricultural regions, with potential feedbacks on weather and climate. Here we use a fully-integrated hydrologic model to directly compare effects of climate change and water management on terrestrial water and energy budgets of a representative agricultural watershed in the semi-arid Southern Great Plains, USA. At local scales, we find that the impacts of pumping and irrigation on latent heat flux, potential recharge and water table depth are similar in magnitude to the impacts of changing temperature and precipitation; however, the spatial distributions of climate and management impacts are substantially different. At the basin scale, the impacts on stream discharge and groundwater storage are remarkably similar. Notably, for the watershed and scenarios studied here, the changes in groundwater storage and stream discharge in response to a 2.5 °C temperature increase are nearly equivalent to those from groundwater-fed irrigation. Our results imply that many semi-arid basins worldwide that practice groundwater pumping and irrigation may already be experiencing similar impacts on surface water and groundwater resources to a warming climate. These results demonstrate that accurate assessment of climate change impacts and development of effective adaptation and mitigation strategies must account for local water management practices.

Indian monsoon rainfall is vital for a large share of the world's population. Both reliably projecting India's future precipitation and unraveling abrupt cessations of monsoon rainfall found in paleorecords require improved understanding of its stability properties. While details of monsoon circulations and the associated rainfall are complex, full-season failure is dominated by large-scale positive feedbacks within the region. Here we find that in a comprehensive climate model, monsoon failure is possible but very rare under pre-industrial conditions, while under future warming it becomes much more frequent. We identify the fundamental intraseasonal feedbacks that are responsible for monsoon failure in the climate model, relate these to observational data, and build a statistically predictive model for such failure. This model provides a simple dynamical explanation for future changes in the frequency distribution of seasonal mean all-Indian rainfall. Forced only by global mean temperature and the strength of the Pacific Walker circulation in spring, it reproduces the trend as well as the multidecadal variability in the mean and skewness of the distribution, as found in the climate model. The approach offers an alternative perspective on large-scale monsoon variability as the result of internal instabilities modulated by pre-seasonal ambient climate conditions.

Agricultural phosphorus (P) use is intricately linked to food security and water quality. Globalization of agricultural systems and changing diets clearly alter these relationships, yet their specific influence on non-renewable P reserves is less certain. We assessed P fertilizer used for production of food crops, livestock and biofuels in the US agricultural system, explicitly comparing the domestic P use required for US food consumption to the P use embodied in the production of US food imports and exports. By far the largest demand for P fertilizer throughout the US agricultural system was for feed and livestock production (56% of total P fertilizer use, including that for traded commodities). As little as 8% of the total mineral P inputs to US domestic agriculture in 2007 (1905 Gg P) was consumed in US diets in the same year, while larger fractions may have been retained in agricultural soils (28%), associated with different post-harvest losses (40%) or with biofuel refining (10%). One quarter of all P fertilizer used in the US was linked to export production, primarily crops, driving a large net P flux out of the country (338 Gg P). However, US meat consumption relied considerably on P fertilizer use in other countries to produce red meat imports. Changes in domestic farm management and consumer waste could together reduce the P fertilizer required for US food consumption by half, which is comparable to the P fertilizer reduction attainable by cutting domestic meat consumption (44%). US export-oriented agriculture, domestic post-harvest P losses and global demand for meat may ultimately have an important influence on the lifespan of US phosphate rock reserves.

This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year).

There are a number of asymmetries in the surface air temperature response to forcing, including polar amplification and changes to the diurnal and seasonal temperature ranges. We propose that such spatial–temporal signatures of climate change can, in part, be explained by differences in the effective heat capacity of the atmosphere. We have demonstrated that predictions arising from this hypothesis are simultaneously satisfied through the analysis of temperature records from daily to inter-decadal timescales using observational and reanalysis datasets. This mechanism can help to explain why we see the largest temperature trends in the winter months (0.42 K/decade in winter compared to 0.18 K/decade in summer) and why the diurnal temperature range decreases in a warming world, having decreased by ∼0.4 K since 1950.

Over the next few decades, it is expected that increasing fossil fuel prices will lead to a proliferation of energy crop cultivation initiatives. The environmental sustainability of these activities is thus a pressing issue—particularly when they take place in vulnerable regions, such as West Africa. In more general terms, the effect of increased CO₂ concentrations and higher temperatures on biomass production and evapotranspiration affects the evolution of the global hydrological and carbon cycles. Investigating these processes for a C4 crop, such as sugarcane, thus provides an opportunity both to extend our understanding of the impact of climate change, and to assess our capacity to model the underpinning processes. This paper applies a process-based crop model to sugarcane in Ghana (where cultivation is planned), and the São Paulo region of Brazil (which has a well-established sugarcane industry). We show that, in the Daka River region of Ghana, provided there is sufficient irrigation, it is possible to generate approximately 75% of the yield achieved in the São Paulo region. In the final part of the study, the production of sugarcane under an idealized temperature increase climate change scenario is explored. It is shown that doubling CO₂ mitigates the degree of water stress associated with a 4 °C increase in temperature.

The concern about Arctic greening has grown recently as the phenomenon is thought to have significant influence on global climate via atmospheric carbon emissions. Earlier work on Arctic vegetation highlighted the role of summer sea ice decline in the enhanced warming and greening phenomena observed in the region, but did not contain enough details for spatially characterizing the interactions between sea ice, temperature and vegetation photosynthetic absorption. By using 1 km resolution data from the Moderate Resolution Imaging Spectrometer (MODIS) as a primary data source, this study presents detailed maps of vegetation and temperature trends for the Siberian Arctic region, using the time integrated normalized difference vegetation index (TI-NDVI) and summer warmth index (SWI) calculated for the period 2000–11 to represent vegetation greenness and temperature respectively. Spatio-temporal relationships between the two indices and summer sea ice conditions were investigated with transects at eight locations using sea ice concentration data from the Special Sensor Microwave/Imager (SSM/I). In addition, the derived vegetation and temperature trends were compared among major Arctic vegetation types and bioclimate subzones. The fine resolution trend map produced confirms the overall greening (+1% yr⁻¹) and warming (+0.27% yr⁻¹) of the region, reported in previous studies, but also reveals browning areas. The causes of such local decreases in vegetation, while surrounding areas are experiencing the opposite reaction to changing conditions, are still unclear. Overall correlations between sea ice concentration and SWI as well as TI-NDVI decreased in strength with increasing distance from the coast, with a particularly pronounced pattern in the case of SWI. SWI appears to be driving TI-NDVI in many cases, but not systematically, highlighting the presence of limiting factors other than temperature for plant growth in the region. Further unravelling those limiting factors constitutes a priority in future research. This study demonstrates the use of medium resolution remotely sensed data for studying the complexity of spatio-temporal vegetation dynamics in the Arctic.

We investigate future changes in the annual cycle of heavy daily precipitation events across the British Isles in the periods 2021–2060 and 2061–2100, relative to present day climate. Twelve combinations of regional and global climate models forced with the A1B scenario are used. The annual cycle is modelled as an inhomogeneous Poisson process with sinusoidal models for location and scale parameters of the generalized extreme value distribution. Although the peak times of the annual cycle vary considerably between projections for the 2061–2100 period, a robust shift towards later peak times is found for the south-east, while in the north-west there is evidence for a shift towards earlier peak times. In the remaining parts of the British Isles no changes in the peak times are projected. For 2021–2060 this signal is weak. The annual cycle's relative amplitude shows no robust signal, where differences in projected changes are dominated by global climate model differences. The relative contribution of anthropogenic forcing and internal climate variability to changes in the relative amplitude cannot be identified with the available ensemble. The results might be relevant for the development of adequate risk-reduction strategies, for insurance companies and for the management and planning of water resources.

Estimates of greenhouse gas (GHG) emissions from shale gas production and use are controversial. Here we assess the level of GHG emissions from shale gas well hydraulic fracturing operations in the United States during 2010. Data from each of the approximately 4000 horizontal shale gas wells brought online that year are used to show that about 900 Gg CH₄ of potential fugitive emissions were generated by these operations, or 228 Mg CH₄ per well—a figure inappropriately used in analyses of the GHG impact of shale gas. In fact, along with simply venting gas produced during the completion of shale gas wells, two additional techniques are widely used to handle these potential emissions: gas flaring and reduced emission 'green' completions. The use of flaring and reduced emission completions reduce the levels of actual fugitive emissions from shale well completion operations to about 216 Gg CH₄, or 50 Mg CH₄ per well, a release substantially lower than several widely quoted estimates. Although fugitive emissions from the overall natural gas sector are a proper concern, it is incorrect to suggest that shale gas-related hydraulic fracturing has substantially altered the overall GHG intensity of natural gas production.

In the 21st century, most of the world's glaciers are expected to retreat due to further global warming. The range of this predicted retreat varies widely as a result of uncertainties in climate and glacier models. To calibrate and validate glacier models, past records of glacier mass balance are necessary, which often only span several decades. Long-term reconstructions of glacier mass balance could increase the precision of glacier models by providing the required calibration data. Here we show the possibility of applying shrub growth increments as an on-site proxy for glacier summer mass balance, exemplified by Salix shrubs in Finse, Norway. We further discuss the challenges which this method needs to meet and address the high potential of shrub growth increments for reconstructing glacier summer mass balance in remote areas.

Mercury is a highly toxic environmental contaminant that damages the endocrine and central nervous systems. In view of the contamination of Hong Kong territorial waters with anthropogenic pollutants such as trace heavy metals, we have investigated the application of our recently developed DNA-based luminescence methodology for the rapid and sensitive detection of mercury(II) ions in real water samples. The assay was applied to water samples from Shing Mun River, Nam Sang Wai and Lamma Island sea water, representing natural river, wetland and sea water media, respectively. The results showed that the system could function effectively in real water samples under conditions of low turbidity and low metal ion concentrations. However, high turbidity and high metal ion concentrations increased the background signal and reduced the performance of this assay.

East China, a major agricultural zone with a dense population, suffers from severe air pollution during June, the agricultural harvest season, every year. Crop burning emits tremendous amounts of combustion products into the atmosphere, not only rapidly degrading the local air quality but also affecting the tropospheric chemistry, threatening public health and affecting climate change. Recently, in mid-June 2012, crop fires left a thick pall of haze over East China. We evaluated the PM₁₀, PM_2.5 (particulates less than 10 and 2.5 μm in aerodynamic diameter) and BC (black carbon) emissions by analyzing detailed census data and moderate resolution imaging spectroradiometer (MODIS) remote sensing images and then simulated the consequent pollution using meteorological and dispersion models. The results show that the crop fires sweeping from the south to the north are responsible for the intensive air pollution during harvest season. It is necessary for scientists and governments to pay more attention to this issue.

Stagnant atmospheric conditions can lead to hazardous air quality by allowing ozone and particulate matter to accumulate and persist in the near-surface environment. By changing atmospheric circulation and precipitation patterns, global warming could alter the meteorological factors that regulate air stagnation frequency. We analyze the response of the National Climatic Data Center (NCDC) air stagnation index (ASI) to anthropogenically enhanced radiative forcing using global climate model projections of late-21st century climate change (SRESA1B scenario). Our results indicate that the atmospheric conditions over the highly populated, highly industrialized regions of the eastern United States, Mediterranean Europe, and eastern China are particularly sensitive to global warming, with the occurrence of stagnant conditions projected to increase by 12–25% relative to late-20th century stagnation frequencies (3–18 +  days yr⁻¹). Changes in the position/strength of the polar jet, in the occurrence of light surface winds, and in the number of precipitation-free days all contribute to more frequent late-21st century air mass stagnation over these high-population regions. In addition, we find substantial inter-model spread in the simulated response of stagnation conditions over some regions using either native or bias corrected global climate model simulations, suggesting that changes in the atmospheric circulation and/or the distribution of precipitation represent important sources of uncertainty in the response of air quality to global warming.

We analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low.

We used SWOT-AHP (strengths, weaknesses, opportunities and threats–analytical hierarchy process) technique to measure perceptions of four stakeholder groups: employees, local promoters, community leaders and end-users, about a nontraditional cookstove (NTCS) in Honduras. These stakeholder groups are part of an ongoing NTCS dissemination project led by Proyecto Mirador. We found that all stakeholder groups have a positive perception about the existing NTCS. Employees and local promoters stakeholder groups share similar perceptions. Smokeless cooking was selected as a prime strength, closely followed by reduction in forest logging and greenhouse gas emissions by all stakeholder groups. Availability of financial resources and responsible management were identified as crucial opportunities. Time spent in wood preparation and NTCS maintenance were identified as principal weaknesses. A long waiting time between a request and installation of NTCS and the risk of losing existing financial resources were acknowledged as major threats. Design improvements that can reduce maintenance and wood preparation time, a secure long-term source of funding through a market mechanism or direct/indirect government involvement, and early execution of pending orders will help in increasing adoption of NTCSs in rural Honduras.

Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions.

Treelines are known to be temperature-sensitive ecotones, and therefore could rapidly expand their range limits in response to climate warming. Observations of lack of range expansion, however, indicate that ecological constraints partly control the treeline ecotones. The main objectives of this study were to evaluate Picea mariana and Larix laricina recruitment and growth at and above the altitudinal treeline of Kangiqsualujjuaq (Nunavik), where warmer temperatures since the 1990s have already triggered shrub expansion. We mapped, harvested, dated and measured tree individuals along two altitudinal gradients from the forested stands below the treeline to hilltops. Since the 1990s, a pulse of L. laricina seedling establishment has occurred at and above the treeline. Dendrochronological analysis revealed that L. laricina underwent a rapid vertical growth and radial growth that accelerated from the 1990s. No recruitment was observed for P. mariana in response to the regional warming, suggesting a regeneration failure of this species. Our results indicated that the L. laricina colonization below and above the treeline in recent decades in response to the regional warming should modify the landscape physiognomy of the study area in the near future.

Recent large and frequent fires above the Alaskan arctic circle have forced a reassessment of the ecological and climatological importance of fire in arctic tundra ecosystems. Here we provide a general overview of the occurrence, distribution, and ecological and climate implications of Alaskan tundra fires over the past half-century using spatially explicit climate, fire, vegetation and remote sensing datasets for Alaska. Our analyses highlight the importance of vegetation biomass and environmental conditions in regulating tundra burning, and demonstrate that most tundra ecosystems are susceptible to burn, providing the environmental conditions are right. Over the past two decades, fire perimeters above the arctic circle have increased in size and importance, especially on the North Slope, indicating that future wildfire projections should account for fire regime changes in these regions. Remote sensing data and a literature review of thaw depths indicate that tundra fires have both positive and negative implications for climatic feedbacks including a decadal increase in albedo radiative forcing immediately after a fire, a stimulation of surface greenness and a persistent long-term (>10 year) increase in thaw depth. In order to address the future impact of tundra fires on climate, a better understanding of the control of tundra fire occurrence as well as the long-term impacts on ecosystem carbon cycling will be required.

Much of the debris in the near-surface ocean collects in so-called garbage patches where, due to convergence of the surface flow, the debris is trapped for decades to millennia. Until now, studies modelling the pathways of surface marine debris have not included release from coasts or factored in the possibilities that release concentrations vary with region or that pathways may include seasonal cycles. Here, we use observational data from the Global Drifter Program in a particle-trajectory tracer approach that includes the seasonal cycle to study the fate of marine debris in the open ocean from coastal regions around the world on interannual to centennial timescales. We find that six major garbage patches emerge, one in each of the five subtropical basins and one previously unreported patch in the Barents Sea. The evolution of each of the six patches is markedly different. With the exception of the North Pacific, all patches are much more dispersive than expected from linear ocean circulation theory, suggesting that on centennial timescales the different basins are much better connected than previously thought and that inter-ocean exchanges play a large role in the spreading of marine debris. This study suggests that, over multi-millennial timescales, a significant amount of the debris released outside of the North Atlantic will eventually end up in the North Pacific patch, the main attractor of global marine debris.

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988–2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI).

Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to ∼0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated.

Cities worldwide are increasingly becoming agents of climate change mitigation, while simultaneously aiming for other goals, such as improved accessibility and clean air. Based on stakeholder interviews and data analysis, we assess the current state of urban mobility in the four European cities of Barcelona, Malmö, Sofia and Freiburg. We then provide scenarios of increasingly ambitious policy packages, reducing greenhouse gas emissions from urban transport by up to 80% from 2010 to 2040. We find significant concurrent co-benefits in cleaner air, reduced noise ambience, fewer traffic-related injuries and deaths, more physical activity, less congestion and monetary fuel savings. Our scenarios suggest that non-motorized transport, especially bicycles, can occupy high modal shares, particularly in cities with less than 0.5 million inhabitants. We think that this kind of multi-criteria assessment of social costs and benefits is a useful complement to cost–benefit analysis of climate change mitigation measures.

Over the past 50 years, there have been major changes in human diets, including a global average increase in meat consumption and total calorie intake. We quantified how changes in annual per capita national average diets affected requirements for mined P between 1961 and 2007, starting with the per capita availability of a food crop or animal product and then determining the P needed to grow the product. The global per capita P footprint increased 38% over the 46 yr time period, but there was considerable variability among countries. Phosphorus footprints varied between 0.35 kg P capita⁻¹ yr⁻¹ (DPR Congo, 2007) and 7.64 kg P capita⁻¹ yr⁻¹ (Luxembourg, 2007). Temporal trends also differed among countries; for example, while China's P footprint increased almost 400% between 1961 and 2007, the footprints of other countries, such as Canada, decreased. Meat consumption was the most important factor affecting P footprints; it accounted for 72% of the global average P footprint. Our results show that dietary shifts are an important component of the human amplification of the global P cycle. These dietary trends present an important challenge for sustainable P management.

Extreme cold winter weather events over Eurasia have occurred more frequently in recent years in spite of a warming global climate. To gain further insight into this regional mismatch with the global mean warming trend, we analyzed winter cyclone and anticyclone activities, and their interplay with the regional atmospheric circulation pattern characterized by the semi-permanent Siberian high. We found a persistent weakening of both cyclones and anticyclones between the 1990s and early 2000s, and a pronounced intensification of anticyclone activity afterwards. It is suggested that this intensified anticyclone activity drives the substantially strengthening and northwestward shifting/expanding Siberian high, and explains the decreased midlatitude Eurasian surface air temperature and the increased frequency of cold weather events. The weakened tropospheric midlatitude westerlies in the context of the intensified anticyclones would reduce the eastward propagation speed of Rossby waves, favoring persistence and further intensification of surface anticyclone systems.

Offshore wind farms constitute a new and fast growing industry all over the world. This study investigates the long term impact on harbour porpoises, Phocoena phocoena, for more than 10 years (2001–12) from the first large scale offshore wind farm in the world, Nysted Offshore Wind Farm, in the Danish western Baltic Sea (72 × 2.3 MW turbines). The wind farm was brought into full operation in December 2003. At six stations, acoustic porpoise detectors (T-PODs) were placed inside the wind farm area and at a reference area 10 km to the east, to monitor porpoise echolocation activity as a proxy of porpoise presence. A modified statistical BACI design was applied to detect changes in porpoise presence before, during and after construction of the wind farm. The results show that the echolocation activity has significantly declined inside Nysted Offshore Wind Farm since the baseline in 2001–2 and has not fully recovered yet. The echolocation activity inside the wind farm has been gradually increasing (from 11% to 29% of the baseline level) since the construction of the wind farm, possibly due to habituation of the porpoises to the wind farm or enrichment of the environment due to reduced fishing and to artificial reef effects.

The letters collected in this focus issue of Environmental Research Letters on 'Environmental, socio-economic and climatic changes in Northern Eurasia and their feedbacks to the global Earth system' represent the third special issue based on the results of research within the Northern Eurasia Earth Science Partnership Initiative (NEESPI: http://neespi.org) program domain. Through the years, NEESPI researchers have presented a diverse array of articles that represent a variety of spatial scales and demonstrate the degree to which abrupt climatic and socio-economic changes are acting across Northern Eurasia and feed back to the global Earth system.

The Deepwater Horizon accident resulted in a substantial uncontrolled hydrocarbon release to the northern Gulf of Mexico, much of which was entrained in deep submerged plumes. While bio-degradation of the hydrocarbons has been inferred from microbial biomass and genetics, the amount of conversion of oil and gas carbon to biomass remains uncertain having only been estimated in modeling studies. Here we examine correlated depletions of nitrate, phosphate and oxygen in the submerged plumes and conclude that a substantial portion of hydrocarbons in these plumes was converted to biomass (0.8–2 × 10¹⁰ mol C). This contrasts with nutrient-limited surface waters where other work has suggested hydrocarbon-induced microbial growth to have been minimal. Our results suggest the need for better monitoring of changes in nutrients as well as study of nutrient recycling in similar future hydrocarbon releases.

To study the impact of the Deepwater Horizon oil spill on photosynthesis of coastal salt marsh plants in Mississippi, we developed a hierarchical Bayesian (HB) model based on field measurements collected from July 2010 to November 2011. We sampled three locations in Davis Bayou, Mississippi (30.375°N, 88.790°W) representative of a range of oil spill impacts. Measured photosynthesis was negative (respiration only) at the heavily oiled location in July 2010 only, and rates started to increase by August 2010. Photosynthesis at the medium oiling location was lower than at the control location in July 2010 and it continued to decrease in September 2010. During winter 2010–2011, the contrast between the control and the two impacted locations was not as obvious as in the growing season of 2010. Photosynthesis increased through spring 2011 at the three locations and decreased starting with October at the control location and a month earlier (September) at the impacted locations.

Using the field data, we developed an HB model. The model simulations agreed well with the measured photosynthesis, capturing most of the variability of the measured data. On the basis of the posteriors of the parameters, we found that air temperature and photosynthetic active radiation positively influenced photosynthesis whereas the leaf stress level negatively affected photosynthesis. The photosynthesis rates at the heavily impacted location had recovered to the status of the control location about 140 days after the initial impact, while the impact at the medium impact location was never severe enough to make photosynthesis significantly lower than that at the control location over the study period. The uncertainty in modeling photosynthesis rates mainly came from the individual and micro-site scales, and to a lesser extent from the leaf scale.

The Deepwater Horizon (Macondo) oil spill released large volumes of oil and gas of distinct carbon isotopic composition to the northern Gulf of Mexico, allowing Graham et al (2010 Environ. Res. Lett.5 045301) to use stable carbon isotopes (δ¹³C) to infer the introduction of spilled oil into the planktonic food web. Surface ocean organic production and measured oil are separated by 5–7‰ in stable carbon isotope (δ¹³C) space, while in radiocarbon (Δ¹⁴C) space these two potential sources are separated by more than 1000‰. Thus radiocarbon isotopes provide a more sensitive tracer by which to infer possible introduction of Macondo oil into the food web. We measured Δ¹⁴C and δ¹³C in plankton collected from within 100 km of the spill site as well as in coastal and offshore DIC (dissolved inorganic carbon or ΣCO₂) to constrain surface production values. On average, plankton values were depleted in ¹⁴C relative to surface DIC, and we found a significant linear correlation between Δ¹⁴C and δ¹³C in plankton. Cumulatively, these results are consistent with the hypothesis that carbon released from the Deepwater Horizon spill contributed to the offshore planktonic food web. Our results support the findings of Graham et al (2010 Environ. Res. Lett.5 045301), but we infer that methane input may be important.

Sea-level is expected to rise for a long time to come, even after stabilization of human-induced climatic warming. Here we use simulations with the Earth system model of intermediate complexity LOVECLIM to project sea-level changes over the third millennium forced with atmospheric greenhouse gas concentrations that stabilize by either 2000 or 2100 AD. The model includes 3D thermomechanical models of the Greenland and Antarctic ice sheets coupled to an atmosphere and an ocean model, a global glacier melt algorithm to account for the response of mountain glaciers and ice caps, and a procedure for assessing oceanic thermal expansion from oceanic heat uptake. Four climate change scenarios are considered to determine sea-level commitments. These assume a 21st century increase in greenhouse gases according to SRES scenarios B1, A1B and A2 with a stabilization of the atmospheric composition after the year 2100. One additional scenario assumes 1000 years of constant atmospheric composition from the year 2000 onwards. For our preferred model version, we find an already committed total sea-level rise of 1.1 m by 3000 AD. In experiments with greenhouse gas concentration stabilization at 2100 AD, the total sea-level rise ranges between 2.1 m (B1), 4.1 m (A1B) and 6.8 m (A2). In all scenarios, more than half of this amount arises from the Greenland ice sheet, thermal expansion is the second largest contributor, and the contribution of glaciers and ice caps is small as it is limited by the available ice volume of maximally 25 cm of sea-level equivalent. Additionally, we analysed the sensitivity of the sea-level contributions from an ensemble of nine different model versions that cover a large range of climate sensitivity realized by model parameter variations of the atmosphere–ocean model. Selected temperature indices are found to be good predictors for sea-level contributions from the different components of land ice and oceanic thermal expansion after 1000 years.

The climate memory of a land surface generally persists for only a few months, but analysis of surface meteorological data revealed a longer-term climate memory carried by soil freeze–thaw processes in Siberia. Surface temperature variability during the snowmelt season corresponds reasonably well with that in the summer of the following year, when most stations show a secondary autocorrelation peak. The surface temperature memory is thought to be stored as variations in the amount of snowmelt water held in the soil, and through soil freezing, which emerges as latent heat variations in the near-surface atmosphere during soil thawing approximately one year later. The ground conditions are dry in the longer-term climate memory regions, such as eastern Siberia, where less snow cover (higher surface air temperature) in spring results in less snowmelt water or lower soil moisture in the summer. Consequently, through soil freezing, it will require less latent heat to thaw in the summer of the following year, resulting in higher surface air temperature. In addition to soil moisture and snow cover, soil freeze–thaw processes can also act as agents of climate memory in the near-surface atmosphere.

Little is known about the frequency and potential mass balance impact of winter glacier melt events. In this study, daily atmospheric temperature soundings from the Puerto Montt radiosonde (41.43°S) are used to reconstruct winter melting events at the glacier equilibrium line altitude in the 38°–42°S region of southern Chile, between 1960 and 2010. The representativeness of the radiosonde temperatures to near-surface glacier temperatures is demonstrated using meteorological records from close to the equilibrium line on two glaciers in the region over five winters. Using a degree-day model we estimate an average of 0.28 m of melt and 21 melt days in the 15 June–15 September period each year, with high inter-annual variability. The majority of melt events are associated with midlatitude migratory high pressure systems crossing Chile and northwesterly flows, that force adiabatic compression and warm advection, respectively. There are no trends in the frequency or magnitude of melt events over the period of record, but the annual frequency of winter melt days shows a significant, although rather weak and probably non-linear, relationship to late winter and early spring values of a multivariate El Niño Southern Oscillation Index (MEI).

We present an updated analysis of monthly means of daily mean, minimum and maximum surface air temperature (SAT) data from Greenland coastal weather stations and from a long-running site on the Greenland ice sheet, and analyse these data for evidence of climate change, especially focusing on the last 20 years but using the whole periods of available records (some since 1873). We demonstrate very strong recent warming along the west coast of Greenland, especially during winter (locally >10 °C since 1991), and rather weaker warming on the east Greenland coast, which is influenced by different oceanographic/sea-ice and meteorological synoptic forcing conditions to the rest of Greenland. Coastal Greenland seasonal mean SAT trends were generally 2–6 °C, strongest in winter (5.7 °C) and least in summer and autumn (both 2.2 °C), during 1981–2011/12. Since 2001 Greenland mean coastal SAT increased significantly by 2.9 °C in winter and 0.8 °C in summer but decreased insignificantly by 1.1 °C in autumn and 0.2 °C in spring, during a period when there was little net change (≤ ± 0.1 °C) in northern hemisphere temperatures. SAT means for the latest 2001–11/12 decade were significantly in excess of those for peak decadal periods during the Early Twentieth Century Warm Period only in summer and winter, and not significantly greater in spring and autumn. Summer SAT increases in southern Greenland for the last 20 years were generally greater for maximum than minimum temperatures. By contrast, in winter, the recent warming was greater for minimum than maximum temperatures. The greatest SAT changes in all seasons are seen on Greenland's west coast. SAT changes on the ice sheet and a key marginal glacier closely followed nearby coastal temperatures over the last 20 years.

Outputs from the regional climate model Modèle Atmosphérique Régionale at a spatial resolution of 25 km are used to study 21st century projected surface mass balance (SMB) over six major drainage basins of the Greenland ice sheet (GrIS). The regional model is forced with the outputs of three different Earth System Models (CanESM2, NorESM1 and MIROC5) obtained when considering two greenhouse gas future scenarios with levels of CO₂ equivalent of, respectively, 850 and >1370 ppm by 2100. Results indicate that the increase in runoff due to warming will exceed the increased precipitation deriving from the increase in evaporation for all basins, with the amount of net loss of mass at the surface varying spatially. Basins along the southwest and north coast are projected to have the highest sensitivity of SMB to increasing temperatures. For these basins, the global temperature anomaly corresponding to a decrease of the SMB below the 1980–99 average (when the ice sheet was near the equilibrium) ranges between +0.60 and +2.16 °C. For the basins along the northwest and northeast, these values range between +1.50 and +3.40 °C. Our results are conservative as they do not account for ice dynamics and changes in the ice sheet topography.

Permafrost degradation exhibits striking and profound influences on the alpine ecosystem, and response characteristics of vegetation and soil environment to such degradation inevitably differ during the entire degraded periods. However, up to now, the related research is lacking in the Qinghai–Tibetan Plateau (QTP). For this reason, twenty ecological plots in the different types of permafrost zones were selected in the upstream regions of the Shule River Basin on the northeastern margin of the QTP. Vegetation characteristics (species diversity, community coverage and biomass etc) and topsoil environment (temperature (ST), water content (SW), mechanical composition (SMC), culturable microorganism (SCM), organic carbon (SOC) and total nitrogen (TN) contents and so on), as well as active layer thickness (ALT) were investigated in late July 2009 and 2010. A spatial–temporal shifts method (the spatial pattern that is represented by different types of permafrost shifting to the temporal series that stands for different stages of permafrost degradation) has been used to discuss response characteristics of vegetation and topsoil environment throughout the entire permafrost degradation. The results showed that (1) ST of 0–40 cm depth and ALT gradually increased from highly stable and stable permafrost (H-SP) to unstable permafrost (UP). SW increased initially and then decreased, and SOC content and the quantities of SCM at a depth of 0–20 cm first decreased and then increased, whereas TN content and SMC showed obscure trends throughout the stages of permafrost degradation with a stability decline from H-SP to extremely unstable permafrost (EUP); (2) further, species diversity, community coverage and biomass first increased and then decreased in the stages from H-SP to EUP; (3) in the alpine meadow ecosystem, SOC and TN contents increased initially and then decreased, soil sandy fractions gradually increased with stages of permafrost degradation from substable (SSP) to transitional (TP), and to UP. Meanwhile, SOC/TN storages increased in the former stage, while they decreased in the latter stage. This study indicated that the response characteristics of vegetation and soil environment varied throughout the entire permafrost degradation, and SW was the dominant ecological factor that limited vegetation distribution and growth. Therefore, SSP and TP phases could provide a favourable environment for plant growth, mainly contributing to high SW.

Climate change is expected to increase migration flows, especially from socially and environmentally vulnerable populations. These 'climate migrants' do not have any official protection under international law, which has implications for the human security of migrants. This work argues that the United Nations Framework Convention on Climate Change (UNFCCC) can and should recognize climate migrants, and is the most relevant international framework for doing so. While not legally binding, the acknowledgment of climate displacement, migration and planned relocation issues in the UNFCCC's Cancun Adaptation Framework indicates a willingness to address the issue through an adaptation lens. Herein, the paper proposes a framework for setting the institutional groundwork for recognizing climate migrants, focusing on the most vulnerable, promoting targeted research and policy agendas, and situating policies within a comprehensive strategy.

The potential for altered ecosystems and extreme weather events in the context of climate change has raised questions concerning the role that migration plays in either increasing or reducing risks to society. Using modeled data on net migration over three decades from 1970 to 2000, we identify sensitive ecosystems and regions at high risk of climate hazards that have seen high levels of net in-migration and out-migration over the time period. This paper provides a literature review on migration related to ecosystems, briefly describes the methodology used to develop the estimates of net migration, then uses those data to describe the patterns of net migration for various ecosystems and high risk regions. The study finds that negative net migration generally occurs over large areas, reflecting its largely rural character, whereas areas of positive net migration are typically smaller, reflecting its largely urban character. The countries with largest population such as China and India tend to drive global results for all the ecosystems found in those countries. Results suggest that from 1970 to 2000, migrants in developing countries have tended to move out of marginal dryland and mountain ecosystems and out of drought-prone areas, and have moved towards coastal ecosystems and areas that are prone to floods and cyclones. For North America results are reversed for dryland and mountain ecosystems, which saw large net influxes of population in the period of record. Uncertainties and potential sources of error in these estimates are addressed.

Migration necessarily precedes environmental change in the form of deforestation and soil degradation in tropical settlement frontiers. But what environmental factors may contribute to these migration streams in the first place? Identification of the environmental characteristics related to this process is crucial for understanding how environmental change and migration may form recurrent feedback loops. Further understanding of this process could be useful for developing policies to both reduce environmentally induced migration from origin areas and also palliate significant environmental change unleashed by settler deforestation in destination areas. Evidently, apprehension of this holistic process cannot be approached only from the destination since this ignores environmental and other antecedents to rural out-migration. This letter presents data from surveys conducted in areas of high out-migration to the agricultural frontier in northern Guatemala. The results suggest that land scarcity and degradation in origin communities are linked to out-migration in general and to the forest frontier of northern Guatemala in particular.

Studies that quantify the spatial and temporal variability of carbon sources and sinks provide process-level information for the prediction of future levels of atmospheric carbon dioxide as well as verification of current emission agreements. Assessments of carbon sources and sinks for North America that compare top-down atmospheric constraints with bottom-up inventories find particularly large carbon sinks in the southeastern US. However, this southeastern US sink may be impacted by extreme land-use disturbance events due to mountaintop coal mining (MCM). Here we apply ecosystem modeling and field experiment data to quantify the potential impact of future mountaintop coal mining on the carbon budget of the southern Appalachian forest region. For projections based on historical mining rates, grassland reclamation, and the continued regrowth of un-mined forests, we find that the southern Appalachian forests switch from a net carbon sink to a net carbon source by year 2025–33 with a 30%–35% loss in terrestrial carbon stocks relative to a scenario with no future mining by the year 2100. Alternatively, scenarios of forest sequestration due to the effect of CO₂ fertilization result in a 15%–24% loss in terrestrial carbon stocks by the year 2100 for mining scenarios relative to scenarios with no future mining. These results suggest that while power plant stack emissions are the dominant life-cycle stage in coal-fired electricity, accounting for mountaintop coal mining in bottom-up inventories may be a critical component of regional carbon budgets.

Bark beetle outbreaks kill billions of trees in western North America, and the resulting tree mortality can significantly impact local and regional carbon cycling. However, substantial variability in mortality occurs within outbreak areas. Our objective was to quantify landscape-scale effects of beetle infestations on aboveground carbon (AGC) stocks using field observations and remotely sensed data across a 5054 ha study area that had experienced a mountain pine beetle outbreak. Tree mortality was classified using multispectral imagery that separated green, red, and gray trees, and models relating field observations of AGC to LiDAR data were used to map AGC. We combined mortality and AGC maps to quantify AGC in beetle-killed trees. Thirty-nine per cent of the forested area was killed by beetles, with large spatial variability in mortality severity. For the entire study area, 40–50% of AGC was contained in beetle-killed trees. When considered on a per-hectare basis, 75–89% of the study area had >25% AGC in killed trees and 3–6% of the study area had >75% of the AGC in killed trees. Our results show that despite high variability in tree mortality within an outbreak area, bark beetle epidemics can have a large impact on AGC stocks at the landscape scale.

Many temperate and boreal forests are subject to insect epidemics. In the eastern US, over 41 million meters squared of tree basal area are thought to be at risk of gypsy moth defoliation. However, the decadal-to-century scale implications of defoliation events for ecosystem carbon dynamics are not well understood. In this study, the effects of defoliation intensity, periodicity and spatial pattern on the carbon cycle are investigated in a set of idealized model simulations. A mechanistic terrestrial biosphere model, ecosystem demography model 2, is driven with observations from a xeric oak–pine forest located in the New Jersey Pine Barrens. Simulations indicate that net ecosystem productivity (equal to photosynthesis minus respiration) decreases linearly with increasing defoliation intensity. However, because of interactions between defoliation and drought effects, aboveground biomass exhibits a nonlinear decrease with increasing defoliation intensity. The ecosystem responds strongly with both reduced productivity and biomass loss when defoliation periodicity varies from 5 to 15 yr, but exhibits a relatively weak response when defoliation periodicity varies from 15 to 60 yr. Simulations of spatially heterogeneous defoliation resulted in markedly smaller carbon stocks than simulations with spatially homogeneous defoliation. These results show that gypsy moth defoliation has a large effect on oak–pine forest biomass dynamics, functioning and its capacity to act as a carbon sink.

Drought is arguably the most important regulator of inter-annual variation in net ecosystem CO₂ exchange (NEE) in peatlands. This study investigates effects of drought periods on NEE and its components, gross primary production (GPP) and ecosystem respiration (R_eco), on the basis of eddy covariance measurements of land–atmosphere exchange of CO₂ in 2006–2009 in a south Swedish nutrient-poor peatland. Two drought periods had dissimilar effects on the CO₂ exchange. In 2006, there was a short but severe drought period in the middle of the growing season resulting in increased R_eco rates, but no detectable effect on GPP rates. In contrast, in 2008 the drought period began early in the growing season and lasted for a longer period of time, resulting in reduced GPP rates, suggesting that GPP is most sensitive to drought during leaf out and canopy development compared with the full canopy stage. Both in 2006 and in 2008 the peatland acted as an annual source of atmospheric CO₂, while in 2007 and 2009, when there were no drought periods, the peatland constituted a CO₂ sink. It was concluded that the timing, severity and duration of drought periods regulate the effects on peatland GPP, R_eco and NEE.

Climatic extreme events strongly affect forest growth and thus significantly influence the inter-annual terrestrial carbon balance. As we are facing an increase in frequency and intensity of climate extremes, extensive empirical archives are required to assess continental scale impacts of temperature and precipitation anomalies. Here we divide a tree-ring network of approximately 1000 sites into fifteen groups of similar high-frequency growth variability to reconstruct regional positive and negative extreme events in different parts of Europe between 1500 and 2008. Synchronized growth maxima or minima within and among regions indicate eighteen years in the pre-instrumental period and two events in the 20th century (1948, 1976) with extensive radial growth fluctuations. Comparisons with instrumental data showed that the European tree-ring network mirrors the spatial extent of temperature and precipitation extremes, but the interpretation of pre-instrumental events is challenged by lagged responses to off-growing season climate extremes. We were able to attribute growth minima in subsequent years to unfavourable August–October conditions and to mild climate during winter months associated with respiratory carbon losses. Our results emphasize the importance of carry-over effects and species-specific growth characteristics for forest productivity. Furthermore, they promote the use of regional tree-ring chronologies in research related to climate variability and terrestrial carbon sink dynamics.

Many parts of the world experience frequent and severe droughts. Summer drought can significantly reduce primary productivity and carbon sequestration capacity. The impacts of spring droughts, however, have received much less attention. A severe and sustained spring drought occurred in southwestern China in 2010. Here we examine the influence of this spring drought on the primary productivity of terrestrial ecosystems using data on climate, vegetation greenness and productivity. We first assess the spatial extent, duration and severity of the drought using precipitation data and the Palmer drought severity index. We then examine the impacts of the drought on terrestrial ecosystems using satellite data for the period 2000–2010. Our results show that the spring drought substantially reduced the enhanced vegetation index (EVI) and gross primary productivity (GPP) during spring 2010 (March–May). Both EVI and GPP also substantially declined in the summer and did not fully recover from the drought stress until August. The drought reduced regional annual GPP and net primary productivity (NPP) in 2010 by 65 and 46 Tg C yr⁻¹, respectively. Both annual GPP and NPP in 2010 were the lowest over the period 2000–2010. The negative effects of the drought on annual primary productivity were partly offset by the remarkably high productivity in August and September caused by the exceptionally wet conditions in late summer and early fall and the farming practices adopted to mitigate drought effects. Our results show that, like summer droughts, spring droughts can also have significant impacts on vegetation productivity and terrestrial carbon cycling.

Thermal electricity generation is a major consumer of freshwater for cooling, fuel extraction and air emissions controls, but the life cycle water impacts of different fossil fuel cycles are not well understood. Much of the existing literature relies on decades-old estimates for water intensity, particularly regarding water consumed for fuel extraction. This work uses contemporary data from specific resource basins and power plants in Texas to evaluate water intensity at three major stages of coal and natural gas fuel cycles: fuel extraction, power plant cooling and power plant emissions controls. In particular, the water intensity of fuel extraction is quantified for Texas lignite, conventional natural gas and 11 unconventional natural gas basins in Texas, including major second-order impacts associated with multi-stage hydraulic fracturing. Despite the rise of this water-intensive natural gas extraction method, natural gas extraction appears to consume less freshwater than coal per unit of energy extracted in Texas because of the high water intensity of Texas lignite extraction. This work uses new resource basin and power plant level water intensity data to estimate the potential effects of coal to natural gas fuel switching in Texas' power sector, a shift under consideration due to potential environmental benefits and very low natural gas prices. Replacing Texas' coal-fired power plants with natural gas combined cycle plants (NGCCs) would reduce annual freshwater consumption in the state by an estimated 53 billion gallons per year, or 60% of Texas coal power's water footprint, largely due to the higher efficiency of NGCCs.

This report provides estimates of operational water withdrawal and water consumption factors for electricity generating technologies in the United States. Estimates of water factors were collected from published primary literature and were not modified except for unit conversions. The water factors presented may be useful in modeling and policy analyses where reliable power plant level data are not available. Major findings of the report include: water withdrawal and consumption factors vary greatly across and within fuel technologies, and water factors show greater agreement when organized according to cooling technologies as opposed to fuel technologies; a transition to a less carbon-intensive electricity sector could result in either an increase or a decrease in water use, depending on the choice of technologies and cooling systems employed; concentrating solar power technologies and coal facilities with carbon capture and sequestration capabilities have the highest water consumption values when using a recirculating cooling system; and non-thermal renewables, such as photovoltaics and wind, have the lowest water consumption factors. Improved power plant data and further studies into the water requirements of energy technologies in different climatic regions would facilitate greater resolution in analyses of water impacts of future energy and economic scenarios. This report provides the foundation for conducting water use impact assessments of the power sector while also identifying gaps in data that could guide future research.

The power sector withdraws more freshwater annually than any other sector in the US. The current portfolio of electricity generating technologies in the US has highly regionalized and technology-specific requirements for water. Water availability differs widely throughout the nation. As a result, assessments of water impacts from the power sector must have a high geographic resolution and consider regional, basin-level differences. The US electricity portfolio is expected to evolve in coming years, shaped by various policy and economic drivers on the international, national and regional level; that evolution will impact power sector water demands. Analysis of future electricity scenarios that incorporate technology options and constraints can provide useful insights about water impacts related to changes to the technology mix. Utilizing outputs from the regional energy deployment system (ReEDS) model, a national electricity sector capacity expansion model with high geographical resolution, we explore potential changes in water use by the US electric sector over the next four decades under various low carbon energy scenarios, nationally and regionally.

Hydrology/water management and electricity generation projections have been modeled separately, but there has been little effort in intentionally and explicitly linking the two sides of the water–energy nexus. This paper describes a platform for assessing power plant cooling water withdrawals and consumption under different electricity pathways at geographic and time scales appropriate for both electricity and hydrology/water management. This platform uses estimates of regional electricity generation by the Regional Energy Deployment System (ReEDS) as input to a hydrologic and water management model—the Water Evaluation and Planning (WEAP) system. In WEAP, this electricity use represents thermoelectric cooling water withdrawals and consumption within the broader, regional water resource context. Here we describe linking the electricity and water models, including translating electricity generation results from ReEDS-relevant geographies to the water-relevant geographies of WEAP. The result of this analysis is water use by the electric sector at the regional watershed level, which is used to examine the water resource implications of these electricity pathways.

This study investigates the air quality impacts of using a high-blend ethanol fuel (E85) instead of gasoline in vehicles in an urban setting when a morning fog is present under summer and winter conditions. The model couples the near-explicit gas-phase Master Chemical Mechanism (MCM v. 3.1) with the extensive aqueous-phase Chemical Aqueous Phase Radical Mechanism (CAPRAM 3.0i) in SMVGEAR II, a fast and accurate ordinary differential equation solver. Summer and winter scenarios are investigated during a two day period in the South Coast Air Basin (SCAB) with all gasoline vehicles replaced by flex-fuel vehicles running on E85 in 2020. We find that E85 slightly increases ozone compared with gasoline in the presence or absence of a fog under summer conditions but increases ozone significantly relative to gasoline during winter conditions, although winter ozone is always lower than summer ozone. A new finding here is that a fog during summer may increase ozone after the fog disappears, due to chemistry alone. Temperatures were high enough in the summer to increase peroxy radical (RO₂) production with the morning fog, which led to the higher ozone after fog dissipation. A fog on a winter day decreases ozone after the fog. Within a fog, ozone is always lower than if no fog occurs. The sensitivity of the results to fog parameters like droplet size, liquid water content, fog duration and photolysis are investigated and discussed. The results support previous work suggesting that E85 and gasoline both enhance pollution with E85 enhancing pollution significantly more at low temperatures. Thus, neither E85 nor gasoline is a 'clean-burning' fuel.

Production of biomass for bioenergy can alter biogeochemical and biogeophysical mechanisms, thus affecting local and global climate. Recent scientific developments have mainly embraced impacts from land use changes resulting from area-expanded biomass production, with several extensive insights available. Comparably less attention, however, has been given to the assessment of direct land surface–atmosphere climate impacts of bioenergy systems under rotation such as in plantations and forested ecosystems, whereby land use disturbances are only temporary. Here, following IPCC climate metrics, we assess bioenergy systems in light of two important dynamic land use climate factors, namely, the perturbation in atmospheric carbon dioxide (CO₂) concentration caused by the timing of biogenic CO₂ fluxes, and temporary perturbations to surface reflectivity (albedo). Existing radiative forcing-based metrics can be adapted to include such dynamic mechanisms, but high spatial and temporal modeling resolution is required. Results show the importance of specifically addressing the climate forcings from biogenic CO₂ fluxes and changes in albedo, especially when biomass is sourced from forested areas affected by seasonal snow cover. The climate performance of bioenergy systems is highly dependent on biomass species, local climate variables, time horizons, and the climate metric considered. Bioenergy climate impact studies and accounting mechanisms should rapidly adapt to cover both biogeochemical and biogeophysical impacts, so that policy makers can rely on scientifically robust analyses and promote the most effective global climate mitigation options.

A climate envelope approach was used to model the response of switchgrass, a model bioenergy species in the United States, to future climate change. The model was built using general additive models (GAMs), and switchgrass yields collected at 45 field trial locations as the response variable. The model incorporated variables previously shown to be the main determinants of switchgrass yield, and utilized current and predicted 1 km climate data from WorldClim. The models were run with current WorldClim data and compared with results of predicted yield obtained using two climate change scenarios across three global change models for three time steps.

Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation.

These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy.

There is growing concern that non-native plants cultivated for bioenergy production might escape and result in harmful invasions in natural areas. Literature-derived assessment tools used to evaluate invasion risk are beneficial for screening, but cannot be used to assess novel cultivars or genotypes. Experimental approaches are needed to help quantify invasion risk but protocols for such tools are lacking. We review current methods for evaluating invasion risk and make recommendations for incremental tests from small-scale experiments to widespread, controlled introductions. First, local experiments should be performed to identify conditions that are favorable for germination, survival, and growth of candidate biofuel crops. Subsequently, experimental introductions in semi-natural areas can be used to assess factors important for establishment and performance such as disturbance, founder population size, and timing of introduction across variable habitats. Finally, to fully characterize invasion risk, experimental introductions should be conducted across the expected geographic range of cultivation over multiple years. Any field-based testing should be accompanied by safeguards and monitoring for early detection of spread. Despite the costs of conducting experimental tests of invasion risk, empirical screening will greatly improve our ability to determine if the benefits of a proposed biofuel species outweigh the projected risks of invasions.

Globally, bioethanol is the largest volume biofuel used in the transportation sector, with corn-based ethanol production occurring mostly in the US and sugarcane-based ethanol production occurring mostly in Brazil. Advances in technology and the resulting improved productivity in corn and sugarcane farming and ethanol conversion, together with biofuel policies, have contributed to the significant expansion of ethanol production in the past 20 years. These improvements have increased the energy and greenhouse gas (GHG) benefits of using bioethanol as opposed to using petroleum gasoline. This article presents results from our most recently updated simulations of energy use and GHG emissions that result from using bioethanol made from several feedstocks. The results were generated with the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model. In particular, based on a consistent and systematic model platform, we estimate life-cycle energy consumption and GHG emissions from using ethanol produced from five feedstocks: corn, sugarcane, corn stover, switchgrass and miscanthus.

We quantitatively address the impacts of a few critical factors that affect life-cycle GHG emissions from bioethanol. Even when the highly debated land use change GHG emissions are included, changing from corn to sugarcane and then to cellulosic biomass helps to significantly increase the reductions in energy use and GHG emissions from using bioethanol. Relative to petroleum gasoline, ethanol from corn, sugarcane, corn stover, switchgrass and miscanthus can reduce life-cycle GHG emissions by 19–48%, 40–62%, 90–103%, 77–97% and 101–115%, respectively. Similar trends have been found with regard to fossil energy benefits for the five bioethanol pathways.

We evaluate the comparative productivity of maize and sugarcane biofuel feedstocks as a function of latitude. Solar radiation for photosynthesis varies by latitude and contributes to differential productivity of tropical and temperate zones. We calculate comparative productivity in two ways—the amount of net sugar energy produced per unit area, and the amount produced per unit of net primary productivity (NPP). NPP measures the accumulation of energy in an ecosystem and can be used as a proxy for the capacity of an ecosystem to support biodiversity and a broader array of ecosystem services. On average sugarcane produces three times more energy per unit area than does maize. The comparative productivity advantage of sugarcane decreases with increases in latitude. Latitudes closer to the equator have higher NPP, so there is a greater trade-off between biofuel production and ecosystem productivity in the equatorial zones. The comparative productivity of sugarcane relative to maize is reduced when comparing biofuel energy per unit of NPP. Sugarcane is still twice as productive on average compared to maize in the amount of biofuel energy produced per unit of NPP. Regions near the equator have lower biofuel energy per unit NPP, making them less attractive for biofuels production.

This letter examines the effectiveness of various biofuel and climate policies in reducing future processing costs of cellulosic biofuels due to learning-by-doing. These policies include a biofuel production mandate alone and supplementing the biofuel mandate with other policies, namely a national low carbon fuel standard, a cellulosic biofuel production tax credit or a carbon price policy. We find that the binding biofuel targets considered here can reduce the unit processing cost of cellulosic ethanol by about 30% to 70% between 2015 and 2035 depending on the assumptions about learning rates and initial costs of biofuel production. The cost in 2035 is more sensitive to the speed with which learning occurs and less sensitive to uncertainty in the initial production cost. With learning rates of 5–10%, cellulosic biofuels will still be at least 40% more expensive than liquid fossil fuels in 2035. The addition of supplementary low carbon/tax credit policies to the mandate that enhance incentives for cellulosic biofuels can achieve similar reductions in these costs several years earlier than the mandate alone; the extent of these incentives differs across policies and different kinds of cellulosic biofuels.

In my original perspective piece (Pyle 2012), I mistakenly suggested that both Sawamura et al (2012) and Bourassa et al (2012) had attributed the lofting of the Nabro plume into the stratosphere to the strong Asian summer monsoon. In fact, while the ash clouds that accompanied the most explosive phases of the Nabro eruption were reported by the Toulouse VAAC to have reached 9–14 km on 13–14 June (Smithsonian Institution 2011), the Micro Pulse Lidar profile from Sede Boker, Israel, for the same date (14 June) shows a strong peak in the scattering ratio at around 17 km elevation. This was interpreted by Sawamura et al (2012) as being potentially due to ash and sulfate particles, and would suggest that the initial phase of the eruption injected material to this altitude. Sawamura et al (2012) also showed that the transport of the volcanic plume to Sede Boker was consistent with forward air-trajectory models, which for that time period showed a strong anticyclonic vortex due to the Asian summer monsoon, but they did not suggest that the monsoonal circulation was responsible for lofting of the plume. Bourassa et al (2012) identified a stratospheric enhancement of aerosol optical depth across eastern Asia beginning in early July 2011, which they attributed to the vertical transport of volcanic SO2 from the eruption plume into the lower stratosphere. Further work, using other techniques that can resolve altitude, is required to fully understand the time-history of the volcanic ash and gas plumes, and the sulfate aerosol that subsequently developed.

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