Applying big data beyond small problems in climate research

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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.

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Change history

  • 18 March 2019

    In the version of this Perspective originally published, the following ‘Journal peer review information’ was missing “Nature Climate Change thanks Prabhat, Wendy Parker and other anonymous reviewer(s) for their contribution to this work.” This statement has now been added.

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Acknowledgements

We thank C. Beisbart, A. Merrifield, S. Sippel, R. McMahon and J. Lilliestam for discussions and comments that have improved the quality of this manuscript. The research was supported by the Swiss National Science Foundation, National Research Programme 75 Big Data, project no. 167215.

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B.K. reviewed and classified the studies and led the writing with contributions from all authors. All authors contributed to the framing and the development of the ideas of the paper.

Correspondence to Benedikt Knüsel.

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The authors declare no competing interests.

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Journal peer review information: Nature Climate Change thanks Prabhat, Wendy Parker and other anonymous reviewer(s) for their contribution to this work.

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