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Introduction: A defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view. Methods: Here we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts. Results: Half of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results. Discussion: Key areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key "known unknowns" includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system. [ABSTRACT FROM AUTHOR]

AbstractClimate change instruction (CCI) is not a consistent component of the science curriculum in American primary education. When it is taught, students may experience stress during instruction as a result of learning about the historical and future harm to humanity and the earth as a result of climate change. Students may also have direct experience with natural disasters or be fearful of the future of the planet if climate change is not effectively managed. Psychological distress is detrimental to the learning environment, therefore a trauma-informed approach to CCI could be a useful framework for science teachers to help students learn the content without overwhelming students with fear and anxiety. The authors of this paper present a rationale for this framework and provide concrete strategies for science instructors to support students in learning about climate change. [ABSTRACT FROM AUTHOR]

We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the "hot models" associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large‐scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure. [ABSTRACT FROM AUTHOR]

New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up‐to‐date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the "hot model" problem. NPCC4 expects to establish new projections‐of‐record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models. [ABSTRACT FROM AUTHOR]

This article provides an epistemological assessment of climate analogue methods, with specific reference to the use of spatial analogues in the study of the future climate of target locations. Our contention is that, due to formal and conceptual inadequacies of geometrical dissimilarity metrics and the loss of relevant information, especially when reasoning from the physical to the socio-economical level, purported inferences from climate analogues of the spatial kind we consider here prove limited in a number of ways. Indeed, we formulate five outstanding problems concerning the search for best analogues, which we call the problem of non-uniqueness of the source, problem of non-uniqueness of the target, problem of average, problem of non-causal correlations and problem of inferred properties, respectively. In the face of such problems, we then offer two positive recommendations for a fruitful application of this methodology to the assessment of impact, adaptation and vulnerability studies of climate change, especially in the context of what we may prosaically dub “twin cities”. Arguably, such recommendations help decision-makers constrain the set of plausible climate analogues by integrating local knowledge relevant to the locations of interest. [ABSTRACT FROM AUTHOR]

Microclimates can behave differently from the larger regional climate, and it is essential to consider various spatiotemporal scales when studying how climate change affects local ecosystems. This research identifies small-scale climate variations within Channel Islands National Park (CINP), particularly in areas where species might find refuge to adapt to climate change. The study identifies different climate characteristics in this region by creating a microclimate framework and analyzing historical data accordingly. It also explains the need for scaling down climate information to the ecosystem level and provides a literature review of all known criteria necessary. The goal is to help inform park managers of local conditions and potential threats to prioritize areas for conservation and restoring biodiversity and natural resources. While global and regional climate models help understand broad trends, they often need more detail to grasp ecological changes at the community or individual species level. Scaling down climate information can enhance the accuracy of predictive models used in environmental assessments and impact studies, and identifying existing microclimates can help assess the overall health of an ecosystem. The research categorizes the scaling process into four levels: macro, meso, topo, and micro. It outlines the procedure for identifying microclimates, analyzes model predictions, illustrates future climate scenarios, and highlights correlations between various physical factors using recent climatological observations. The study starts with a review of existing literature to provide context for each climate variable's impact on the overall ecosystem, explains the research methods, presents the results, and concludes with a discussion of the findings and suggestions for future research beyond the scope of this study. The research was conducted in collaboration with The Nature Conservancy and the National Park Service to address the specific needs of the park.

Abstract Tackling environmental challenges that face humanity requires us to acknowledge new ways of working and to cross disciplinary boundaries. However, the methodological toolkit used by environmental researchers to explore the human attitudes, knowledge and behaviours that drive global challenges such as biodiversity loss and climate breakdown remains constrained. Here, we describe participatory video, a methodology for capturing and communicating knowledge, which goes beyond interviews, focus groups and participant observation. We draw from the literature and our own experience of conducting participatory video projects in Nepal, Guyana and Peru. We demonstrate the diverse ways in which the methodology can be applied to environmental research and highlight its strengths and limitations. Participatory video provides a more holistic understanding of environmental issues by using multiple types of data, its longer‐term engagement with issues, opening channels of communication between stakeholders, engaging a diversity of knowledge systems and advocating for transformative change. By taking a participatory video approach, environmental researchers may begin to counter commonplace criticisms about lack of diversity and entrenched colonialism. This simultaneously responds to wider calls for environmental research to engage with social justice issues, represent diverse voices, understand different contexts and acknowledge the role of power. Crucially, this helps build trust amongst all those involved. By demonstrating how we have successfully used participatory video in projects in conservation, ecology and climate science, we provide guidance for researchers looking to expand their methodological toolkit. Ultimately, we seek to improve the use of participatory methods to help support communities to tackle the environmental challenges that they face. Read the free Plain Language Summary for this article on the Journal blog.

The participation of a diverse --in terms of geography, discipline and gender-- group of Early Career Researchers (ECRs) in the peer review process can help alleviate the workload of senior researchers and counteract the perceptual biases that the latter tend to show. Moreover, ECRs can benefit from developing skills that are often not included in educational programs. From 2018 to 2021, the Association of Polar Early Career Scientists, in collaboration with other associations, organized six group reviews of the Intergovernmental Panel on Climate Change (IPCC) reports by a total of more than 600 ECRs from over 70 different countries. This study aims to evaluate this group review in terms of its contribution to the production of scientific knowledge, and as a career development opportunity for ECRs. The data analyzed consists of application forms, review comments, and feedback surveys that were collected during each review process. The results of this study show that, overall, the group reviews were a success in terms of the experience of ECRs and their contribution to the peer review of the IPCC reports. Most survey respondents considered the general organization of the group reviews satisfactory and expressed interest in participating in future group reviews. However, most participants did not engage in discussions with their peers, which constitutes a missed opportunity to engage in active learning and the shared production of knowledge. ECRs made a significant contribution to the review of the IPCC reports by producing an average of 2,422 ± 532 comments per group review, 36% of which were substantive. PhD students were shown to be as proficient reviewers as postdoctoral researchers and faculty reviewers. More importantly, the diversity of reviewers in terms of geography and discipline, together with the fact that they are ECRs, can help produce more balanced scientific reports since they bring new perspectives, thus counteracting the biases that senior researchers have. These group reviews could be improved by providing more comprehensive training and facilitating communication among reviewers so that they can engage in meaningful exchanges. We conclude that the IPCC should formalize the inclusion of ECRs in future reviews of the IPCC reports. [ABSTRACT FROM AUTHOR]

In the 20th century, Australia's Great Barrier Reef emerged as a political battleground when governing bodies planned to turn its coral territories into a vast mining zone. But in the 21st century, as the temporalisation of the Reef exerts increasing influence on the governance, securitisation and anticipation of planetary futures, coral time has emerged as a new site of political and imaginative conflict. Responding to this shift from territory to temporality, how can we pay closer attention to those skilfully making coral time? In this article, I introduce 'dimensional friction' as a tool for considering how the temporal structure of corals intersects with the temporal structure of global climate science in a coring laboratory. Based on my fieldwork at the Australian Institute of Marine Science, I analyse simultaneously discursive, technical, and imaginative problems that emerge when scientists transform the mineral skeletons of corals into time data. Dimensional friction appears whenever this skeletal matter is manipulated, surfacing the lab-based production of vertical time-depth but also suggesting other ways of temporalising (and corporally appropriating) coral time. Viewed in this way, coral cores might be better understood as 'temporal volumes' rather than chronostratigraphic records amenable to linear timelines and trajectories. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to view how public sentiment regarding climate change has shifted over time and to identify any trends in opinion that could prove useful for future climate change and general sentiment analysis. Positive sentiment is defined as the post having a positive emotion while a negative sentiment is defined as a post having a negative emotion. The primary hypothesis was that the average sentiment would remain slightly negative over time (H1). This study analyzes the relationship of location, popularity metrics, and emojis to sentiment in posts from the social media platform X, formerly known as tweets on Twitter. The hypothesis for emojis’ relationship to the sentiment of a post (H2) was that a post with an emoji is more likely to have a positive sentiment. This hypothesis was to determine if emojis can be used as a sentiment indicator in the future. For the locations, the prediction (H3) was that even in countries/groups, there would not be a consensus or similar sentiment. The results did not align with H1; instead of a continuous slightly negative view, the average remained neutral over the years 2015- 2022. However, the results did confirm H2 by showing the sentiment of a post with an emoji tended to have a higher sentiment than a post without one. A “weighted popularity”, which accounted for likes in addition to the original post’s sentiment, was used to confirm the findings of average sentiment per year. The results regarding location show a distribution of sentiment that doesn’t lean one way or another when close together, which aligns with the location-related hypothesis (H3). [ABSTRACT FROM AUTHOR]

Tackling environmental challenges that face humanity requires us to acknowledge new ways of working and to cross disciplinary boundaries. However, the methodological toolkit used by environmental researchers to explore the human attitudes, knowledge and behaviours that drive global challenges such as biodiversity loss and climate breakdown remains constrained.Here, we describe participatory video, a methodology for capturing and communicating knowledge, which goes beyond interviews, focus groups and participant observation. We draw from the literature and our own experience of conducting participatory video projects in Nepal, Guyana and Peru. We demonstrate the diverse ways in which the methodology can be applied to environmental research and highlight its strengths and limitations.Participatory video provides a more holistic understanding of environmental issues by using multiple types of data, its longer‐term engagement with issues, opening channels of communication between stakeholders, engaging a diversity of knowledge systems and advocating for transformative change.By taking a participatory video approach, environmental researchers may begin to counter commonplace criticisms about lack of diversity and entrenched colonialism. This simultaneously responds to wider calls for environmental research to engage with social justice issues, represent diverse voices, understand different contexts and acknowledge the role of power. Crucially, this helps build trust amongst all those involved.By demonstrating how we have successfully used participatory video in projects in conservation, ecology and climate science, we provide guidance for researchers looking to expand their methodological toolkit. Ultimately, we seek to improve the use of participatory methods to help support communities to tackle the environmental challenges that they face. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Although scientific research is often crucial for efforts to achieve improved environmental regulation for industrial products and processes, scientists who document or publicize research on possible risks can face suppression or censorship by industry, government, and other actors. This study contributes to the sociology of science by examining the challenges and responses of environmental scientists in the U.S. in two research areas: toxic chemicals and climate change. Drawing on comparative and processual methods applied to a small‐N, unique data set of cases, the study conducts formal coding of variables for contextual conditions and four general categories of the suppression sequence: triggering circumstances and actions, suppression actions, responses, and outcomes. The first stage of the analysis identifies significant relationships between contextual conditions and the suppression sequence, such as the different forms of suppression that government employees and university professors face. The second stage identifies three composite processual sequences: employment risk for government scientists, records attacks for both government and university scientists, and reputation attacks on university scientists. Together, the two types of analysis advance research by identifying novel relationships in a more systematic way than is accomplished with the standard approach of one or a few cases. The approach also examines the benefits of a mode of comparative analysis that can be more readily connected with theory testing via process tracing at the case level. The practical issue of responding to suppression or censorship is considered, which could be of value to environmental scientists and their partners. [ABSTRACT FROM AUTHOR]

Previous failures of policymakers to minimize the effects of industry-born air pollution created a decrease in conditions for low-income communities in the U.S. and a rise in environmental racism. The dominating explanation for this trend is housing discrimination, attributed to the 1930s residential security maps deconstructing neighborhoods based on class, nationality, and skin color under the guise of mortgage default threats. However, other racist and anti-immigrant policies in America also contributed to the new form of segregation that barred marginalized communities from affluent and middle-class neighborhoods because they were used to benefit private enterprises for the sake of economic growth. Today, racial and ethnic minorities and low-income people are disproportionately impacted by airborne particulate matter. As methods of combating pollution-borne diseases create a more significant financial burden on these communities, individuals affected by environmental racism in industrial areas may reside in inadequate facilities, further increasing the risk of long-term exposure to pollution (PM2.5). Introducing air pollution mitigation strategies such as renewable energy, green infrastructure, and deindustrialization in low-income communities can help alleviate the effects of air pollution, ending environmental racism. [ABSTRACT FROM AUTHOR]

The growing understanding of how and why the climate is changing has led to mounting calls on climate scientists to take on more responsibility in the context of climate science. While an increasing responsibilisation takes place in the academic literature, asking scientists to “do more”, there is limited engagement with the responsibilities that scientists already assume in practice. Drawing on novel empirical insights from 77 semi-structured interviews with participants of the Intergovernmental Panel on Climate Change (IPCC), I take the increasing ‘peer-to-peer responsibilisation’ as a point of departure to contextualise such calls, asking what scientists themselves already feel and assume responsibility for at both the personal and professional level. I find that climate experts participating in the IPCC not only assume increasing responsibility across different stages of the IPCC process but also beyond. As my data analysis demonstrates, IPCC participants increasingly feel and take on responsibility not only for producing and assessing climate science but also for communicating and/or enacting it (PACE). The contribution of the article is threefold. Firstly, it makes sense of the mounting peer-to-peer responsibilisation by surfacing and contextualising how, why and with what consequences particular climate knowledge holders already assume responsibility for climate science at four key moments (PACE). Secondly, conceiving of the IPCC as a community of practice, the article provides novel insights into the work of IPCC participants and their individual experiences with the institution and its processes. Thirdly, the article adds evidence to a growing body of literature on practices of responsibility and climate emotions by focussing on participants' individual affective experiences. As the 7th Assessment Cycle gathers pace, I propose some measures the IPCC may undertake to support participants in assuming their responsibilities in the context of climate science. [ABSTRACT FROM AUTHOR]

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view.MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts.ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results.DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system.

While dissent is key to successful science, it is not always beneficial. By requiring scientists to respond to objections, epistemically detrimental dissent (EDD) consumes resources that could be better devoted to furthering scientific discovery. Moreover, bad-faith dissent can create a chilling effect on certain lines of inquiry and make settled controversies seem open to debate. Such dissent results in harm to scientific progress and the public policy that depends on this science. Biddle and Leuschner propose four criteria that draw on inductive risk as a method for separating this EDD from beneficial dissent while de Melo-Martín and Intemann reject this approach for failing to capture paradigmatic instances of EDD. Against de Melo-Martín and Intemann's objections, I propose the inductive risk account can be saved and strengthened through the following modifications: (1) removing the requirement that the four conditions of EDD be jointly satisfied, (2) requiring that each criterion be measured as a matter of degree rather than as a binary, and (3) requiring that the four criteria are measured holistically. These modifications not only mitigate the criticisms but produce five benefits over Biddle and Leuschner's account, including: (1) capturing paradigmatic instances of EDD, (2) reflecting the degree to which an instance of EDD is problematic, (3) capturing the interactions between criteria, (4) avoiding legitimizing inappropriate dissent, and (5) reflecting changes to the epistemic standing of dissent. As such, I argue that the modified IndRA provides a powerful tool for identifying EDD and strengthening science. [ABSTRACT FROM AUTHOR]

The participation of a diverse –in terms of geography, discipline and gender– group of Early Career Researchers (ECRs) in the peer review process can help alleviate the workload of senior researchers and counteract the perceptual biases that the latter tend to show. Moreover, ECRs can benefit from developing skills that are often not included in educational programs. From 2018 to 2021, the Association of Polar Early Career Scientists, in collaboration with other associations, organized six group reviews of the Intergovernmental Panel on Climate Change (IPCC) reports by a total of more than 600 ECRs from over 70 different countries. This study aims to evaluate this group review in terms of its contribution to the production of scientific knowledge, and as a career development opportunity for ECRs. The data analyzed consists of application forms, review comments, and feedback surveys that were collected during each review process. The results of this study show that, overall, the group reviews were a success in terms of the experience of ECRs and their contribution to the peer review of the IPCC reports. Most survey respondents considered the general organization of the group reviews satisfactory and expressed interest in participating in future group reviews. However, most participants did not engage in discussions with their peers, which constitutes a missed opportunity to engage in active learning and the shared production of knowledge. ECRs made a significant contribution to the review of the IPCC reports by producing an average of 2,422 ± 532 comments per group review, 36% of which were substantive. PhD students were shown to be as proficient reviewers as postdoctoral researchers and faculty reviewers. More importantly, the diversity of reviewers in terms of geography and discipline, together with the fact that they are ECRs, can help produce more balanced scientific reports since they bring new perspectives, thus counteracting the biases that senior researchers have. These group reviews could be improved by providing more comprehensive training and facilitating communication among reviewers so that they can engage in meaningful exchanges. We conclude that the IPCC should formalize the inclusion of ECRs in future reviews of the IPCC reports.

This paper, aims to analyse the relationship that exists between artificial intelligence (AI) and climate science, focusing on the opportunities and the risks that new technologies could open up for global governance. This research seeks to review how AI technologies can help solve climate change challenges effectively and how they can be harnessed with an eye on the potential risks and ethical considerations in implementation in global governance frameworks. The approach used in this study is through literature review, case studies, interviews of experts, and analysis of the policies developed that find the increasing tendency of utilization of AI applications in climate science from climate modelling to data analysis, predictive analysis, and policy recommendation. Key findings of the study underline the great opportunities that AI can create toward bettering climate resilience, mitigation, and adaptation strategies. AI would also have a great contribution to supporting the governance of the climate for evidence-based decision-making. Moreover, the research also highlights risks and challenges of how AI is used in global governance: concerns related to privacy, data protection, algorithmic biases, transparency, accountability, and socio-economic impacts. These, therefore, have far-reaching implications for policymakers, researchers, and other stakeholders in climate governance that point to the necessity of ethical AI frameworks, regulative measures, international cooperation, and interdisciplinary approaches so that the benefits and the associated risks to AI are minimized. [ABSTRACT FROM AUTHOR]

Misinformation produced by various interest groups is a significant contributing factor to public confusion about climate policy. Character assassination against climate scientists and policymakers is the most common type of misinformation strategy used by contrarians in climate debates (Coan, T. G., Boussalis, C., Cook, J., & Nanko, M. O. (2021). Computer-assisted classification of contrarian claims about climate change. Scientific Reports, 11(1), 22320). Despite its widespread use, however, character assassination remains understudied by social scientists, especially in the context of climate change. This study adapts Douglas Walton's (1998. Ad hominem arguments. University of Alabama Press) typology of 'ad hominem' attacks – personal attacks targeting an individual's character, competence, or motives – to misinformation campaigns against the climate community. We developed an original codebook for classifying ad hominem arguments made by climate contrarians. Drawing on a 553-paragraph sample from a corpus from 55 contrarian blogs and 15 conservative think-tank websites published in English between 2008 and 2020, we then determined the relative prominence of each type of attack using a consensus-coding approach. Bias attacks, which entail accusing climate scientists of political partisanship or having an ideological agenda, were the most common form of contrarian ad hominem attack. The dominance of bias attacks can be explained by their strong relevance for scientific credibility. The study found that ad hominem attacks, often with bias and moral attacks clustered together, are the most common combination. The article concludes by discussing the implications of these findings for climate policy and future research. Key Policy Insights Climate misinformation politicizes climate science, further amplifying ideological conflict and fostering ideological polarization; Climate misinformation campaigns feature a range of different types of ad hominem attacks designed to undermine the credibility of climate scientists; The most common type of ad hominem attack on climate scientists in our sample was bias attacks, which entail accusing climate scientists of political partisanship or of having an ideological agenda; Attacks on the moral character of climate scientists were the only type of ad hominem that increased during the period under study (2008–2020); Different types of ad hominems often appeared together, with the most common combination being bias and moral attacks; Ad hominem attacks on climate scientists are part of misinformation campaigns designed to stall discussion on climate change and delay the implementation of climate policies. [ABSTRACT FROM AUTHOR]

Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the phenomena. Discovering equations, laws, and principles that are invariant, robust, and causal has been fundamental in physical sciences throughout the centuries. Discoveries emerge from observing the world and, when possible, performing interventions on the system under study. With the advent of big data and data-driven methods, the fields of causal and equation discovery have developed and accelerated progress in computer science, physics, statistics, philosophy, and many applied fields. This paper reviews the concepts, methods, and relevant works on causal and equation discovery in the broad field of physics and outlines the most important challenges and promising future lines of research. We also provide a taxonomy for data-driven causal and equation discovery, point out connections, and showcase comprehensive case studies in Earth and climate sciences, fluid dynamics and mechanics, and the neurosciences. This review demonstrates that discovering fundamental laws and causal relations by observing natural phenomena is revolutionised with the efficient exploitation of observational data and simulations, modern machine learning algorithms and the combination with domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems. [ABSTRACT FROM AUTHOR]

In this article, we examine the ways in which the notion of interdisciplinarity was understood, implemented and experienced by researchers at a government-funded Chilean climate research centre. Our multi-site ethnography, consisting of interviews, participant observations, and document analysis, was motivated by three key aims. First, to generate an inductive, multi-faceted picture of the lived meaning of "interdisciplina" at the Centre; second, to explore whether and to what extent the "peripheral" features of the research context would exacerbate the challenges associated with practicing interdisciplinarity, and third, to see whether frictions between disciplines at the Centre could be considered productive "dissonances" in Stark's sense of the term. We found that despite the centre efforts to produce a common framework to regulate interdisciplinary research, its researchers nevertheless understood, enacted and experienced it in diverse ways. More specifically, we found that researcher´s conceptions of interdisciplinarity were coloured by their lived experiences of attempting to practice it, and in particular by the benefits and costs they associated with doing so. This in turn was linked to several variables, including the specific balance between disciplines, the absence or presence of shared, clearly-defined goals, the affirmation of a common research ethic or motivational commitment, and the structural-material conditions of the research in question. We also found that the research conditions characteristic of the Global South do tend to exacerbate the well-documented challenges associated with interdisciplinarity, yet that the adversities associated with precarious conditions were often met by increased resilience and bonding among researchers, who use creative and collaborative strategies to adapt to adversity. [ABSTRACT FROM AUTHOR]

Climate change is taken as a new site of scientific inquiry across the disciplines against the backdrop of the global discourses of the crisis human society confronts today. Our inability to predict and forecast the future and the problems of climate change led to a theoretical vacuum and thereby burden on the scientific communities. Climate change-induced uncertainties manifested in the manifold and their implications on human society, livelihood and ecosystem have increasingly become the objects of analysis for devising empirical tools for field enquiry. It challenges the specificities while looking at the events of uncertainties in context. The new set of evidence on climate change has also redefined the role of the scientific community. This paper discusses climate-related events in the lives of people and the changes in the ecosystem and explores how such factors became an object of scientific inquiry. With the ideas of political ecology, the domain of scientific practices is transformed into an arena of co-production of knowledge in which place, social context and agencies become central. This study explores (1) how the scientific community adapted to outline an interdisciplinary research programme to systematically investigate and register climate-change-affected areas and (2) how the local people in Ladakh Himalaya have participated and reflected on the changing pattern of livelihood and ecosystem through this research enquiry. It has further complicated the analysis on nature-culture dialectics to adapt a robust scientific method to signify the importance of mutual learning and knowledge co-production in climate science. [ABSTRACT FROM AUTHOR]

The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and now finds applications across a wide range of disciplines. This multidisciplinary expansion has impressively demonstrated the potential of digital twin research. While the simulation aspect of a digital twin is often emphasized, the role of artificial intelligence (AI) and machine learning (ML) is severely understudied. For this reason, in this paper, we highlight the pivotal role of AI and ML for digital twin research. By recognizing that a digital twin is a component of a broader Digital Twin System (DTS), we can fully grasp the diverse applications of AI and ML. In this paper, we explore six AI techniques—(1) optimization (model creation), (2) optimization (model updating), (3) generative modeling, (4) data analytics, (5) predictive analytics and (6) decision making—and their potential to advance applications in health, climate science, and sustainability.

Although natural philosophers of Enlightenment Europe shared common ideals, like reliance on reason and natural philosophy, to promote what they deemed to be progress; there were national differences in attitude and disciplinary focus. This paper takes various eligibility criteria as a starting point from which to define a Nordic Enlightenment science; and situates endeavours in climate science within visions of useful science and international conventions for scientific practice. Two perspectives are explored: the make-up of the Nordic Enlightenment science; and the Nordic natural philosopher's various platforms for work and knowledge transfer. While historians differ as to what constitutes Enlightenment thought and spirit, I establish the existence of a Nordic Enlightenment science by identifying and examining several of its indicators. The paper concludes with a more specific discussion of climate science in Norway in which I show how climate observations performed during the eighteenth century by a sample of Norway's clergymen and civil servants bear testimony to an internationally-oriented science, through articles produced for science journals and conventions followed for data presentation and instrumentation. The findings corroborate existing knowledge of a progress-driven, Enlightenment science in Nordic countries; reveal differences between countries, and present Norway's early-modern climate science in an international light. [ABSTRACT FROM AUTHOR]

There is a clear consensus among climate scientists about the reality and serious consequences of anthropogenic climate change. However, a vocal minority challenges this consensus. While some research has drawn attention to how conservative foundations support these anti-consensus scientists, less is known about how these scholars are embedded within the broader scientific community. Here, we analyze the networks of anti-consensus and consensus scientists and observe the extent to which these groups are maintained through peer collaborations (e.g. co-authorship) or substantive focus (e.g. research specialization). Using bibliometric data, we construct co-authorship and bibliographic networks linking scientists that appear in two key reports representing the consensus and anti-consensus positions. We identify specialty areas using text analysis and model participation in either series of reports. Results indicate that anti-consensus scientists are not in the same network as consensus scientists and have somewhat different research specializations than consensus scientists although there is substantive overlap. Additionally, anti-consensus scientists do not form a coherent network among themselves, which suggests they do not constitute a separate scientific community, but rather are composed of a disparate group of idiosyncratic scientists. • Clear consensus exists among climate scientists about anthropogenic climate change, yet a small minority is anti-consensus. • Consensus and anti-consensus scientists differ by collaboration and somewhat by specialization, among other factors. • Consensus scientists form a community, while anti-consensus scientists have few ties to consensus scientists or each other. [ABSTRACT FROM AUTHOR]

The concept of a digital twin is intriguing as it presents an innovative approach to solving numerous real-world challenges. Initially emerging from the domains of manufacturing and engineering, digital twin research has transcended its origins and now finds applications across a wide range of disciplines. This multidisciplinary expansion has impressively demonstrated the potential of digital twin research. While the simulation aspect of a digital twin is often emphasized, the role of artificial intelligence (AI) and machine learning (ML) is severely understudied. For this reason, in this paper, we highlight the pivotal role of AI and ML for digital twin research. By recognizing that a digital twin is a component of a broader Digital Twin System (DTS), we can fully grasp the diverse applications of AI and ML. In this paper, we explore six AI techniques—(1) optimization (model creation), (2) optimization (model updating), (3) generative modeling, (4) data analytics, (5) predictive analytics and (6) decision making—and their potential to advance applications in health, climate science, and sustainability. [ABSTRACT FROM AUTHOR]

In the field of climate change adaptation and mitigation studies, as in many other areas of Western science, there has often been a tendency to overlook and exclude marginalized populations in the course of scientific research (Forman and Pellow 2019). This can lead to incomplete knowledge and flawed solutions to complex problems such as climate change, which requires an understanding of the interconnectedness of ecology and society (Lubchenco et al. 2016). Close partnership with communities and resource user groups can expose those inaccuracies and enable better adaptation and mitigation strategies (Miller 2018; Mitchell 2020). A diversity of perspectives leads to a diversity of solutions (Redmond 2014), a critical tool in adapting to climate change. The purpose of this capstone project is to encourage researchers to develop a holistic perspective of the problem of climate change and give them the tools to incorporate community knowledge into their research and proposed solutions in an equitable manner. The end result, a training for researchers on engaging in equitable, collaborative work with communities, can be found here: https://humanecology.ucsd.edu/cooperative-research-for-climate-resilience/. There is no similar training at Scripps Institution of Oceanography, and will be implemented by the faculty working group “Connecting Scripps to Communities.

In this essay, the author summarizes the facts established by the science of climate change and then gives some opinions about what people and governments should do about the climate problem. [ABSTRACT FROM AUTHOR]

Political conflict over climate change loss and damage (L&D) has made it difficult for the Intergovernmental Panel on Climate Change (IPCC) to engage with the topic in its entirety, especially in the intergovernmentally agreed Summaries for Policymakers (SPMs). The Sixth Assessment Report (AR6), however, saw the inclusion of the term "losses and damages" in SPMs for the first time. Drawing on evidence from twenty-eight interviews with IPCC authors, reviewers, and L&D experts as well as an analysis of IPCC materials, this article traces the representation of L&D in the IPCC. I suggest that the clarification of different L&D orthographies ("Loss and Damage," "loss and damage," and "losses and damages") through the IPCC Glossary in 2018 paved the way for L&D wording to be consensually approved in multiple AR6 SPMs. Discussing the implications of orthographic choice, I show how L&D orthographies are appraised differently by individuals, depending on their position in the L&D science–policy discourse. Building on insights from science and technology studies and international relations scholarship, I contribute to a more nuanced understanding of the role of language and spelling in reaching consensus at the climate science–policy interface. [ABSTRACT FROM AUTHOR]

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Abstract: Climate models calibrated exclusively with observations from the 19th through 21st centuries are unsuitable for assessing many important hypotheses about the future. Many systems in the modern climate are expected to cross dynamic thresholds in the near future, requiring more than the instrumental record for adequate calibration. In this paper I argue that paleoclimate analogues from earth’s past can mitigate this threshold problem, even if the modern climate exhibits features that make it historically unique. While this requires that paleoclimatologists be increasingly discriminate in the past systems they target for modern analogues, the upshot is a practice of climate model construction that improves the reliability of future projections. All of this is achieved by integrating features of past climate systems discovered by the study of earth deep in the past. My analysis synthesizes important empirical work done by climate modelers and paleoclimatologists with relevant philosophical work on analogical reasoning in science. [ABSTRACT FROM AUTHOR]

Advances in applied mechanics have facilitated a better understanding of the recycling of heat and work in the troposphere. This goal is important to meet practical needs for better management of climate science. Achieving this objective may require the application of quantum principles in action mechanics, recently employed to analyze the reversible thermodynamics of Carnot's heat engine cycle. The testable proposals suggested here seek to solve several problems including (i) the phenomena of decreasing temperature and molecular entropy but increasing Gibbs energy with altitude in the troposphere; (ii) a reversible system storing thermal energy to drive vortical wind flow in anticyclones while frictionally warming the Earth's surface by heat release from turbulence; (iii) vortical generation of electrical power from translational momentum in airflow in wind farms; and (iv) vortical energy in the destructive power of tropical cyclones. The scalar property of molecular action (@t ≡ ∫mvds, J-sec) is used to show how equilibrium temperatures are achieved from statistical equality of mechanical torques (mv2 or mr2ω2); these are exerted by Gibbs field quanta for each kind of gas phase molecule as rates of translational action (d@t/dt ≡ ∫mr2ωdϕ/dt ≡ mv2). These torques result from the impulsive density of resonant quantum or Gibbs fields with molecules, configuring the trajectories of gas molecules while balancing molecular pressure against the density of field energy (J/m3). Gibbs energy fields contain no resonant quanta at zero Kelvin, with this chemical potential diminishing in magnitude as the translational action of vapor molecules and quantum field energy content increases with temperature. These cases distinguish symmetrically between causal fields of impulsive quanta (Σhν) that energize the action of matter and the resultant kinetic torques of molecular mechanics (mv2). The quanta of these different fields display mean wavelengths from 10−4 m to 1012 m, with radial mechanical advantages many orders of magnitude greater than the corresponding translational actions, though with mean quantum frequencies (v) similar to those of radial Brownian movement for independent particles (ω). Widespread neglect of the Gibbs field energy component of natural systems may be preventing advances in tropospheric mechanics. A better understanding of these vortical Gibbs energy fields as thermodynamically reversible reservoirs for heat can help optimize work processes on Earth, delaying the achievement of maximum entropy production from short-wave solar radiation being converted to outgoing long-wave radiation to space. This understanding may improve strategies for management of global changes in climate. [ABSTRACT FROM AUTHOR]

The study of climate and its change had traditionally been descriptive and regionally oriented and regarded as a minor branch of meteorology. With advances in computing technology, however, climate studies gradually moved towards highly mathematical endeavors. By the mid-1970s, climate research became dominated by dynamical meteorologists, atmospheric physicists, and physical oceanographers armed with complex numerical modeling as a principal methodology. The observational studies of climate, as well as simple climate modeling studies focusing on climate sensitivity and feedback processes, continued to play an essential role in raising the issue of climate change -- both natural and anthropogenic -- in the 1960s and early 1970s. On the other hand, many meteorologists firmly believed that climate and its change could only be properly studied using numerical models of the large-scale atmospheric circulation -- i.e., general circulation models (GCMs). This tendency was particularly strong in Britain. From early on, the British Meteorological Office devoted much of its climate research efforts to developing GCMs. This paper traces the history of GCM developments at the British Meteorological Office from the 1950s to the mid-1970s and also explores how particular styles of scientific practice, disciplinary traditions, institutional cultures, and broader political environments shaped these developments. [ABSTRACT FROM AUTHOR]

Engaging students in epistemic and conceptual aspects of modeling practices is crucial for phenomena-based learning in science classrooms. However, many students and teachers still struggle to actualize the reformed vision of the modeling practice in their classrooms. Through a discourse analysis of 150 students' explanatory models (as social semiotic spaces) from 14 classes, we propose a qualitative framework that investigates conceptual coherence and epistemic discourses to achieve a gapless explanation of scientific phenomena. Our framework draws attention to four critical components of students' explanatory models: (a) key ideas based on evidence, (b) the discourse modalities of how evidence is presented, (c) scientific representations from the cultures of scientific disciplines, (d) systems thinking approaches directly and indirectly related to oceans and marine ecosystems. Our results indicate that students struggled to construct cohesive explanatory models that communicated all key ideas and the relationships among them, with the majority of student-developed models in our study categorized as 'insufficiently' cohesive (lacking key ideas and the relationships among them), and only a small percentage of the models considered 'extensively' cohesive (all key ideas attended to, as well as the relationships among them). [ABSTRACT FROM AUTHOR]