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Applying big data beyond small problems in climate research

Author

Listed:
  • Benedikt Knüsel

    (Institute for Environmental Decisions
    Institute for Atmospheric and Climate Science)

  • Marius Zumwald

    (Institute for Environmental Decisions
    Institute for Atmospheric and Climate Science)

  • Christoph Baumberger

    (Institute for Environmental Decisions)

  • Gertrude Hirsch Hadorn

    (Institute for Environmental Decisions)

  • Erich M. Fischer

    (Institute for Atmospheric and Climate Science)

  • David N. Bresch

    (Institute for Environmental Decisions
    Federal Office of Meteorology and Climatology MeteoSwiss)

  • Reto Knutti

    (Institute for Atmospheric and Climate Science)

Abstract

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-data elements can be useful for climate research beyond small problems if combined with more traditional approaches based on domain-specific knowledge. The biggest potential for big-data elements, we argue, lies in socioeconomic climate research.

Suggested Citation

  • Benedikt Knüsel & Marius Zumwald & Christoph Baumberger & Gertrude Hirsch Hadorn & Erich M. Fischer & David N. Bresch & Reto Knutti, 2019. "Applying big data beyond small problems in climate research," Nature Climate Change, Nature, vol. 9(3), pages 196-202, March.
    • Handle: RePEc:nat:natcli:v:9:y:2019:i:3:d:10.1038_s41558-019-0404-1
    DOI: 10.1038/s41558-019-0404-1
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    Cited by:

    1. Faxi Yuan & Amir Esmalian & Bora Oztekin & Ali Mostafavi, 2022. "Unveiling spatial patterns of disaster impacts and recovery using credit card transaction fluctuations," Environment and Planning B, , vol. 49(9), pages 2378-2391, November.
    2. Marius Zumwald & Benedikt Knüsel & Christoph Baumberger & Gertrude Hirsch Hadorn & David N. Bresch & Reto Knutti, 2020. "Understanding and assessing uncertainty of observational climate datasets for model evaluation using ensembles," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(5), September.

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