Table of contents

The diversity of wine production depends on subtle differences in microclimate and is therefore especially sensitive to climate change. A warmer climate will impact directly on wine-grapes through over-ripening, drying out, rising acidity levels, and greater vulnerability to pests and disease, resulting in changes in wine quality (e.g. complexity, balance and structure) or potentially the style of wine that can be produced. The growing scientific evidence for significant climate change in the coming decades means that adaptation will be of critical importance to the multi-billion dollar global wine-industry in general, and to quality wine producers in particular (White et al 2006, 2009; Hertsgaard 2011).

Adaptation is understood as an adjustment in natural or human systems in response to actual or expected environmental change, which moderates harm or exploits beneficial opportunities (IPCC 2007). Autonomous adaptation has been an integral part of the 20th century wine industry. Technological advances, changes in consumer demand, and global competition have meant that growers and producers have had to adapt to stay in business. The gradual temperature rise in the 20th Century (0.7 °C globally) has been accommodated successfully by gradual changes in vine management, technological measures, production control, and marketing (White et al 2009), although this has in many cases resulted in the production of bolder, more alcoholic wines (Hertsgaard 2011). In spite of this success, the wine industry is surprisingly conservative when it comes to considering longer term planned adaptation for substantial climate change impacts. A few producers are expanding to new locations at higher altitudes or cooler climates (e.g. Torres is developing new vineyards high in the Pyrenees, and Mouton Rothschild is setting up new vineyards in South America), and the legal and cultural restrictions of Appelation d'Origine Cȏntrollée (AOC) systems are being discussed (White et al 2009). Changes in the AOC regulations would, for example, be imperative if different grape varieties were to be cultivated in response to climate change. Thus far, however, there has been little coordinated action to plan ahead. The third Climate Change and Wine conference organised by the wine industry (April 2011 in Marbella, Spain; www.climatechangeandwine.com), exemplifies this situation since it focused on observed impacts and sustainable production (mitigation), rather than on adaptation to cope with projected change.

Awareness and understanding of potential change is crucial in raising adaptive capacity (Metzger et al 2008). Diffenbaugh et al (2011) have recently developed a novel method for communicating potential climate change impacts for the wine industry using climate adaptation wedges. These diagrams summarise projected climate change impacts over time and distinguish the net gain or loss in wine production under a range of adaptation strategies. The climate adaptation wedges form a strong synthesis, illustrating how some losses can be negated with continued autonomous adaptation, but that even with effective planned adaptation the quality of premium wine-grapes is likely to alter. Although the study focused on the western US, the adaptation wedges can be compiled fairly easily for other wine regions, or even individual producers. As such, they can form an important communication tool, but can also help guide longer term strategic planning.

Adaptation wedges require careful interpretation and it is probably this interpretation process that will provide the most valuable insights. The climate change impacts in the diagrams are based on observed relationships between climate and wine production, which is assumed to stay unchanged in the future. However, rapid climate change will be a great stimulus for a complex and unprecedented transformation of the industry. Similarly, the potential contributions of the alternative adaptation strategies to cope with climate change are best-estimates given current knowledge, but are open to discussion among experts. As such, the adaptation wedges can form an important component of strategic conversations (cf Van der Heijden 2000) as part of wider foresight analysis regarding the future directions for a region or a producer.

However, changes in the wine sector will not be mediated by physical changes in the climate alone. Changes in consumer preferences and the geography of global wine demand will have a strong effect on what wine is produced where. Moreover the method of changing grape varieties as an adaptation to climate change has potential pitfalls since consumers associate wine produced in a region with certain grape varieties. Changing this will change dramatically the content of the wine bottle, and how consumers will react to this is unknown. Regions such as Burgundy are likely to be strongly adversely affected by this issue since the pinot noir grape used to produce most Burgundian red wines is especially sensitive to climate conditions (White et al 2009). Would Burgundy wines continue to command such high prices if they were produced from Syrah rather than Pinot noir?

There are clearly challenging times ahead for the wine industry. Greater awareness of the likely changes ahead will benefit the industry at large, while strategic planning will provide individual producers with a comparative advantage over competitors. To cope with projected change, long term planned adaptation strategies deserve greater attention. These include possible geographic shifts in production, adjustments to AOC systems, and marketing strategies to influence consumer demand. Foresight methods, including scenario analysis (Rounsevell & Metzger 2010) and the exploration of climate adaptation wedges (Diffenbaugh et al 2011) are important tools that can help the wine industry in planning for an uncertain future.

References

Diffenbaugh N S, White M A, Jones G V and Ashfaq M 2011 Climate adaptation wedges: a case study of premium wine in the western United States Environ. Res. Lett.6 024024

Hertsgaard M 2011 Hot: Living Through the Next Fifty Years on Earth (New York: Houghton Mifflin Harcourt)

IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press)

Metzger M J, Schröter D, Leemans R and Cramer W 2008 A spatially explicit and quantitative vulnerability assessment of ecosystem service change in Europe Reg. Environ. Change8 91–107

Rounsevell M D A and Metzger M J 2010 Developing qualitative scenario storylines for environmental change assessment Wiley Interdisciplinary Reviews: Climate Change1 606–19

Van der Heijden K 2000 Scenarios: The Art of Strategic Conversation 2nd ed (Chichester: John Wiley & Sons)

White M A, Diffenbaugh N S, Jones G V, Pal J S and Giorgi F 2006 Extreme heat reduces and shifts United States premium wine production in the 21st century Proc. Natl Acad. Sci.103 11217–22

White M A, Whalen P and Jones G V 2009 Land and wine Nature Geoscience2 82–4

Observed and model simulated warming is particularly large in high latitudes, and hence the Arctic is often seen as the posterchild of vulnerability to global warming. However, Mahlstein et al (2011) point out that the signal of climate change is emerging locally from that of climate variability earliest in regions of low climate variability, based on climate model data, and in agreement with observations. This is because high latitude regions are not only regions of strong feedbacks that enhance the global warming signal, but also regions of substantial climate variability, driven by strong dynamics and enhanced by feedbacks (Hall 2004). Hence the spatial pattern of both observed warming and simulated warming for the 20th century shows strong warming in high latitudes, but this warming occurs against a backdrop of strong variability. Thus, the ratio of the warming to internal variability is not necessarily highest in the regions that warm fastest—and Mahlstein et al illustrate that it is actually the low-variability regions where the signal of local warming emerges first from that of climate variability. Thus, regions with strongest warming are neither the most important to diagnose that forcing changes climate, nor are they the regions which will necessarily experience the strongest impact.

The importance of the signal-to-noise ratio has been known to the detection and attribution community, but has been buried in technical 'optimal fingerprinting' literature (e.g., Hasselmann 1979, Allen and Tett 1999), where it was used for an earlier detection of climate change by emphasizing aspects of the fingerprint of global warming associated with low variability in estimates of the observed warming. What, however, was not discussed was that the local signal-to-noise ratio is of interest also for local climate change: where temperatures emerge from the range visited by internal climate variability, it is reasonable to assume that changes in climate will also cause more impacts than temperatures that have occurred frequently due to internal climate variability. Determining when exactly temperatures enter unusual ranges may be done in many different ways (and the paper shows several, and more could be imagined), but the main result of first local emergence in low latitudes remains robust.

A worrying factor is that the regions where the signal is expected to emerge first, or is already emerging are largely regions in Africa, parts of South and Central America, and the Maritime Continent; regions that are vulnerable to climate change for a variety of regions (see IPCC 2007), and regions which contribute generally little to global greenhouse gas emissions. In contrast, strong emissions of greenhouse gases occur in regions of low warming-to-variability ratio.

To get even closer to the relevance of this finding for impacts, it would be interesting to place the emergence of highly unusual summer temperatures in the context not of internal variability, but in the context of variability experienced by the climate system prior to the 20th century, as, e.g. documented in palaeoclimatic reconstructions and simulated in simulations of the last millennium (see Jansen et al 2007). External forcing has moved the temperature range around more strongly for some regions and in some seasons than others. For example, while reconstructions of summer temperatures in Europe appear to show small long-term variations, winter shows deep drops in temperature in the little Ice Age and a long-term increase since then (Luterbacher et al 2004), which was at least partly caused by external forcing (Hegerl et al 2011a) and therefore 'natural variability' may be different from internal variability. A further interesting question in attempts to provide a climate-based proxy for impacts of climate change is: to what extent does the rapidity of change matter, and how does it compare to trends due to natural variability? It is reasonable to assume that fast changes impact ecosystems and society more than slow, gradual ones. Also, is it really the mean seasonal temperature that counts, or should the focus change to extremes (see Hegerl et al 2011b)? Is seasonal mean exceedance of the prior temperature envelope a good and robust measure that also reflects these other, more complex diagnostics? Lots of food for thought and research!

References

Allen M R and Tett S F B 1999 Checking for model consistency in optimal finger printing Clim. Dyn.15 419–34

Hall A 2004 The role of surface albedo feedback in climate J. Clim.17 1550–68

Hasselmann K 1979 On the signal-to-noise problem in atmospheric response studies Meteorology of Tropical Oceans ed D B Shaw (Bracknell: Royal Meteorological Society) pp 251–9

Hegerl G C, Luterbacher J, Gonzalez-Ruoco F, Tett S F B and Xoplaki E 2011a Influence of human and natural forcing on European seasonal temperatures Nature Geoscience4 99–103

Hegerl G, Hanlon H and Beierkuhnlein C 2011b Climate science: elusive extremes Nature Geoscience4 142–3

IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press)

Jansen E et al 2007 Palaeoclimate 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 et al (Cambridge: Cambridge University Press)

Luterbacher J et al 2004 European seasonal and annual temperature variability, trends, and extremes since 1500 Science303 1499–503

Mahlstein I, Knutti R, Solomon S and Portmann R W 2011 Early onset of significant local warming in low latitude countries Environ. Res. Lett.6 034009

Transport currently represents approximately 19% of the global energy demand and accounts for about 23% of the global carbon dioxide emissions (IEA 2009). As the demand for mobility is expected to continue to increase in the coming decades, the stabilization of atmospheric carbon dioxide levels will require the evolution of transport, along with power generation, building design and manufacturing. The continued development of these sectors will need to include changes in energy sources, energy delivery, materials, infrastructure and human behavior. Pathways to reducing carbon from the transport sector have unique challenges and opportunities that are inherent to the human choices and behavioral patterns that mold the transportation systems and the associated energy needs. Technology, government investment, and regulatory policies have a significant impact on the formulation of transportation infrastructure; however, the role of human behavior and public acceptance on the efficiency and effectiveness of transport systems should not be underestimated.

Although developed, rapidly developing, and underdeveloped nations face different challenges in the establishment of transport infrastructure that can meet transport needs while achieving sustainable carbon dioxide emissions, the constraints that establish the domain of possibilities are closely related for all nations. These constraints include capital investment, fuel supplies, power systems, and human behavior. Throughout the world, there are considerable efforts directed at advancing and optimizing the financing of sustainable infrastructures, the production of low carbon fuels, and the production of advanced power systems, but the foundational work on methods to understand human preferences and behavior within the context of transport and the valuation of reductions in carbon dioxide emissions is greatly lagging behind. These methods and the associated understanding of human behavior and the willingness to pay for reduced carbon emissions are central to the design and optimization of future low carbon transport systems.

Gaker et al (2011) suggest a framework, and provide insight into the willingness of transport consumers to pay for emission reductions of carbon dioxide from their personal transport choices within the context of other attributes of transport variables. The results of this study, although limited to a small demographic segment of the US population, demonstrate that people can integrate information on greenhouse gas emissions with other transport attributes including cost and time. Likewise, the research shows that the study group was willing to pay for reduction in greenhouse gas emissions associated with their transport choices. The study examined auto purchase choice, transport mode choice and transport route choice, which represent key decisions associated with transport that impact greenhouse gas emissions. Interestingly, they found that the study group was willing to pay for reductions in greenhouse gas emissions at a relatively consistent price across these transport choices. Clearly, the study results may not broadly apply to all demographics of users of transport, even in the study domain, due to the small demographic segment that was examined and the fact that the study was conducted in the laboratory. However, the methods used by Gaker et al (2011) are cause for optimism that future studies can obtain much needed mapping of transport preferences and willingness to pay for greenhouse gas emission reductions associated with personal transport choices.

Although the Gaker et al (2011) study is directed at understanding the promotion of low carbon transport in the context of existing infrastructures, the ability of these studies to elucidate human behavior and preferences within the trade-offs of transport are critical to the design of future transport systems that seek to meet transport demand with constrained greenhouse gas emissions. Additional studies of this nature that examine broader demographic groups in real world conditions are greatly needed in different regions of the US and around the world.

As interventions are sought to stabilize atmospheric carbon dioxide levels at levels that are expected to have limited climate impact, there is recognition that the mitigation strategies that will be implemented in the next 5–10 years will have a profound impact on the ability to constrain climate change. The evolution of the transport infrastructure over the next decade, which will provide intermodal opportunities and modal trade-offs, will be an important constraint in the ability of transport systems to reduce greenhouse gas emissions. Likewise, the evolution of the transport infrastructure over the next decade will have an equally profound impact on the ability of transport systems to meet society's expectations for transport in a cost effective and efficient manner. The ability to design and build transport infrastructures that can achieve maximum reductions in greenhouse gas emissions while satisfying the demand for transport by the society relies on the ability to understand the human behavior and human preferences for transport in the context of costs, time, time variability, safety and emission reductions. The study by Gaker et al (2011) is central to answering these questions and will hopefully serve as a conduit to motivate additional studies that examine broader segments of society in developed, rapidly developing, and underdeveloped nations to provide the human input needed to assure future transport systems that can meet greenhouse gas emission reduction targets and the transport needs of society.

References

Gaker D, Vautin D, Vij A and Walker J L 2011 The power and value of green in promoting sustainable transport behavior Environ. Res. Lett.6 034010

IEA 2009 Transport, Energy and CO₂: Moving Toward Sustainability (Paris: International Energy Agency) (available at www.iea.org/publications/free_new_Desc.asp?PUBS_ID=2133)

Modifications to the surface albedo through the deployment of cool roofs and pavements (reflective materials) and photovoltaic arrays (low reflection) have the potential to change radiative forcing, surface temperatures, and regional weather patterns. In this work we investigate the regional climate and radiative effects of modifying surface albedo to mimic massive deployment of cool surfaces (roofs and pavements) and, separately, photovoltaic arrays across the United States. We use a fully coupled regional climate model, the Weather Research and Forecasting (WRF) model, to investigate feedbacks between surface albedo changes, surface temperature, precipitation and average cloud cover. With the adoption of cool roofs and pavements, domain-wide annual average outgoing radiation increased by 0.16 ± 0.03 W m ^{− 2} (mean ± 95% C.I.) and afternoon summertime temperature in urban locations was reduced by 0.11–0.53 °C, although some urban areas showed no statistically significant temperature changes. In response to increased urban albedo, some rural locations showed summer afternoon temperature increases of up to + 0.27 °C and these regions were correlated with less cloud cover and lower precipitation. The emissions offset obtained by this increase in outgoing radiation is calculated to be 3.3 ± 0.5 Gt CO₂ (mean ± 95% C.I.). The hypothetical solar arrays were designed to be able to produce one terawatt of peak energy and were located in the Mojave Desert of California. To simulate the arrays, the desert surface albedo was darkened, causing local afternoon temperature increases of up to + 0.4 °C. Due to the solar arrays, local and regional wind patterns within a 300 km radius were affected. Statistically significant but lower magnitude changes to temperature and radiation could be seen across the domain due to the introduction of the solar arrays. The addition of photovoltaic arrays caused no significant change to summertime outgoing radiation when averaged over the full domain, as interannual variation across the continent obscured more consistent local forcing.

Three rural electrification options are analysed showing the cost optimal conditions for a sustainable energy development applying renewable energy sources in Africa. A spatial electricity cost model has been designed to point out whether diesel generators, photovoltaic systems or extension of the grid are the least-cost option in off-grid areas. The resulting mapping application offers support to decide in which regions the communities could be electrified either within the grid or in an isolated mini-grid. Donor programs and National Rural Electrification Agencies (or equivalent governmental departments) could use this type of delineation for their program boundaries and then could use the local optimization tools adapted to the prevailing parameters.

This study illustrates how alternative and supplemental community-level greenhouse gas (GHG) inventory techniques could improve climate action planning. Eighteen US community GHG inventories are reviewed for current practice. Inventory techniques could be improved by disaggregating the sectors reported, reporting inventory uncertainty and variability, and aligning inventories with local organizations that could facilitate emissions reductions. The potential advantages and challenges of supplementing inventories with comparative benchmarks are also discussed. While GHG inventorying and climate action planning are nascent fields, these techniques can improve CAP design, help communities set more meaningful emission reduction targets, and facilitate CAP implementation and progress monitoring.

Recent research has suggested that relatively cold UK winters are more common when solar activity is low (Lockwood et al 2010 Environ. Res. Lett.5 024001). Solar activity during the current sunspot minimum has fallen to levels unknown since the start of the 20th century (Lockwood 2010 Proc. R. Soc. A 466 303–29) and records of past solar variations inferred from cosmogenic isotopes (Abreu et al 2008 Geophys. Res. Lett.35 L20109) and geomagnetic activity data (Lockwood et al 2009 Astrophys. J.700 937–44) suggest that the current grand solar maximum is coming to an end and hence that solar activity can be expected to continue to decline. Combining cosmogenic isotope data with the long record of temperatures measured in central England, we estimate how solar change could influence the probability in the future of further UK winters that are cold, relative to the hemispheric mean temperature, if all other factors remain constant. Global warming is taken into account only through the detrending using mean hemispheric temperatures. We show that some predictive skill may be obtained by including the solar effect.

Well informed decisions on climate policy necessitate simulation of the climate system for a sufficiently wide range of emissions scenarios. While recent literature has been devoted to low emissions futures, the potential for very high emissions has not been thoroughly explored. We specify two illustrative emissions scenarios that are significantly higher than the A1FI scenario, the highest scenario considered in past IPCC reports, and simulate them in a global climate model to investigate their climate change implications. Relative to the A1FI scenario, our highest scenario results in an additional 2 K of global mean warming above A1FI levels by 2100, a complete loss of arctic summer sea-ice by 2070 and an additional 43% sea level rise due to thermal expansion above A1FI levels by 2100. Regional maximum temperature increases from late 20th century values are 50–100% greater than A1FI increases, with some regions such as the Central US, the Tibetan plateau and Alaska showing a 300–400% increase above A1FI levels.

The role of leading modes of Indo-Pacific climate variability is investigated for modulation of the strength of the Indian summer monsoon during the period 1877–2006. In particular, the effect of Indian Ocean conditions on the relationship between the El Niño–Southern Oscillation (ENSO) and the Indian monsoon is explored. Using an extended classification for ENSO and Indian Ocean dipole (IOD) events for the past 130 years and reanalyses, we have expanded previous interannual work to show that variations in Indian Ocean conditions modulate the ENSO–Indian monsoon relationship also on decadal timescales. El Niño events are frequently accompanied by a significantly reduced Indian monsoon and widespread drought conditions due to anomalous subsidence associated with a shift in the descending branch of the zonal Walker circulation. However, for El Niño events that co-occur with positive IOD (pIOD) events, Indian Ocean conditions act to counter El Niño's drought-inducing subsidence by enhancing moisture convergence over the Indian subcontinent, with an average monsoon season resulting. Decadal modulations of the frequency of independent and combined El Niño and pIOD events are consistent with a strengthened El Niño–Indian monsoon relationship observed at the start of the 20th century and the apparent recent weakening of the El Niño–Indian monsoon relationship.

The ¹³C concentration in atmospheric CO₂ has been declining over the past 150 years as large quantities of ¹³C-depleted CO₂ from fossil fuel burning are added to the atmosphere. Deforestation and other land use changes have also contributed to the trend. Looking at the ¹³C variations in the atmosphere and in annual growth rings of trees allows us to estimate CO₂ uptake by land plants and the ocean, and assess the response of plants to climate. Here I show that the effects of the declining ¹³C trend in atmospheric CO₂ are recorded in the isotopic composition of paper used in the printing industry, which provides a well-organized archive and integrated material derived from trees' cellulose. ¹³C analyses of paper from two European and two American publications showed, on average, a − 1.65 ± 1.00‰ trend between 1880 and 2000, compared with − 1.45 and − 1.57‰ for air and tree-ring analyses, respectively. The greater decrease in plant-derived ¹³C in the paper we tested than in the air is consistent with predicted global-scale increases in plant intrinsic water-use efficiency over the 20th century. Distinct deviations from the atmospheric trend were observed in both European and American publications immediately following the World War II period.

A generalized distribution for the water residence time in hydrological transport is proposed in the form of the tempered one-sided stable (TOSS) density. It is shown that limiting cases of the TOSS distribution recover virtually all distributions that have been considered in the literature for hydrological transport, from plug flow to flow reactor, the advection–dispersion model, and the gamma and Levy densities. The stable property of TOSS is particularly important, enabling a seamless transition between a time-domain random walk, and the Lagrangian (trajectory) approach along hydrological transport pathways.

The Earth is warming on average, and most of the global warming of the past half-century can very likely be attributed to human influence. But the climate in particular locations is much more variable, raising the question of where and when local changes could become perceptible enough to be obvious to people in the form of local warming that exceeds interannual variability; indeed only a few studies have addressed the significance of local signals relative to variability. It is well known that the largest total warming is expected to occur in high latitudes, but high latitudes are also subject to the largest variability, delaying the emergence of significant changes there. Here we show that due to the small temperature variability from one year to another, the earliest emergence of significant warming occurs in the summer season in low latitude countries (≈25°S–25°N). We also show that a local warming signal that exceeds past variability is emerging at present, or will likely emerge in the next two decades, in many tropical countries. Further, for most countries worldwide, a mean global warming of 1 °C is sufficient for a significant temperature change, which is less than the total warming projected for any economically plausible emission scenario. The most strongly affected countries emit small amounts of CO₂ per capita and have therefore contributed little to the changes in climate that they are beginning to experience.

While it is increasingly popular to broadcast information regarding environmental impact, little is known regarding the effects that this information has on human behavior. This research aims to provide insight into whether, and to what extent, presenting environmental attributes of transport alternatives influences individual transport decisions. We designed and conducted three experiments in which subjects (UC Berkeley undergraduates) were presented with hypothetical scenarios of transport decisions, including auto purchase choice, mode choice, and route choice. We analyzed their decisions via a choice model to determine how they value reducing their emissions relative to other attributes. We found that our subjects are willing to adjust their behavior to reduce emissions, exhibiting an average willingness to pay for emissions reduction, or value of green (VoG), of 15 cents per pound of CO₂ saved. Despite concern that people cannot meaningfully process quantities of CO₂, we found evidence to the contrary in our subject pool in that the estimated VoG was consistent across context (the wide range of transport decisions that we presented) and presentation (e.g., whether the information was presented in tons or pounds, or whether a social reference point of the emissions of an average person was provided). We also found significant heterogeneity in VoG, with most of the respondents valuing green somewhere between 0 and 70 cents per pound and with women, on average, willing to pay 7 cents more per saved pound than men. While the findings are encouraging, further work is required to determine whether they hold outside of a lab environment and with a more representative pool of subjects.

Measurements of ¹³¹I (T_1/2 = 8.04 days) activities have been performed in the IFIN HH (Horia Hulubei National Institute of Physics and Nuclear Engineering) underground laboratory situated in Unirea salt mine, Slănic-Prahova, Romania. The rainwater samples were collected starting on 27 March from Braşov and Slănic-Prahova. Also sheep and goat milk samples were collected in the Slănic, Braşov and Iaşi areas and measurements were subsequently made on them. The measurements on the samples were made at the IFIN HH's underground laboratory in an ultra-low radiation background, using a high resolution gamma-ray spectrometer equipped with a GeHP (hyperpure) detector having a full width at half-maximum of 1.80 keV at 1332.48 keV for the second ⁶⁰Co gamma ray and a relative efficiency of 22.8%. The results show a specific activity of ¹³¹I from < 0.063 to 0.75 Bq l ^{− 1} for rain. In the milk samples the specific activity varied from < 0.12 to 5.2 Bq l ^{− 1}.

Multivariate alteration detection (MAD) and Bayesian inference (BI) methods are used to analyze land cover changes with Landsat images for the Alaskan Yukon River Basin from 1984 to 2008. The US Geological Survey National Land Cover Database 2001 (NLCD 2001) is treated as reference information to detect the changes. It is found that the regional land cover change has three general trends with various potential causes during the study period: (1) forests decreased mainly due to wildfire, (2) the closed water bodies were shrinking possibly due to permafrost degradation if water drains well in discontinuous permafrost regions, (3) shrubs had expanded and a large portion of grassland was converted into shrubland likely due to forest fire and warming. The uncertainty of this analysis may mainly arise from image acquisition date differences and illumination angles and remaining cloud contamination to the images. This study provides a method to analyze land cover changes with Landsat data for other regions. The developed land cover data should help future understanding of permafrost dynamics, biogeochemistry, hydrology and regional climate in the region.

The frequency and intensity of typhoons have been a focus in studying typhoon-related climate changes. In this study, we focus on a seasonal cycle of intense typhoons (category 4 and 5) over the western North Pacific, particularly changes in the number of intense typhoons in early summer. In general, 81% of intense typhoons occur in July–November (JASON), with maxima in September and October. Our analysis shows that intense typhoons have tended to occur more frequently in May since the year 2000. Before 2000, intense typhoons seldom occurred in May, with a frequency of around once per decade. After 2000, however, the frequency of intense typhoons has become much higher in May—almost once per year. We have also examined changes in the large-scale environment in the past few decades. The results show that the large-scale environment did become more favorable for intense typhoons in the 2000s, which is consistent with a larger tropical cyclone genesis index. The changes include warmer sea surface temperature, higher sea surface height, larger upper-ocean heat content, weaker vertical wind shear, increased tropospheric water vapor, and greater water vapor in the mid-troposphere. The last two might be more important than the others.

This study estimates the life cycle greenhouse gas (GHG) emissions from the production of Marcellus shale natural gas and compares its emissions with national average US natural gas emissions produced in the year 2008, prior to any significant Marcellus shale development. We estimate that the development and completion of a typical Marcellus shale well results in roughly 5500 t of carbon dioxide equivalent emissions or about 1.8  g CO₂e/MJ of gas produced, assuming conservative estimates of the production lifetime of a typical well. This represents an 11% increase in GHG emissions relative to average domestic gas (excluding combustion) and a 3% increase relative to the life cycle emissions when combustion is included. The life cycle GHG emissions of Marcellus shale natural gas are estimated to be 63–75  g CO₂e/MJ of gas produced with an average of 68 g CO₂e/MJ of gas produced. Marcellus shale natural gas GHG emissions are comparable to those of imported liquefied natural gas. Natural gas from the Marcellus shale has generally lower life cycle GHG emissions than coal for production of electricity in the absence of any effective carbon capture and storage processes, by 20–50% depending upon plant efficiencies and natural gas emissions variability. There is significant uncertainty in our Marcellus shale GHG emission estimates due to eventual production volumes and variability in flaring, construction and transportation.

Thermoelectric power plants require large volumes of water for cooling, which can introduce drought vulnerability and compete with other water needs. Alternative cooling technologies, such as cooling towers and hybrid wet–dry or dry cooling, present opportunities to reduce water diversions. This case study uses a custom, geographically resolved river basin-based model for eleven river basins in the state of Texas (the Brazos and San Jacinto–Brazos, Colorado and Colorado–Brazos, Cypress, Neches, Nueces, Red, Sabine, San Jacinto, and Trinity River basins), focusing on the Brazos River basin, to analyze water availability during drought. We utilized two existing water availability models for our analysis: (1) the full execution of water rights—a scenario where each water rights holder diverts the full permitted volume with zero return flow, and (2) current conditions—a scenario reflecting actual diversions with associated return flows. Our model results show that switching the cooling technologies at power plants in the eleven analyzed river basins to less water-intensive alternative designs can potentially reduce annual water diversions by 247–703  million m³—enough water for 1.3–3.6 million people annually. We consider these results in a geographic context using geographic information system tools and then analyze volume reliability, which is a policymaker's metric that indicates the percentage of total demand actually supplied over a given period. This geographic and volume reliability analysis serves as a measure of drought susceptibility in response to changes in thermoelectric cooling technologies. While these water diversion savings do not alleviate all reliability concerns, the additional streamflow from the use of dry cooling alleviates drought concerns for some municipal water rights holders and might also be sufficient to uphold instream flow requirements for important bays and estuaries on the Texas Gulf coast.

Large lakes may constitute a significant component of regional surface–atmosphere fluxes, but few efforts have been made to quantify these fluxes. Tracer-transport inverse models that infer the CO₂ flux from the atmospheric concentration typically assume that the influence from large lakes is negligible. CO₂ observations from a tall tower in Wisconsin segregated by wind direction suggested a CO₂ signature from Lake Superior. To further investigate this difference, source–receptor influence functions derived using a mesoscale transport model were applied and results revealed that air masses sampled by the tower have a transit time over the lake, primarily in winter when the total lake influence on the tower can exceed 20% of the total influence of the regional domain. When the influence functions were convolved with air–lake fluxes estimated from a physical–biogeochemical lake model, the overall total contribution of lake fluxes to the tall tower CO₂ were mostly negligible, but potentially detectable in certain periods of fall and winter when lake carbon exchange can be strong and land carbon efflux weak. These findings suggest that large oligotrophic lakes would not significantly influence inverse models that incorporate tall tower CO₂.

Biomass from cellulosic bioenergy crops is expected to play a substantial role in future energy systems, especially if climate policy aims at stabilizing greenhouse gas concentration at low levels. However, the potential of bioenergy for climate change mitigation remains unclear due to large uncertainties about future agricultural yield improvements and land availability for biomass plantations.

This letter, by applying a modelling framework with detailed economic representation of the land and energy sector, explores the cost-effective contribution of bioenergy to a low-carbon transition, paying special attention to implications for the land system. In this modelling framework, bioenergy competes directly with other energy technology options on the basis of costs, including implicit costs due to biophysical constraints on land and water availability.

As a result, we find that bioenergy from specialized grassy and woody bioenergy crops, such as Miscanthus or poplar, can contribute approximately 100 EJ in 2055 and up to 300 EJ of primary energy in 2095. Protecting natural forests decreases biomass availability for energy production in the medium, but not in the long run. Reducing the land available for agricultural use can partially be compensated for by means of higher rates of technological change in agriculture. In addition, our trade-off analysis indicates that forest protection combined with large-scale cultivation of dedicated bioenergy is likely to affect bioenergy potentials, but also to increase global food prices and increase water scarcity. Therefore, integrated policies for energy, land use and water management are needed.

Numerical models predict that the recycling rate of atmospheric moisture decreases with time at the global scale, in response to global warming. A recent observational study (Wentz et al 2007 Science317 233–5) did not agree with the results from numerical models. Here, we examine the recycling rate by using the latest data sets for precipitation and water vapor, and suggest a consistent view of the global recycling rate of atmospheric moisture between numerical models and observations. Our analyses show that the recycling rate of atmospheric moisture has also decreased over the global oceans during the past two decades. In addition, we find different temporal variations of the recycling rate in different regions when exploring the spatial pattern of the recycling rate. In particular, the recycling rate has increased in the high-precipitation region around the equator (i.e., the intertropical convergence zone) and decreased in the low-precipitation region located either side of the equator over the past two decades. Further exploration suggests that the temporal variation of precipitation is stronger than that of water vapor, which results in the positive trend of the recycling rate in the high-precipitation region and the negative trend of the recycling rate in the low-precipitation region.

Markets influence the global patterns of urbanization, deforestation, agriculture and other land use systems. Yet market influence is rarely incorporated into spatially explicit global studies of environmental change, largely because consistent global data are lacking below the national level. Here we present the first high spatial resolution gridded data depicting market influence globally. The data jointly represent variations in both market strength and accessibility based on three market influence indices derived from an index of accessibility to market locations and national level gross domestic product (purchasing power parity). These indices show strong correspondence with human population density while also revealing several distinct and useful relationships with other global environmental patterns. As market influence grows, the need for high resolution global data on market influence and its dynamics will become increasingly important to understanding and forecasting global environmental change.

We assess the issues of urban effects on the precipitation over the Pearl River Delta (PRD) metropolitan regions of China. The spatial and temporal variations of strong versus weak precipitation over the PRD and surrounding nonurban areas are investigated. The results show that the urbanization signatures in strong precipitation are significantly different from those in weak precipitation over the urban areas. The PRD experiences more strong precipitation but less weak precipitation compared to surrounding nonurban regions. In addition, the strong precipitation over the PRD displays a pronounced seasonal variation. The seasonality of weak precipitation, however, is much weaker over the PRD compared to the surrounding nonurban regions. Moreover, a strengthening in the precipitation intensity, a reduction in the rainfall frequency and an increase in the convective precipitation as well as the afternoon precipitation are found over the urban areas, which are probably associated with the abundance in strong precipitation and the deficit in weak precipitation over the PRD.

Over the last 40 years, Lake Chad, once the sixth largest lake in the world, has decreased by more than 90% in area. In this study, we use a hydrological model coupled with a lake/wetland algorithm to simulate the effects of lake bathymetry, human water use, and decadal climate variability on the lake's level, surface area, and water storage. In addition to the effects of persistent droughts and increasing irrigation withdrawals on the shrinking, we find that the lake's unique bathymetry—which allows its division into two smaller lakes—has made it more vulnerable to water loss. Unfortunately the lake's split is favored by the 1952–2006 climatology. Failure of the lake to remerge with renewed rainfall in the 1990s following the drought years of the 1970s and 1980s is a consequence of irrigation withdrawals. Under current climate and water use, a full recovery of the lake is unlikely without an inter-basin water transfer. Breaching the barrier separating the north and south lakes would reduce the amount of supplemental water needed for recovery.

Coupled ocean–atmospheric models suffer from the common bias of a spurious rain belt south of the central equatorial Pacific throughout the year. Observational constraints on key processes responsible for this bias are scarce. The recently available reanalysis from a coupled model system for the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data is a potential benchmark for climate models in this region. Its suitability for model evaluation and validation, however, needs to be established. This paper examines the mixed layer heat budget and the ocean surface currents—key factors for the sea surface temperature control in the double Inter-Tropical Convergence Zone in the central Pacific—from 5°S to 10°S and 170°E to 150°W. Two independent approaches are used. The first approach is through comparison of CFSR data with collocated station observations from field experiments; the second is through the residual analysis of the heat budget of the mixed layer. We show that the CFSR overestimates the net surface flux in this region by 23 W m ^{− 2}. The overestimated net surface flux is mainly due to an even larger overestimation of shortwave radiation by 44 W m ^{− 2}, which is compensated by a surface latent heat flux overestimated by 14 W m ^{− 2}. However, the quality of surface currents and the associated oceanic heat transport in CFSR are not compromised by the surface flux biases, and they agree with the best available estimates. The uncertainties of the observational data from field experiments are also briefly discussed in the present study.

Electricity from geothermal resources has the potential to supply a significant portion of US baseload electricity. We estimate the water requirements of geothermal electricity and the impact of potential scaling up of such electricity on water demand in various western states with rich geothermal resources but stressed water resources. Freshwater, degraded water, and geothermal fluid requirements are estimated explicitly. In general, geothermal electricity has higher water intensity (l kWh ^{− 1}) than thermoelectric or solar thermal electricity. Water intensity decreases with increase in resource enthalpy, and freshwater gets substituted by degraded water at higher resource temperatures. Electricity from enhanced geothermal systems (EGS) could displace 8–100% of thermoelectricity generated in most western states. Such displacement would increase stress on water resources if re-circulating evaporative cooling, the dominant cooling system in the thermoelectric sector, is adopted. Adoption of dry cooling, which accounts for 78% of geothermal capacity today, will limit changes in state-wide freshwater abstraction, but increase degraded water requirements. We suggest a research and development focus to develop advanced energy conversion and cooling technologies that reduce water use without imposing energy and consequent financial penalties. Policies should incentivize the development of higher enthalpy resources, and support identification of non-traditional degraded water sources and optimized siting of geothermal plants.

Satellite remote sensing was combined with the NASA-CASA (Carnegie Ames Stanford Approach) carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO₂ uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon river basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO₂ to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to those for forests outside the main river floodplains.

Using high-quality precipitation data from 524 stations, the trends of a set of precipitation variables during the main rain season (May–September) from 1961 to 2008 for different climate regions in China were analysed. However, different characteristics were displayed in different regions of China. In most temperate monsoon regions (north-eastern China), total rain-season precipitation and precipitation days showed decreasing trends; positive tendencies in precipitation intensity were, however, noted for most stations in this region. It is suggested that the decrease in rain-season precipitation is mainly related to there being fewer rain days and a change towards drier conditions in north-eastern China, and as a result, the available water resources have been negatively affected in the temperate monsoon regions. In most subtropical and tropical monsoon climate regions (south-eastern China), the rain-season precipitation and precipitation days (11–50, with > 50 mm) showed slightly positive trends. However, precipitation days with ≤ 10 mm decreased in these regions. Changes towards wetter conditions in this area, together with more frequent heavy rainfall events causing floods, have a severe impact on peoples' lives and socio-economic development. In general, the rain-season precipitation, precipitation days and rain-season precipitation intensity had all increased in the temperate continental and plateau/mountain regions of western China. This increase in rain-season precipitation has been favourable to pasture growth.

Soot particles are an important component of atmospheric aerosol and their interaction with water is important for their climate effects. The hygroscopicity of fresh and photochemically aged soot and secondary organic aerosol (SOA) from diesel passenger car emissions was studied under atmospherically relevant conditions in a smog chamber at sub-and supersaturation of water vapor. Fresh soot particles show no significant hygroscopic growth nor cloud condensation nucleus (CCN) activity. Ageing by condensation of SOA formed by photooxidation of the volatile organic carbon (VOC) emission leads to increased water uptake and CCN activity as well as to a compaction of the initially non-spherical soot particles when exposed to high relative humidity (RH). It is important to consider the latter effect for the interpretation of mobility based measurements. The vehicle with oxidation catalyst (EURO3) emits much fewer VOCs than the vehicle without after-treatment (EURO2). Consequently, more SOA is formed for the latter, resulting in more pronounced effects on particle hygroscopicity and CCN activity. Nevertheless, the aged soot particles did not reach the hygroscopicity of pure SOA particles formed from diesel VOC emissions, which are similarly hygroscopic (0.06 < κ_{H − TDMA} < 0.12 and 0.09 < κ_CCN < 0.14) as SOA from other precursor gases investigated in previous studies.

Studies indicate that the mortality effects of temperature may vary by population and region, although little is known about the vulnerability of subgroups to these risks in Korea. This study examined the relationship between temperature and cause-specific mortality for Seoul, Korea, for the period 2000–7, including whether some subgroups are particularly vulnerable with respect to sex, age, education and place of death. The authors applied time-series models allowing nonlinear relationships for heat- and cold-related mortality, and generated exposure–response curves. Both high and low ambient temperatures were associated with increased risk for daily mortality. Mortality risk was 10.2% (95% confidence interval 7.43, 13.0%) higher at the 90th percentile of daily mean temperatures (25 °C) compared to the 50th percentile (15 °C). Mortality risk was 12.2% (3.69, 21.3%) comparing the 10th (−1 °C) and 50th percentiles of temperature. Cardiovascular deaths showed a higher risk to cold, whereas respiratory deaths showed a higher risk to heat effect, although the differences were not statistically significant. Susceptible populations were identified such as females, the elderly, those with no education, and deaths occurring outside of a hospital for heat- and cold-related total mortality. Our findings provide supportive evidence of a temperature–mortality relationship in Korea and indicate that some subpopulations are particularly vulnerable.

Since the end of World War II, global agriculture has undergone a period of rapid intensification achieved through a combination of increased applications of chemical fertilizers, pesticides, and herbicides, the implementation of best management practice techniques, mechanization, irrigation, and more recently, through the use of optimized seed varieties and genetic engineering. However, not all crops and not all regions of the world have realized the same improvements in agricultural intensity. In this study we examine both the magnitude and spatial variation of new agricultural production potential from closing of 'yield gaps' for 20 ethanol and biodiesel feedstock crops. With biofuels coming under increasing pressure to slow or eliminate indirect land-use conversion, the use of targeted intensification via established agricultural practices might offer an alternative for continued growth. We find that by closing the 50th percentile production gap—essentially improving global yields to median levels—the 20 crops in this study could provide approximately 112.5 billion liters of new ethanol and 8.5 billion liters of new biodiesel production. This study is intended to be an important new resource for scientists and policymakers alike—helping to more accurately understand spatial variation of yield and agricultural intensification potential, as well as employing these data to better utilize existing infrastructure and optimize the distribution of development and aid capital.

We have combined the US EPA MM5/MCIP/SMOKE/CMAQ modeling system with a dynamic soil model, the pesticide emission model (PEM), to create a multimedia chemical transport model capable of describing the important physical and chemical processes involving pesticides in the soil, in the atmosphere, and on the surface of vegetation. These processes include: agricultural practices (e.g. soil tilling and pesticide application mode); advection and diffusion of pesticides, moisture, and heat in the soil; partitioning of pesticides between soil organic carbon and interstitial water and air; emissions from the soil to the atmosphere; gas–particle partitioning and transport in the atmosphere; and atmospheric chemistry and dry and wet deposition of pesticides to terrestrial and water surfaces. The modeling system was tested by simulating toxaphene in a domain that covers most of North America for the period from 1 January 2000 to 31 December 2000. The results show obvious transport of the pesticide from the heavily contaminated soils in the southern United States and Mexico to water bodies including the Atlantic Ocean, the Gulf of Mexico and the Great Lakes, leading to significant dry and wet deposition into these ecosystems. The spatial distributions of dry and wet depositions differ because of their different physical mechanisms; the former follows the distribution of air concentrations whereas the latter is more biased to the North East due to the effect of precipitation.

Pesticides have adverse health effects and can be transported over long distances to contaminate sensitive ecosystems. To address problems caused by environmental pesticides we developed a multimedia multi-pollutant modeling system, and here we present an evaluation of the model by comparing modeled results against measurements. The modeled toxaphene air concentrations for two sites, in Louisiana (LA) and Michigan (MI), are in good agreement with measurements (average concentrations agree to within a factor of 2). Because the residue inventory showed no soil residues at these two sites, resulting in no emissions, the concentrations must be caused by transport; the good agreement between the modeled and measured concentrations suggests that the model simulates atmospheric transport accurately. Compared to the LA and MI sites, the measured air concentrations at two other sites having toxaphene soil residues leading to emissions, in Indiana and Arkansas, showed more pronounced seasonal variability (higher in warmer months); this pattern was also captured by the model. The model-predicted toxaphene concentration fraction on particles (0.5–5%) agrees well with measurement-based estimates (3% or 6%). There is also good agreement between modeled and measured dry (1:1) and wet (within a factor of less than 2) depositions in Lake Ontario. Additionally this study identified erroneous soil residue data around a site in Texas in a published US toxaphene residue inventory, which led to very low modeled air concentrations at this site. Except for the erroneous soil residue data around this site, the good agreement between the modeled and observed results implies that both the US and Mexican toxaphene soil residue inventories are reasonably good. This agreement also suggests that the modeling system is capable of simulating the important physical and chemical processes in the multimedia compartments.

Ongoing climate change is likely to enhance the deterioration of rice quality that has been observed in western Japan, especially in Kyushu, since the 1990s. Therefore, it is important to examine the response of rice quality to environmental variation over a wide geographical domain. To that end, the aims of this study were (i) to propose a statistical model to predict rice quality based on temperature, total radiation during the ripening period, and their multiple effects; and (ii) to evaluate the model validity and uncertainty in prediction. A Bayesian calibration was adopted to account for uncertainty in the parameter values associated with non-climatic factors. The validation results showed that the model performed well in capturing the temporal trend and interannual variation in observed rice quality in all prefectures of Kyushu. We then performed the prediction experiment for rice quality in the extremely hot summer of the year 2010, which was omitted from the model calibration data. The results showed that the predictive capability of the statistical model is somewhat dependent on the calibration data, but this dependency does not necessarily mean that useful predictions for climates not in the calibration data are impossible.

Land use and land cover changes affect the partitioning of latent and sensible heat, which impacts the broader climate system. Increased latent heat flux to the atmosphere has a local cooling influence known as 'evaporative cooling', but this energy will be released back to the atmosphere wherever the water condenses. However, the extent to which local evaporative cooling provides a global cooling influence has not been well characterized. Here, we perform a highly idealized set of climate model simulations aimed at understanding the effects that changes in the balance between surface sensible and latent heating have on the global climate system. We find that globally adding a uniform 1  W m ^{− 2} source of latent heat flux along with a uniform 1  W m ^{− 2} sink of sensible heat leads to a decrease in global mean surface air temperature of 0.54 ± 0.04 K. This occurs largely as a consequence of planetary albedo increases associated with an increase in low elevation cloudiness caused by increased evaporation. Thus, our model results indicate that, on average, when latent heating replaces sensible heating, global, and not merely local, surface temperatures decrease.

Typhoons originating in the west Pacific are major contributors to climate-related risk over the Korean peninsula. The current perspective regarding improved characterization of climatic risk and the projected increases in the intensity, frequency, duration, and power dissipation of typhoons during the 21st century in the western North Pacific region motivated a reappraisal of historical trends in precipitation. In this study, trends in the magnitude and frequency of seasonal precipitation in the five major river basins in Korea are analyzed on the basis of a separation analysis, with recognition of moisture sources (typhoon and non-typhoon). Over the 1966–2007 period, typhoons accounted for 21–26% of seasonal precipitation, with the largest values in the Nakdong River Basin. Typhoon-related precipitation events have increased significantly over portions of Han, Nakdong, and Geum River Basins. Alongside broad patterns toward increases in the magnitude and frequency of precipitation, distinct patterns of trends in the upper and lower quartiles (corresponding to changes in extreme events) are evident. A trend typology—spatially resolved characterization of the combination of shifts in the upper and lower tails of the precipitation distribution—shows that a number of sub-basins have undergone significant changes in one or both of the tails of the precipitation distribution. This broader characterization of trends illuminates the relative role of causal climatic factors and an identification of 'hot spots' likely to experience high exposure to typhoon-related climatic extremes in the future.

Hindering urban sprawl is one of the main goals for contemporary urban planning. Urban density is considered crucial in climate change mitigation since it reduces automobile dependence and decreases unit sizes, for example. This letter analyzes the effect of density in a city context. In the study the Finnish capital Helsinki is divided into two areas of different urban densities: the high density downtown area and the more scarcely populated suburbs. The study is a continuation of a recently published study on the implications of urban structure on carbon emissions, and analyzes further the main finding of the first study—that higher urban density might have negligible or even reverse effect on the per capita carbon emissions. Similarly to the previous study, a consumption based tiered hybrid life cycle assessment (LCA) approach is employed in order to produce a comprehensive assessment, free of territorial boundaries and system cutoffs typical of traditional LCAs. Based on the findings of the previous study, it is hypothesized that when assessing city level carbon dioxide emissions from a wider, consumer oriented LCA perspective, increased urban density may not necessarily reduce carbon emissions. Surprisingly, the study finds that carbon dioxide equivalent (CO₂e) emissions are substantially higher in the dense downtown area than in the surrounding suburbs, which is suggested to imply that the increased consumption due to the higher standard of living increases emissions more than the higher density is able to reduce them. The results demonstrate that, while increasing urban density can be justified from a number of ecological, social and economic viewpoints, density is not necessarily a key parameter in the particular case of climate change. In cities like Helsinki, where wealth is concentrated in the downtown area, climate policies should give higher priority to the energy consumption of buildings, to alternative energy production and distribution modes, as well as to low carbon consumption within the city.

Photosynthetic assimilation of carbon dioxide and inorganic nutrients by phytoplankton constitutes a necessary prerequisite for sustaining marine life. This process is tightly linked to the concentration of chlorophyll in the ocean's euphotic zone. According to a recent field study marine chlorophyll(a) concentrations have declined over the last century with an estimated global rate of 1.0% of the global median per year. Here we attempt to identify possible mechanisms which could explain such trends. We explore these questions using an ocean general circulation model forced with documented historic and projected future anthropogenic emissions of carbon dioxide according to the IPCC SRES A1FI emission scenario until the year 2100. We further extend the time period covered by the A1FI scenario by assuming a linear decline in emissions from 2100 to 2200 and keeping them at zero levels until 2400. Our numerical simulations reveal only weak reductions in chlorophyll(a) concentrations during the twentieth century, but project a 50% decline between 2000 and 2200. We identify a local and a remotely acting mechanism for this reduction in the North Atlantic: (I) increased sea surface temperatures reduce local deep mixing and, hence, reduce the nutrient supply from waters at intermediate depths; (II) a steady shoaling of the Atlantic overturning cell tends to transport increasingly nutrient depleted waters from the Southern Hemisphere toward the north, leading to further diminishment of nutrient supply. These results provide support for a temperature-driven decline in ocean chlorophyll(a) and productivity, but suggest that additional mechanisms need to be invoked to explain observed declines in recent decades.

The functioning of many ecosystems and their associated resilience could become severely compromised by climate change over the 21st century. We present a global risk analysis of terrestrial ecosystem changes based on an aggregate metric of joint changes in macroscopic ecosystem features including vegetation structure as well as carbon and water fluxes and stores. We apply this metric to global ecosystem simulations with a dynamic global vegetation model (LPJmL) under 58 WCRP CMIP3 climate change projections. Given the current knowledge of ecosystem processes and projected climate change patterns, we find that severe ecosystem changes cannot be excluded on any continent. They are likely to occur (in > 90% of the climate projections) in the boreal–temperate ecotone where heat and drought stress might lead to large-scale forest die-back, along boreal and mountainous tree lines where the temperature limitation will be alleviated, and in water-limited ecosystems where elevated atmospheric CO₂ concentration will lead to increased water use efficiency of photosynthesis. Considerable ecosystem changes can be expected above 3 K local temperature change in cold and tropical climates and above 4 K in the temperate zone. Sensitivity to temperature change increases with decreasing precipitation in tropical and temperate ecosystems. In summary, there is a risk of substantial restructuring of the global land biosphere on current trajectories of climate change.

An analytical three-band algorithm for spectrally estimating chlorophyll-a (Chl-a) has been proposed recently and the model does not need to be trained. However, the model did not consider the effects of the absorption due to colored detritus matter (CDM) and backscattering of the water column, resulting in an overestimation when Chl-a < 50 mg m ^{− 3} and an underestimation when Chl-a ≥ 50 mg m ^{− 3}. In this letter, an improved three-band algorithm is proposed by integrating both backscattering and CDM absorption coefficients into the model. The results demonstrate that the improved three-band model resulted in more accurate estimation of Chl-a than the previously used three-band model when they were applied to water samples collected from five highly turbid water bodies with Chl-a ranging from 2.54 to 285.8  mg m ^{− 3}. The best results, after model modification, were observed in three Indiana reservoirs with R² = 0.905 and relative root mean square error of 20.7%, respectively.

The number of offshore wind farms is increasing rapidly, leading to questions about the environmental impact of such farms. In the Netherlands, an extensive monitoring programme is being executed at the first offshore wind farm (Offshore Windfarm Egmond aan Zee, OWEZ). This letter compiles the short-term (two years) results on a large number of faunal groups obtained so far. Impacts were expected from the new hard substratum, the moving rotor blades, possible underwater noise and the exclusion of fisheries. The results indicate no short-term effects on the benthos in the sandy area between the generators, while the new hard substratum of the monopiles and the scouring protection led to the establishment of new species and new fauna communities. Bivalve recruitment was not impacted by the OWEZ wind farm. Species composition of recruits in OWEZ and the surrounding reference areas is correlated with mud content of the sediment and water depth irrespective the presence of OWEZ. Recruit abundances in OWEZ were correlated with mud content, most likely to be attributed not to the presence of the farm but to the absence of fisheries. The fish community was highly dynamic both in time and space. So far, only minor effects upon fish assemblages especially near the monopiles have been observed. Some fish species, such as cod, seem to find shelter inside the farm. More porpoise clicks were recorded inside the farm than in the reference areas outside the farm. Several bird species seem to avoid the park while others are indifferent or are even attracted. The effects of the wind farm on a highly variable ecosystem are described. Overall, the OWEZ wind farm acts as a new type of habitat with a higher biodiversity of benthic organisms, a possibly increased use of the area by the benthos, fish, marine mammals and some bird species and a decreased use by several other bird species.

Noise continues to be a significant factor in the development of wind energy resources. In the case of building-mounted wind turbines (BMWTs), in addition to the usual airborne sound there is the potential for occupants to be affected by structure-borne sound and vibration transmitted through the building structure. Usual methods for prediction and evaluation of noise from large and small WTs are not applicable to noise of this type. This letter describes an investigation aiming to derive a methodology for prediction of structure-borne sound and vibration inside attached dwellings. Jointly funded by three UK government departments, the work was motivated by a desire to stimulate renewable energy generation by the removal of planning restrictions where possible. A method for characterizing BMWTs as sources of structure-borne sound was first developed during a field survey of two small wind turbines under variable wind conditions. The 'source strength' was established as a function of rotor speed although a general relationship to wind speed could not be established. The influence of turbulence was also investigated. The prediction methodology, which also accounts for the sound transmission properties of the mast and supporting building, was verified in a field survey of existing installations. Significant differences in behavior and subjective character were noted between the airborne and structure-borne noise from BMWTs.

Wind turbines emit low frequency noise (LFN) and large turbines generally generate more LFN than small turbines. The dominant source of LFN is the interaction between incoming turbulence and the blades. Measurements suggest that indoor levels of LFN in dwellings typically are within recommended guideline values, provided that the outdoor level does not exceed corresponding guidelines for facade exposure. Three cross-sectional questionnaire studies show that annoyance from wind turbine noise is related to the immission level, but several explanations other than low frequency noise are probable. A statistically significant association between noise levels and self-reported sleep disturbance was found in two of the three studies. It has been suggested that LFN from wind turbines causes other, and more serious, health problems, but empirical support for these claims is lacking.

West Siberia contains the largest extent of wetlands in the world, including large peat deposits; the wetland area is equivalent to 27% of the total area of West Siberia. This study used inverse modeling to refine emissions estimates for West Siberia using atmospheric CH₄ observations and two wetland CH₄ emissions inventories: (1) the global wetland emissions dataset of the NASA Goddard Institute for Space Studies (the GISS inventory), which includes emission seasons and emission rates based on climatology of monthly surface air temperature and precipitation, and (2) the West Siberian wetland emissions data (the Bc7 inventory), based on in situ flux measurements and a detailed wetland classification. The two inversions using the GISS and Bc7 inventories estimated annual mean flux from West Siberian wetlands to be 2.9 ± 1.7 and 3.0 ± 1.4 Tg yr ^{− 1}, respectively, which are lower than the 6.3 Tg yr ^{− 1} predicted in the GISS inventory, but similar to those of the Bc7 inventory (3.2  Tg yr ^{− 1}). The well-constrained monthly fluxes and a comparison between the predicted CH₄ concentrations in the two inversions suggest that the Bc7 inventory predicts the seasonal cycle of West Siberian wetland CH₄ emissions more reasonably, indicating that the GISS inventory predicts more emissions from wetlands in northern and middle taiga.

Changes of total and low cloud fraction and the occurrence of different cloud types over Russia were assessed. The analysis was based on visual observations from more than 1600 meteorological stations. Differences between the 2001–10 and 1991–2000 year ranges were evaluated. In general, cloud fraction has tended to increase during recent years. A major increase of total cloud fraction and a decrease of the number of days without clouds are revealed in spring and autumn mostly due to an increase of the occurrence of convective and non-precipitating stratiform clouds. In contrast, the occurrence of nimbostratus clouds has tended to decrease. In general, the ratio between the occurrence of cumulonimbus and nimbostratus clouds has increased for the period 2001–10 relative to 1991–2000. Over particular regions, a decrease of total cloud fraction and an increase of the number of days without clouds are noted.

Analysis of vegetation cover and tendencies in forest cover changes at a typical site in the south of West Siberia was performed using remote sensing observations from Landsat. The Northern Eurasia Land Cover legend was used for the assessment of unsupervised classification results. The land cover maps constructed have shown that about half of the study area is occupied by wetlands with several distinctively different vegetation types. The area studied is typical for the South Taiga zone (ecoregion) of Western Siberia from the Ob' river to the Irtysh river, where loamy and clayey soil forming rocks are widespread. Similar vegetation structures dominate over 600 000  km², or about 20%, of the West Siberia area. Analyses of the forest cover changes show that the forest cover loss is not very significant. The area of forest disturbed in 1990–9 is equal to 16 008 ha. The area of forest disturbances during the 2000–7 period was about twice as high (30 907 ha). The main reasons for the forest reduction are intensive forest harvesting and strong windthrow. The high sustainability of the region studied against anthropogenic impacts is explained by the high overall wetness of the territory, the small population density, and the prevalence of deciduous forests at different succession stages with rich vegetation cover.

We analyze snow cover extent (SCE) trends in the National Oceanic and Atmospheric Administration's (NOAA) northern hemisphere weekly satellite SCE data using the Mann–Kendall trend test and find that North American and Eurasian snow cover in the pan-Arctic have declined significantly in spring and summer over the period of satellite record beginning in the early 1970s. These trends are reproduced, both in trend direction and statistical significance, in reconstructions using the variable infiltration capacity (VIC) hydrological model. We find that spring and summer surface radiative and turbulent fluxes generated in VIC have strong correlations with satellite observations of SCE. We identify the role of surface energy fluxes and determine which is most responsible for the observed spring and summer SCE recession. We find that positive trends in surface net radiation (SNR) accompany most of the SCE trends, whereas modeled latent heat (LH) and sensible heat (SH) trends associated with warming on SCE mostly cancel each other, except for North America in spring, and to a lesser extent for Eurasia in summer. In spring over North America and summer in Eurasia, the SH contribution to the observed snow cover trends is substantial. The results indicate that ΔSNR is the primary energy source and ΔSH plays a secondary role in changes of SCE. Compared with ΔSNR and ΔSH, ΔLH has a minor influence on pan-Arctic snow cover changes.

The Deepwater Horizon oil spill was one of the largest oil spills in history, and the fate of this oil within the Gulf of Mexico ecosystem remains to be fully understood. The goal of this study—conducted in mid-June of 2010, approximately two months after the oil spill began—was to understand the key role that microbes would play in the degradation of the oil in the offshore oligotrophic surface waters near the Deepwater Horizon site. As the utilization of organic carbon by bacteria in the surface waters of the Gulf had been previously shown to be phosphorus limited, we hypothesized that bacteria would be unable to rapidly utilize the oil released from the Macondo well. Although phosphate was scarce throughout the sampling region and microbes exhibited enzymatic signs of phosphate stress within the oil slick, microbial respiration within the slick was enhanced by approximately a factor of five. An incubation experiment to determine hydrocarbon degradation rates confirmed that a large fraction of this enhanced respiration was supported by hydrocarbon degradation. Extrapolating our observations to the entire area of the slick suggests that microbes had the potential to degrade a large fraction of the oil as it arrived at the surface from the well. These observations decidedly refuted our hypothesis. However, a concomitant increase in microbial abundance or biomass was not observed in the slick, suggesting that microbial growth was nutrient limited; incubations amended with nutrients showed rapid increases in cell number and biomass, which supported this conclusion. Our study shows that the dynamic microbial community of the Gulf of Mexico supported remarkable rates of oil respiration, despite a dearth of dissolved nutrients.

This study explores relationships between the normalized difference vegetation index (NDVI) and structural characteristics associated with deciduous shrub dominance in arctic tundra. Our structural measures of shrub dominance are stature, branch abundance, aerial per cent woody stem cover (deciduous and evergreen species), and per cent deciduous shrub canopy cover. All measurements were taken across a suite of transects that together represent a gradient of deciduous shrub height. The transects include tussock tundra shrub and riparian shrub tundra communities located in the northern foothills of the Brooks Range, in northern Alaska. Plot-level NDVI measurements were made in 2010 during the snow-free period prior to deciduous shrub leaf-out (early June, NDVI_{pre − leaf}), at the point in the growing season when canopy NDVI has reached half of its maximum growing season value (mid-June, NDVI_{demi − leaf}) and during the period of maximum leaf-out (late July, NDVI_{peak − leaf}). We found that: (1) NDVI_{pre − leaf} is best suited to capturing variation in the per cent woody stem cover, maximum shrub height, and branch abundance, particularly between 10 and 50 cm height in the canopy; (2)  NDVI_{peak − leaf} is best suited to capturing variation in deciduous canopy cover; and (3)  NDVI_{demi − leaf} does not capture variability in any of our measures of shrub dominance. These findings suggest that in situ NDVI measurements made prior to deciduous canopy leaf-out could be used to identify small differences in maximum shrub height, woody stem cover, and branch abundance (particularly between 10 and 50 cm height in the canopy). Because shrubs are increasing in size and regional extent in several regions of the Arctic, investigation into spectrally based tools for monitoring these changes are worthwhile as they provide a first step towards development of remotely sensed techniques for quantifying associated changes in regional carbon cycling, albedo, radiative energy balance, and wildlife habitat.

Recently observed Arctic greening trends from normalized difference vegetation index (NDVI) data suggest that shrub growth is increasing in response to increasing summer temperature. An increase in shrub cover is expected to decrease summer albedo and thus positively feed back to climate warming. However, it is unknown how albedo and NDVI are affected by shrub cover and inter-annual variations in the summer climate. Here, we examine the relationship between deciduous shrub fractional cover, NDVI and albedo using field data collected at a tundra site in NE Siberia. Field data showed that NDVI increased and albedo decreased with increasing deciduous shrub cover. We then selected four Arctic tundra study areas and compiled annual growing season maximum NDVI and minimum albedo maps from MODIS satellite data (2000–10) and related these satellite products to tundra vegetation types (shrub, graminoid, barren and wetland tundra) and regional summer temperature. We observed that maximum NDVI was greatest in shrub tundra and that inter-annual variation was negatively related to summer minimum albedo but showed no consistent relationship with summer temperature. Shrub tundra showed higher albedo than wetland and barren tundra in all four study areas. These results suggest that a northwards shift of shrub tundra might not lead to a decrease in summer minimum albedo during the snow-free season when replacing wetland tundra. A fully integrative study is however needed to link results from satellite data with in situ observations across the Arctic to test the effect of increasing shrub cover on summer albedo in different tundra vegetation types.