The nineteenth-century distinction between the nomothetic and the idiographic approach to scientific inquiry can provide valuable insight into the epistemic challenges faced in contemporary earth modelling. However, as it stands, the nomothetic-idiographic dichotomy does not fully encompass the range of modelling committments and trade-offs that geoscientists need to navigate in their practice. Adopting a historical epistemology perspetive, I propose to further spell out this dichotomy as a set of modelling decisions concerning historicity, model complexity, scale, and closure. Then, I suggest that, to address the challenges posed by these decisions, a pluralist stance towards the cognitive aims of earth modelling should be endorsed, especially beyond predictive aims.
BarnesTJvan MeeterenM (2022) The great debate in mid-twentieth century American geography: Fred K. Schaefer vs. Richard Hartshorne. In: LovellSCoenSRosenbergM (eds.) The Routledge Handbook of Methodologies in Human Geography. London: Routledge, pp. 9–23.
2.
BensonE (2020) Random river: Luna Leopold and the promise of chance in fluvial geomorphology. Journal of Historical Geography67: 14–23.
3.
BokulichA (2013) Explanatory models versus predictive models: Reduced complexity modeling in geomorphology. In: KarakostasVDieksD (eds.) EPSA11 Perspectives and Foundational 115 Problems in Philosophy of Science, The European Philosophy of Science Association Proceedings 2. Berlin: Springer.
4.
BokulichA (2021) Taming the tyranny of scales: Models and scale in the geosciences. Synthese199: 14167–14199.
5.
BokulichAOreskesN (2017) Models in geosciences. In: MagnaniLBertolottiT (eds.) Springer handbook of model-based science. Berlin: Springer, pp. 891–911.
6.
BoydNM (2018) Evidence enriched. Philosophy of Science85(3): 403–421.
7.
CanhamJColeWLauenrothWK (2001) Understanding ecosystems: The role of quantitative models in observation, synthesis, and prediction. In: Cary Conference IX, 1–3May2001, Millbrook, NY. Institute of Ecosystems Studies.
8.
CarnapRHahnHNeurathO (1929/1973) The scientific conception of the world: The Vienna Circle. Trans. of Wissenschaftliche Weltauffassung. Der Wiener Kreis. In: NeurathMCohenR (eds.) Empiricism and Sociology. Dordrecht: Reidel, pp. 298–318.
9.
CamprubíL (2018) Experiencing deep and global currents at a ‘Prototypical Strait’, 1870s and 1980s. Studies in History and Philosophy of Science70: 6–17.
10.
ChangH (2012) Is Water H2O? Boston Studies in the Philosophy and History of Science. Berlin: Springer.
11.
ClelandCE (2002) Methodological and epistemic differences between historical science and experimental science. Philosophy of Science69(3): 447–451.
12.
CoenD (2016) Big is a thing of the past: Climate change and methodology in the history of ideas. Journal of the History of Ideas77(2): 305–321.
13.
CurrieA (2018) Existential risk, creativity and well-adapted science. Studies in History and Philosophy of Science76: 39–48.
14.
CurrieA (2019) Scientific Knowledge and the Deep Past. Cambridge, UK: Cambridge Elements, Cambridge University Press.
15.
Dahan-DelmedicoA (2001) History and epistemology of models: Meteorology as a case study (1946–1963). Archive for the History of the Exact Science55: 395–422.
16.
De ChadarevianSHopwoodN (eds.) (2004) Models: The Third Dimension of Science. California: Stanford University Press.
17.
DiltheyW (1883/1989) Einleitung in Die Geisteswissenschaften, Leipzig: Duncker & Humblot. Translated as Introduction to the Human Sciences, by MakkreelR.A.RodiF. in Wilhelm Dilthey: Selected Works, vol. I, Princeton: Princeton University Press, pp. 47–242.
18.
DouglasH (2013) The value of cognitive values. Philosophy of Science80(5): 796–806.
19.
EdwardsP (2010) Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming. Cambridge, MA: MIT Press.
20.
ElginC (2017) True Enough. Cambridge, MA: MIT Press.
21.
FisherGGelfertASteinleF (2021) Exploratory models and exploratory modeling in science: Introduction. Perspectives on Science29(4): 355–358.
22.
FreemanJ (1930) Mastering rivers in the laboratory: Progress in hydraulic laboratory research. The Technology Review32: 3.
23.
FuhrerO (2018) Near-global climate simulation at 1 km resolution: Establishing a performance baseline on 4888 GPUs with COSMO 5.0. Geoscientific Model Development11(4): 1665–1681.
24.
FultzD (1951) Experimental analogies to atmospheric motions. In: ByersHR (ed.) Compendium of Meteorology. Cambridge, MA: American Meteorological Society.
25.
GelfertA (2016) How to Do Science with Models. Berlin: Springer.
26.
GouldSJ (1980) The promise of paleobiology as a nomothetic, evolutionary discipline. Paleobiology6(1): 96–118.
27.
GramelsbergerG (2017) Calculating the weather: Emerging cultures of prediction in late nineteenth- and early twentieth-century Europe. In: HeymannMGramelsbergerGMahonyM (eds.) Cultures of Prediction in Atmospheric and Climate Science: Epistemic and Cultural Shifts in Computer-based Modelling and Simulation. New York: Routledge, pp. 45–66.
28.
GramelsbergerGFleichterJ (2011) Modelling the climate system: An overview. In: GramelsbergerGFleichterJ (eds.) Climate Change and Policy. The Calculability of Climate Change and the Challenge of Uncertainty. Berlin: Springer, pp. 9–90.
29.
GramelsbergerGLenhardJParkerWS (2020) Philosophical perspectives on earth system modeling: Truth, adequacy, and understanding. Journal of Advances in Modeling Earth Systems12: e2019MS001720.
30.
GuillemotH (2017) How to develop climate models? The “gamble” of improving climate model parameterizations. In: HeymannMGramelsbergerGMahonyM (eds.) Cultures of Prediction in Atmospheric and Climate Science: Epistemic and Cultural Shifts in Computer-based Modelling and Simulation. New York: Routledge, pp. 120–135.
31.
HallamA (1983) Great Geological Controversies. New York, NY: Oxford University Press.
32.
HannahWMJonesCRHillmanBR, et al. (2020) Initial results from the super-parameterized E3SM. Journal of Advances in Modeling Earth Systems12: e2019MS001863.
33.
HartshorneR (1959) Perspective on the Nature of Geography. Chicago, IL: Rand McNally.
34.
HeldIM (2005) The gap between simulation and understanding in climate modeling. Bulletin of the American Meteorological Society86(11): 1609–1614.
35.
HellerV (2011) Scale effects in physical hydraulic engineering models. Journal of Hydraulic Research49(3): 293–306.
36.
HeymannMGramelsbergerGMahonyM (2017a) Introduction. In: HeymannMGramelsbergerGMahonyM (eds.) Cultures of Prediction in Atmospheric and Climate Science: Epistemic and Cultural Shifts in Computer-based Modelling and Simulation. New York: Routledge, pp. 1–17.
37.
HeymannMGramelsbergerGMahonyM (2017b) Key characteristics of cultures of prediction. In: HeymannMGramelsbergerGMahonyM (eds.) Cultures of Prediction in Atmospheric and Climate Science: Epistemic and Cultural Shifts in Computer-based Modelling and Simulation.New York: Routledge, pp. 18–41.
38.
HeymannMHundebølR (2017) From heuristic to predictive: Making climate models into political instruments. In: HeymannMGramelsbergerGMahonyM (eds.) Cultures of Prediction in Atmospheric and Climate Science: Epistemic and Cultural Shifts in Computer-based Modelling and Simulation.New York: Routledge, pp. 100–119.
39.
JeffaresB (2008) Testing times: Regularities in the historical sciences. Studies in History and Philosophy of Biological and Biomedical Sciences39(4): 469–475.
40.
JonesM (2005) Idealization and abstraction: A framework. In: CartwrightNJonesM (ed.) Idealization XII: Correcting the Model. Idealization and Abstraction in the Sciences. Amsterdam, The Netherlands: Rodopi, pp. 173–217.
41.
KatzavJParkerW (2015) The future of climate modeling. Climate Change132: 475–487.
42.
KinzelK (2021) Wilhelm Windelband. In: ZaltaEn (ed.) The Stanford Encyclopedia of Philosophy Archive. Redwood City, CA: Stanford University.
43.
KleinhansMBuskesCde RegtH (2005) Terra incognita: Explanation and reduction in earth science. International Studies in the Philosophy of Science19(3): 289–317.
44.
KnuuttilaTCarrilloNKoskinenR (eds.) (2024) The Routledge Handbook of Philosophy of Scientific Modeling. London, UK: Routledge.
45.
LaneS (2003) Numerical modelling: Understanding explanation and prediction in physical geography. In: CliffordNFrenchSValentineG (eds.) Key Methods in Geography, 2nd edition.Washington, DC: Sage, pp. 274–298.
46.
LeonelliS (2019) What distinguishes data from models?European Journal for Philosophy of Science9: 22.
LonginoH (2004) How values can be good for science. In: MachamerPWoltersG (eds.) Science, Values and Objectivity. Pittsburgh, PA: University of Pittsburgh Press, pp. 127–142.
49.
LowenthalD (2019) The Quest for the Unity of Knowledge. London, UK: Routledge.
50.
MagnaniLBertolottiT (eds.) (2017) Springer Handbook of Model-Based Science. Berlin: Springer.
51.
MatthewsonJWeisbergM (2009) The structure of tradeoffs in model building. Synthese170: 169–190.
52.
MorganM (2012) The World in the Model. Cambridge, UK: Cambridge University Press.
53.
MurrayABPaolaC (1994) A cellular model of braided rivers. Nature371: 54–57.
54.
NicholasA (2010) Reduced-complexity modeling of free bar morphodynamics in alluvial channels. Journal of Geophysical Research115: F04021.
55.
O’ReillyJBrysseKOppenheimerM, et al. (2011) Characterizing uncertainty in expert assessments: Ozone depletion and the west Antarctic ice sheet. WIREs Climate Change2(5): 728–743.
56.
OreskesN (1999) The Rejection of Continental Drift: Theory and Method in American Earth Science. Oxford, UK: Oxford University Press.
57.
OreskesN (2003) The role of quantitative models in science. In: CanhamJColeWLauenrothWK (eds.) Models in Ecosystem Science. Princeton: Princeton University Press, pp. 13–31.
58.
OreskesN (2007) From scaling to simulation: Changing meanings and ambitions of models in the earth sciences. In: CreagerALunbeckEWiseMN (eds.) Science Without Laws: Model Systems, Cases, and Exemplary Narratives. Durham, NC: Duke University Press, pp. 93–124.
59.
PaceM (2003) The utility of simple models in ecosystem science. In: CanhamJColeWLauenrothWK (eds.) Models in Ecosystem Science. Princeton: Princeton University Press, pp. 49–62.
60.
PageM (2021) The role of historical science in methodological actualism. Philosophy of Science88: 461–482.
61.
PaolaCStraubKMohrigD, et al. (2009) The ‘unreasonable effectiveness’ of stratigraphic and geomorphic experiments. Earth-Science Reviews97: 1–43.
62.
ParkerW (2018) Climate science. In: ZaltaENNodelmanU (eds.) The Stanford Encyclopedia of Philosophy, Fall 2023 Edition. Stanford, CA: The Metaphysics Research Lab.
63.
ParkerW (2020) Model evaluation: An adequacy-for-purpose view. Philosophy of Science87: 457–477.
PopperK (1963/2002) Conjectures and Refutations. London, UK: Routledge.
66.
PotochnikA (2015) The diverse aims of science. Studies in History and Philosophy of Science53: 71–80.
67.
PotochnikA (2017) Idealization and the Aims of Science. Chicago, IL: University of Chicago Press.
68.
PyneS (1980) Grove Karl Gilbert. A Great Engine of Research. Austin, TX: University of Texas Press.
69.
RandallDBitzCMDanabasogluG, et al. (2018) 100 years of earth system model development. Meteorological Monographs59: 12.1–12.66.
70.
RiceC (2021) Leveraging Distortions. Explanation, Idealization, and Universality in Science. Cambridge, MA: MIT Press.
71.
RosolC (2015) Hauling data: Anthropocene analogues, paleoceanography and missing paradigm shifts. Historical Social Research40(2): 37–66.
72.
Sánchez-DoradoJ (2019) Scientific Representation in Practice: Models and Creative Similarity. Doctoral thesis (PhD), UCL (University College London), London.
73.
SchaeferFK (1953) Exceptionalism in geography: A methodological introduction. Annals of the Association of American Geographers43(3): 226–249.
74.
SchummS (1979) Geomorphic thresholds: The concept and its applications. Transactions of the Institute of British Geographers4(4): 485–515.
75.
SepkoskiD (2012) Rereading the Fossil Record: The Growth of Paleobiology as an Evolutionary Discipline. Chicago, IL: University of Chicago Press.
76.
SterrettS (2017) Experimentation on analogue models. In: MagnaniLTommaso BertolottiT (eds.) Springer Handbook of Model-Based Science. Dordrecht: Springer, pp. 857–878.
77.
ShuklaJPalmerTNHagedornR, et al. (2010) Toward a new generation of world climate research and computing facilities. Bulletin of the American Meteorological Society91: 1407–1412.
78.
SnowCP (1959/2001) The Two Cultures. London, UK: Cambridge University Press.
79.
TsingAL (2013) On nonscalability: The living world is not amenable to precision-nested scales. Common Knowledge18(3): 505–524.
80.
TurnerD (2014) Philosophical issues in recent paleontology. Philosophy Compass9(7): 494–505.
81.
WatkinsA (2023) Scaling procedures in climate science: Using temporal scaling to identify a paleoclimate analogue. Studies in History and Philosophy of Science102: 31–44.
82.
WeisbergM (2013) Simulation and Similarity. Oxford, UK: Oxford University Press.
83.
WimsattWC (1987) False models as a means to truer theories. In: NiteckiMHHoffmanA (eds.) Neutral Models in Biology. Oxford, UK: Oxford University Press, pp. 23–55.
84.
WindelbandW (1894/1980) Geschichte und Naturwissenschaft, reprinted in his Präludien, vol. 2, pp. 136–160. Translated as “Windelband on History and Natural Science. Rectorial address, Strasbourg, 1894”. History and Theory19(2): 169–185.
85.
WinsbergE (2018) Philosophy and Climate Science. Cambridge, UK: Cambridge University Press.
