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Scientific agreement on climate change has strengthened over the past few decades, with around 97% of publishing climate scientists agreeing that human activity is causing global warming. While scientific understanding has strengthened, a small but persistent proportion of the public actively opposes the mainstream scientific position. A number of factors contribute to this rejection of scientific evidence, with political ideology playing a key role. Conservative think tanks, supported with funding from vested interests, have been and continue to be a prolific source of misinformation about climate change. A major strategy by opponents of climate mitigation policies has been to cast doubt on the level of scientific agreement on climate change, contributing to the gap between public perception of scientific agreement and the 97% expert consensus. This “consensus gap” decreases public support for mitigation policies, demonstrating that misconceptions can have significant societal consequences. While scientists need to communicate the consensus, they also need to be aware of the fact that misinformation can interfere with the communication of accurate scientific information. As a consequence, neutralizing the influence of misinformation is necessary. Two approaches to neutralize misinformation involve refuting myths after they have been received by recipients (debunking) or preemptively inoculating people before they receive misinformation (prebunking). Research indicates preemptive refutation or “prebunking” is more effective than debunking in reducing the influence of misinformation. Guidelines to practically implement responses (both preemptive and reactive) can be found in educational research, cognitive psychology, and a branch of psychological research known as inoculation theory. Synthesizing these separate lines of research yields a coherent set of recommendations for educators and communicators. Clearly communicating scientific concepts, such as the scientific consensus, is important, but scientific explanations should be coupled with inoculating explanations of how that science can be distorted.
The 2°C target for global warming had been under severe scrutiny in the run-up to the climate negotiations in Paris in 2015 (COP21). Clearly, with a remaining carbon budget of 470–1,020 GtCO2eq from 2015 onwards for a 66% probability of stabilizing at concentration levels consistent with remaining below 2°C warming at the end of the 21st century and yearly emissions of about 40 GtCO2 per year, not much room is left for further postponing action. Many of the low stabilization pathways actually resort to the extraction of CO2 from the atmosphere (known as negative emissions or Carbon Dioxide Removal [CDR]), mostly by means of Bioenergy with Carbon Capture and Storage (BECCS): if the biomass feedstock is produced sustainably, the emissions would be low or even carbon-neutral, as the additional planting of biomass would sequester about as much CO2 as is generated during energy generation. If additionally carbon capture and storage is applied, then the emissions balance would be negative. Large BECCS deployment thus facilitates reaching the 2°C target, also allowing for some flexibility in other sectors that are difficult to decarbonize rapidly, such as the agricultural sector. However, the large reliance on BECCS has raised uneasiness among policymakers, the public, and even scientists, with risks to sustainability being voiced as the prime concern. For example, the large-scale deployment of BECCS would require vast areas of land to be set aside for the cultivation of biomass, which is feared to conflict with conservation of ecosystem services and with ensuring food security in the face of a still growing population.
While the progress that has been made in Paris leading to an agreement on stabilizing “well below 2°C above pre-industrial levels” and “pursuing efforts to limit the temperature increase to 1.5°C” was mainly motivated by the extent of the impacts, which are perceived to be unacceptably high for some regions already at lower temperature increases, it has to be taken with a grain of salt: moving to 1.5°C will further shrink the time frame to act and BECCS will play an even bigger role. In fact, aiming at 1.5°C will substantially reduce the remaining carbon budget previously indicated for reaching 2°C. Recent research on the biophysical limits to BECCS and also other negative emissions options such as Direct Air Capture indicates that they all run into their respective bottlenecks—BECCS with respect to land requirements, but on the upside producing bioenergy as a side product, while Direct Air Capture does not need much land, but is more energy-intensive. In order to provide for the negative emissions needed for achieving the 1.5°C target in a sustainable way, a portfolio of negative emissions options needs to minimize unwanted effects on non–climate policy goals.
Rasmus Fensholt, Cheikh Mbow, Martin Brandt, and Kjeld Rasmussen
In the past 50 years, human activities and climatic variability have caused major environmental changes in the semi-arid Sahelian zone and desertification/degradation of arable lands is of major concern for livelihoods and food security. In the wake of the Sahel droughts in the early 1970s and 1980s, the UN focused on the problem of desertification by organizing the UN Conference on Desertification (UNCOD) in Nairobi in 1976. This fuelled a significant increase in the often alarmist popular accounts of desertification as well as scientific efforts in providing an understanding of the mechanisms involved. The global interest in the subject led to the nomination of desertification as focal point for one of three international environmental conventions: the UN Convention to Combat Desertification (UNCCD), emerging from the Rio conference in 1992. This implied that substantial efforts were made to quantify the extent of desertification and to understand its causes. Desertification is a complex and multi-faceted phenomenon aggravating poverty that can be seen as both a cause and a consequence of land resource depletion. As reflected in its definition adopted by the UNCCD, desertification is “land degradation in arid, semi-arid[,] and dry sub-humid areas resulting from various factors, including climate variation and human activities” (UN, 1992). While desertification was seen as a phenomenon of relevance to drylands globally, the Sahel-Sudan region remained a region of specific interest and a significant amount of scientific efforts have been invested to provide an empirically supported understanding of both climatic and anthropogenic factors involved. Despite decades of intensive research on human–environmental systems in the Sahel, there is no overall consensus about the severity of desertification and the scientific literature is characterized by a range of conflicting observations and interpretations of the environmental conditions in the region. Earth Observation (EO) studies generally show a positive trend in rainfall and vegetation greenness over the last decades for the majority of the Sahel and this has been interpreted as an increase in biomass and contradicts narratives of a vicious cycle of widespread degradation caused by human overuse and climate change. Even though an increase in vegetation greenness, as observed from EO data, can be confirmed by ground observations, long-term assessments of biodiversity at finer spatial scales highlight a negative trend in species diversity in several studies and overall it remains unclear if the observed positive trends provide an environmental improvement with positive effects on people’s livelihood.
Sander van der Linden
Individuals, both within and between different countries, vary substantially in the extent to which they view climate change as a risk. What could explain such variation in climate change risk perception around the world? Climate change is relatively unique as a risk in the sense that it is difficult for people to experience directly or even detect on a purely perceptual or sensory level. In fact, research across the social and behavioral sciences has shown that although people might correctly perceive some changes in long-term climate conditions, psychological factors are often much more influential in determining how the public perceives the risk of climate change. Indeed, decades of research has shown that cognitive, affective, social, and cultural factors all greatly influence the public’s perception of risk, and that these factors, in turn, often interact with each other in complex ways. Yet, although a wide variety of cognitive, experiential, socio-cultural and demographic characteristics have all proven to be relevant, are there certain factors that systematically stand out in explaining and predicting climate change risk perception around the world? And even if so, what do we mean, exactly, by the term “risk perception” and to what extent does the way in which risk perception is measured influence the outcome? Last but certainly not least, how important is public concern about climate change in determining people’s level of behavioral engagement and policy-support for the issue?
Dramatic climate changes have occurred in the Baltic Sea region caused by changes in orbital movement in the earth–sun system and the melting of the Fennoscandian Ice Sheet. Added to these longer-term changes, changes have occurred at all timescales, caused mainly by variations in large-scale atmospheric pressure systems due to competition between the meandering midlatitude low-pressure systems and high-pressure systems. Here we follow the development of climate science of the Baltic Sea from when observations began in the 18th century to the early 21st century. The question of why the water level is sinking around the Baltic Sea coasts could not be answered until the ideas of postglacial uplift and the thermal history of the earth were better understood in the 19th century and periodic behavior in climate related time series attracted scientific interest. Herring and sardine fishing successes and failures have led to investigations of fishery and climate change and to the realization that fisheries themselves have strongly negative effects on the marine environment, calling for international assessment efforts. Scientists later introduced the concept of regime shifts when interpreting their data, attributing these to various causes. The increasing amount of anoxic deep water in the Baltic Sea and eutrophication have prompted debate about what is natural and what is anthropogenic, and the scientific outcome of these debates now forms the basis of international management efforts to reduce nutrient leakage from land. The observed increase in atmospheric CO2 and its effects on global warming have focused the climate debate on trends and generated a series of international and regional assessments and research programs that have greatly improved our understanding of climate and environmental changes, bolstering the efforts of earth system science, in which both climate and environmental factors are analyzed together.
Major achievements of past centuries have included developing and organizing regular observation and monitoring programs. The free availability of data sets has supported the development of more accurate forcing functions for Baltic Sea models and made it possible to better understand and model the Baltic Sea–North Sea system, including the development of coupled land–sea–atmosphere models. Most indirect and direct observations of the climate find great variability and stochastic behavior, so conclusions based on short time series are problematic, leading to qualifications about periodicity, trends, and regime shifts. Starting in the 1980s, systematic research into climate change has considerably improved our understanding of regional warming and multiple threats to the Baltic Sea. Several aspects of regional climate and environmental changes and how they interact are, however, unknown and merit future research.
Nelya Koteyko and Dimitrinka Atanasova
Discourse analysis is an interdisciplinary field of inquiry that has been increasingly used by climate change communication scholars since the late 1990s. In its broadest sense, discourse analysis is the study of the social through analysis of language, including face-to-face talk, written media texts, and documents, as well as images and symbols. Studies in this field encompass a broad range of theories and analytic approaches for investigating meaning. Due to its focus on the sociocultural and political context in which text and talk occur, discourse analysis is pertinent to the concerns of climate change communication scholars as it has the potential to reveal the ideological dimensions of stakeholder beliefs and the dissemination of climate change-related information in the media. In contrast to studies under the rubric of frame analysis and survey-based analyses of public perceptions, this research places emphasis on the situated study of different stakeholders involved in climate change communication. Here attention is paid not only to the content being communicated (e.g., themes) but also to the linguistic forms and contexts that shape language and interaction. Both of these require an understanding of audiences’ cultural, political, and socioeconomic conditions. From the participatory perspective, discourse analysis can therefore illuminate the moral, ethical, and cultural dimensions of the climate change issue.
Kathryn E. Cooper and Erik C. Nisbet
As climate change becomes an increasingly serious problem, mass media are tasked with educating the public. Documentary films and television shows (also called “edutainment”) have been used for decades to communicate about the natural world so that the public may hopefully become informed about science in a simplified, easy-to-understand way. Although producers ostensibly create environmental documentaries in order to inform and/or advocate, theory development and empirical research is limited and insufficient in explaining how this genre influences audiences and why this genre may or may not be an effective means of science communication.
Environmental documentaries have the potential to deeply impact audiences because these films promote learning while viewers are entertained, because engagement with the documentary narrative (story) can overcome biases such as politically driven motivated reasoning (conforming new evidence to existing beliefs) and can leverage biases such as the tendency to rely on affect (emotions) when estimating risks. Documentary storytelling can also enhance learning by connecting the causes and consequences of climate change in a sequential narrative.
Climate change is a highly contentious political issue, which is reflected in the diversity of viewpoints found in climate change documentaries despite scientific consensus about the issue. While many of these films serve an educational purpose, others are geared toward advocacy. These advocacy programs aim to mobilize value-congruent audiences to engage in personal and collective action and/or to demand policy change. However, people prefer messages that align with their preexisting values, and so the belief disparity between climate change advocates and deniers grows with increasing media exposure as audiences with different beliefs watch and receive climate change messages in very different ways. Filmmakers and scientists must focus future efforts on creating visually engaging narratives within documentaries to promote both education and advocacy to diverse audiences.
What are the local consequences of a global climate change? This question is important for proper handling of risks associated with weather and climate. It also tacitly assumes that there is a systematic link between conditions taking place on a global scale and local effects. It is the utilization of the dependency of local climate on the global picture that is the backbone of downscaling; however, it is perhaps easiest to explain the concept of downscaling in climate research if we start asking why it is necessary.
Global climate models are our best tools for computing future temperature, wind, and precipitation (or other climatological variables), but their limitations do not let them calculate local details for these quantities. It is simply not adequate to interpolate from model results. However, the models are able to predict large-scale features, such as circulation patterns, El Niño Southern Oscillation (ENSO), and the global mean temperature. The local temperature and precipitation are nevertheless related to conditions taking place over a larger surrounding region as well as local geographical features (also true, in general, for variables connected to weather/climate). This, of course, also applies to other weather elements.
Downscaling makes use of systematic dependencies between local conditions and large-scale ambient phenomena in addition to including information about the effect of the local geography on the local climate. The application of downscaling can involve several different approaches. This article will discuss various downscaling strategies and methods and will elaborate on their rationale, assumptions, strengths, and weaknesses.
One important issue is the presence of spontaneous natural year-to-year variations that are not necessarily directly related to the global state, but are internally generated and superimposed on the long-term climate change. These variations typically involve phenomena such as ENSO, the North Atlantic Oscillation (NAO), and the Southeast Asian monsoon, which are nonlinear and non-deterministic.
We cannot predict the exact evolution of non-deterministic natural variations beyond a short time horizon. It is possible nevertheless to estimate probabilities for their future state based, for instance, on projections with models run many times with slightly different set-up, and thereby to get some information about the likelihood of future outcomes.
When it comes to downscaling and predicting regional and local climate, it is important to use many global climate model predictions. Another important point is to apply proper validation to make sure the models give skillful predictions.
For some downscaling approaches such as regional climate models, there usually is a need for bias adjustment due to model imperfections. This means the downscaling doesn’t get the right answer for the right reason. Some of the explanations for the presence of biases in the results may be different parameterization schemes in the driving global and the nested regional models.
A final underlying question is: What can we learn from downscaling? The context for the analysis is important, as downscaling is often used to find answers to some (implicit) question and can be a means of extracting most of the relevant information concerning the local climate. It is also important to include discussions about uncertainty, model skill or shortcomings, model validation, and skill scores.
S.C. Pryor and A.N. Hahmann
Winds within the atmospheric boundary layer (i.e., near to Earth’s surface) vary across a range of scales from a few meters and sub-second timescales (i.e., the scales of turbulent motions) to extremely large and long-period phenomena (i.e., the primary circulation patterns of the global atmosphere). Winds redistribute momentum and heat, and short- and long-term predictions of wind characteristics have applications to a number of socioeconomic sectors (e.g., engineering infrastructure). Despite its importance, atmospheric flow (i.e., wind) has been subject to less research within the climate downscaling community than variables such as air temperature and precipitation. However, there is a growing comprehension that wind storms are the single biggest source of “weather-related” insurance losses in Europe and North America in the contemporary climate, and that possible changes in wind regimes and intense wind events as a result of global climate non-stationarity are of importance to a variety of potential climate change feedbacks (e.g., emission of sea spray into the atmosphere), ecological impacts (such as wind throw of trees), and a number of other socioeconomic sectors (e.g., transportation infrastructure and operation, electricity generation and distribution, and structural design codes for buildings). There are a number of specific challenges inherent in downscaling wind including, but not limited to, the fact that it has both magnitude (wind speed) and orientation (wind direction). Further, for most applications, it is necessary to accurately downscale the full probability distribution of values at short timescales (e.g., hourly), including extremes, while the mean wind speed averaged over a month or year is of little utility. Dynamical, statistical, and hybrid approaches have been developed to downscale different aspects of the wind climate, but have large uncertainties in terms of high-impact aspects of the wind (e.g., extreme wind speeds and gusts). The wind energy industry is a key application for right-scaled wind parameters and has been a major driver of new techniques to increase fidelity. Many opportunities remain to refine existing downscaling methods, to develop new approaches to improve the skill with which the spatiotemporal scales of wind variability are represented, and for new approaches to evaluate skill in the context of wind climates.
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.
Dynamical downscaling (DD) consists of the use of physical models to downscale the large-scale climate information produced by coupled Atmosphere-Ocean Global Climate Models (AOGCMs). This can be achieved with global high-resolution atmospheric GCMs (HIRGCMs), variable resolution GCMs (VARGCMs) and limited area Regional Climate Models (RCMs). Borrowing from numerical weather prediction, DD techniques originated in the late 1980s from the need to produce high-resolution regional climate information for application to impact studies. The philosophy behind DD is that the AOGCM can simulate the response of the global circulation to large-scale forcings (e.g., due to greenhouse gases) and the DD tools can regionally enhance this response to account for the contribution of fine-scale processes and forcings, for example, due to aerosols and complex topography, coastlines, and vegetation cover.
Since the 1990s the use of DD for climate studies, and principally RCMs, has grown tremendously, to the point that DD techniques, along with Empirical-Statistical Downscaling (ESD), are considered key elements in the production of climate information for regions. In fact, the use of DD is justified to the extent that it adds useful and robust high-resolution information to that produced by AOGCMs, and considerable research has gone into investigating this central issue, often referred to as “added value,” which is still often debated. Today a number of flexible and portable RCM systems are available, which can be routinely run for up to centennial-scale experiments over domains distributed worldwide for a wide range of applications, from process studies to paleo and future climate simulations. The model resolution has steadily increased up to grid spacings of ~10–25 km, and a new generation of non-hydrostatic RCMs is being developed and tested for use in very-high-resolution (~ few km) convection-permitting simulations. In addition, the development of coupled regional earth system models is a new frontier area of research aimed at exploring the importance of air-sea-land interactions at regional scales.
A fundamental step toward a better understanding of DD techniques has been the inception of multimodel intercomparison studies. These were originally regional in nature, which prevented the application of common protocols and thus hindered the transfer of know-how across projects. However, this problem was addressed through the creation in the late 2000s of the Coordinated Regional Climate Downscaling Experiment (CORDEX), which provided a common simulation protocol across regions worldwide, representing a fundamental growth step for the DD community.
Often different DD and ESD techniques have been seen in competition with each other, and with AOGCMs. However the realization is growing that they all represent complementary pieces to compose the puzzle of generating robust and credible climate services to address the needs and concerns of different regions, countries, and societal sectors. DD will continue to be increasingly used in the generation of actionable climate information, but a solid understanding of the advantages and limitations of DD is paramount to its use in this process.
B.N. Goswami and Soumi Chakravorty
Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.
The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.
The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.
A. Johannes Dolman, Luis U. Vilasa-Abad, and Thomas A. J. Janssen
Drylands cover around 40% of the land surface on Earth and are inhabited by more than 2 billion people, who are directly dependent on these lands. Drylands are characterized by a highly variable rainfall regime and inherent vegetation-climate feedbacks that can enhance the resilience of the system, but also can amplify disturbances. In that way, the system may get locked into two alternate stable states: one relatively wet and vegetated, and the other dry and barren. The resilience of dryland ecosystems derives from a number of adaptive mechanisms by which the vegetation copes with prolonged water stress, such as hydraulic redistribution. The stochastic nature of both the vegetation dynamics and the rainfall regime is a key characteristic of these systems and affects its management in relation to the feedbacks. How the ecohydrology of the African drylands will change in the future depends on further changes in climate, human disturbances, land use, and the socioeconomic system.
Salil Benegal and Lyle Scruggs
How do economic conditions affect public opinion about climate change? Since the early days of the modern environmental movement, people have debated three main perspectives on how economic conditions impact environmental attitudes. The post-materialism perspective suggests that social and individual affluence leads to increasing concern and demands for action on climate change through long-run cultural change. A second view suggests that attitudes about climate change are shaped largely independently of economic conditions and reflect the emergence of a new environmental paradigm. A third view, associated with ecological modernization theory, suggests that attitudes about climate change are shaped in important ways by short-term economic factors, such as economic self-interest, and are likely to vary among citizens over time. While all of these perspectives have merit, we emphasize the impact of macroeconomic risk and business cycle fluctuations in shaping public attitudes toward climate change and more general aspects of environmental policy. Rising unemployment rates, for example, tend to be associated with declines in concern about environmental problems. This is a trend that is repeated across more than four decades and multiple recessions and recoveries dating back to the 1970s.
Although it is obviously a more recently recognized environmental problem, public attitudes about climate change are also affected considerably by short-run economic conditions. This fact can influence the possibilities for policy reform. Through a process of motivated reasoning, in which immediate concerns and preferences to address economic risk lead individuals to adjust other attitudes about the environment, public concerns about climate change have ebbed and flowed with the business cycle. Other economic factors—such as societal affluence, personal employment status, or income—have more limited effects on attitudes about climate change, at least in most developed countries.
The impact of economic risk on public attitudes about climate change has important implications for policy reform in democratic societies, because public support matters. While partisanship and ideology are frequently cited as explanations for fluctuating public opinion about climate change, macroeconomic risk offers a complementary explanation, which suggests that the framing and timing of environmental policy initiatives is as important as ideological acceptability. Positioning environmental actions or initiatives in better economic conditions, emphasizing immediate economic benefits, and countering unwarranted beliefs about personal costs, especially during challenging economic circumstances, should improve the prospects for efforts to address climate change.
Timothy A. Gibson
Over the past two decades, the global news industry has embarked upon a major project of economic, organizational, and technological restructuring. In organizational terms, successive waves of mergers and buyouts have yielded a global news landscape where most of the larger firms are owned by shareholders and run by executives whose singular focus is on rationalizing news production and improving profitability. Although in some cases, these shareholders and executives have used their authority to influence climate coverage directly, more often their goals are non-ideological: reducing labor costs and increasing revenues. At the same time, in a parallel development, the digital media revolution not only has spawned a host of new online competitors but also has cut deeply into the advertising revenue once enjoyed by traditional media firms.
Within legacy news organizations, these industrial and technological trends have converged to dramatically intensify the work pressures facing environmental journalists. For example, in an effort to reduce costs, many firms have reduced newsroom staff to a small core of multi-tasking reporters, supported by a wider web of part-time freelancers. In this process, the science and environment beat is often the first to go, with environmental specialists among the first to be reassigned or downsized (and pushed into freelance work). For all reporters, there is increased pressure to produce more stories in less time on multiple media platforms, a trend that, in turn, enhances the power of special interests to influence climate coverage through public relations and other external information subsidies.
Due to these converging industrial and technological trends, environmental reporters now work in a new media ecosystem that is complex, subject to contradictory pressures, and in many ways hostile to the production of high-quality climate news. When the environmental beat is cut, climate change often becomes the purview of general assignment reporters who lack experience and expertise. For their part, freelance specialists continue to cover climate news, but their ability to sustain this coverage over the long term is constrained by their part-time status. Finally, although niche climate blogs have provided welcome spaces for environmental journalists to produce in-depth coverage, these outlets usually reach only tiny audiences composed of the already-engaged.
In short, without significant action, the regrettable status quo of climate news—that is, an episodic sprinkling of climate coverage scattered across the media ecosystem—will continue indefinitely. Policy-makers should therefore restore long-term institutional and economic support for environmental journalists specializing in climate science and policy.
Courtney Plante, Johnie J. Allen, and Craig A. Anderson
Given the dire nature of many researchers’ predictions about the effects of global climate change (e.g., rising sea levels, droughts, more extreme weather), it comes as little surprise that less attention has been paid to the subtler, less direct outcomes of rapid climate change: psychological, sociological, political, and economic effects. In this chapter we explore one such outcome in particular: the effects of rapid climate change on aggression. We begin by exploring the potential for climate change to directly affect aggression in individuals, focusing on research showing the relationship between uncomfortably hot ambient temperature and aggression. Next, we review several lines of research illustrating ways that climate change can indirectly increase aggression in individuals. We then shift our focus from individuals to the effects of climate change on group-level aggression. We finish by addressing points of contention, including the challenge that the effects of climate change on aggression are too remote and too small to be considered relevant.
Ashley A. Anderson
Early research on the relationship between social media use and its relationship to climate change opinion, knowledge, and behavior suggests several positive impacts. Social media encourages greater knowledge of climate change, mobilization of climate change activists, space for discussing the issue with others, and online discussions that frame climate change as a negative for society. Social media, however, does provide space for framing climate change skeptically and activating those with a skeptical perspective of climate change. Further examination of the relationship between social media use and climate change perceptions is warranted.
For the general public, the news media are an important source of information about climate change. They have significant potential to influence public understanding and perceptions of the issue. Television news, because of its visual immediacy and authoritative presentation, is likely to be particularly influential. Numerous studies have shown that television news can affect public opinion directly and indirectly through processes such as agenda setting and framing. Moreover, even in a fragmented media environment largely dominated by online communication, television remains a prominent medium through which citizens follow news about science issues. Given this, scholars over the last several decades have endeavored to map the content of television news reporting on climate change and its effects on public opinion and knowledge. Results from this research suggest that journalists’ adherence to professional norms such as balance, novelty, dramatization, and personalization, along with economic pressures and sociopolitical influences, have produced inaccuracies and distortions in television news coverage of climate change. For example, content analyses have found that U.S. network television news stories tend to over-emphasize dramatic impacts and imagery, conflicts between political groups and personalities, and the uncertainty surrounding climate science and policy. At the same time, those skeptical of climate change have been able to exploit journalists’ norms of balance and objectivity to amplify their voices in television coverage of climate change. In particular, the increasingly opinionated 24-hour cable news networks have become a megaphone for ideological viewpoints on climate change. In the United States, a coordinated climate denial movement has used Fox News to effectively spread its message discrediting climate science. Coverage on Fox News is overwhelmingly dismissive of climate change and disparaging toward climate science and scientists. Coverage on CNN and MSNBC is more accepting of climate change; however, while MSNBC tends to vilify the conservative opposition to climate science and policy, and occasionally exaggerates the impacts of climate change, CNN sends more mixed signals. Survey and experimental analyses indicate that these trends in television news coverage of climate change have important effects on public opinion and may, in particular, fuel confusion and apathy among the general U.S. public and foster opinion extremity among strong partisans.
Xiaodong Liu and Libin Yan
As a unique and high gigantic plateau, the Tibetan Plateau (TP) is sensitive and vulnerable to global climate change, and its climate change tendencies and the corresponding impact on regional ecosystems and water resources can provide an early alarm for global and mid-latitude climate changes. Growing evidence suggests that the TP has experienced more significant warming than its surrounding areas during past decades, especially at elevations higher than 4 km. Greater warming at higher elevations than at lower elevations has been reported in several major mountainous regions on earth, and this interesting phenomenon is known as elevation-dependent climate change, or elevation-dependent warming (EDW).
At the beginning of the 21st century, Chinese scholars first noticed that the TP had experienced significant warming since the mid-1950s, especially in winter, and that the latest warming period in the TP occurred earlier than enhanced global warming since the 1970s. The Chinese also first reported that the warming rates increased with the elevation in the TP and its neighborhood, and the TP was one of the most sensitive areas to global climate change. Later, additional studies, using more and longer observations from meteorological stations and satellites, shed light on the detailed characteristics of EDW in terms of mean, minimum, and maximum temperatures and in different seasons. For example, it was found that the daily minimum temperature showed the most evident EDW in comparison to the mean and daily maximum temperatures, and EDW is more significant in winter than in other seasons. The mean daily minimum and maximum temperatures also maintained increasing trends in the context of EDW. Despite a global warming hiatus since the turn of the 21st century, the TP exhibited persistent warming from 2001 to 2012.
Although EDW has been demonstrated by more and more observations and modeling studies, the underlying mechanisms for EDW are not entirely clear owing to sparse, discontinuous, and insufficient observations of climate change processes. Based on limited observations and model simulations, several factors and their combinations have been proposed to be responsible for EDW, including the snow-albedo feedback, cloud-radiation effects, water vapor and radiative fluxes, and aerosols forcing. At present, however, various explanations of the mechanisms for EDW are mainly derived from model-based research, lacking more solid observational evidence. Therefore, to comprehensively understand the mechanisms of EDW, a more extensive and multiple-perspective climate monitoring system is urgently needed in the areas of the TP with high elevations and complex terrains.
High-elevation climate change may have resulted in a series of environmental consequences, such as vegetation changes, permafrost melting, and glacier shrinkage, in mountainous areas. In particular, the glacial retreat could alter the headwater environments on the TP and the hydrometeorological characteristics of several major rivers in Asia, threatening the water supply for the people living in the adjacent countries. Taking into account the climate-model projections that the warming trend will continue over the TP in the coming decades, this region’s climate change and the relevant environmental consequences should be of great concern to both scientists and the general public.
Maxwell Boykoff and Gesa Luedecke
During the past three decades, elite news media have become influential translators of climate change linking science, policy, and the citizenry. Historical trends in public discourse—shaped in significant part by elite media—demonstrate news media’s critical role in shaping public perception and the level of concern towards climate change. Media representations of climate change and global warming are embedded in social, cultural, political, and economic dimensions that influence individual-level processes such as everyday journalistic practices. Media have a strong influence on policy decision-making, attitudes, perspectives, intentions, and behavioral change, but those connections can be challenging to pinpoint; consequently, examinations of elite news coverage of climate change, particularly in recent decades, have sought to gain a stronger understanding of these complex and dynamic webs of interactions. In so doing, research has more effectively traced how media have taken on varied roles in the climate change debate, from watch dogs to lap dogs to guard dogs in the public sphere. Within these areas of research, psychological aspects of media influence have been relatively underemphasized. However, interdisciplinary and problem-focused research investigations of elite media coverage stand to advance considerations of public awareness, discourse, and engagement. Elite news media critically contribute to public discourse and policy priorities through their “mediating” and interpretative influences. Therefore, a review of examinations of these dynamics illuminate the bridging role of elite news coverage of climate change between formal science and policy, and everyday citizens in the public sphere.
Aristita Busuioc and Alexandru Dumitrescu
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.
The concept of statistical downscaling or empirical-statistical downscaling became a distinct and important scientific approach in climate science in recent decades, when the climate change issue and assessment of climate change impact on various social and natural systems have become international challenges. Global climate models are the best tools for estimating future climate conditions. Even if improvements can be made in state-of-the art global climate models, in terms of spatial resolution and their performance in simulation of climate characteristics, they are still skillful only in reproducing large-scale feature of climate variability, such as global mean temperature or various circulation patterns (e.g., the North Atlantic Oscillation). However, these models are not able to provide reliable information on local climate characteristics (mean temperature, total precipitation), especially on extreme weather and climate events. The main reason for this failure is the influence of local geographical features on the local climate, as well as other factors related to surrounding large-scale conditions, the influence of which cannot be correctly taken into consideration by the current dynamical global models.
Impact models, such as hydrological and crop models, need high resolution information on various climate parameters on the scale of a river basin or a farm, scales that are not available from the usual global climate models. Downscaling techniques produce regional climate information on finer scale, from global climate change scenarios, based on the assumption that there is a systematic link between the large-scale and local climate. Two types of downscaling approaches are known: a) dynamical downscaling is based on regional climate models nested in a global climate model; and b) statistical downscaling is based on developing statistical relationships between large-scale atmospheric variables (predictors), available from global climate models, and observed local-scale variables of interest (predictands).
Various types of empirical-statistical downscaling approaches can be placed approximately in linear and nonlinear groupings. The empirical-statistical downscaling techniques focus more on details related to the nonlinear models—their validation, strengths, and weaknesses—in comparison to linear models or the mixed models combining the linear and nonlinear approaches. Stochastic models can be applied to daily and sub-daily precipitation in Romania, with a comparison to dynamical downscaling. Conditional stochastic models are generally specific for daily or sub-daily precipitation as predictand.
A complex validation of the nonlinear statistical downscaling models, selection of the large-scale predictors, model ability to reproduce historical trends, extreme events, and the uncertainty related to future downscaled changes are important issues. A better estimation of the uncertainty related to downscaled climate change projections can be achieved by using ensembles of more global climate models as drivers, including their ability to simulate the input in downscaling models. Comparison between future statistical downscaled climate signals and those derived from dynamical downscaling driven by the same global model, including a complex validation of the regional climate models, gives a measure of the reliability of downscaled regional climate changes.