•  51
    Applying big data beyond small problems in climate research
    with Marius Zumwald, Christoph Baumberger, Gertrude Hirsch Hadorn, Erich M. Fischer, Reto Knutti, and David M. Bresch
    Nature Climate Change 9 (March 2019): 196-202. 2019.
    Commercial success of big data has led to speculation that big-data-like reasoning could partly replace theory-based approaches in science. Big data typically has been applied to ‘small problems’, which are well-structured cases characterized by repeated evaluation of predictions. Here, we show that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation. Big…Read more
  •  48
    Understanding climate phenomena with data-driven models
    Studies in History and Philosophy of Science Part A 84 (C): 46-56. 2020.
    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 grasp…Read more
  •  31
    Understanding and assessing uncertainty of observational datasets for model evaluation using ensembles
    with Marius Zumwald, Christoph Baumberger, Gertrude Hirsch Hadorn, David Bresch, and Reto Knutti
    WIREs Climate Change 10 1-19. 2020.
    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) un…Read more
  •  2
    Climate Research and Big Data
    with Christoph Baumberger and Reto Knutti
    In Pellegrino Gianfranco & Marcello Di Paola (eds.), Handbook of Philosophy of Climate Change, Springer Nature. pp. 125-149. 2023.
    In recent years, the ability to gather and store information has increased dramatically, and the ability to make use of these increasing volumes of data has improved. This advent of big data has opened up new opportunities for scientific research, including for research on climate change. These changes are associated with a number of interesting philosophical questions. This chapter provides an introduction to these questions. It starts by first clarifying terminological issues concerning “big d…Read more