Philosophy of Earth Sciences

Computation of seismic parameters and its interpretation from the recorded earthquake signal is empowered by digital data acquisition systems. This enables seismologist to automatically compute all the relevant parameters. Futuristic applications require extensive software development to implement seismic prediction and forecasting models. While developing such models, software developer prefer to write their own in-house analysis & modeling software with complete control over the required computations and models. This paper presents simplified mathematical framework of the seismic events and back-end computational software (...) logic & algorithm to provide a simple framework to software engineers develop customized seismic analysis & computation software. (shrink)

Level measurements, thickness measurement or remote surface detection using ultrasonic pulse transit method require that the target surface be at 90 O to the incident beam so that reflected beam comes back at 180-degree angle to effectively use this method. This is perfectly true in case of flat, solid surface at right angle to the incident beam. But surface irregularities of a porous, non-smooth, uneven material such as snow cause penetration of incident wave into the surface, absorption of the incident (...) energy, scatter of energy in many directions and further attenuation of reflected signal making it difficult to detect the reflected echo. Such a received reflected echo is very low in amplitude and is heavily noise-ridden. The successful surface detection with excellent repeatability and accuracy without any false measurement in this case requires combination of physical acoustic, mechanical, hardware and software techniques together. In this paper we discuss the suitable physical, mechanical, electronics design to physically implement the theory of Arrayed Ultrasonic transducers to shape up the directional response, beam width and avoid interference to improve the chances of proper and sufficient reflection from the non-smooth, highly porous, uneven, non-planar irregular surface. (shrink)

There are many parts of science in which a certain sort of underdetermination of theory by evidence is known to be common. It is argued that reflection on this fact should serve to shift the burden of proof from scientific anti-realists to scientific realists at a crucial point in the debate between them.

Climate models don’t give us probabilistic forecasts. To interpret their results, alternatively, as serious possibilities seems problematic inasmuch as climate models rely on contrary-to-fact assumptions: why should we consider their implications as possible if their assumptions are known to be false? The paper explores a way to address this possibilistic challenge. It introduces the concepts of a perfect and of an imperfect credible world, and discusses whether climate models can be interpreted as imperfect credible worlds. That would allow one to (...) use models for possibilistic prediction and salvage widespread scientific practice. (shrink)

Frank Knight (1921) famously distinguished the epistemic modes of certainty, risk, and uncertainty in order to characterize situations where deterministic, probabilistic or possibilistic foreknowledge is available. Because our probabilistic knowledge is limited, i.e. because many systems, e.g. the global climate, cannot be described and predicted probabilistically in a reliable way, Knight's third category, possibilistic foreknowledge, is not simply swept by the probabilistic mode. This raises the question how to justify possibilistic predictionsincluding the identication of the worst case. The development of (...) such a modal methodology is particularly vital with respect to predictions of climate change. I show that a methodological dilemma emerges when possibilistic predictions are framed in traditional terms and argue that a more nuanced conceptual framework, distinguishing dierent types of possibility, should be used in order to convey our uncertain knowledge about the future. The new conceptual scheme, however, questions the applicability of standard rules of rational decision-making, thus generating new challenges. (shrink)

Climate policy decisions are decisions under uncertainty and are, therefore, based on a range of future climate scenarios, describing possible consequences of alternative policies. Accordingly, the methodology for setting up such a scenario range becomes pivotal in climate policy advice. The preferred methodology of the Intergovernmental Panel on Climate Change will be characterised as ,,modal verificationism"; it suffers from severe shortcomings which disqualify it for scientific policy advice. Modal falsificationism, as a more sound alternative, would radically alter the way the (...) climate scenario range is set up. Climate science's inability to find robust upper bounds for future temperature rise in line with modal falsificationism does not disprove that methodology, rather, this very fact prescribes even more drastic efforts to curb CO2 emissions than currently proposed. (shrink)

As climate policy decisions are decisions under uncertainty, being based on a range of future climate change scenarios, it becomes a crucial question how to set up this scenario range. Failing to comply with the precautionary principle, the scenario methodology widely used in the Third Assessment Report of the International Panel on Climate Change (IPCC) seems to violate international environmental law, in particular a provision of the United Nations Framework Convention on Climate Change. To place climate policy advice on a (...) sound methodological basis would imply that climate simulations which are based on complex climate models had, in stark contrast to their current hegemony, hardly an epistemic role to play in climate scenario analysis at all. Their main function might actually consist in ‘foreseeing future ozone-holes’. In order to argue for these theses, I explain first of all the plurality of climate models used in climate science by the failure to avoid the problem of underdetermination. As a consequence, climate simulation results have to be interpreted as modal sentences, stating what is possibly true of our climate system. This indicates that climate policy decisions are decisions under uncertainty. Two general methodological principles which may guide the construction of the scenario range are formulated and contrasted with each other: modal inductivism and modal falsificationism. I argue that modal inductivism, being the methodology implicitly underlying the third IPCC report, is severely flawed. Modal falsificationism, representing the sound alternative, would in turn require an overhaul of the IPCC practice. (shrink)

The Intergovernmental Panel on Climate Change has developed a novel framework for assessing and communicating uncertainty in the findings published in their periodic assessment reports. But how should these uncertainty assessments inform decisions? We take a formal decision-making perspective to investigate how scientific input formulated in the IPCC’s novel framework might inform decisions in a principled way through a normative decision model.

Climate model projections are used to inform policy decisions and constitute a major focus of climate research. Confidence in climate projections relies on the adequacy of climate models for those projections. The question of how to argue for the adequacy of models for climate projections has not gotten sufficient attention in the climate modelling community. The most common way to evaluate a climate model is to assess in a quantitative way degrees of “model fit”; i.e., how well model results fit (...) observation-based data (empirical accuracy) and agree with other models or model versions (robustness). However, such assessments are largely silent about what those degrees of fit imply for a model’s adequacy for projecting future climate. We provide a conceptual framework for discussing the evaluation of the adequacy of models for climate projections. Drawing on literature from philosophy of science and climate science, we discuss the potential and limits of inferences from model fit. We suggest that support of a model by background knowledge is an additional consideration that can be appealed to in arguments for a model’s adequacy for long-term projections, and that this should explicitly be spelled out. Empirical accuracy, robustness and support by background knowledge neither individually nor collectively constitute sufficient conditions in a strict sense for a model’s adequacy for long-term projections. However, they provide reasons that can be strengthened by additional information and thus contribute to a complex non-deductive argument for the adequacy of a climate model or a family of models for long-term climate projections. (shrink)

Climate model projections are used to inform policy decisions and constitute a major focus of climate research. Confidence in climate projections relies on the adequacy of climate models for those projections. The question of how to argue for the adequacy of models for climate projections has not gotten sufficient attention in the climate modeling community. The most common way to evaluate a climate model is to assess in a quantitative way degrees of ‘model fit’; that is, how well model results (...) fit observation‐based data (empirical accuracy) and agree with other models or model versions (robustness). However, such assessments are largely silent about what those degrees of fit imply for a model's adequacy for projecting future climate. We provide a conceptual framework for discussing the evaluation of the adequacy of models for climate projections. Drawing on literature from philosophy of science and climate science, we discuss the potential and limits of inferences from model fit. We suggest that support of a model by background knowledge is an additional consideration that can be appealed to in arguments for a model's adequacy for long‐term projections, and that this should explicitly be spelled out. Empirical accuracy, robustness and support by background knowledge neither individually nor collectively constitute sufficient conditions in a strict sense for a model's adequacy for long‐term projections. However, they provide reasons that can be strengthened by additional information and thus contribute to a complex non‐deductive argument for the adequacy of a climate model or a family of models for long‐term climate projections. (shrink)

The state of geoscience education, in terms of numbers of teachers, students taught, and perceived importance, has been lagging behind the other science disciplines for decades. Part of the reason for this is that geology is seen as a “derivative” science as compared to its “experimental” counterparts (for instance, physics and chemistry). However, with current global issues facing the populations of the world (climate change, scarcity of clean water, increasing fossil fuel usage), being geoscience literate is a must. We will (...) show that, in fact, the geological sciences have their own philosophical structure, being both historical and hermeneutic, and it is the structure that makes the teaching of the geosciences for addressing such global issues advantageous. In addition, we will explore the use of historical controversies as a pedagogical tool for geoscience instruction. The history of geology is rife with controversy and the use of such a strategy has been shown to be effective for developing students’ interest in the content, sharpening critical thinking skills, as well as emphasizing the nature of science. This chapter consolidates the knowledge base by describing the structure of the geosciences in terms of its philosophical, theoretical, and cognitive frameworks. It highlights four geoscience controversies in terms of these frameworks, all the while reviewing the literature for the use of HPS in geoscience teaching. Finally it contains recommendations for possible future directions for geoscience education research within this context. (shrink)

This essay furthers debate about the burgeoning science of Probabilistic Event Attribution (PEA) and its relevance to imminent climate policy decisions. It critically examines Allen Thompson and Friederike Otto’s recent arguments concerning the implications of PEA studies for how the United Nations Framework Convention on Climate Change (UNFCCC) policy framework should be revised during the 2016 ‘review and decision.’ I show that their contention that PEA studies cannot usefully inform decision-making about adaptation policies and strategies is misguided and argue that (...) the current UNFCCC treaty, the “Paris Agreement,” supersedes their proposed revision. (shrink)

Primarily between 1833 and 1840, Whewell attempted to accomplish what natural philosophers and scientists since at least Galileo had failed to do: to provide a systematic and broad-ranged study of the tides and to attempt to establish a general scientific theory of tidal phenomena. In the essay at hand, I document the close interaction between Whewell’s philosophy of science (especially his methodological views) and his scientific practice as a tidologist. I claim that the intertwinement between Whewell’s methodology and his tidology (...) is more fundamental than has hitherto been documented. (shrink)

When attendant to the agency of models and the general context in which they perform, climate models can be seen as instrumental policy tools that may be evaluated in terms of their adequacy for purpose. In contrast, when analysed independently of their real-world usage for informing decision-making, the tendency can be to prioritise their representative role rather than their instrumental role. This paper takes as a case study the development of the UK Climate Projections 2009 in relation to its probabilistic (...) treatment of uncertainties and the implications of this approach for adaptation decision-making. It is considered that the move towards ensemble-based probabilistic climate projections has the benefit of encouraging organisations to reshape their adaptation strategies and decisions towards a risk-based approach, where they are confronted definitively with climate modelling uncertainties and drawn towards a more nuanced understanding of how climate impacts could affect their operations. This is further illustrated through the example of the built environment sector, where it can be seen that the probabilistic approach may be of limited salience for the urban heat island in the absence of a corresponding effort towards a more place-based analysis of climate vulnerabilities. Therefore, further assessment of the adequacy-for-purpose of climate models might also consider the usability of climate projections at the urban scale. (shrink)

Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via what (...) is sometimes referred to as ‘uncertainty cascade’ in the technical literature, the uncertainties of various models accumulate in the input to political decision making. This paper aims to chart the uncertainties in the multi-disciplinary enterprise of current climate modeling in broad strokes. It is shown that the uncertainty cascade makes it impossible to quantify uncertainties in the form of probability estimates. Moreover the paper highlights how global climate models fail to provide probability estimates. A better treatment of the uncertainties of climate predictions on the political level would require an overhaul of the current IPCC practice that separates the various scientific fields in various working groups. (shrink)

Darcy's law is a phenomenological relationship for fluid flow rate that finds one of its principle applications in hydrology. Theoretical hydrologists rely upon a multiplicity of conceptual models to carry out approximate derivations of Darcy's law. These derivations provide structural explanations of the law; they require the application of fundamental principles, such as conservation of momentum, to idealized models of the porous media within which the flow occurs. In practice, recognition of the idealized conditions incorporated into models facilitates the empirical (...) clarification of the domain within which the law remains accurate. Structural explanations also contribute to the physical interpretation of phenomenological parameters. (shrink)

The history of sonar technology provides a fascinating case study for philosophers of science. During the first and second World Wars, sonar technology was primarily associated with activity on the part of the sonar technicians and researchers. Usually this activity is concerned with creation of sound waves under water, as in the classic “ping and echo”. The last fifteen years have seen a shift toward passive, ambient noise “acoustic daylight imaging” sonar. Along with this shift a new relationship has begun (...) between sonar technicians and environmental ethics. I have found a significant shift in the values, and the environmental ethics, of the underwater community by looking closely at the term “noise” as it has been conceptualized and reconceptualized in the history of sonar technology. To illustrate my view, I will include three specific sets of information: 1) a discussion of the 2003 debate regarding underwater active low- frequency sonar and its impact on marine life; 2) a review of the history of sonar technology in diagrams, abstracts, and artifacts; 3) the latest news from February 2004 on how the military and the acoustic daylight imaging passive sonar community has responded to the current debates. (shrink)

In this thesis, I argue that a good historical science will have the following characteristics: Firstly, it will seek to construct causal histories of the past. Secondly, the construction of these causal histories will utilise well-tested regularities of science. Additionally, well-tested regularities will secure the link between observations of physical traces and the causal events of interest. However, the historical sciences cannot use these regularities in a straightforward manner. The regularities must accommodate the idiosyncrasies of the past, and the degradation (...) of evidence over time. Through an examination of how the historical sciences work in practice, I show how they can confirm these unique causal histories, and the limits to their confirmatory strategies. (shrink)

Nach der Problemumgrenzung werden im zweiten Abschnitt die Möglichkeiten der aktualistischen Methode behandelt. Zuerst werden Beispiele für die Anwendung der Methode auf vorwiegend geologischem Gebiet gebracht, gegliedert in exogene und endogene Vorgänge. Wegen der gleichzeitigen Bedeutung für Geologie und Paläontologie und Biologie schliesst sich eine Besprechung der Biostratonomie an. Der letzte Teil dieses Abschnittes behandelt ausgewählte Beispiele aus der Paläontologie. Der dritte Abschnitt schliesslich behandelt die Grenzen aktualistischer Betrachtungsmethode an Hand typischer Beispiele.The theory of actualism is the most important in (...) geological and palaeontological thinking. In this paper the historical development of this theory, its possibilities and boundaries are described and elucidated by geological and palaeontological examples. (shrink)

I examine the warrants we have in light of the empirical successes of a kind of model I call ‘ hybrid models ’, a kind that includes climate models among its members. I argue that these warrants ’ strengths depend on inferential virtues that are not just explanatory virtues, contrary to what would be the case if inference to the best explanation provided the warrants. I also argue that the warrants in question, unlike those IBE provides, guide inferences only to (...) model implications about which there is real uncertainty. My conclusion provides criteria of adequacy for epistemologies of climate and other hybrid models. (shrink)

I examine, from Mayo's severe testing perspective, the case found in the Intergovernmental Panel on Climate Change fourth report for the claim that increases in anthropogenic greenhouse gas concentrations caused most of the post-1950 global warming. My examination begins to provide an alternative to standard, probabilistic assessments of OUR FAULT. It also brings out some of the limitations of variety of evidence considerations in assessing this and other hypotheses about the causes of climate change, and illuminates the epistemology of optimal (...) fingerprinting studies. Finally, it shows that some features of Mayo's perspective should be kept in whatever approach is preferred for assessing hypotheses about the causes of climate change. (shrink)

The present paper draws on climate science and the philosophy of science in order to evaluate climate-model-based approaches to assessing climate projections. We analyze the difficulties that arise in such assessment and outline criteria of adequacy for approaches to it. In addition, we offer a critical overview of the approaches used in the IPCC working group one fourth report, including the confidence building, Bayesian and likelihood approaches. Finally, we consider approaches that do not feature in the IPCC reports, including three (...) approaches drawn from the philosophy of science. We find that all available approaches face substantial challenges, with IPCC approaches having as a primary source of difficulty their goal of providing probabilistic assessments. (shrink)

Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, and the two (...) often compound one another. This paper explores the common roots of the two problems in concerns about the precision of predictions generated by scientific models, and discusses how both concerns bear on the study of complex natural systems, particularly the global climate. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

Reference models of the earth’s interior play an important role in the acquisition of knowledge about the earth’s interior and the earth as a whole. Such models are used as a sort of standard reference against which data are compared. I argue that the use of reference models merits more attention than it has gotten so far in the literature on models, for it is an example of a method of doing science that has a long and significant history, and (...) a study of reference models could increase our understanding of this methodology. (shrink)

To study Earth’s climate, scientists now use a variety of computer simulation models. These models disagree in some of their assumptions about the climate system, yet they are used together as complementary resources for investigating future climatic change. This paper examines and defends this use of incompatible models. I argue that climate model pluralism results both from uncertainty concerning how to best represent the climate system and from difficulties faced in evaluating the relative merits of complex models. I describe how (...) incompatible climate models are used together in ‘multi-model ensembles’ and explain why this practice is reasonable, given scientists’ inability to identify a ‘best’ model for predicting future climate. Finally, I characterize climate model pluralism as involving both an ontic competitive pluralism and a pragmatic integrative pluralism. (shrink)

Computer simulation modeling is an important part of contemporary scientific practice but has not yet received much attention from philosophers. The present project helps to fill this lacuna in the philosophical literature by addressing three questions that arise in the context of computer simulation of Earth's climate. Computer simulation experimentation commonly is viewed as a suspect methodology, in contrast to the trusted mainstay of material experimentation. Are the results of computer simulation experiments somehow deeply problematic in ways that the results (...) of material experiments are not? I argue against categorical skepticism toward the results of computer simulation experiments by revealing important parallels in the epistemologies of material and computer simulation experimentation. It has often been remarked that simple computer simulation models---but not complex ones---contribute substantially to our understanding of the atmosphere and climate system. Is this view of the relative contributions of simple and complex models tenable? I show that both simple and complex climate models can promote scientific understanding and argue that the apparent contribution of simple models depends upon whether a causal or deductive account of scientific understanding is adopted. When two incompatible scientific theories are under consideration, they typically are viewed as competitors, and we seek evidence that refutes at least one of the theories. In the study of climate change, however, logically incompatible computer simulation models are accepted as complementary resources for investigating future climate. How can we make sense of this use of incompatible models? I show that a collection of incompatible climate models persists in part because of difficulties faced in evaluating and comparing climate models. I then discuss the rationale for using these incompatible models together and argue that this climate model pluralism has both competitive and integrative components. (shrink)

The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding (...) our knowledge of near-Earth space. To facilitate data-sharing interoperability among distinct orbital debris and space object catalogs, and SSA information systems, I proposed ontology in (Rovetto, 2015) and (Rovetto and Kelso, 2016). I continue this effort toward formal representations and models of the overall domain that may serve to improve peaceful SSA and increase our scientific knowledge. This paper explains the project concept introduced in those publications, summarizing efforts to date as well as the research field of ontology development and engineering. I describe concepts for an ontological framework for the orbital space environment, near-Earth space environment and SSA domain. An ontological framework is conceived as a part of a potential international information system. The purpose of such a system is to consolidate, analyze and reason over various sources and types of orbital and SSA data toward the mutually beneficial goals of safer space navigation and scientific research. Recent internationals findings on the limitations of orbital data, in addition to existing publications on collaborative SSA, demonstrate both the overlap with this project and the need for data-sharing and integration. (shrink)

A short summary paper of my Orbital Space Domain Ontology project (purl.org/space-ontology), originally conceived in 2011. Since then I've sought (without success) opportunities to realize it (either as a PhD or other degree thesis; or in an employment position) toward my original passion of entering the space sector and gaining further space education. Since then persons in the relevant space disciplines have seen the potential in it, and unfortunately some have taken advantage of my ideas yet excluded me from work. (...) I continue to struggle to fight for my own ideas as I see others professionally and financially benefit at my expense. References and documentation are available upon request to confirm my early ideation and origination on this topic. Please contact me if you have opportunities. Thank you. (shrink)

This paper develops the ontology of space objects for theoretical and computational ontology applied to the space (astronautical/astronomical) domain. It follows “An ontological architecture for Orbital Debris Data” (Rovetto, 2015) and “Preliminaries of a Space Situational Awareness Ontology” (Rovetto, Kelso, 2016). Important considerations for developing a space object ontology, or more broadly, a space domain ontology are presented. The main category term ‘Space Object’ is analyzed from a philosophical perspective. The ontological commitments of legal definitions for artificial space objects are (...) also discussed. Space object taxonomies are offered and space object terms are defined. -/- == Originally conceived in 2011, since then I've sought (without success) opportunities to realize the overall project (either as a PhD or other degree thesis; or in an employment position) toward my original passion of entering the space sector and gaining further space education. Since then persons have seen the potential in it, sought my ideas, and unfortunately some have taken advantage of my ideas ad excluded me from work. I continue to struggle to fight for my own ideas as I see others professionally and financially benefit at my expense. References and documentation are available upon request to confirm my early ideation and origination on this topic. (shrink)

The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris and broader SSA domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain (...) knowledge, (II) structure, and standardize where needed, orbital data and terminology, and (III) foster semantic interoperability and data-sharing. In doing so I hope to (IV) contribute to solving the orbital debris problem, improving peaceful global SSA, and ensuring safe space travel for future generations. (shrink)

The question is: should the United States and nations at large pursue a human spaceflight program (and if so, why)? I offer an unwavering positive answer to this question, and state the reasons for it while considering the broad challenges and benefits of (human) spaceflight. Space exploration is a human activity that is intrinsically forward-looking, and as such, has positive potential. Both national and international space programs can galvanize the population, inspire the youth, foster job-creation, and motivate the existing workforce. (...) The nature of the enterprises involved—their scale, novelty, and complexity—requires a steady and continuous upward progression toward greater societal, scientific and technological development. That is, in order to overcome the challenges of human spaceflight, progress is required. More to the point, the survival of humanity depends on expanding beyond the confines of our planet. Human spaceflight, in short, presents us with an opportunity to significantly advance the nation and the global community. (shrink)

Space situational awareness (SSA) is vital for international safety and security, and for the future of space travel. The sharing of SSA data and information should improve the state of global SSA for planetary defense and spaceflight safety. I take steps toward a Space Situational Awareness (SSA) Ontology, and outline some central objectives, requirements and desiderata in the ontology development process for this domain. The purpose of this ontological system is to explore the potential for the ontology research topic to (...) (i) represent SSA general knowledge, data, and entities/objects, (ii) clearly express the meaning of SSA data, and (iii) foster SSA data-sharing. The overall goal and motivation is to (iv) improve our capacity for planetary defense, e.g., from near- or deep-space objects and phenomena, and (v) facilitate safer and peaceful space access, navigation and travel, by improving global SSA. This research is thereby intended only for peaceful space-domain applications and uses, with particular interests in orbital debris. There is little application of ontology to the space domain as compared with other disciplines and little if any ontological development of SSA and related domains. In this respect, this paper offers novel concepts. (shrink)

Summary Analogue models are actual physical setups used to model something else. They are especially useful when what we wish to investigate is difficult to observe or experiment upon due to size or distance in space or time: for example, if the thing we wish to investigate is too large, too far away, takes place on a time scale that is too long, does not yet exist or has ceased to exist. The range and variety of analogue models is too (...) extensive to attempt a survey. In this article, I describe and discuss several different analogue model experiments, the results of those model experiments, and the basis for constructing them and interpreting their results. Examples of analogue models for surface waves in lakes, for earthquakes and volcanoes in geophysics, and for black holes in general relativity, are described, with a focus on examining the bases for claims that these analogues are appropriate analogues of what they are used to investigate. A table showing three different kinds of bases for reasoning using analogue models is provided. Finally, it is shown how the examples in this article counter three common misconceptions about the use of analogue models in physics. (shrink)

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.

For applied geologists working in the minerals industry the tasks of problem formulation, observation and data collection, interpretation and modelling invoke various philosophical considerations whether the practitioner is aware of them or not. A primary goal of applied geologists is to build models that accurately predict reality to an acceptable degree. In this paper, we describe the key philosophical frameworks proposed for conducting scientific investigations and relate them to the field of applied geology. We consider the very important differences in (...) the types of problem confronted in experimental sciences (such as physics and chemistry) compared to the historical sciences, such as geology, where the processes studied are unique and only evidential traces of past events are available. The prediction quality of models is likely to be materially improved if the geologist is firmly and consciously practiced in the scientific method. In addition, if the predictions are framed and presented in terms of the underlying science, the quality of decisions made based on those predictions will likewise be improved. The implications for creating additional value to a project or operation can be very significant when geological models are constructed and used by a practitioner with an understanding of the philosophical basis of the activities constituting a scientific investigation. The method of multiple working hypotheses is particularly important when working in historical sciences. We argue that working within the framework of multiple working hypotheses can provide a valuable insurance against the adoption of, or persistence with, flawed models. (shrink)

A new theory concerning charge separation of atmospheric electricity is proposed, based on the selective capture of negative charge from atmospheric ion pairs by material surfaces. It explains why the earth's surface becomes negatively charged during fine weather, and provides a mechanism for the phenomenon of charge separation within clouds during the violent growth of thunderstorms. Also included is a description of laboratory and field experiments substantiating our views.