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.

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)

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)

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)

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)

Philosophers and metrologists have refuted the view that measurement’s epistemic privilege in scientific practice is explained by its theory-neutrality. Rather, they now explicitly appeal to the role that theories play in measurement. I formulate a challenge for this view: scientists sometimes ascribe epistemic privilege to measurements even if they lack a shared theory about their target quantity, which I illustrate through a case study from early geodesy. Drawing on that case, I argue that the epistemic privilege of measurement precedes shared (...) background theory and is better explained by its pre-theoretic function in enabling a distinctive kind of inquiry. (shrink)

Over the last twenty-five years, climate scientists working on the attribution of climate change to humans have developed increasingly sophisticated statistical models in a process that can be understood as a kind of calibration: the gradual changes to the statistical models employed in attribution studies served as iterative revisions to a measurement(-like) procedure motivated primarily by the aim of neutralizing particularly troublesome sources of error or uncertainty. This practice is in keeping with recent work on the evaluation of models more (...) generally that views models as tools for particular tasks: what drives the process is the desire for models that provide more reliable grounds for inference rather than accuracy to the underlying mechanisms of data-generation. (shrink)

There are distinctive methodological and conceptual challenges in rare and severe event (RSE) forecast verification, that is, in the assessment of the quality of forecasts of rare but severe natural hazards such as avalanches, landslides or tornadoes. While some of these challenges have been discussed since the inception of the discipline in the 1880s, there is no consensus about how to assess RSE forecasts. This article offers a comprehensive and critical overview of the many different measures used to capture the (...) quality of categorical, binary RSE forecasts – forecasts of occurrence and non-occurrence – and argues that of skill scores in the literature there is only one adequate for RSE forecasting. We do so by first focusing on the relationship between accuracy and skill and showing why skill is more important than accuracy in the case of RSE forecast verification. We then motivate three adequacy constraints for a measure of skill in RSE forecasting. We argue that of skill scores in the literature only the Peirce skill score meets all three constraints. We then outline how our theoretical investigation has important practical implications for avalanche forecasting, basing our discussion on a study in avalanche forecast verification using the nearest-neighbour method (Heierli et al., 2004). Lastly, we raise what we call the “scope challenge”; this affects all forms of RSE forecasting and highlights how and why working with the right measure of skill is important not only for local binary RSE forecasts but also for the assessment of different diagnostic tests widely used in avalanche risk management and related operations, including the design of methods to assess the quality of regional multi-categorical avalanche forecasts. (shrink)

For several decades, a debate has been waged over how to interpret the significance of fossils from the Burgess Shale and Cambrian Explosion. Stephen Jay Gould argued that if the “tape of life” was rerun, then the resulting lineages would differ radically from what we find today, implying that humans are a happy accident of evolution. Simon Conway Morris argued that if the “tape of life” was rerun, the resulting lineages would be similar to what we now observe, implying that (...) intelligence would still emerge from an evolutionary process. Recent methodological innovations in paleontological practice call into question both positions and suggest that global claims about the history of life, whether in terms of essential contingency or predictable convergence, are unwarranted. (shrink)

Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' (...) predictive and experimental control over perturbations of the measurement process. Second, I identify a methodology by which scientists can solve hard problems of coordination and gradually increase their predictive control over perturbations. I dub this methodology ‘operational pluralism’ since it is driven by the introduction of alternative measurement operations that involve different physical indicators. (shrink)

The research observed, in parallel and comparatively, a surveillance state’s use of communication & cyber networks with satellite applications for power political & realpolitik purposes, in contrast to the outer space security & legit scientific purpose driven cybernetics. The research adopted a psychoanalytic & psychosocial method of observation in the organizational behaviors of the surveillance state, and a theoretical physics, astrochemical, & cosmological feedback method in the contrast group of cybernetics. Military sociology and multilateral movements were adopted in the diagnostic (...) studies & research on cybersecurity, and cross-channeling in communications were detected during the research. The paper addresses several key points of technicalities in security & privacy breach, from personal devices to ontological networks and satellite applications - notably telecommunication service providers & carriers with differentiated spectrum. The paper discusses key moral ethical risks posed in the mal-adaptations in commercial devices that can corrupt democracy in subtle ways but in a mass scale. The research adopted an analytical linguistics approach with linguistic history in unjailing from the artificial intelligence empowered pancomputationalism approach of the heterogenous dictatorial semantic network, and the astronomical & cosmological research in information theory implies that noncomputable processes are the only defense strategy for the new technology-driven pancomputationalism developments. (shrink)

This paper argues that the value of openness to epistemic plurality and the value of social responsiveness are essential for epistemic agents such as scientists who are expected to carry out non-epistemic missions. My chief philosophical claim is that the two values should play a joint role in their communication about earthquake-related damages when their knowledge claims are advisory. That said, I try to defend a minimal normative account of science in the context of communication. I show that these epistemic (...) agents when acting as communicators may encounter various epistemic and practical uncertainties in making their knowledge claims. Using four vignettes, I show that the value of openness to epistemic plurality and the value of social responsiveness may best serve their epistemic and practical purposes across different contexts by reducing their epistemic and practical risks associated with the knowledge claims they communicated. The former may reduce the risks of prematurely excluding epistemic alternatives and is conducive to two types of epistemic plurality; the latter is supposed to reduce the risks of making self-defeating advisory claims and harmful wishful speaking by minimizing the values in tension that can be embedded in the social roles the epistemic agents play. (shrink)

Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case (...) study of the construction of data models at the LHCb for testing Lepton Flavour Universality in rare decays of B-mesons. The close examination of the scientific practice at the LHCb leads to the following four main conclusions: raw data in their pure form are practically useless for the comparison of experimental results with theory, and processed data are in some cases epistemically more reliable, real and simulated data are involved in the co-production of the final data model and cannot be easily distinguished, theory-ladenness emerges at three different levels depending on the scope and the purpose for which background theory guides the overall experimental process and the overall process of acquiring and analysing data in high energy physics is too complicated to be fully captured by a generic methodological description of the experimental practice. (shrink)

This essay explores the history of the silty sediments that make up the littorals of the Bengal Delta to see how they emerged as an object of scientific inquiry and as part of a hydrosocial and political history. By using the conceptual framing of hydrosociality, the piece investigates the political and legal possibilities of amphibious landscapes to document the colonial legal engagement with and scientific puzzlement over these silty sediments and their postcolonial afterlives. As temporary landscapes, silts and sediments pose (...) a unique problem for historians, for they leave scanty archival traces. When they emerge in the state archive it is as sites of conflict, rather than sites of life. They also emerge as a problem for science to map and solve. This essay gathers some snippets of the fragmentary journey of shoals as they emerge and disappear in the scientific and legal archive. Focusing on three moments of interruption in the colonial and postcolonial encounters with the littorals of the Bengal Delta, it argues that the inability of scientific discourse to come up with a conceptual grammar was conducive to new legal articulations about these spaces. Unfortunately, the consequences of this are playing out in the contemporary moment as a humanitarian crisis. (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)

The development of nineteenth-century geodetic measurement challenges the dominant coherentist account of measurement success. Coherentists argue that measurements of a quantity are epistemically successful if their numerical outcomes converge across varying contextual constraints. Aiming at numerical convergence, in turn, offers an operational aim for scientists to solve problems of coordination. Geodesists faced such a problem of coordination between two indicators of the earth’s ellipticity, which were both based on imperfect ellipsoid models. While not achieving numerical convergence, their measurements produced novel (...) data that grounded valuable theoretical hypotheses. Consequently, they ought to be regarded as epistemically successful. This insight warrants a dynamic revision of coherentism, allowing to judge the success of a metric based on both its coherence and fruitfulness. On that view, scientific measurement aims to coordinate theoretical definitions and produce novel data and theoretical insights. (shrink)

Histories of ocean science have emphasized the ways that state-sponsored deep-sea expeditions ushered in a new age of oceanic understanding during the late eighteenth and early nineteenth centuries. This essay, on the other hand, examines the ways that shallow waters played host to less formal but nevertheless important efforts to create oceanic natural knowledge, often centuries earlier. By documenting the legends and experiences of people who worked on and lived by the ocean—divers, sailors, and fishermen, among others—and corroborating their stories (...) with firsthand observation, seventeenth- and early eighteenth-century natural historians built a nascent science of the sea. In its close focus on “sea beans” and “barnacle geese,” subjects of wide conjecture and earnest curiosity, the essay shows how shallow waters welcomed new actors onto the scientific stage and decentered the geographies of knowledge production, thereby advancing contemporary knowledge of oceanic circulation as well as the taxonomies and ecologies of coastal creatures. (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)

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)

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)

We explore three questions about Earth system modeling that are of both scientific and philosophical interest: What kind of understanding can be gained via complex Earth system models? How can the limits of understanding be bypassed or managed? How should the task of evaluating Earth system models be conceptualized?

In this review of Milan Ćirković’s The Great Silence: Science and Philosophy of Fermi’s Paradox, we attempt to reconstruct the logic of Fermi’s paradox as understood by the author, and we critically examine the reasoning that leads to the paradox. We show that there is no plausible solution to Fermi’s paradox that can satisfy all of Ćirković’s proposed desiderata, which in turn suggests that the author’s standards for hypothesis adjudication need to be revised.

Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: “How can ensemble studies be designed so that they probe uncertainty in desired ways?” This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs (...) made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by “plugging and playing” with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs. (shrink)

In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational accuracy, representational depth, and graspability. We show that this framework does justice to the intuition that classical process-based climate models give understanding of phenomena. While simple climate models are characterized by a larger graspability, state-of-the-art models have a higher representational accuracy and representational (...) depth. We then compare the fitness-for-providing understanding of process-based to data-driven models that are built with machine learning. We show that at first glance, data-driven models seem either unnecessary or inadequate for understanding. However, a case study from atmospheric research demonstrates that this is a false dilemma. Data-driven models can be useful tools for understanding , specifically for phenomena for which scientists can argue from the coherence of the models with background knowledge to their representational accuracy and for which the model complexity can be reduced such that they are graspable to a satisfactory extent. When citing this paper, please use the full journal title Studies in History and Philosophy of Science. (shrink)

In climate science, observational gridded climate datasets that are based on in situ measurements serve as evidence for scientific claims and they are used to both calibrate and evaluate models. However, datasets only represent selected aspects of the real world, so when they are used for a specific purpose they can be a source of uncertainty. Here, we present a framework for understanding this uncertainty of observational datasets which distinguishes three general sources of uncertainty: (1) uncertainty that arises during the (...) generation of the dataset; (2) uncertainty due to biased samples; and (3) uncertainty that arises due to the choice of abstract properties, such as resolution and metric. Based on this framework, we identify four different types of dataset ensembles — parametric, structural, resampling, and property ensembles—as tools to understand and assess uncertainties arising from the use of datasets for a specific purpose. We advocate for a more systematic generation of dataset ensembles by using these sorts of tools. Finally, we discuss the use of dataset ensembles in climate model evaluation. We argue that a more systematic understanding and assessment of dataset uncertainty is needed to allow for a more reliable uncertainty assessment in the context of model evaluation. The more systematic use of such a framework would be beneficial for both scientific reasoning and scientific policy advice based on climate datasets. (shrink)

Book Review of “Beyond the Dynamical Universe,” by Michael Silberstein, W.M. Stuckey and Timothy McDewitt.

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

Model evaluation for long term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, yet (...) there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustness, and how to incorporate background knowledge. Under¬standing those issues has the potential to increase confidence in model predictions in modeling efforts outside of climate science where similar challenges exist. (shrink)

This introductory chapter summarises key findings of the twenty-two book chapters in terms of five propositions. These propositions, each building on relevant findings linked to forward-looking suggestions for research, policy and practice, reflect the architecture of the book, whose sections proceed from setting the stage to critical issues, followed by a section on methods and tools, to chapters that provide geographic perspectives, and finally to a section that identifies potential policy options. The propositions comprise (1) Risk management can be an (...) effective entry point for aligning perspectives and debates, if framed comprehensively, coupled with climate justice considerations and linked to established risk management and adaptation practice; (2) Attribution science is advancing rapidly and fundamental to informing actions to minimise, avert, and address losses and damages; (3) Climate change research, in addition to identifying physical/hard limits to adaptation, needs to more systematically examine soft limits to adaptation, for which we find some evidence across several geographies globally; (4) Climate risk insurance mechanisms can serve the prevention and cure aspects emphasised in the L&D debate but solidarity and accountability aspects need further attention, for which we find tentative indication in applications around the world; (5) Policy deliberations may need to overcome the perception that L&D constitutes a win-lose negotiation “game” by developing a more inclusive narrative that highlights collective ambition for tackling risks, mutual benefits and the role of transformation. [Open access]. (shrink)

Mineral species are, at first glance, an excellent candidate for an ideal set of natural kinds somewhere beyond the periodic table. Mineralogists have a detailed set of rules and formal procedure for ratifying new species, and minerals are a less messy subject matter than biological species, psychological disorders, or even chemicals more broadly—all areas of taxonomy where the status of species as natural kinds has been disputed. After explaining how philosophers have tended to get mineralogy wrong in discussions of natural (...) kinds, I show how minerals species don’t behave like natural kinds. They are defined on the basis of human intentionality, not merely natural distinctions. They aren’t ideal grounds for inductive inference. And they don’t form a system that divides nature along a set of equivalent joints. While this is a regrettable outcome to those of us who like the idea of science relying on natural kinds, I contend that mineralogy is doing just fine without a natural kind-based taxonomy, and may in fact be better off without one. (shrink)

The idea that we are living in the Anthropocene, a new geological epoch defined by human activity, has gained substantial currency across the academy and with the broader public. Within the earth sciences, however, the question of the Anthropocene is hotly debated, recognized as a question that gets at both the foundations of geological science and issues of broad philosophical importance. For example, official recognition of the Anthropocene requires us to find a way to use the methods of historical science (...) to make predictions. It also involves determining the role that political motivations should play in establishing scientific kinds. I bring the perspective of philosophy of science to bear on these questions, ultimately arguing that formal recognition of the Anthropocene should be indefinitely deferred. 1A New Epoch 1.1Criteria for designating a new epoch2The Future Geologist’s Perspective 2.1Climate change2.2The fossil record, excluding humans2.3The human fossil record2.4Direct anthropogenic deposits2.5Chemical markers2.6Hydrology2.7Summing up3The Synchronic Perspective4The Anthropocene Is Not yet Set in Stone. (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)

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)

Reports of the Intergovernmental Panel on Climate Change (IPCC) employ an evolving framework of calibrated language for assessing and communicating degrees of certainty in findings. A persistent challenge for this framework has been ambiguity in the relationship between multiple degree-of-certainty metrics. We aim to clarify the relationship between the likelihood and confidence metrics used in the Fifth Assessment Report (2013), with benefits for mathematical consistency among multiple findings and for usability in downstream modeling and decision analysis. We discuss how our (...) proposal meshes with current and proposed practice in IPCC uncertainty assessment. (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.

In this paper we take a close look at current interdisciplinary modeling practices in the environmental sciences, and suggest that closer attention needs to be paid to the nature of scientific practices when investigating and planning interdisciplinarity. While interdisciplinarity is often portrayed as a medium of novel and transformative methodological work, current modeling strategies in the environmental sciences are conservative, avoiding methodological conflict, while confining interdisciplinary interactions to a relatively small set of pre-existing modeling frameworks and strategies (a process we (...) call crystallization). We argue that such practices can be rationalized as responses in part to cognitive constraints which restrict interdisciplinary work. We identify four salient integrative modeling strategies in environmental sciences, and argue that this crystallization, while contradicting somewhat the novel goals many have for interdisciplinarity, makes sense when considered in the light of common disciplinary practices and cognitive constraints. These results provide cause to rethink in more concrete methodological terms what interdisciplinarity amounts to, and what kinds of interdisciplinarity are obtainable in the environmental sciences and elsewhere. (shrink)

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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)