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Climate change impact research and risk assessment require accurate estimates of the climate change signal (CCS). Raw climate model data include systematic biases that affect the CCS of high-impact variables such as daily precipitation and wind speed. This paper presents a novel, general, and extensible analytical theory of the effect of these biases on the CCS of the distribution mean and quantiles. The theory reveals that misrepresented model intensities and probability of nonzero (positive) events have the potential to distort raw model CCS estimates. We test the analytical description in a challenging application of bias correction and downscaling to daily precipitation over alpine terrain, where the output of 15 regional climate models (RCMs) is reduced to local weather stations. The theoretically predicted CCS modification well approximates the modification by the bias correction method, even for the station–RCM combinations with the largest absolute modifications. These results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect. The analytical theory can be used as a tool to 1) detect model biases with high potential to distort the CCS and 2) efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. Future research needs to focus on developing process-based bias corrections that depend on simulated intensities rather than preserving the raw model CCS. [ABSTRACT FROM AUTHOR]

China’s FengYun 3 (FY-3) polar orbiting satellites are set to become an important source of observational data for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies over the next two decades. As part of the Climate Science for Service Partnership China (CSSP China) program, FY-3B Microwave Humidity Sounder 1 (MWHS-1) and FY-3C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation. This represents the first time observations from China’s polar orbiting satellites have been used in the UK’s global NWP model. Since 2016, continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies. Nonetheless, MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%, respectively, and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%. The observations from the Microwave Radiation Imager (MWRI) also are a potentially significant source of benefits for NWP models, but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation. This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data. [ABSTRACT FROM AUTHOR]

This bibliometric study of a large publication set dealing with research on climate change aims at mapping the relevant literature from a bibliometric perspective and presents a multitude of quantitative data: (1) The growth of the overall publication output as well as (2) of some major subfields, (3) the contributing journals and countries as well as their citation impact, and (4) a title word analysis aiming to illustrate the time evolution and relative importance of specific research topics. The study is based on 222,060 papers (articles and reviews only) published between 1980 and 2014. The total number of papers shows a strong increase with a doubling every 5–6 years. Continental biomass related research is the major subfield, closely followed by climate modeling. Research dealing with adaptation, mitigation, risks, and vulnerability of global warming is comparatively small, but their share of papers increased exponentially since 2005. Research on vulnerability and on adaptation published the largest proportion of very important papers (in terms of citation impact). Climate change research has become an issue also for disciplines beyond the natural sciences. The categories Engineering and Social Sciences show the strongest field-specific relative increase. The Journal of Geophysical Research, the Journal of Climate, the Geophysical Research Letters, and Climatic Change appear at the top positions in terms of the total number of papers published. Research on climate change is quantitatively dominated by the USA, followed by the UK, Germany, and Canada. The citation-based indicators exhibit consistently that the UK has produced the largest proportion of high impact papers compared to the other countries (having published more than 10,000 papers). Also, Switzerland, Denmark and also The Netherlands (with a publication output between around 3,000 and 6,000 papers) perform top—the impact of their contributions is on a high level. The title word analysis shows that the term climate change comes forward with time. Furthermore, the term impact arises and points to research dealing with the various effects of climate change. The discussion of the question of human induced climate change towards a clear fact (for the majority of the scientific community) stimulated research on future pathways for adaptation and mitigation. Finally, the term model and related terms prominently appear independent of time, indicating the high relevance of climate modeling. [ABSTRACT FROM AUTHOR]

Emissions from aviation will continue to increase in the future, in contradiction of global climate policy objectives. Yet, airlines and airline organisations suggest that aviation will become climatically sustainable. This paper investigates this paradox by reviewing fuel-efficiency gains since the 1960s in comparison to aviation growth, and by linking these results to technology discourses, based on a two-tiered approach tracing technology-focused discourses over 20 years (1994–2013). Findings indicate that a wide range of solutions to growing emissions from aviation have been presented by industry, hyped in global media, and subsequently vanished to be replaced by new technology discourses. Redundant discourses often linger in the public domain, where they continue to be associated with industry aspirations of ‘sustainable aviation’ and ‘zero-emission flight’. The paper highlights and discusses a number of technology discourses that constitute ‘technology myths’, and the role these ‘myths’ may be playing in the enduring but flawed promise of sustainable aviation. We conclude that technology myths require policy-makers to interpret and take into account technical uncertainty, which may result in inaction that continues to delay much needed progress in climate policy for aviation. [ABSTRACT FROM AUTHOR]

This paper's central concern is to trace how dominant, scientific understanding of climate change is mobilized in ways that set a course towards slow violence. Slow violence is indirect, latent, and results in neglectful human suffering. It can result from particular actions or decisions; it can result from epistemic and political dominance of particular narratives or understandings. This paper takes a constructivist Science and Technology Studies (STS) perspective to look at the emergence of a technoscientific understanding of climate change and to consider political geographic implications of this interpretation. Following an overview of inroads already made in applying an STS approach to climate studies, I turn to two examples of specific scientific narratives or practices, reliance on Global Circulation Models by the Intergovernmental Panel on Climate Change (IPCC) and carbon data, to consider ways in which selective, political mobilization of these interpretations of climate change may contribute to forms of slow violence. The science in either case is not in question. Instead, the foreclosure of other ways of understanding human-environment interactions is brought about in part by geopolitics as usual and through the work of powerful actors and interests. The paper argues for a re-politicization of climate change and considers examples of alternative narratives and efforts towards equity and transparency. [ABSTRACT FROM AUTHOR]

Purpose – Research into the emergence of a hype requires a mixed methods approach that takes into account both the evolution over time and mutual influences across different types of media. The purpose of this paper is to present a methodological approach to detect an emerging hype in online communications. Design/methodology/approach – The paper combines Auto Regressive Integrated Moving Average (ARIMA) time series modelling and semantic co-word networks, and this combination of methods provides a view on the emergence and development of a hype at the level of mutual influences across a heterogeneous set of newspaper and blog data. The subject scope of the paper is the climategate hype. The climategate hype was triggered by the online publication of a set of hacked e-mails belonging to climate researchers at the East Anglia University in November 2009. Findings – The main findings show that the climategate hype was initiated in the blogs, and the newspapers were reacting to the blogs. At the level of semantics, the blogs and the newspapers framed the issue from opposite perspectives. Research limitations/implications – The combination of methods contributes theoretical insights to how blogs interact with more traditional media on hype generation and methodological insights to internet researchers investigating emergent online hypes. The method calls for further validation. Practical implications – Investigating the emergence and evolution of a hype, and the interaction of the two media is relevant for journalists in becoming more reflexive in their practices and the cues from the outside world. Originality/value – The paper is novel in its combination of the two specific methods, ARIMA time series modelling and co-word networks and its attempt to identify the media origins of a hype, and especially the interaction between blogs and newspapers. [ABSTRACT FROM AUTHOR]

The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findings in scientific papers may be too opaque for the public to understand. Social media, however, is a forum where individuals of diverse backgrounds can share their thoughts and opinions. As consumption shifts from old media to new, Twitter has become a valuable resource for analyzing current events and headline news. In this research, we analyze tweets containing the word “climate” collected between September 2008 and July 2014. Through use of a previously developed sentiment measurement tool called the Hedonometer, we determine how collective sentiment varies in response to climate change news, events, and natural disasters. We find that natural disasters, climate bills, and oil-drilling can contribute to a decrease in happiness while climate rallies, a book release, and a green ideas contest can contribute to an increase in happiness. Words uncovered by our analysis suggest that responses to climate change news are predominately from climate change activists rather than climate change deniers, indicating that Twitter is a valuable resource for the spread of climate change awareness. [ABSTRACT FROM AUTHOR]

Urban drainage systems are in general failing in their functions mainly due to non-stationary climate and rapid urbanization. As these systems are becoming less efficient, issues such as sewer overflows and increase in urban flooding leading to surge in pollutant loads to receiving water bodies are becoming pervasive rapidly. A comprehensive investigation is required to understand these factors impacting the functioning of urban drainage, which vary spatially and temporally and are more complex when weaving together. It is necessary to establish a cost-effective, integrated planning and design framework for every local area by incorporating fit for purpose alternatives. Carefully selected adaptive measures are required for the provision of sustainable drainage systems to meet combined challenges of climate change and urbanization. This paper reviews challenges associated with urban drainage systems and explores limitations and potentials of different adaptation alternatives. It is hoped that the paper would provide drainage engineers, water planners, and decision makers with the state of the art information and technologies regarding adaptation options to increase drainage systems efficiency under changing climate and urbanization. [ABSTRACT FROM AUTHOR]

This paper explores the responses of faith-based movements in Indonesia to globalized environmental issues, including climate change. As a plural nation with six official religions, the leaders of the major recognized religions in Indonesia (i.e., Islam, Protestant and Roman Catholic Christianity, Hinduism, Buddhism and Confusianism) all offered statements in 2007 at COP 13, the international forum in response to the environmental challange and climate change in Bali. Each called for religious adherents to act in order to contribute to halting the problem of climate change. Faith is seen to be a key factor in motivating people to change their behavior towards the environment. The slogan, "Think globally, act locally,'' is at the heart of this commitment, in hopes that environmental challenges including climate change, become a common issue among all the religions in Indonesia, and so that Indonesian responses may be collaborative and cooperative. This paper will document and analyze the development of such faithbased action with respect to environmental challenges in Indonesia, in light of global conditions. [ABSTRACT FROM AUTHOR]

In recent times, increasing economic losses due to unexpected extreme environmental conditions have been noticed. The occurrence of these extreme environmental events requires us to have a clearer understanding of climatic influence on our lives. This paper utilizes the case of Singapore to investigate the influence of climate extremes on a country. The environmental elements of Singapore whose extremes are most likely to change in the future are identified. The impacts of these extremes on an entire nation's economy and public health are discussed. Additionally, climate-induced statistical uncertainties in the modeling of extreme values are investigated. Based on the available knowledge of climate uncertainty information, the change of statistical structure in the extreme value model is discussed. The impact of various types of climate uncertainty in the extreme value modeling for a physical environmental variable is summarized at the end of this paper. [ABSTRACT FROM AUTHOR]

Technological advances in forecasting the Earth's climate offer a potentially useful tool to support planning and management decisions in water resources. Previous research has found that the implementation of new ideas and practices are impeded by many challenges such as low forecast skill, institutional obstacles, and political disincentives to innovation. To better understand barriers to forecast use at seasonal-to-interannual, decadal, or longer time scales, this paper evaluates a diffusion of innovations (Do!) framework to assess the adoption of hydroclimatic forecasts by water managers in the Northeast United States. Specifically, this paper seeks to understand how five innovation characteristics, relative advantage, compatibility, complexity, trialability, and observability, influence the rate of adoption. Methods used for this analysis include the distribution of a survey, interviews, and a literature review. Results indicated that while much attention has focused on institutional obstacles, in the Connecticut River Basin obstacles were related to characteristics of the forecasts themselves. Evaluation of the DoI makes clear that the challenges to forecast use are common to all innovations. [ABSTRACT FROM AUTHOR]

This paper explores the emergence of a global climate change mitigation regime through an analysis of the language employed in international science-policy reports. We assume that a global climate regime can only operate effectively on the basis of a shared understanding of climate change which is itself based on a shared language of governance. We therefore carried out an in-depth thematic and metaphor analysis of 63 policy documents published between 1992 and 2012. Results show that global climate science-policy discourses universalise the myriad impacts of a changing climate into a single dichotomous impacted/not-impacted scenario and aim to govern this world according to economic principles of cost–benefit analysis. These discourses use metaphors that draw on narrative structures prevalent in the wider culture to produce and legitimate a reductionist representation of climate change. This representation undermines public understanding of and engagement with climate change by marginalising subordinate policy framings which do not align with the prevailing dichotomous framing. The types of documents we analyse in this paper represent important sources for journalists reporting on climate change. We therefore suggest that any attempt to improve public communication of climate change should include revisions to these organisational discourses. [ABSTRACT FROM AUTHOR]

Climate change impacts are already happening through the world, and it is now clear that there is the need for an adaptive response from global institutions down to the local level. Reducing vulnerability to cope with climate variability might be more challenging in tropical countries than in North America or Europe. The ten papers of this special issue were presented during the Adaptclim conference that was held by the Sinergia Project, the CLARIS LPB project, and the GeoData Institute in Asunción, Paraguay, in 2010. All papers, except one regarding the Brahmaputra Basin in South Asia, present studies from South America. These studies are first contextualized geographically and then are related one to another by a simplified vulnerability concept linking climate stress to sensitivity and adaptive capacity of natural and human systems. One half of the papers focus on actual or future climate change and the present-day causes of the vulnerability of natural and agrosystems. Droughts are and will be the main source of stress for agriculture in South America. Increasing fragmentation of forest of the center of this continent is aggravating their vulnerability to dry spells. Another half of the studies of this special issue deal with the adaptive capacity human populations to system perturbations produced or enhanced by climate change. The studies point out inclusion of traditional knowledge and involvement of local actors in their own vulnerability assessment to increase adaptive capacity. These elements of climate justice, giving voice to those less responsible for carbon emissions but bearing their most severe consequences, allow the particular needs of a community to be considered and can direct adaptation policy toward preserving or rebuilding their specific capabilities under threat from climate change. The special issue also made clear that a basin analysis of the climate change problem could provide information, results, and methods more readily of use for the local population and decision makers. [ABSTRACT FROM AUTHOR]

The assessment of the potential impact of climate change on transport is an area of research very much in its infancy, and one that requires input from a multitude of disciplines including geography, engineering and technology, meteorology, climatology and futures studies. This paper investigates the current state of the art for assessments on urban surface transport, where rising populations and increasing dependence on efficient and reliable mobility have increased the importance placed on resilience to weather. The standard structure of climate change impact assessment (CIA) requires understanding in three important areas: how weather currently affects infrastructure and operations; how climate change may alter the frequency and magnitude of these impacts; and how concurrent technological and socio-economic development may shape the transport network of the future, either ameliorating or exacerbating the effects of climate change. The extent to which the requisite knowledge exists for a successful CIA is observed to decrease from the former to the latter. This paper traces a number of developments in the extrapolation of physical and behavioural relationships on to future climates, including a broad move away from previous deterministic methods and towards probabilistic projections which make use of a much broader range of climate change model output, giving a better representation of the uncertainty involved. Studies increasingly demand spatially and temporally downscaled climate projections that can represent realistic sub-daily fluctuations in weather that transport systems are sensitive to. It is recommended that future climate change impact assessments should focus on several key areas, including better representation of sub-daily extremes in climate tools, and recreation of realistic spatially coherent weather. Greater use of the increasing amounts of data created and captured by ‘intelligent infrastructure’ and ‘smart cities’ is also needed to develop behavioural and physical models of the response of transport to weather and to develop a better understanding of how stakeholders respond to probabilistic climate change impact projections. [ABSTRACT FROM AUTHOR]

Geographer C. W. Thornthwaite proposed in 1948 a moisture index called Thornthwaite Moisture Index ( TMI) as part of a water balance model for a new classification system for climate. The importance of TMI climatic classification has been recognised in many areas of knowledge and practice worldwide over the last 60 years. However, although past climate research was focused on developing adequate methods for climate classification, current research is more concerned with understanding the patterns of climate change. The use of TMI as an indicator for climate change is still an incipient area of research. The contributions of this paper are twofold. First, it is to fully document a methodology based on geostatistics adopted to produce a time series of TMI maps that are accurate and have high spatial resolution. The state of Victoria, in Australia, over the last century, is used as the case study. Second, by analysing these maps, the paper presents a general evaluation of the spatial patterns found in Victoria related to moisture variability across space and over time. Some potential implications of the verified moisture changes are discussed, and a number of ideas for further development are suggested. [ABSTRACT FROM AUTHOR]

The paper by Scafetta entitled “High resolution coherence analysis between planetary and climate oscillations”, May 2016 claims coherence between planetary movements and the global temperature anomaly. The claim is based on data analysis using the canonical covariance analysis (CCA) estimator for the magnitude squared coherence (MSC). It assumes a model with a predetermined number of sinusoids for the climate data. The results are highly dependent on this prior assumption, and may therefore be criticized for being based on the opposite of a null hypothesis. More importantly, since values of key parameters in the CCA method are not given, some experiments have been performed using the software of the original authors of the CCA estimator. The purpose was to replicate the results of Scafetta using what was perceived to be the most probable parameter values. Despite best efforts, this was not possible. [ABSTRACT FROM AUTHOR]

In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance weight (IDW), and Mann-Kendall’s non-parametric statistical tests) were applied to analyze the annual sequences of meteorological data for the period 1960-2014. The results indicated that the mean annual air temperature in the Pan-Hexi and the surrounding regions has increased by 0.9 °C. Over the 55-year period of study, this represented a warming rate that was significantly higher than the contemporaneous warming rate in China and the rest of the world. The warming trend in northeastern Tibet was the most pronounced. Here, the mean warming rate exhibited an increasing trend from the mid-late 1980s, and the cold season-dominated warming changed to year-round warming. The rise in the amplitude of the mean minimum temperature was significant, and the variation in the amplitude of the extreme minimum temperature was greater than that of the extreme maximum temperature, exhibiting a variation period of approximately 10 years. Since 1960, the mean precipitation in the study region and the surrounding areas first increased, and then decreased, and then increased again rapidly from 2007. Precipitation and relative humidity trend showed a 13- and a 10-year variation period, respectively. Crop evapotranspiration exhibited a decreasing trend, but from 1993 onwards, there was an increasing trend and a 9-year variation period was also notable based on observed datasets. In the most recent 55 years (1960-2014), the sunshine duration and mean wind velocity in the study area first showed a decreasing trend followed by an increasing trend, and then it exhibited a decreasing trend from east to west of the study region. The temporal variations in the climatic elements were similar to those of China, suggesting that the climate change signal in the study region over the last 55 years appeared to be well correlated with the global climate change signal. [ABSTRACT FROM AUTHOR]

Climate change poses severe risks for businesses, which companies as well as governments need to understand in order to take appropriate steps to manage those. This, however, represents a significant challenge as climate change risk assessment is itself a complex, dynamic and geographically diverse process. A wide range of factors including the nature of production processes and value chains, the location of business sites as well as relationships and interdependencies with customers and suppliers play a role in determining if and how companies are impacted by climate risks. This research explores the methodological challenges for a national-scale assessment of climate risks through the lens of the UK Climate Change Risk Assessment (UKCCRA) process and compares the approaches adopted in the first and second UKCCRA (2011, 2016), while also reflecting on international experiences elsewhere. A review of these issues is presented, drawing on a wide body of contemporary evidence from a range of sources including the research disciplines, grey literature and government policy. The study reveals the methodological challenges and highlights six broad themes, namely scale, evidence base, adaptation responses, scope, interdependencies and public policy. The paper concludes by identifying suitable lessons for future national climate risk assessments, which should guide the next phase of research in preparation for UKCCRA3 and those of national-level risk assessments elsewhere. [ABSTRACT FROM AUTHOR]

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of largescale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. [ABSTRACT FROM AUTHOR]

This paper applies the detrended fluctuation analysis (DFA) method to investigate the long-range correlation of monthly mean temperatures from three typical measurement stations at Harbin, Changchun, and Shenyang in Northeast China from 1909 to 2014. The results reveal the memory characteristics of the climate system in this region. By comparing the temperatures from different time periods and investigating the variations of its scaling exponents at the three stations during these different time periods, we found that the monthly mean temperature has long-range correlation, which indicates that the temperature in Northeast China has long-term memory and good predictability. The monthly time series of temperatures over the past 106 years also shows good long-range correlation characteristics. These characteristics are also obviously observed in the annual mean temperature time series. Finally, we separated the centennial-length temperature time series into two time periods. These results reveal that the long-range correlations at the Harbin station over these two time periods have large variations, whereas no obvious variations are observed at the other two stations. This indicates that warming affects the regional climate system’s predictability differently at different time periods. The research results can provide a quantitative reference point for regional climate predictability assessment and future climate model evaluation. [ABSTRACT FROM AUTHOR]

Federal climate policy in the United States is still in its infancy and is in large part characterized by efforts to reach a consensus on the very existence and causality of climate change. This has stemmed from a sociopolitical rift within the country, with the objectivity and usefulness of science attacked by detractors. Scientists who are most qualified to defend their methods and provide information to policymakers rarely have an institutional incentive to share this knowledge, but should be encouraged to communicate their findings to the public, especially those who receive public funding. By not doing so, they are effectively 1) keeping data and their interpretations within the academy alone, despite their importance to the public welfare, 2) losing public support through inactivity, and 3) potentially harming the future availability of research support in what has rapidly become a politically polarized funding atmosphere. Archaeologists and geoscientists in particular, as repositories of past ecological knowledge established through one method (Western academic) of empirical examination, are well positioned to broadcast to the public a variety of societal responses to long-term environmental change as well as the repercussions of political reorganization in the wake of resource shortage-induced societal collapse. This paper summarizes a few promising public outreach engagements on environment and climate change, and suggests further venues for institutional change at the university level. As an example of how multi-causal socio-ecological processes can be concisely packaged for consumption by the public and policymakers without oversimplifying data, we present a synthesis of regional case studies from the New and Old Worlds. Case studies are connected through anthropological processes of cooperation versus exclusion, subsistence shifts, sociopolitical (re)organization and hierarchy, violence, and disease in a preliminary attempt a) to identify the emotional and anecdotal psychology of our own society when it comes to the chang-ing global environment, b) to discuss the issue of scalar differences between ancient and modern ecology, and c) to call on academics to introspectively alter our own attitudes and systems of incentives at the university level. [ABSTRACT FROM AUTHOR]

The role of forest management in mitigating climate change is a central concern for the Canadian province of British Columbia. The successful implementation of forest management activities to achieve climate change mitigation in British Columbia will be strongly influenced by public support or opposition. While we now have increasingly clear ideas of the management opportunities associated with forest mitigation and some insight into public support for climate change mitigation in the context of sustainable forest management, very little is known with respect to the levels and basis of public support for potential forest management strategies to mitigate climate change. This paper, by describing the results of a web-based survey, documents levels of public support for the implementation of eight forest carbon mitigation strategies in British Columbia’s forest sector, and examines and quantifies the influence of the factors that shape this support. Overall, respondents ascribed a high level of importance to forest carbon mitigation and supported all of the eight proposed strategies, indicating that the British Columbia public is inclined to consider alternative practices in managing forests and wood products to mitigate climate change. That said, we found differences in levels of support for the mitigation strategies. In general, we found greater levels of support for a rehabilitation strategy (e.g. reforestation of unproductive forest land), and to a lesser extent for conservation strategies (e.g. old growth conservation, reduced harvest) over enhanced forest management strategies (e.g. improved harvesting and silvicultural techniques). We also highlighted multiple variables within the British Columbia population that appear to play a role in predicting levels of support for conservation and/or enhanced forest management strategies, including environmental values, risk perception, trust in groups of actors, prioritized objectives of forest management and socio-demographic factors. [ABSTRACT FROM AUTHOR]

Local and indigenous knowledge is being transformed globally, particularly being eroded when pertaining to ecology. In many parts of the world, rural and indigenous communities are facing tremendous cultural, economic and environmental changes, which contribute to weaken their local knowledge base. In the face of profound and ongoing environmental changes, both cultural and biological diversity are likely to be severely impacted as well as local resilience capacities from this loss. In this global literature review, we analyse the drivers of various types of local and indigenous ecological knowledge transformation and assess the directionality of the reported change. Results of this analysis show a global impoverishment of local and indigenous knowledge with 77% of papers reporting the loss of knowledge driven by globalization, modernization, and market integration. The recording of this loss, however, is not symmetrical, with losses being recorded more strongly in medicinal and ethnobotanical knowledge. Persistence of knowledge (15% of the studies) occurred in studies where traditional practices were being maintained consiously and where hybrid knowledge was being produced as a resut of certain types of incentives created by economic development. This review provides some insights into local and indigenous ecological knowledge change, its causes and implications, and recommends venues for the development of replicable and comparative research. The larger implication of these results is that because of the interconnection between cultural and biological diversity, the loss of local and indigenous knowledge is likely to critically threaten effective conservation of biodiversity, particularly in community-based conservation local efforts. [ABSTRACT FROM AUTHOR]

The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000-12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century-complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks. [ABSTRACT FROM AUTHOR]

In the context of climate adaptation planning there are relationships between adaptation drivers and adaptation measures, which makes the selection and implementation of the adaptation measures a challenging task. This challenge may be addressed by: structuring the adaptation problem using a multiple perspective adaptation framework; and applying a context specific precedence grammar logic for selecting and evaluating adaptation measures. Precedence grammar logic is a set of rule based algorithms (grammar) that are based on the relationships in a local adaptation context. This paper demonstrates the application of a context specific precedence grammar logic in an adaptation context in Can Tho, Vietnam. Adaptation pathways comprising flood adaptation measures (i.e. dike heightening) for this case were generated using rule based algorithms based on the relationships between the drivers and the adaptation measures. The results show that complex adaptation issues that are structured, can be resolved using a context specific adaptation grammar approach. [ABSTRACT FROM AUTHOR]

El Niño Modoki events can be further classified into El Niño Modoki I and II in terms of their opposite impacts on southern China rainfall (Wang and Wang, J Clim 26:1322-1338, 2013) and the Indian Ocean dipole mode (Wang and Wang, Clim Dyn 42:991-1005, 2014). The present paper develops an index to identify the types of El Niño events. The El Niño Modoki II (MII) index is defined as the leading principle component of multivariate empirical orthogonal function analysis of the normalized El Niño Modoki index, Niño4 index and 850 hPa relative vorticity anomalies averaged near the Philippine Sea during autumn. The MII index exhibits dominant variations on interannual (2-3 and 4-5 years) and decadal (10-20 years) timescales. El Niño Modoki II events can be well identified by using the MII index value being larger than 1 standard deviation. Further analyses and numerical model experiments confirm that the MII index can portray the major oceanic and atmospheric features of El Niño Modoki II events. The constructed MII index along with previous ENSO indices can be used for classifying and identifying all types of El Niño events. Because of distinct impacts induced by different types of El Niño events, the implication of the present study is that climate prediction and future climate projection under global warming can be improved by using the MII index and other indices to identify the types of El Niño events. [ABSTRACT FROM AUTHOR]

Climate change impact studies for the Northwest European Shelf (NWES) make use of various dynamical downscaling strategies in the experimental setup of regional ocean circulation models. Projected change signals from coupled and uncoupled downscalings with different domain sizes and forcing global and regional models show substantial uncertainty. In this paper, we investigate influences of the downscaling strategy on projected changes in the physical and biogeochemical conditions of the NWES. Our results indicate that uncertainties due to different downscaling strategies are similar to uncertainties due to the choice of the parent global model and the downscaling regional model. Downscaled change signals reveal to depend stronger on the downscaling strategy than on the model skills in simulating present-day conditions. Uncoupled downscalings of sea surface temperature (SST) changes are found to be tightly constrained by the atmospheric forcing. The incorporation of coupled air-sea interaction, by contrast, allows the regional model system to develop independently. Changes in salinity show a higher sensitivity to open lateral boundary conditions and river runoff than to coupled or uncoupled atmospheric forcings. Dependencies on the downscaling strategy for changes in SST, salinity, stratification and circulation collectively affect changes in nutrient import and biological primary production. [ABSTRACT FROM AUTHOR]

Climate change is a potential threat to achieving food security, particularly in the most food insecure regions. However, interpreting climate change projections to better understand the potential impacts of a changing climate on food security outcomes is challenging. This paper addresses this challenge through presenting a framework that enables rapid country-level assessment of vulnerability to food insecurity under a range of climate change and adaptation investment scenarios. The results show that vulnerability to food insecurity is projected to increase under all emissions scenarios, and the geographic distribution of vulnerability is similar to that of the present-day; parts of sub-Saharan Africa and South Asia are most severely affected. High levels of adaptation act to off-set these increases; however, only the scenario with the highest level of mitigation combined with high levels of adaptation shows improvements in vulnerability compared to the present-day. The results highlight the dual requirement for mitigation and adaptation to avoid the worst impacts of climate change and to make gains in tackling food insecurity. The approach is an update to the existing Hunger and Climate Vulnerability Index methodology to enable future projections, and the framework presented allows rapid updates to the results as and when new information becomes available, such as updated country-level yield data or climate model output. This approach provides a framework for assessing policy-relevant human food security outcomes for use in long-term climate change and food security planning; the results have been made available on an interactive website for policymakers (www.metoffice.gov.uk/food-insecurity-index). [ABSTRACT FROM AUTHOR]

In the last several decades, extended dry periods have affected the Mediterranean area with dramatic impacts on water resources. Climate models are predicting further warming, with negative effects on water availability. The authors analyze the hydroclimatic tendencies of a typical Mediterranean basin, the Flumendosa basin located in Sardinia, an island in the center of the Mediterranean Sea, where in the last 30 years a sequence of dry periods has seriously impacted the water management system. Interestingly, in the historic record the annual runoff reductions have been more pronounced than the annual precipitation reductions. This paper performs an analysis that links this runoff decrease to changes in the total annual precipitation and its seasonal structure. The seasonality is a key determinant of the surface runoff process, as it reflects the degree to which rainfall is concentrated during the winter. The observed reductions in winter precipitation are shown here to be well correlated (Pearson correlation coefficient of 20.5) with the North Atlantic Oscillation (NAO) index. Considering the predictability of the winter NAO, there is by extension an opportunity to predict future winter precipitation and runoff tendencies. The recent hydroclimatic trends are shown to impact hydrologic design criteria for water resources planning. The authors demonstrate that there is a dangerous increase of the drought severity viewed from the perspective of water resources planning. [ABSTRACT FROM AUTHOR]

Decadal prediction is a relatively new branch of climate science that bridges the gap between seasonal climate forecasts and multidecadal-to-century projections of climate change. This paper develops a three-step framework toward the potential application of decadal temperature predictions using the Community Climate System Model, version 4 (CCSM4). In step 1, the predictions are evaluated and it is found that the temperature hindcasts show skill over some regions of the United States and Canada. In step 2, the predictions are manipulated using two methods: a deterministic-anomaly approach (like climate change projections) and a probabilistic tercile-based approach (like seasonal forecasts). In step 3, the predictions are translated by adding a delta (for the anomaly manipulation) and conducting a weighted resample (for the probabilistic manipulation), as well as using a new hybrid method. Using the 2010 initialized hindcast, the framework is demonstrated for predicting 2011-15 over two case-study watersheds [Ottawa (Canada) and Colorado]. For the Colorado watershed, there was a noticeable shift toward higher temperatures, and the delta, weighted resample, and hybrid translations all were better at capturing the observed temperatures than was an approach that used climatological values. For the Ottawa watershed, the observed temperatures over the period of prediction were only subtly different than the climatological values; therefore, the difference between the translation methods was less noticeable. The advantages and disadvantages of the manipulation and translation approaches are discussed, as well as how their use will depend on the user context. The authors emphasize that skill evaluations should be tailored to particular applications and identify additional steps that are needed before the decadal temperature predictions can be readily incorporated into applications. [ABSTRACT FROM AUTHOR]

The Going Green! Middle Schoolers Out to Save the World project aims to direct middle school students' enthusiasm for hands‐on activities toward interest in science and other STEM areas while guiding them to solve real‐world problems. Students in this project are taught by their teachers to use energy monitoring equipment to audit standby power consumed by electronic devices in their homes and communities. Major findings were: (a) Beliefs in climate change increased more for students in the treatment than comparison group, pre to post; and (b) For girls there was a larger positive impact on climate change beliefs than for boys. These and additional findings presented in this paper provide evidence that a hands‐on engaged‐learning curriculum can have a positive influence on climate change beliefs and intentions and strengthen the association between the two constructs. [ABSTRACT FROM AUTHOR]

Particle depolarization ratio retrieved from lidar measurements are commonly used for aerosol-typing studies, microphysical inversion, or mass concentration retrievals. The particle depolarization ratio is one of the primary parameters that can differentiate several major aerosol components but only if the measurements are accurate enough. The accuracy related to the retrieval of particle depolarization ratios is the driving factor for assessing and improving the uncertainties of the depolarization products. This paper presents different depolarization calibration procedures used to improve the quality of the depolarization data. The results illustrate a significant improvement of the depolarization lidar products for all the selected lidar stations that have implemented depolarization calibration procedures. The calibrated volume and particle depolarization profiles at 532 nm show values that fall within a range that is generally accepted in the literature. [ABSTRACT FROM AUTHOR]

Traditionally, the daily average air temperature at a weather station is computed by taking the mean of two values, the maximum temperature (Tmax) and the minimum temperature (Tmin), over a 24-h period. These values form the basis for numerous studies of long-term climatologies (e.g., 30-yr normals) and recent temperature trends and changes. However, many first-order weather stations-such as those at airports-also record hourly temperature data. Using an average of the 24 hourly temperature readings to compute daily average temperature has been shown to provide a more precise and representative estimate of a given day's temperature. This study assesses the spatial variability of the differences in these two methods of daily temperature averaging [i.e., (Tmax 1 Tmin)/2; average of 24 hourly temperature values] for 215 first-order weather stations across the conterminous United States (CONUS) over the 30-yr period 1981-2010. A statistically significant difference is shown between the two methods, as well as consistent overestimation of temperature by the traditional method [(Tmax 1 Tmin)/2], particularly in southern and coastal portions of the CONUS. The explanation for the long-term difference between the two methods is the underlying assumption for the twice-daily method that the diurnal curve of temperature is symmetrical. Moreover, this paper demonstrates a spatially coherent pattern in the difference compared to the most recent part of the temperature record (2001-15). The spatial and temporal differences shown have implications for assessments of the physical factors influencing the diurnal temperature curve, as well as the exact magnitude of contemporary climate change. [ABSTRACT FROM AUTHOR]

Previous studies in the literature show that the annual cycle of surface air temperature (SAT) is changing in both amplitude and phase, and the SAT departures from the annual cycle are long-term correlated. However, the classical definition of temperature anomalies is based on the assumption that the annual cycle is constant, which contradicts the fact of changing annual cycle. How to quantify the impact of the changing annual cycle on the long-term correlation of temperature anomaly variability still remains open. In this paper, a recently developed data adaptive analysis tool, the nonlinear mode decomposition (NMD), is used to extract and remove time-varying annual cycle to reach the new defined temperature anomalies in which time-dependent amplitude of annual cycle has been considered. By means of detrended fluctuation analysis, the impact induced by inter-annual variability from the time-dependent amplitude of annual cycle has been quantified on the estimation of long-term correlation of long historical temperature anomalies in Europe. The results show that the classical climatology annual cycle is supposed to lack inter-annual fluctuation which will lead to a maximum artificial deviation centering around 600 days. This maximum artificial deviation is crucial to defining the scaling range and estimating the long-term persistence exponent accurately. Selecting different scaling range could lead to an overestimation or underestimation of the long-term persistence exponent. By using NMD method to extract the inter-annual fluctuations of annual cycle, this artificial crossover can be weakened to extend a wider scaling range with fewer uncertainties. [ABSTRACT FROM AUTHOR]

The disputes about the climate change are about the future. This paper distinguishes between different discourses on climate change taht correspond to different ways of imagining the future. These differences correspond to alternative ways of conceiving the formal and practicalcognitive dimensions of future horizons. Given the relevance of social struggels over climate change and the confrontation of different imaginary futures, it concludes that, away from the diagnosis of the presentification, we find ourselves in a situation where a contested futurization dominates. [ABSTRACT FROM AUTHOR]

During the World Climate Conference-3, Capacity Development has been acknowledged as a transversal component underpinning all the other Pillars of the Global Framework for Climate Services. Within the Mediterranean basin, the interest of climate services based on seasonal climate forecasts is rising because they provide an opportunity for developing a proactive approach towards water management. In 2014, the Regional Training Center (RTC) in Italy, in agreement with World Meteorological Organization (WMO) and member countries of Region I and VI, identified seasonal climate forecasts as a strategic subject of capacity development for the Mediterranean Region. Following design-based research methods, this paper presents the evolution of the training approaches adopted, from classroom lessons to a blend of practical and theoretical classroom and distance learning. This evolution, as well as the rising satisfaction of trainees' expectations encouraged WMO and the RTC to widen the spectrum of beneficiaries and to make the resulting course materials available for other regions and RTCs as a course package. The course package provides essential guidelines to facilitate adoption and adaptation of the course by different institutions and instructors, including those in other WMO Regions, based on regional or institutional learning needs and standards, while also serving the needs of individual learners. [ABSTRACT FROM AUTHOR]

In this paper, a climate dynamics model with the effects of topography and a non-constant external force, which consists of the Navier-Stokes equations and a temperature equation arising from the evolution process of the atmosphere, was considered. Under certain assumptions imposed on the initial data and by using some delicate estimates and compactness arguments, we proved the L -stability of weak solutions to the atmospheric equations. [ABSTRACT FROM AUTHOR]

Ice deposits of the permanent northern polar cap of Mars exhibit a clearly expressed layered structure connected with consecutive accumulation of a solid phase of H2O (ice) with different impurity fractions of dust. The observed structure of the northern polar cap deposits is direct evidence of the uneven accumulation of ice associated with climate variations on Mars over a long period of time. Outside the boundaries of the present northern polar cap, there are isolated remnant massifs of bright deposits with a clearly distinguishable layered structure. In this paper, we analyze the morphology, spatial distribution, and material composition of remnant massifs within the latitude belt of 60°-85°. The similarity in the structure and material composition found in the remnant massifs and the layered deposits of the northern polar cap of Mars apparently suggests that these formations were genetically connected in the past climatic epochs. [ABSTRACT FROM AUTHOR]

There is growing attention that the contrail by aviation may affect the earth's energy balance and climate change. In this paper, we propose a novel approach, the convolutional neural network model termed ContrailMod, which can be used in contrail classification with Himawari-8 stationary satellite and outperforms the representative conventional algorithm contrail detection algorithm (CDA). We estimate the distribution of potential contrail formation using temperature and specific humidity from ECMWF reanalysis (ERA-Interim) in South China region. According to the convolutional neural network identification (CNNI) and artificial visual inspection (AVI), we adopt the contrail occurrence and persistence (COP) measured from Himawari-8 stationary satellite imagery to evaluate the potential contrail coverage (PCC) fractions of the ECMWF reanalysis data. There is a high correlation between contrail occurrence and persistence and potential contrail coverage. The correlation coefficient of convolutional neural network identification is close to artificial visual inspection, which illustrates that the parameterization is reliable by comparing the observation results and the actual reflection of contrail coverage in parameterization calculation of South China region. [ABSTRACT FROM AUTHOR]

This paper offers new high-resolution oxygen and carbon isotope data from Stalagmite S1 from Mavri Trypa Cave, SW Peloponnese. Our data provide the climate background to the destruction of the nearby Mycenaean Palace of Nestor at Pylos at the transition from Late Helladic (LH) IIIB to LH IIIC, ~3150–3130 years before present (before AD 1950, hereafter yrs BP) and the subsequent period. S1 is dated by 24 U-Th dates with an averaged precision of ±26 yrs (2σ), providing one of the most robust paleoclimate records from the eastern Mediterranean for the end of the Late Bronze Age (LBA). The δ18O record shows generally wetter conditions at the time when the Palace of Nestor at Pylos was destroyed, but a brief period of drier conditions around 3200 yrs BP may have disrupted the Mycenaean agricultural system that at the time was likely operating close to its limit. Gradually developing aridity after 3150 yrs BP, i.e. subsequent to the destruction, probably reduced crop yields and helped to erode the basis for the reinstitution of a central authority and the Palace itself. [ABSTRACT FROM AUTHOR]

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts. [ABSTRACT FROM AUTHOR]

Almost all climate change studies of plants and animals adopt an 'equilibrium assumption' that analyses of natural distributions provide reliable estimates of species climatic requirements. Yet commercial forestry trials around the world have shown that many tree species can grow successfully under climatic conditions somewhat different from those of their natural distributions. Under climate change it is reasonable to assume that a long-lived tree species, already well-established at particular sites, may be able to display some of the climatic adaptability shown in trials outside its natural distribution. The purpose of this paper is to outline how some species distribution modelling (SDM) and ecological niche modelling (ENM) studies have estimated species climatic requirements beyond those shown by conventional analyses of just their natural distributions, and to show how recent developments are facilitating these analyses. Some of the earliest SDM studies of trees demonstrated the desirability of assessing species climatic requirements using data from outside, as well as within, their natural distributions. In recent years, with the advent of large biodiversity databases and some revised SDM analysis methods, there has been a revival of interest in measuring species climatic requirements using data from beyond their realized niches. It is recommended that at least for tree species, natural distribution data, and where possible results from plantings beyond natural distributions, should be analysed in climate change studies. When this is not possible, some alternative methods of estimating species climatic requirements are identified and some of their advantages and disadvantages are considered. [ABSTRACT FROM AUTHOR]

This paper reports on a study in which students used agent-based computer models to learn about complex systems ideas of relevance to understanding climate change. The experimental condition used a Productive Failure (PF) learning design in which ninth grade students initially worked with agent-based computer models to solve challenge problems followed by teacher instruction about targeted climate and complexity ideas. In contrast, the comparison condition employed a Direct Instruction (DI) learning design in which the teacher instruction was provided initially, followed by the students working on the same computer models and challenge problems as the experimental group. The students in the PF group scored significantly higher on the post-test on measures of climate and complex systems explanatory knowledge and near and far knowledge transfer. Theoretical and practical implications of these findings are considered. [ABSTRACT FROM AUTHOR]