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A topography of climate change research

Author

Listed:
  • Max W. Callaghan

    (Mercator Research Institute on Global Commons and Climate Change
    University of Leeds)

  • Jan C. Minx

    (Mercator Research Institute on Global Commons and Climate Change
    University of Leeds)

  • Piers M. Forster

    (University of Leeds)

Abstract

The massive expansion of scientific literature on climate change1 poses challenges for global environmental assessments and our understanding of how these assessments work. Big data and machine learning can help us deal with large collections of scientific text, making the production of assessments more tractable, and giving us better insights about how past assessments have engaged with the literature. We use topic modelling to draw a topic map, or topography, of over 400,000 publications from the Web of Science on climate change. We update current knowledge on the IPCC, showing that compared with the baseline of the literature identified, the social sciences are in fact over-represented in recent assessment reports. Technical, solutions-relevant knowledge—especially in agriculture and engineering—is under-represented. We suggest a variety of other applications of such maps, and our findings have direct implications for addressing growing demands for more solution-oriented climate change assessments that are also more firmly rooted in the social sciences2,3. The perceived lack of social science knowledge in assessment reports does not necessarily imply an IPCC bias, but rather suggests a need for more social science research with a focus on technical topics on climate solutions.

Suggested Citation

  • Max W. Callaghan & Jan C. Minx & Piers M. Forster, 2020. "A topography of climate change research," Nature Climate Change, Nature, vol. 10(2), pages 118-123, February.
  • Handle: RePEc:nat:natcli:v:10:y:2020:i:2:d:10.1038_s41558-019-0684-5
    DOI: 10.1038/s41558-019-0684-5
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    Citations

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    Cited by:

    1. Ivan Savin & Kristina Chukavina & Andrey Pushkarev, 2023. "Topic-based classification and identification of global trends for startup companies," Small Business Economics, Springer, vol. 60(2), pages 659-689, February.
    2. Lea Berrang‐Ford & Friederike Döbbe & Ruth Garside & Neal Haddaway & William F. Lamb & Jan C. Minx & Wolfgang Viechtbauer & Vivian Welch & Howard White, 2020. "Editorial: Evidence synthesis for accelerated learning on climate solutions," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(4), December.
    3. Hansu Hwang & SeJin An & Eunchang Lee & Suhyeon Han & Cheon-hwan Lee, 2021. "Cross-Societal Analysis of Climate Change Awareness and Its Relation to SDG 13: A Knowledge Synthesis from Text Mining," Sustainability, MDPI, vol. 13(10), pages 1-21, May.
    4. Barbara Kump, 2021. "When do threats mobilize managers for organizational change toward sustainability? An environmental belief model," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2713-2726, July.
    5. Pavel Tcvetkov, 2021. "Climate Policy Imbalance in the Energy Sector: Time to Focus on the Value of CO 2 Utilization," Energies, MDPI, vol. 14(2), pages 1-22, January.
    6. Paul Wolfram & Stephanie Weber & Kenneth Gillingham & Edgar G. Hertwich, 2021. "Pricing indirect emissions accelerates low—carbon transition of US light vehicle sector," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    7. Kerstin K. Zander & Stephen T. Garnett & Harald Sterly & Sonja Ayeb-Karlsson & Barbora Šedová & Hermann Lotze-Campen & Carmen Richerzhagen & Hunter S. Baggen, 2022. "Topic modelling exposes disciplinary divergence in research on the nexus between human mobility and the environment," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.
    8. Iván López & Rodrigo Suarez & Mercedes Pardo, 2022. "A System of Indicators for Socio-Economic Evaluation and Monitoring of Global Change: An Approach Based on the Picos de Europa National Park," Land, MDPI, vol. 11(5), pages 1-17, May.
    9. Neal R. Haddaway & Max W. Callaghan & Alexandra M. Collins & William F. Lamb & Jan C. Minx & James Thomas & Denny John, 2020. "On the use of computer‐assistance to facilitate systematic mapping," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(4), December.
    10. Tian-Yuan Huang & Liangping Ding & Yong-Qiang Yu & Lei Huang & Liying Yang, 2023. "From AR5 to AR6: exploring research advancement in climate change based on scientific evidence from IPCC WGI reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5227-5245, September.
    11. E. Lisa F. Schipper & Navroz K. Dubash & Yacob Mulugetta, 2021. "Climate change research and the search for solutions: rethinking interdisciplinarity," Climatic Change, Springer, vol. 168(3), pages 1-11, October.
    12. Jacopo A. Baggio, 2021. "Knowledge generation via social-knowledge network co-evolution: 30 years (1990–2019) of adaptation, mitigation and transformation related to climate change," Climatic Change, Springer, vol. 167(1), pages 1-16, July.
    13. AbdulRafiu, Abbas & Sovacool, Benjamin K. & Daniels, Chux, 2022. "The dynamics of global public research funding on climate change, energy, transport, and industrial decarbonisation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    14. Mariana Madruga de Brito & Danny Otto & Christian Kuhlicke, 2021. "Tracking Topics and Frames Regarding Sustainability Transformations during the Onset of the COVID-19 Crisis," Sustainability, MDPI, vol. 13(19), pages 1-19, October.
    15. Anne J. Sietsma & Rick W. Groenendijk & Robbert Biesbroek, 2023. "Progress on climate action: a multilingual machine learning analysis of the global stocktake," Climatic Change, Springer, vol. 176(12), pages 1-12, December.

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