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The purpose of the present paper is to examine a selection of macro- and micro-linguistic features (at text and sentence/word level respectively) of the South-African Green Paper 'National Climate Change Response' from 2010. Our overarching assumption is that the Green Paper needs to handle competing interests, beliefs and voices in a narrative structure favouring specific courses of action. How does the government portray the complex natural and societal phenomenon of climate change, and how does it take into account the many and often competing national and international views and interests which come into play? Our hypothesis is that the Green Paper constructs a narrative and that it relates to a number of voices other than that of the authors, through linguistic markers of polyphony, such as negation, sentence connectives, adverbs and reported speech. Thus we propose a narrative and polyphonic analysis of the Green Paper, at the level of the text as a whole (macro-level) but also with attention to linguistic constructions of polyphony or 'multi-voicedness' (micro-level). We find that the narrative-polyphonic properties of the Green Paper contribute to a strategy for building consensus on climate change policy. The South African government assumes the role of main hero in its own climate change 'story', and there are subtle forms of interaction with different and typically non-identified voices, such as concessive constructions and presuppositions. These results support our overarching interpretation of the whole document as striving to impose a South African consensus on the issue of climate change. [ABSTRACT FROM AUTHOR]

Article 7 of the Paris Agreement recognizes that adaptation is a 'global challenge faced by all with local, regional and international dimensions.' It further establishes the 'global goal on adaptation focusing on enhancing adaptive capacity, strengthening resilience and reducing vulnerability to climate change, with a view to contributing to sustainable development.' However, the lack of international cooperation between the global north and global south challenge the formulation and implementation of climate change adaptation strategies. This paper brings in the concept of global public goods (GPGs) to the lexicon of climate adaptation and highlights that adverse impacts of climate change such as climate-induced global migration are global public bad. Hence, the measures taken to respond to such impacts, which consequently enhance the resilience of affected countries, make them more adaptive to those adverse impacts, and deliver common values of universal character, should be construed as the global public good. The paper argues that that the idea of GPGs with its universality offers a normative and practical foundation for understanding, addressing, and strengthening the international community's climate adaptation actions and cooperation. [ABSTRACT FROM AUTHOR]

Rainfall in the Moist Tropical Caribbean Region (MTCR) in Costa Rica occurs practically throughout the year, with the quarters June–August (JJA) and December–February (DJF) concentrating over 70% of annual rainfall. Contrarily, in March–April and September–October, it rains below 100 mm per month. This seasonal rainfall behavior makes the region ideal for producing bananas (Musa spp.) and pineapple (Ananas comosus) for export (10% and 8% of total exports in 2021, respectively). A national-scale study determined that agriculture in the MTCR is one of the most vulnerable sectors to climate changes. However, the climate in this region has been poorly studied so far. This research analyzed the spatial and temporal variability of annual, monthly, and seasonal (DJF, JJA, SO) rainfall in the MTCR and how they change in the study period based on quality-checked series of daily rainfall from 28 weather stations in two periods: 1985–2009 and 1997–2019. The results show that rainfall regimes in the region are variable in space and throughout the year, with peaks occurring close to the mountain range and minimum values close to the coast. Trends were statistically significant in the period 1985–2009 with a predominance of significant positive trends in DJF and significant negative trends in SO. No significant trends (positive or negative) were observed in the period 1997–2019. JJA rainfall has uneven regional distribution and presents a positive and significant trend in the mountain region. This paper contributes to filling the knowledge gap in rainfall seasonality, variability, and trends in a region where banana and pineapple commercial plantations are fundamental to the country's economy thus providing information to decision-making in the agri-food sector to reduce the negative impacts of changing rainfall regimes. [ABSTRACT FROM AUTHOR]

Soil and other Earth scientists who conduct research on C management found themselves, in the past decade within a swirl of efforts concerning climate mitigation, economic and business investments in carbon markets, and political aspirations. All these external pressures are issues with which soil science is largely unfamiliar. As a result, science has responded without deeply considering the landscape in which it finds itself, and some of the unanticipated challenges these issues present. Here, we suggest soil C scientists now consider and respond to these issues. The first order challenge is to transition from the concept of technical carbon sequestration potentials, made in the absence of social and policy contexts, to societally achievable sequestration estimates based on highly transdisciplinary teams of natural and social sciences and scientists. To achieve this will requires re-thinking national science funding programs, in which climate-relevant social science is under-funded. In addition, the science of soil C itself is in need of a priority shift. Presently, publications in soil C sequestration out-strip papers on soil feedbacks to climate change, and on how to adapt soil to climate change: two areas of research which may well be more societal important in the next few decades than sequestering C. Most seriously, given the urgent nature of our collective societal climate problem, our profession must not find itself a decade from now continuing the now 20-year-old narrative that soil C can potentially mitigate climate change and compensate for greenhouse gas emissions. We must consider the possibility that other options and expenditures of resources are more viable, and we must reframe our science's objectives to expand into the many other urgent needs that confront humanity. [ABSTRACT FROM AUTHOR]

The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth's land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted. [ABSTRACT FROM AUTHOR]

There has been a global trend away from delivering 'climate information' towards producing 'climate services' for decision-makers. The rationale for this shift is said to be the demand for timely and actionable climate knowledge, whilst the means of its delivery involves a shift from public good to more privatised forms of climate science. This paper identifies important implications of this shift to climate services by examining the role of consultants, drawing on an in-depth study of adaptation consultants in Australia. The role of consultants is instructive, not just because these private sector experts are engaged in climate services, but also because publicly funded climate science agencies are increasingly encouraged to behave as consulting firms do. Four imperatives of knowledge businesses—to be client-focussed, solutions-oriented, resource-efficient and self-replicating—are described. The paper argues that an emphasis on climate services shifts the incentives for climate science away from the public interest towards the ongoing pursuit of profit. There is a subsequent diversion of effort away from publicly accessible and transparent climate information to private knowledge for discrete clients. Climate services also emphasise knowledge for climate solutions as opposed to the politically charged identification of climate risks. The paper concludes with a warning that the trend towards climate services undermines the knowledge required for societies to adequately respond to the scale, speed and severity of climate change. At the heart of this issue is a climate services paradox: how to achieve customisation without exclusion. [ABSTRACT FROM AUTHOR]

Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the Max-Planck-Institut für Meteorologie (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD. [ABSTRACT FROM AUTHOR]

Research on using climate information has often focused on the interaction between users and producers and the technical fit of information for real decision-making. However, due to resource and capacity constraints within both user and producer communities, this approach will not always be feasible or indeed necessary depending on the decisions at hand. These contexts have been relatively under-explored by scholars, and this paper provides an original empirical contribution using three case studies of sub-national governments in India, Kenya and Uganda. In the paper, we analyse how social learning supports changing the usability of climate information and the role of intermediary organisations in these processes. Firstly, the paper shows that intermediaries often choose to build the commitment to project aims rather than using climate information as an entry point to working on climate change, and this allows them to instigate challenging learning processes. Secondly, there are barriers to iterative processes and critical reflection with government stakeholders but these processes can gain traction when built into institutional practices such as formal M&E processes. Lastly, social learning can broaden the framing of climate change from a single sector issue to a multi-sectoral one. We conclude by arguing that bringing together scholarship on social learning with that on the usability of climate information can deepen understanding of the dynamic context in which the information becomes usable. The evidence from the case studies shows that learning processes can alter this context across scales. [ABSTRACT FROM AUTHOR]

The topical issue includes 22 papers on different aspects of meteorology and climatology of the Mediterranean and Black Seas. The papers are grouped into three categories, based on scale analysis of processes, and whether the study is dominantly related to the atmospheric or oceanic phenomenon. The category “Storms, Extremes and Mesoscale Processes” encompasses seven papers, ranging from observation and modelling data analysis of extreme atmospheric (severe winds, hailstorms, waterspout, cyclones) and oceanic (meteotsunamis, surface waves) events, occurring locally, but being connected to wider patterns and processes. The six papers in category “Atmospheric Climate, Variability and Climate Change” contain analyses of long-term observations and climate projection outputs, but also assess atmosphere-ocean-land interactions and cycles, that are important in a climate perspective. The category “Ocean Climate and Variability” includes nine papers, which map ocean processes (sea level variability, circulation, sea surface temperatures, vertical thermal structure, water masses and dense water formation) on a climate timescale, both, in the Mediterranean and Black Sea sub-basins, or taking them as a whole. [ABSTRACT FROM AUTHOR]

Early adolescence (12–13 years old) is a critical but under-researched demographic for the formation of attitudes related to climate change. We address this important area by exploring adolescent views about climate change. This paper presents opinions collected from surveys of 463 1st-year secondary school students (12–13 years old) in public secondary schools in inner-urban centres in Austria and Australia on whether climate change is (1) something about which to worry, (2) caused by humans and (3) happening now. Eligible respondents in both countries showed similar levels of agreement that climate change was probably or definitely something we should (1) worry about (84.6% Austria, 89.1% Australia), which is significantly higher than either country's adult population. Eligible respondents agreed that climate change probably or definitely is (2) caused by humans (75.6% Austria, 83.6% Australia) and that climate change is probably or definitely something that is (3) happening now (73.1% Austria, 87.5% Australia). Their response differed from the respective adult populations, but in opposite directions. Our results suggest that socio-cultural worldview may not have as much influence on this age group as it does on the respective adult populations and suggests that this age group would be receptive and ready for climate science education and engagement initiatives. [ABSTRACT FROM AUTHOR]

The Indiana Climate Change Impacts Assessment (IN CCIA) is a collaborative effort to provide professionals, decision makers, and the public with information about how climate change affects state and local interests throughout Indiana, USA. This assessment effort has three interrelated goals: (1) analyze and document the best available climate change impacts research, (2) develop and maintain a network of stakeholders and experts, and (3) start a dialog about climate change throughout Indiana. The project adopted a process that prioritized stakeholder engagement, re-envisioned traditional dissemination approaches, and that had limited state government involvement, setting the IN CCIA apart from most other state climate assessments (SCAs) in the USA. This overview describes the motivations, principles, and processes that guided the IN CCIA development, explores how Indiana's approach compares with those of other SCAs, and briefly summarizes the papers presented in this special issue. As interest in SCAs grows in non-coastal and politically conservative locations, the IN CCIA serves as one example of how a bottom-up assessment with limited funding can deliver credible climate science to diverse stakeholder groups in the absence of state-level mandates or direction and attract public attention over an extended period of time. [ABSTRACT FROM AUTHOR]

International assessments of evidence on climate change (e.g. Intergovernmental Panel on Climate Change, IPCC) or national climate change risk assessments (e.g. UK Climate Change Risk Assessment, CCRA) do not offer a sufficiently granular perspective on climate impacts to adequately inform governance of resilience to climate risks at the local level. Using an analysis of UK decision-makers managing and responding to heatwaves and flood risks, this paper argues how more robust local evidence is needed to inform decision-making regarding adaptation options for enhancing local resilience. We identify evidence gaps and issues relating to local climate change impacts, including sources and quality of evidence used, adequacy and accessibility of evidence available, ill-communicated evidence and conflicting or misused evidence. A lack of appreciation regarding how scientific evidence and personal judgement can mutually enhance the quality of decision-making underpins all of these gaps. Additionally, we find that the majority of evidence currently used is reductively based upon socio-economic and physical characteristics of climate risks. We argue that a step change is needed in local climate resilience that moves beyond current physical and socio-economic risk characterisation to a more inclusive co-constitution of social and politically defined climate risks at the local scale that are better aligned with the local impacts felt and needs of stakeholders. [ABSTRACT FROM AUTHOR]

This paper distinguishes between bridging and bonding social capital to assess their roles for individual farmers’ adaptation strategies taken through technology adoption. Based on primary data collected in Langcang River (LCR) basin area in southwestern China, the paper finds: (1) adaptation measures have been widely taken by surveyed households, but non-infrastructure-based measures are more prevalent than infrastructure-based measures and (2) surveyed households have strong social capital while having weak bridging social capital. Their bonding social capital has significantly positive relationship with their adaptation decisions, but bridging social capital does not have such statistically significant relationship. It recommends that the governments contemplate carefully how to help the poor to get a good combination of bonding and bridging social capital when designing policies to help the rural poor to improve their long-term adaptive capacity and achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Climate change and environmental hazards affect the entire world, but their interactions with—and consequences on—human migration are unevenly distributed geographically. Research on climate and migration have their own geographies which do not necessarily coincide. This paper critically confronts these two geographies by presenting the first detailed mapping of research in the field of environmentally induced migration. After a brief review of the geography of research on climate change, the paper presents an overview of nearly 50 years of case studies on the basis of CliMig, a bibliographic database of 1193 scientific papers and books on climate/environmental change and migration, among them 463 empirical case studies. We analyze the locations of these case studies, the academic affiliations of their researchers, and the origin of their funding. Mapping the locations of case studies worldwide points toward blind spots in the research and identifies “overstudied” areas. We describe the methodologies used in the studies and present a typology of environmental hazards. Our results show that research on environmental migration is mainly done in countries of the Global South, whereas climate science research in general is focused on countries of the Global North. We contend that the peculiar geography of environmental migration cannot be explained solely by the uneven vulnerability of southern populations to the environment. It must also be understood through the lens of post-colonial and securitization studies as the result of a framing of “environmental refugees” (and refugees in general) as an intrinsically “southern problem” and as a security risk for the North. This paper is an original contribution to the literature on the North-South divide in scientific research and will help to outline future directions of investigation. [ABSTRACT FROM AUTHOR]

To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a significant methodological challenge in how to best compare and combine information produced using different models and methods. In this paper, we present the landscape of climate model data available in the Philippines and show how multi-model, multi-method climate projections are being used and communicated to inform climate change policy and planning, focusing on the agriculture sector. We highlight the importance of examining and communicating methodological strengths and weaknesses as well as understanding the needs and capabilities of different user communities. We discuss the assessment of projections from different methods, including global and regional downscaled simulations, and discuss ways to summarise and communicate this information to stakeholders using co-production approaches. The paper concludes with perspectives on how to best use an “ensemble of opportunity” to construct defensible, plausible and usable climate projections. [ABSTRACT FROM AUTHOR]

Amid pressure for climate action worldwide, processes of deliberative democracy are being called upon to address public policy complexities, include citizens in decision-making, restore faith in public institutions and enhance governance processes. The citizens' assembly model is lauded internationally for the much-needed structure it provides to support bottom-up governance efforts as well as the potential for effective citizen engagement on complex topics. The Irish Citizens' Assembly, which took place from 2016 to 2018, is heralded as an example of best practice in design and execution. Yet, there is a dearth in analysis of its form, structure, impact and content, particularly in the climate crisis context. This paper examines one element of the deliberative democracy process that aimed to include a wider breadth of publics beyond the 99 citizens randomly selected to take part: the public submissions invited as part of the Citizens' Assembly process. In total, 1185 submissions were received on the topic of climate change. Our study undertakes a comprehensive content analysis of these submissions. Specifically, we explore (1) the content and concerns foregrounded within the submissions, (2) the frames and rhetorical strategies employed and (3) the stakeholders and scales called upon for climate action. The study identifies trends, preoccupations and salience within the corpus of written submissions and expands our understanding of citizen perceptions of climate science and policy. We offer both operational lessons for others aiming to enact similar deliberative forums as well as communications lessons for wider efforts to deepen public engagement on the climate crisis. [ABSTRACT FROM AUTHOR]

Based on the theory of "snapshot/pullback attractors", we show that important features of the climate change that we are observing can be understood by imagining many replicas of Earth that are not interacting with each other. Their climate systems evolve in parallel, but not in the same way, although they all obey the same physical laws, in harmony with the chaotic-like nature of the climate dynamics. These parallel climate realizations evolving in time can be considered as members of an ensemble. We argue that the contingency of our Earth's climate system is characterized by the multiplicity of parallel climate realizations rather than by the variability that we experience in a time series of our observed past. The natural measure of the snapshot attractor enables one to determine averages and other statistical quantifiers of the climate at any instant of time. In this paper, we review the basic idea for climate changes associated with monotonic drifts, and illustrate the large number of possible applications. Examples are given in a low-dimensional model and in numerical climate models of different complexity. We recall that systems undergoing climate change are not ergodic, hence temporal averages are generically not appropriate for the instantaneous characterization of the climate. In particular, teleconnections, i.e. correlated phenomena of remote geographical locations are properly characterized only by correlation coefficients evaluated with respect to the natural measure of a given time instant, and may also change in time. Physics experiments dealing with turbulent-like phenomena in a changing environment are also worth being interpreted in view of the attractor-based ensemble approach. The possibility of the splitting of the snapshot attractor to two branches, near points where the corresponding time-independent system undergoes bifurcation as a function of the changing parameter, is briefly mentioned. This can lead in certain climate-change scenarios to the coexistence of two distinct sub-ensembles representing dramatically different climatic options. The problem of pollutant spreading during climate change is also discussed in the framework of parallel climate realizations. [ABSTRACT FROM AUTHOR]

The correct mathematical approach to climate change requires the knowledge of the time-dependent system's pullback/snapshot attractor (PBA). Once the governing equations and external forcing are known, the PBA can be estimated by performing an ensemble simulation (ES) of many forward time integrations differing only by their respective initialization; the resulting ensemble mean and spread are usually considered as representative of the forced and internal variability (FV and IV), respectively. In this paper the PBA of an excitable conceptual ocean model subjected to an idealized decadal time-scale aperiodic forcing is determined and is then used to show that the system's relaxation oscillations contribute substantially to the ensemble mean, despite their intrinsic nature: as a consequence, a clear separation between the FV and IV is impossible in this case study. This provides an example of dynamical behaviour which may be typical of climate ESs under fluctuating aperiodic forcing. The impact of the number of ensemble members N on the statistical significance of the ES is then investigated. The complexity of realistic climate modelling currently imposes N = O(100): how significant is the statistical information derived from such small ESs? To answer this question for the present case study, the knowledge of the PBA is exploited to carry out a systematic comparison between the latter and small ESs with N = 50, also by using novel quantifiers specifically conceived for this purpose. The results reveal a remarkable significance of such ESs beyond the predictability time and may provide useful information for the design of future realistic ESs. [ABSTRACT FROM AUTHOR]

The time of emergence (TOE) of climate change is defined as the time when a new climate state emerges from a prior one. TOE assessment is particularly relevant in West Africa, a region highly threatened by climate change and urgently needing trustworthy climate predictions. In this paper, the TOE of precipitation change in West Africa is assessed for the first time, by analyzing 6 precipitation metrics (cumulated precipitation, number of wet and very wet days, onset and length of the rainy season) computed from the output of 29 state-of-the-art climate models. In West Sahel, climate conditions characterized by reduced occurrence of wet days are likely to emerge before 2036, leading to the possible emergence of a dryer climate in 2028–2052. In East Sahel, a wetter precipitation regime characterized by increased occurrence of very wet days is likely to emerge before 2054. Results do not provide a clear indication about a possible climate shift in the onset and length of the rainy season. Although uncertainty in climate model future projections still limits the robust determination of TOE locally, this study provides reliable time constraints to the expected climate shift in West Africa at the sub-regional scale, supporting adaptation measures to the future change in the precipitation regime. [ABSTRACT FROM AUTHOR]

With global action being outpaced by climate change impacts, communities in climate-vulnerable countries are at increased risk of incurring climate-induced losses and damages. In the last few years, disasters from extreme weather events such as typhoons have increased and have breached records, with typhoon Haiyan being the strongest ever typhoon to make landfall. Such an event solicited global compassion and altruism where Canada and the USA, apart from doling out traditional humanitarian aid, also offered immigration relief opportunities to typhoon Haiyan victims who have familial connections to their residents. Drawing from these immigration relief interventions, this paper uses a sociopolitical approach in proposing a climate humanitarian visa that would be offered to climate change victims on the basis of transnational family networks and skilled labor. Noting that several countries such as in Europe have demographic deficits and labor shortages, such a scheme would benefit both climate change victims and receiving countries. To counter the risk of selective compassion against economically trapped populations, potential receiving countries could provide skills upgrading geared toward addressing their labor shortages through their existing development programs. While migration is only one strategy in a spectrum of responses to climate change impacts, a climate humanitarian visa could provide climate change victims a legal choice for mobility while invoking altruism, hospitality, and compassion from potential receiving countries, whether or not they historically cause climate change. [ABSTRACT FROM AUTHOR]

In this paper, 16 cities representing four major architectural climate zones of China were selected, and the heating and cooling loads of office building during the period of 1961–2017 were simulated by using TRNSYS software. Daily extreme heating and cooling loads were determined by percentile methods, and the climate change impact on extreme loads was analyzed. The results showed that the days of extreme heating load of office building significantly decreased in almost all the selected cities, whereas there were no significant changes in the days of extreme cooling load. The daily extreme heating load was dominantly affected by the temperature (R2 = 0.43–0.79), but the daily extreme cooling load was related to multiple climate factors, including temperature, relative humidity, and solar radiation. Single temperature can only explain 3–37% of the changes of daily extreme cooling load, and the combination of multiple climate factors can explain 58–85%. Importantly, the effect of temperature on extreme cooling load showed decrease from the cold to hot climate zones, but the impacts of relative humidity and solar radiation gradually increased. These results suggest that the maximum design capacity of heating systems can properly decrease, and the design capacity of cooling systems may not largely increase with the climate warming. In addition, the combined effect of multiple climate factors rather than the single temperature, as well as the different responses of extreme cooling energy consumption to climate change in different climate zones, should be considered when making measures for improving operating efficiency of air-conditioning system. [ABSTRACT FROM AUTHOR]

This paper addresses two fundamental questions on climate change and variability: to what extent has climate changed and/or varied over years in two districts of different agro-ecological regions or zones and how do any changes differ between the zones or districts? Given the rural-rural migration pattern observed between the districts, understanding climate change risk to rural livelihoods cannot be overemphasised. To assess change and variability, we utilise rainfall data-records over a 36-year period from 1980 to 2016. Results show that there are wide variations and differences within and between the districts. Evidence suggests a general reduction in both annual rainfall and wet days. There is also ground to suggest that the rainy season duration is becoming shorter, given that rainfall onset is increasingly starting late, while cessation is increasingly coming early. Dry spells frequency and duration trends within rainy season show an increase over the period examined. We conclude that local climate in both areas has changed over the period investigated. However, while Livingstone seems to have experienced more droughts and unreliable rainfall, Kabwe experienced a bigger change in both rainfall and rainy season duration. We further conclude that migrants into Kabwe and other inhabitants are not any safer from climate change risk. [ABSTRACT FROM AUTHOR]

Though a small fraction of the US citizenry, agricultural producers are directly responsible for the stewardship of almost half of the country's land. This group is therefore an especially important one to understand from the standpoint of how they process and respond to science as it relates to agroecological phenomena. Data from a sample (n = 111) of farmers and ranchers located in the US state of Colorado are used to expand our understanding of how food producers process scientific claims. These insights, I argue, help us think through public understandings of science more generally. Using semi-structured interviews, the paper unpacks an identified asymmetry in how respondents perceive climate science and the science associated with genetically modified food and seed. These tensions are interrogated with the help of a novel methodological design that generated data converted to shading matrices—also known as heat maps. The heat maps illuminate certain cultural values among respondents, which were reinforced by motivated reasoning. This allows for an interrogation of tensions and inconsistencies in respondents' remarks about a variety of scientific claims. The heat maps, coupled with the qualitative data, allow for an exploration into how respondents perceive certain salient socio-technical issues. [ABSTRACT FROM AUTHOR]

The public education system can play a pivotal role in creating an electorate that is well informed of the consensus around climate change and its anthropogenic causes. In particular, more states have education standards that specifically address climate change today than ever before. However, previous research raises concerns about the discretion teachers have in if and how particular types of content are presented. The effectiveness of new state standards and the extent to which such state-level standards are coopted by teacher discretion has received minimal attention. Therefore, using a nationally representative sample of 1500 middle school and high school science teachers, this research examines the effectiveness of such state-level standards and the extent to which teacher ideology and knowledge mediate the relationship between standards and actual use of a consensus-informed approach to teaching climate science. Results show that teachers in states with any type of standards around climate change spend significantly more time on the topic in the classroom. However, teachers in states that have standards that require teachers to present "both sides" of climate change are significantly less likely to use a consensus-informed approach. While teacher characteristics (knowledge and ideology) can weaken their effect, standards continue to be important predictors of the time spent on climate change in the classroom and how content is presented. The paper concludes with a discussion of the policy implications of climate science standards. [ABSTRACT FROM AUTHOR]

Models disagree on a significant number of responses to climate change, such as climate feedback, regional changes, or the strength of equilibrium climate sensitivity. Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections. In this paper, the concepts underlying this framework are recalled with an emphasis on the statistical inference used for narrowing uncertainties, and a review of emergent constraints found in the last two decades. Potential links between highlighted predictors are explored, especially those targeting uncertainty reductions in climate sensitivity, cloud feedback, and changes of the hydrological cycle. Yet the disagreement across emergent constraints suggests that the spread in climate sensitivity can not be significantly narrowed. This calls for weighting the realism of emergent constraints by quantifying the level of physical understanding explaining the relationship. This would also permit more efficient model evaluation and better targeted model development. In the context of the upcoming CMIP6 model intercomparison a growing number of new predictors and uncertainty reductions is expected, which call for robust statistical inferences that allow cross-validation of more likely estimates. [ABSTRACT FROM AUTHOR]

Interest in climate service efforts continues to grow. However, more critical analysis could enhance how well climate services align with the needs of society. Collaborations between Native American Tribes (Tribes) and Climate Science Organizations (CSOs) providing decision-support for climate change planning accentuate the potential for climate services to have social justice implications through either deepening or softening existing inequities. This paper compares 30 Tribe-affiliated and 36 CSO-affiliated individuals' perceptions about potential harms and benefits associated with their collaborations with one another. The importance of the potential benefits of collaborations listed outweighed the potential harms listed for both groups, but while climate science organizations rated the potential benefits listed slightly higher than Tribes did, the potential harms listed were much more salient for Tribes. This finding highlights concerns that, without proper training and management, these collaborations may reinforce unequal relationships between settler and Indigenous populations. While CSOs appeared cognizant of their Tribe-affiliated colleagues' concerns, transitioning from a focus on building trust to establishing and sustaining shared systems of responsibilities might help these collaborations meet the needs of both groups more effectively. [ABSTRACT FROM AUTHOR]

Located in a monsoon domain, East Asia suffers devastating natural hazards induced by anomalous monsoon behaviors. East Asian monsoon (EAM) research has traditionally been a high priority for the Chinese climate community and is particularly challenging in a changing climate where the global mean temperature has been rising. Recent advances in studies of the variabilities and mechanisms of the EAM are reviewed in this paper, focusing on the interannual to interdecadal time scales. Some new results have been achieved in understanding the behaviors of the EAM, such as the evolution of the East Asian summer monsoon (EASM), including both its onset and withdrawal over the South China Sea, the changes in the northern boundary activity of the EASM, or the transitional climate zone in East Asia, and the cycle of the EASM and the East Asian winter monsoon and their linkages. In addition, understanding of the mechanism of the EAM variability has improved in several aspects, including the impacts of different types of ENSO on the EAM, the impacts from the Indian Ocean and Atlantic Ocean, and the roles of mid- to high-latitude processes. Finally, some scientific issues regarding our understanding of the EAM are proposed for future investigation. [ABSTRACT FROM AUTHOR]

The Paris pledges are unique documents in climate governance that outline what each country intends to do to combat climate change. Often, these documents contain headline greenhouse gas percentage reduction targets that appear to summarize countries' contributions to mitigation. This is a boon for comparative climate policy research. However, I show in this paper that the Paris pledges require detailed interpretation to be comparable. I demonstrate the risks in comparing these targets by re-visiting a recent studying linking national public opinion to the stringency of countries' mitigation goals. I develop new indicators that better account for the structure of the targets and show in replications that the original finding is inconsistent with the underlying data. I conclude by drawing lessons for studying the Paris pledges. [ABSTRACT FROM AUTHOR]

This paper builds on recent research on polycentric governance and the Ecology of Games to understand climate politics in the USA. Complementing previous work from 2005 to 2009, we map out the ideological networks of political actors engaged in the climate policy network using data from the US Congress as an arena of symbolic interaction. Our analysis identifies polycentric sites of ideological congruence and conflict in the discourse network on climate change. Political actors from different levels and including several actor types formed multiple centers that became bipolarized between the 112th and 114th sessions of the US Congress. This process took place in tandem with the increased participation of subnational actors in the polycentric system. By the 114th session of the Congress—during which the 2016 election took place—subnational policy actors, along with a diversity of other actors, contributed to an extremely polarized discussion of one of the central policies in the Obama Administration's Climate Action Plan: the Clean Power Plan. This finding is remarkable as the concept of polycentricity tends to be normatively associated with policy innovation, rather than stagnation. Our longitudinal analysis demonstrates, using Discourse Network Analysis, how increased multi-level participation can be associated with policy blockage of progressive climate policies rather than enabling policy innovation. [ABSTRACT FROM AUTHOR]

Climate change is now unequivocal; however, the type and extent of terrestrial impacts are still widely debated. Among these, the effects on slope stability are receiving a growing attention in recent years, both as terrestrial indicators of climate change and implications for hazard assessment. High-elevation areas are particularly suitable for these studies, because of the presence of the cryosphere, which is particularly sensitive to climate. In this paper, we analyze 358 slope failures which occurred in the Italian Alps in the period 2000–2016, at an elevation above 1500 m a.s.l. We use a statistical-based method to detect climate anomalies associated with the occurrence of slope failures, with the aim to catch an eventual climate signal in the preparation and/or triggering of the considered case studies. We first analyze the probability values assumed by 25 climate variables on the occasion of a slope-failure occurrence. We then perform a dimensionality reduction procedure and come out with a set of four most significant and representative climate variables, in particular heavy precipitation and short-term high temperature. Our study highlights that slope failures occur in association with one or more climate anomalies in almost 92% of our case studies. One or more temperature anomalies are detected in association with most case studies, in combination or not with precipitation (47% and 38%, respectively). Summer events prevail, and an increasing role of positive temperature anomalies from spring to winter, and with elevation and failure size, emerges. While not providing a final evidence of the role of climate warming on slope instability increase at high elevation in recent years, the results of our study strengthen this hypothesis, calling for more extensive and in-depth studies on the subject. [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

The practice of using climate metrics to estimate carbon dioxide equivalent emissions has long been subject to scientific discussion. One strand of this literature has analysed whether the choice of metric affects the relative cost-effectiveness of options for climate change abatement, but there has been little discussion on the effect of metric choices on cost-effective abatement of near-term climate forcers (NTCFs). These NTCFs are air pollutants primarily regulated by policies outside the climate policy arena and their estimated carbon dioxide equivalent emissions are not typically considered in the evaluation of cost-effective abatement. However, the attention to NTCFs as climate forcers has increased during the last decade. The objective of this paper is to identify whether the relative cost-effectiveness of different NTCF abatement options is robust to climate metric choices. We assess nine plausible NTCF abatement options available in Sweden (with negligible effect on long-lived GHG emissions) and evaluate the robustness of the ranking of these, according to their estimated cost-effectiveness. Different metric designs are considered as well as climate impact uncertainty of NTCFs, with corresponding uncertainty in metric values. The results indicate that the choice of metric has little effect on the ranking of the options according to their cost-effectiveness, with options affecting NOx indicated as an exception. This suggests that the choice of metric utilised when calculating cost-effectiveness of NTCF abatement options is likely to have minor effect on which NTCF abatement options should be targeted for policy interventions (if NOx emissions are not significantly affected). [ABSTRACT FROM AUTHOR]

Climate change adaptation is increasingly concerned with how organisations develop capacity to adapt to uncertain futures. A participatory action research project conducted in Victoria, Australia, examined how health and social service organisations developed their organisational adaptive capacity through the use of adaptation decision-support tools. It can be challenging for any organisation to select and apply a decision-support tool, but this is particularly the case where resources and capacities are limited. For most organisations, climate change is only one of a complex set of dynamic stressors they must consider in meeting organisational goals. This paper shows that while decision-support tools can help co-generate knowledge and facilitate customised organisational adaptation processes, for them to be practically helpful for organisations with limited resources and capacities, intensive collaborative and discursive processes are needed to adjust such tools to fit specific organisational contexts and needs. Facilitators and participatory approaches that enable co-inquiry can play a critical role in supplementing scarce resources and initiating adaptation processes that go well beyond the scope and purpose of the decision-support tool used. Organisations working effectively with decision-support tools to adapt to climate change will need to feel ownership of them and have confidence in modifying them to suit their particular adaptation needs and organisational goals. [ABSTRACT FROM AUTHOR]

For hundreds of years, human activity has modified the planet's surface through land-use practices. Policies and decisions on how land is managed and land-use changes due to replacement of forests by agricultural cropping and grazing lands affect greenhouse gas emissions. Agricultural management and agroforestry and the resulting changes to the land surface alter the global carbon cycle as well as the Earth's surface albedo, both of which in turn change the Earth's radiation balance. This makes land-use change the second anthropogenic source of climate change after fossil fuel burning. However, the scientific research community has so far not been able to identify the direction and magnitude of the global impact of land-use change. This paper examines the effects of net carbon flux from land-use change on temperature by applying Granger causality and error correction models. The results reveal a significant positive long-run equilibrium relationship between land-use change and the temperature series as well as an opposing short-term effect such that land-use change tends to lead to global warming; however, a rise in temperature causes a decline in land-use change. [ABSTRACT FROM AUTHOR]

Artificial neural networks are widely applied for different forecasting applications including rainfall forecasting. The climate input features and parameters for neural networks highly affect the overall performance of the prediction model. Therefore, an appropriate approach for the selection of features and parameters is needed. In this paper, a novel approach is proposed to select the input features and neural network parameters. A hybrid genetic algorithm that combines natural reproduction and particle swarm optimization characteristics was developed to select the best input features and network parameters for each month. The developed model was compared against alternative climate and network parameters feature selection model, climate feature selection model and climatology where a better accuracy was recorded with the proposed model. The skill score against the three alternative climate models was 17.41, 21.68 and 32.12%, respectively. The aggregated time series of the proposed model showed a root-mean-square error of 141.67 mm for a location with 3553.00 mm annual average. [ABSTRACT FROM AUTHOR]

The present paper offers a brief assessment of climate change and associated impact in Poland, based on selected results of the Polish-Norwegian CHASE-PL project. Impacts are examined in selected sectors, such as water resources, natural hazard risk reduction, environment, agriculture and health. Results of change detection in long time series of observed climate and climate impact variables in Poland are presented. Also, projections of climate variability and change are provided for time horizons of 2021-2050 and 2071-2100 for two emission scenarios, RCP4.5 and RCP8.5 in comparison with control period, 1971-2000. Based on climate projections, examination of future impacts on sectors is also carried out. Selected uncertainty issues relevant to observations, understanding and projections are tackled as well. [ABSTRACT FROM AUTHOR]

In order to understand the behavior of the glaciers, their mass balance should be studied. The loss of water produced by melting, known as glacier discharge, is one of the components of this mass balance. In this paper, a vine copula structure is proposed to model the multivariate and nonlinear dependence among the glacier discharge and other related meteorological variables such as temperature, humidity, solar radiation and precipitation. The multivariate distribution of these variables is expressed as a mixture of four components according to the presence or not of positive discharge and/or positive precipitation. Then, each of the four subgroups is modelled with a vine copula. The conditional probability of zero discharge for given meteorological conditions is obtained from the proposed joint distribution. Moreover, the structure of the vine copula allows us to derive the conditional distribution of the glacier discharge for the given meteorological conditions. Three different prediction methods for the values of the discharge are used and compared. The proposed methodology is applied to a large database collected since 2002 by the GLACKMA association from a measurement station located in the King George Island in the Antarctica. Seasonal effects are included by using different parameters for each season. We have found that the proposed vine copula model outperforms a previous work where we only used the temperature to predict the glacier discharge using a time-varying bivariate copula. [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]

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]

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]

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]

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]

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]

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]

Since the interaction between atmospheric synoptic eddy (SE) (2-8 days) activity and low-frequency (LF) (monthly) flow (referred to as SELF) plays an essential role in generating and maintaining dominant climate modes, an evaluation of the performance of BCC_CSM1.1(m) in simulating the SE feedback onto the LF flow is given in this paper. The model captures well the major spatial features of climatological eddy vorticity forcing, eddy-induced growth rate, and patterns of SELF feedback for the climate modes with large magnitudes in cold seasons and small magnitudes in warm seasons for both the Northern and Southern Hemisphere. As in observations, the eddy-induced growth rate and SELF feedback patterns in the model also show positive SE feedback. Overall, the relationships between SE and LF flow show that BCC_CSM1.1(m) satisfactorily captures the basic features of positive SE feedback, which demonstrates the simulation skill of the model for LF variability. Specifically, such an evaluation can help to find model biases of BCC_CSM1.1(m) in simulating SE feedback, which will provide a reference for the model's application. [ABSTRACT FROM AUTHOR]

Malaria is a climate sensitive disease that is causing rampant deaths in sub-Saharan Africa (SSA) and its impact is expected to worsen under climate change. Thus, pre-emptive policies for future malaria control require projections based on integrated models that can accommodate complex interactions of both climatic and non-climatic factors that define malaria landscape. In this paper, we combined Geographical Information System (GIS) and Bayesian belief networks (BBN) to generate GIS-BBN models that predicted malaria hotspots in 2030, 2050 and 2100 under representative concentration pathways (RCPs) 4.5 and 8.5. We used malaria data of children of SSA, gridded environmental and social-economic data together with projected climate data from the 21 Coupled Model Inter-comparison Project Phase 5 models to compile the GIS-BBN models. Our model on which projections were made has an accuracy of 80.65% to predict the high, medium, low and no malaria prevalence categories correctly. The non-spatial BBN model projection shows a moderate variation in malaria reduction for the high prevalence category among RCPs. Under the low prevalence category, an increase in malaria is seen but with little variation ranging between 4.6 and 5.6 percentage points. Spatially, under RCP 4.5, most parts of SSA will have medium malaria prevalence in 2030, while under RCP 8.5, most parts will have no malaria except in the highlands. Our BBN-GIS models show an overall shift of malaria hotspots from West Africa to the eastern and southern parts of Africa especially under RCP 8.5. RCP 8.5 will not expand the high and medium malaria prevalence categories in all the projection years. The generated probabilistic maps highlight future malaria hotspots under climate change on which pre-emptive policies can be based. [ABSTRACT FROM AUTHOR]

A mathematical model is developed in this study with the goal of maximizing agricultural benefits in the Aidoghmush river basin, Iran. The results show that the cultivated area of various crops and their agricultural benefits would be increased over the planning horizon with proper management and modification of cropping patterns despite the decline in streamflow and increasing water demand under climate-change conditions. Therefore, considering the optimal cropping pattern increases agricultural benefits by 14 and 17% under baseline climatic and climate-change conditions, respectively, compared to present conditions. This paper's results indicate that areas cultivated with various crops would increase under climate-change conditions compared to baseline climatic conditions, except for alfalfa. [ABSTRACT FROM AUTHOR]