Philosophy of Earth Sciences

When we look at 800,000 year ice core data CO2 levels since 1950 have risen at a rate of 123-fold faster than the fastest rate in 800,000 years. When we see that this rise is precisely correlated with global carbon emissions the human link to climate change seems certain and any rebuttal becomes ridiculously implausible. The 800,000 year correlation between CO2 and global temperatures seems to be predicting at least 9 degrees C of more warming based on current CO2 levels.

The central aim of astrobiology is to study origins, evolution and distribution of life in the universe, combining data from various disciplines. However, I will argue that from a philosophical standpoint, astrobiology requires the affirmation of astrophilosophy. Fry (2015) claims that philosophical presuppositions guiding science are general, for example, we hold the notion that natural laws necessarily hold at the whole universe at large, and on the basis of the universal applicability of natural laws, the astrobiological research is conducted. Jakosky (...) (2000) mentions that finding any life elsewhere that had an origin independent of that on Earth would be philosophically profound. Kolb (2005) covers various definitions of life and establishes thought experiments about the survival of life in the Solar System. Most of the (scarce) research has dealt with specific philosophical topics in astrobiology, instead of seeing it as a new philosophical discipline or perhaps a new subdiscipline for each of the classical philosophical disciplines. -/- Persson (2013) has made a step towards this by systematizing the most important philosophical questions in astrobiology, along with Dunér (2013) emphasizing its importance for ethics, epistemology, semiotics and linguistics, and cognition. Persson mentions that the justification of resources is a question of ethics, but I would also like to add political philosophy, since not only is there a question of preference over "earthly manners" but also fair distribution of costs and the concept of ownership of the new worlds. The question of a new definition of life is another one, that I would argue holds one of the central places in metaphysics. Persson mentions various definitions of life and that such a discussion is important for both biology and philosophy, a notion I would like to add to by stating that the question of finding another life is also an ontological question, giving us either categorical similarity or dissimilarity, and establishing a new kind, which is of metaphysical importance. Persson also establishes the importance of is it possible to know whether we are alone or not, a question I would like to tie to the modern epistemological questions of possibility of knowledge (cf. Cassam, 2007). Persson also connects astrobiology with ethical questions such as biocentrism or colonization, which also might be tied to philosophy of mind, and philosophy of politics and culture respectively. -/- One major step forward was established recently by Dick (2020), focusing on a new discipline combining astronomy, cosmology, and astrobiology, in which there is a focus on the nature of reasoning, the problematic nature of evidence, the influence of metaphysical preconceptions, the epistemological status of these disciplines, the role of technology, and the mutual interaction between these disciplines. The purpose of this paper is to see how the creation of astrophilosophy could better emphasize the role of philosophy today, and would it behave as a side-by-side major philosophical discipline or a complement to the current philosophical disciplines, for example, bringing new light into metaphysics, epistemology, ethics, or philosophy of mind. In the first case, we would make a metaphysical difference between human-related problems and other possible kinds, and in the second case, we would have to incorporate current astrobiological questions into modern philosophical dialogue, establishing, for example, metaphysics and epistemology of life, or, a possibility to incorporate non-human life into epistemology, philosophy of mind, and philosophy of biology. This goes hand to hand with Dunér's (2013) points of seeing the philosophy of astrobiology as both a type of individual and collective self-understanding, and conceptual analysis. That way, using astrophilosophical novelties, we can improve not only our current philosophical intuitions, but also expand the territory of philosophical subdisciplines to become more universal. -/- . (shrink)

In both scientific and popular circles it is often said that we are in the midst of a sixth mass extinction. Although the urgency of our present environmental crises is not in doubt, such claims of a present mass extinction are highly controversial scientifically. Our aims are, first, to get to the bottom of this scientific debate by shedding philosophical light on the many conceptual and methodological challenges involved in answering this scientific question, and, second, to offer new philosophical perspectives (...) on what the value of asking this question has been — and whether that value persists today. We show that the conceptual challenges in defining ‘mass extinction’, uncertainties in past and present diversity assessments, and data incommensurabilities undermine a straightforward answer to the question of whether we are in, or entering, a sixth mass extinction today. More broadly we argue that an excessive focus on the mass extinction framing can be misleading for present conservation efforts and may lead us to miss out on the many other valuable insights that Earth’s deep time can offer in guiding our future. (shrink)

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, (...) data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data. (shrink)

Like all human activities, scientific research is infused with values. Scientific discovery can, for example, be valued as an end in itself. The phrase ethical values is an umbrella term for much of what people care about aside from knowledge for its own sake. Ethical values encompass reasons for caring about the harms caused by climate impacts or the injustice of how those harms are distributed. The closer that research gets to informing real-world actions, the more the design of that (...) research can be examined from the perspective of ethical values. Which societal challenges does the research aim to inform? From whose perspective does a policy analysis view potential outcomes? In this chapter we use a series of examples to illustrate how researchers’ choices regarding the treatment of uncertainties can have important consequences from the perspective of ethical values. Our aims in this chapter are: to familiarize readers with the key concept of coupled ethical–epistemic choices; to build capacity for recognizing such choices within the treatment of uncertainties; to encourage engagement with ethical values as a part of climate change research; and to offer some guidance on how to start doing so. (shrink)

what is the ontology of planets?Our access point to this question is the ontology of planet Earth. Although the presence of life marks planet Earth as special among other planets, Earth shares a basic commonality with them – namely, its material existence. We take this commonality as a point of departure for our reflections on the ontology of both planet Earth and other planets. In this chapter, we ask for the ontology of this materiality of planets. We consult the ontology (...) of planet Earth as I developed it in an earlier contribution (Blok, 2019), explore the ontology of planets as absolute boundary of the natural habitats on Earth, and reflect on the opportunities and limitations such ontology provides for future human colonies on other planets. (shrink)

There’s a general assumption that teleology and function do not exist in inanimate nature. Throughout biology, it is generally taken as granted that teleology (or teleonomy) and functions are not only unique to life, but perhaps even a defining quality of life. For many, it’s obvious that rocks, water, and the like, are not teleological, nor could they possibly have stand-alone functions. This idea - that teleology and function are unique to life - is the target of this paper. I (...) begin with an overview of McShea’s field theoretic account of teleology. I start with the field theoretic account because it presents a promising analysis of teleological systems. It is promising because, in not making any assumptions about life’s special status in teleological systems, it avoids counterexamples that have problematized other accounts. I then consider some of the prominent efforts that have been made to attempt to avoid ascribing functions or teleology to some form of inanimate nature. In my assessment, none of the efforts are successful. I conclude by offering mineral evolution as a case study to show how inanimate nature can be both teleological and functional. The evolution of mineral species reveals that teleology and function extend to inanimate nature, and that teleology and function come in degrees. (shrink)

A number of authors, including me, have argued that the output of our most complex climate models, that is, of global climate models and Earth system models, should be assessed possibilistically. Worries about the viability of doing so have also been expressed. I examine the assessment of the output of relatively simple climate models in the context of discovery and point out that this assessment is of epistemic possibilities. At the same time, I show that the concept of epistemic possibility (...) used in the relevant studies does not fit available analyses of this concept. Moreover, I provide an alternative analysis that does fit the studies and broad climate modelling practices as well as meshes with my existing view that climate model assessment should typically be of real possibilities. On my analysis, to assert that a proposition is epistemically possible is to assert that it is not known to be false and is consistent with at least approximate knowledge of the basic way things are. I, finally, consider some of the implications of my discussion for available possibilistic views of climate model assessment and for worries about such views. I conclude that my view helps to address worries about such assessment and permits using the full range of climate models in it. (shrink)

Earthquakes are among the world’s deadliest natural phenomena. On an increasingly crowded Earth, earthquake risk management therefore should be taken seriously as a global policy problem. Thus, this chapter discusses some of the ethical dimensions of earthquakes as a phenomenon of planetary significance in the Anthropocene. I do not attempt an exhaustive survey, but consider one background ethical issue: the kinds of harms that occur when an earthquake impacts human habitation. We may distinguish three categories of human-related harms: personal harms, (...) which accrue to individual humans; social harms, which impact on social relationships between humans; and institutional harms, which compromise the ability of institutions to respond to the quake. This analysis will help us better appreciate the moral salience of earthquakes as a global policy imperative in the Anthropocene. (shrink)

Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriately termed “model-based,” and I examine the use of statistics in climate fingerprinting to show (...) how the difficulties that climate scientists encounter in applying statistics to ensemble-generated data are the practical difficulties of normal statistical practice. The upshot is that whether the application of statistics to ensemble-generated data yields trustworthy results should be expected to vary from case to case. (shrink)

While the predominant focus of the philosophical literature on scientific modeling has been on single-scale models, most systems in nature exhibit complex multiscale behavior, requiring new modeling methods. This challenge of modeling phenomena across a vast range of spatial and temporal scales has been called the tyranny of scales problem. Drawing on research in the geosciences, I synthesize and analyze a number of strategies for taming this tyranny in the context of conceptual, physical, and mathematical modeling. This includes several strategies (...) that can be deployed in physical modeling, even when strict dynamical scaling fails. In all cases, I argue that having an adequate conceptual model—given both the nature of the system and the particular purpose of the model—is essential. I draw a distinction between depiction and representation, and use this research in the geosciences to advance a number of debates in the philosophy of modeling. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

When do probability distribution functions (PDFs) about future climate misrepresent uncertainty? How can we recognise when such misrepresentation occurs and thus avoid it in reasoning about or communicating our uncertainty? And when we should not use a PDF, what should we do instead? In this paper we address these three questions. We start by providing a classification of types of uncertainty and using this classification to illustrate when PDFs misrepresent our uncertainty in a way that may adversely affect decisions. We (...) then discuss when it is reasonable and appropriate to use a PDF to reason about or communicate uncertainty about climate. We consider two perspectives on this issue. On one, which we argue is preferable, available theory and evidence in climate science basically excludes using PDFs to represent our uncertainty. On the other, PDFs can legitimately be provided when resting on appropriate expert judgement and recognition of associated risks. Once we have specified the border between appropriate and inappropriate uses of PDFs, we explore alternatives to their use. We briefly describe two formal alternatives, namely imprecise probabilities and possibilistic distribution functions, as well as informal possibilistic alternatives. We suggest that the possibilistic alternatives are preferable. -/- . (shrink)

Most philosophical discussions of disagreement have used idealized disagreements to draw conclusions about the nature of disagreement. I closely examine an actual, non-idealized disagreement in dinosaur paleobiology and show that it can not only teach us about the features of some of our real world disagreements, but can help us to argue for the possibility of reasonable real world disagreement.

Outside the philosophy classroom, global skeptics – skeptics about all (purported) knowledge of the external world – are rare. But there are people who describe themselves as “skeptics” about various more specific domains, including self-professed “skeptics” about the reality of anthropogenic climate change. There is little to no philosophical literature that juxtaposes the climate change skeptic with the external world skeptic. While many “traditional” epistemologists assume that the external world skeptic poses a serious philosophical challenge in a way that the (...) climate change skeptic doesn’t, many “applied” or “social” epistemologists assume that there isn’t much to be learned from debates about the external world skeptic, finding her challenge to be distant from both common sense and real-world concerns. I try to show that both of these views are mistaken. The external world skeptic raises deep questions that are important for our everyday deliberation about what to believe, and there are significant structural parallels between the arguments for external world skepticism and those for at least a form of climate change skepticism that is idealized – but not too idealized! – from the views of flesh-and-blood climate change skeptics. As such, we have strong reasons to think in parallel about how to reply to both skeptics’ challenges. I thus finish by (briefly) considering how different widespread responses to the external world skeptic might or might not generalize happily to the climate change skeptic’s challenge. (shrink)

In 2012, the Geological Time Scale, which sets the temporal framework for studying the timing and tempo of all major geological, biological, and climatic events in Earth’s history, had one-quarter of its boundaries moved in a widespread revision of radiometric dates. The philosophy of metrology helps us understand this episode, and it, in turn, elucidates the notions of calibration, coherence, and consilience. I argue that coherence testing is a distinct activity preceding calibration and consilience, and I highlight the value of (...) discordant evidence and trade-offs scientists face in calibration. The iterative nature of calibration, moreover, raises the problem of legacy data. (shrink)

At the intersection of taxonomy and nomenclature lies the scientific practice of typification. This practice occurs in biology with the use of holotypes (type specimens), in geology with the use of stratotypes, and in metrology with the use of measurement prototypes. In this paper I develop the first general definition of a scientific type and outline a new philosophical theory of types inspired by Pierre Duhem. I use this general framework to resolve the necessity-contingency debate about type specimens in philosophy (...) of biology, to advance the debate over the myth of the absolute accuracy of standards in metrology, and to address the definition-correlation debate in geology. I conclude that just as there has been a productive synergy between philosophical accounts of natural kinds and scientific taxonomic practices, so too there is much to be gained from developing a deeper understanding of the practices and philosophy of scientific types. (shrink)

A review of Thomas Moynihan's Spinal Catastrophism: A Secret History (2019).

In the spirit of explanatory pluralism, this chapter argues that causal and noncausal explanations of a phenomenon are compatible, each being useful for bringing out different sorts of insights. After reviewing a model-based account of scientific explanation, which can accommodate causal and noncausal explanations alike, an important core conception of noncausal explanation is identified. This noncausal form of model-based explanation is illustrated using the example of how Earth scientists in a subfield known as aeolian geomorphology are explaining the formation of (...) regularlyspaced sand ripples. The chapter concludes that even when it comes to everyday "medium-sized dry goods" such as sand ripples, where there is a complete causal story to be told, one can find examples of noncausal scientific explanations. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of its epistemic reliability. (...) Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

The theoretical foundations of climate science have received little attention from philosophers thus far, despite a number of outstanding issues. We provide a brief, non-technical overview of several of these issues – related to theorizing about climates, climate change, internal variability and more – and attempt to make preliminary progress in addressing some of them. In doing so, we hope to open a new thread of discussion in the emerging area of philosophy of climate science, focused on theoretical foundations.

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.

Uncertainty is recognized as a key issue in water resources research, amongst other sciences. Discussions of uncertainty typically focus on tools and techniques applied within an analysis, e.g. uncertainty quantification and model validation. But uncertainty is also addressed outside the analysis, in writing scientific publications. The language that authors use conveys their perspective of the role of uncertainty when interpreting a claim —what we call here “framing” the uncertainty. This article promotes awareness of uncertainty framing in four ways. 1) It (...) proposes a typology of eighteen uncertainty frames, addressing five questions about uncertainty. 2) It describes the context in which uncertainty framing occurs. This is an interdisciplinary topic, involving philosophy of science, science studies, linguistics, rhetoric, and argumentation. 3) We analyze the use of uncertainty frames in a sample of 177 abstracts from the Water Resources Research journal in 2015. This helped develop and tentatively verify the typology, and provides a snapshot of current practice. 4) Provocative recommendations promote adjustments for a more influential, dynamic science. Current practice in uncertainty framing might be described as carefully-considered incremental science. In addition to uncertainty quantification and degree of belief (present in ~5% of abstracts), uncertainty is addressed by a combination of limiting scope, deferring to further work (~25%) and indicating evidence is sufficient (~40%) – or uncertainty is completely ignored (~8%). There is a need for public debate within our discipline to decide in what context different uncertainty frames are appropriate. Uncertainty framing cannot remain a hidden practice evaluated only by lone reviewers. (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)

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)

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)

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. (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)

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.

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.

Recently a number of scientists have proposed substantial changes to the practice of climate modeling, though they disagree over what those changes should be. We provide an overview and critical examination of three leading proposals: the unified approach, the hierarchy approach and the pluralist approach. The unified approach calls for an accelerated development of high-resolution models within a seamless prediction framework. The hierarchy approach calls for more attention to the development and systematic study of hierarchies of related models, with the (...) aim of advancing understanding. The pluralist approach calls for greater diversity in modeling efforts, including, on some of its variants, more attention to empirical modeling. After identifying some of the scientific and institutional challenges faced by these proposals, we consider their expected gains and costs, relative to a business-as-usual modeling scenario.We find the proposals to be complementary, having valuable synergies. But since resource limitations make it unlikely that all three will be pursued, we offer some reflections on more limited changes in climate modeling that seem well within reach and that can be expected to yield substantial benefits. (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)

Origin of life studies have presented one of the most serious challenges to the mechanistic conception that life can be explained scientifically as a mere product of chemistry and physics. Hypotheses about the origin of life can be divided into two categories: (1) biogenesis – life comes from life, and (2) abiogenesis – life comes from non-living matter. The theory of the spontaneous generation of life from inanimate matter had been held even by the ancient Greeks and by numerous scientists (...) well into the 19th century. The theory of abiogenesis poses many problems for understanding the origin of life on Earth, and the appearance of life early in Earth’s history. Numerous chemical, mathematical and informational problems arise which make random mechanical processes of cellular formation and function unlikely. Fossil evidence contradicts a gradualist evolutionary mechanism of development of life, especially the well-known Cambrian explosion, in which highly developed metazoan species suddenly appear in the geological column without intermediate predecessors. But the physical conundrums that mechanistic theories of chemistry and physics face are only one side of the problem. Along with a rising chorus of philosophers, Thomas Nagel, an atheist philosopher, has protested that essential questions about the origin of life, and features such as mind, intelligence and morality are completely left unexplained by mechanistic evolutionary theories. In Mind and Cosmos: Why the Materialist Neo-Darwinian Conception of Nature Is Almost Certainly False, Nagel plainly lays out his argument that the modern materialist approach to life has conspicuously failed to explain something so integral to nature as mind or consciousness, thereby threatening to unravel the entire naturalistic world picture of biology, evolutionary theory and cosmology. [13] As an alternative he argues that at least natural teleological principles must be admitted to play a role in our view of science. He writes: “Each of our lives is a part of the lengthy process of the universe gradually waking up and becoming aware of itself.” The Vedantic view of the Absolute as sentient conceives of Bhagavan as the conscious and consequently personal source of the universe. This view holds that life is fundamental, and not merely coextensive with matter. It is thus consistent with the law of biogenesis which is scientifically established in agreement with empirical evidence. Life is the basis of Nature, not matter, and Nature is a system in which the different species are nodes or niches, each possessed of variety and adaptability. Evolution is of consciousness, not of the bodies of organisms. The sedimentary fossils are the result of catastrophic deposits, and are thus not indicative of gradual evolution which is concluded only on the questionable assumption of uniformitarianism. (shrink)

Are physics and chemistry sufficient to provide a basis for a theory of everything? The worldview of materialist naturalism that forms the foundation of NeoDarwinian evolution, Big Bang cosmogony, and molecular biology in general has been subjected to challenge for its monumental failure to explain life, consciousness and other mind-related aspects of reality. Two recent books, Why Evolution is True by Jerry Coyne [1], and Thomas Nagel’s Mind and Cosmos: Why the Materialist NeoDarwinian Conception of Nature Is Almost Certainly False (...) [2], both authors being atheists, reflect the deep rift we find, not only in the religious conflict between creation and evolution, but in the fundamental awareness we all have that we are more than just molecular matter. This common sense understanding can only escape the notice of a particularly shallow ideological dogmatism that insists it has all the answers based solely on its unprecedented technological success. Science has come to represent two different things: (a) a body of knowledge, and (b) a method for acquiring knowledge. The problem arises when it is forgotten that there is no independent body of knowledge for science apart from its method – it keeps changing according to the results of the latest findings of the scientific method. The method is not to be abandoned because of those who would like to replace it with a fixed body of knowledge, which then becomes ideology. If biogenesis is hypothesized as the law of Nature, and we observe that life comes from pre-existing life in all our experience, while the hypothesis of abiogenesis, that life comes from matter, is never backed by any observation, then according to the scientific method—which one is to be accepted as true scientific knowledge? Obviously, the one backed by empirical observation. It is necessary to get free of ideological “knowledge,” and return to science as a method for gathering evidence that may lead to conclusions beyond the material naturalist view of Nature, and conforms to what we experience and rationally understand about the world in which we live. (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)

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)

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)